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DOUBLE BLIND PEER REVIEW OPEN ACCESS ONLINE JOURNAL TWO ISSUES PER YEAR FAST AND EFFICIENT REVIEW DEDICATED EDITORIAL TEAM

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BUSINESS SYSTEMS REVIEW

ISSN: 2280-3866

Business Systems Laboratory www.bslaboratory.net

BUSINESS SYSTEMS REVIEW – ISSN 2280-3866 www.business-systems-review.org

Volume 1, Issue 1 June-December 2012

JOURNAL SCOPE Business Systems Review is an on-line, open access, peer reviewed, half-yearly journal, published by the non-profit association Business Systems Laboratory (Italy). BSR publishes high level and innovative theoretic, qualitative, quantitative and empirical contributions of researchers and practitioners in the business systems field. The journal aims to endow a multi-field approach with a special emphasis on the systemic approach for business. We welcome submissions based upon both primary research and reviews including papers in areas that may not directly be systemic but concern a topic that is of interest to researchers in the field of business systems. All papers are subject to strict double blind peer review by the international research community. PUBLICATION FREQUENCY Six-monthly, published in June and December. Articles are published online shortly after acceptance. COVERAGE The main topics covered in the journal may include, but not are limited to, the following topic areas: Systemic Approach for Business; Complex Systems Theory; Management Cybernetics; Economic and Social Systems; Business Communication Systems; Innovation Systems; Financial Systems; Service Science; Sustainability; Knowledge Management; Supply Chain Management; Strategic Management; Environmental Business; Environmental Management; Marketing; Consumer Behavior; Customer Satisfaction; Corporate Finance; Banking; Finance for SME; e-Business; e-Learning; Business Process Management, Fuzzy Logic, Heterodox Economics. KEY JOURNAL AUDIENCES Academics, researchers, business consultants, business engineers, computer scientists, management systemists. Online libraries supplying students, academics and researchers. OPEN ACCESS POLICY BSR provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. KEY BENEFITS BSR is an important forum for the exchange of knowledge, addressing major areas of concern and debate whilst highlighting future developments. The challenging and comprehensive nature of systems science in business is reflected in the published articles which involve not only theoretical and methodological-oriented studies but also in-depth discussions of their related appliances and implementations. PEER REVIEW The journal adopts a double-blind system for peer-review; both reviewers and authors’ identities remain anonymous. The paper will be peer-reviewed by three experts: two reviewers from outside and one associate editor from the journal. Our commitment is to complete the entire review process within a maximum of three months since the submission. INDEXING AND ABSTRACTING Google Scholar, Cabell’s Directories, Index Copernicus, Ulrichs web, Open J-Gate, Journal Seek, GIFGlobal Impact Factor, SSRN, Sherpa Romeo.

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BUSINESS SYSTEMS REVIEW – ISSN 2280-3866 www.business-systems-review.org

Volume 1, Issue 1 June-December 2012

BUSINESS SYSTEMS REVIEW ETHICAL CODE The Business Systems Review (BSR) aims to choose and publish, through a double blind peer review process, the highest quality research in business systems. In order to achieve this goal, the whole peer review and publication process must be scrupulous and fair. Journal standing depends greatly on the trust of all people involved in the process coming from their acknowledgment of the fairness of the double blind peer review and publication process. This trust can be enhanced by the implementation of a formal ethical code, with clear guidelines for fair behavior. For these reasons, the BSR Ethical Code is intended to be a complete policy for peer review and publication ethics in the Business Systems Review. The Code depicts BSR's policies to guarantee the ethical conduct of all participants in the peer review and publication process. BSR Authors, Editors and Reviewers are encouraged to read these guidelines and address any questions or concerns to one of the BSR co-Editor in Chief. For further details about BSR ethical code: http://www.business-systems-review.org/BSR_ethical_code.htm

AUTHOR'S GUIDELINES Submission of an article implies that the work described has not been published previously (except in the form of an abstract or a conference proceeding), that it is not under consideration for publication elsewhere, that its publication is approved by all authors and that, if accepted, will not be published elsewhere in the same form, in English or in any other language, without the consent of the Publisher. The Editors reserve the right to edit or otherwise alter all contributions, but authors will receive proofs for approval before publication. Authors must check their manuscripts for possible violations of copyright law and obtain the required permissions before submission. Authors should be punctual with their manuscript revisions. If an Author cannot meet the deadline given, he should contact the Editor to determine whether a longer time period or withdrawal from the review process should be chosen. Authors authorize the publisher to archive the article into databases and indexes, and permit the publisher to apply DOI to the article. After paper acceptance the corresponding author will pay a handling fee by PayPal or Bank Transfer. All manuscripts should be prepared in MS-Word format, and submitted by e-mail to the editor in chief. For further details please go to: http://www.business-systems-review.org/BSR_authors_guidelines.htm

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BUSINESS SYSTEMS REVIEW – ISSN 2280-3866 www.business-systems-review.org

Volume 1, Issue 1 June-December 2012

EDITOR IN CHIEF GANDOLFO DOMINICI e-mail: [email protected] CO-EDITOR ENZO SCANNELLA ASSOCIATE EDITORS Dimitris Antoniadis. Lecturer in Project Management, Univeristy of West London (UK) Gianpaolo Basile. Adjunct Professor of Marketing, Univ. of Salerno (ITA) Nikhilesh Dholakia. Professor of Marketing, University of Rhode Island (USA) Primiano Di Nauta. Ass. Professor of Business Management, Univ. of Foggia (Italy) Valerio Eletti. Scientific Director LABeL Cattid., University "Sapienza" of Rome (ITA) Nezihe Figen Ersoy. Associate Professor of Marketing. Anadolu University, (Turkey) Lucio Fuentelsaz. Professor of Strategy & Management, University of Zaragoza, (ESP) Marco Galvagno. Ass. Professor of Marketing, University of Catania (ITA) Giuseppe Giordano. Associate Professor of Statistics. University of Salerno (ITA) José Rodolfo Hernandez Carrìon. Associate Professor of Applied Economics, Univ. of Valencia (ESP) Giulio Maggiore. Ass. Professorof Business Management, Univ. "Unitelma Sapienza" (ITA) Ignacio Martinez de Lejarza. Associate Professor of Applied Economics, University of Valencia (ESP) Mahito Okura. Associate Professor of Risk Manang.& Insurance, Nagasaki University (JP) Nacima Ourahmoune. Assistant Professor of Marketing, Reims Manag. School (France) Luca Pazzi. Ass. Professor of Information Systems, Univ. Modena & R. E. (ITA) Vincenzo Pisano. Ass. Professor of Business Management. Univ. of Catania (ITA) John Schouten. Professor of Marketing Aalto University School of Economics (Finland) Mauro Sciarelli. Professor of Business Management University "Federico II" Naples (ITA) Giancarlo Scozzese. Ass. Prof. of Business Management "Univ. Stranieri" Perugia (ITA) Josip Stepanić. Ass. Professor of Social Thermodynamics, University of Zagreb (Croatia) Eleuterio Vallelado. Professor of Finance, University of Valladolid (ESP) Ivona Vrdoljak Raguž. Ass. Professor of Management, University of Dubrovnik (Croatia) Zhenghu Yang. Scientific Director, Guangdong Center of Contemporary Economy Research (China) Maurice Yolles. Head Centre for Creating Coherent Change and Knowledge (UK)

REVIEWERS Niksa Alfirevic, University of Split (Croatia); Luigi Balletta, University of Palermo (Italy); Gordana Barić, University of Zagreb (Croatia); Nathalie Belhoste, Reims Management School (France); Roberto Bruni, Univ. Cassino (Italy); Antonino Buscemi, University of “LUSPIO” Rome (Italy); Aw Yoke Cheng. Asia Pacific Univ. of Techn.& Innov. (Malaysia); Giorgia M. D'Allura University of Catania (Italy); Alessandra Distefano, University of Florida (USA); Helmi Hammami, Qatar University (Qatar); Valerio Lacagnina, University of Palermo (Italy); Diane Martin, Aalto University (Finland); Marco Mele, Univ. LUSPIO (Italy); Anna Minà, University of Catania (Italy); Sevgi Ayse Ozturk, Anadolu University (Turkey); Sergio Palomas, Universidad de Zaragoza (Spain); Federica Palumbo, “Sapienza” University of Rome (Italy); Ornella Papaluca. Univ.di Napoli Federico II (Italy); Massimo Picone, University of Catania (Italy); Razaq Raj, Leeds Metropolitan University (UK); Fanny Reniou, Reims Management School (France); José Carlos Rodríguez, UMSNH (Mexico); Biserka Runje, University of Zagreb (Croatia); Mario Tani, Univ.di Napoli Federico II (Italy); Rosanna Verde, Second University of Naples (Italy); Henri Weijo, Aalto University (Finland); Medet Yolal, Anadolu University (Turkey); Ahmad. M. A. Zamil, King Saud University (Saudi Arabia); Yanmei Zhou, Huazhong Univ.of Science and Technology (China)

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Volume 1, Issue 1 June-December 2012

TABLE OF CONTENTS pp. 1-2 pp. 3-4 pp. 5-9 pp. 10-26 pp. 27-38 pp. 39-48 pp. 49-63 pp. 64-84

pp. 85-102

pp. 103-121

pp. 122-138 pp. 139-156 pp. 157-177 pp. 178-201 pp. 202-224 pp. 225-247

pp. 248-262 pp. 263-275

Why Does Systems Thinking Matter? (Editorial) Gandolfo Dominici Editorial Note Enzo Scannella Complexity and Systemic Models: tools to understand and manage crises Charles François A Test of Strong-Form Efficiency of the Nigerian Capital Market Oke Micheal Ojo & B.A. Azeez Imbibing Social Entrepreneurship in Biotechnology Mousumi Majumdar & Vasanth Kiran Insurance as Credence Goods: On the Allocation of the Burden of Proof Mahito Okura & Yunho Lee Customer’s Advisory as a Facilitator of Innovation and a Game-Changer in the Competition Mustafa Özgür Güngör Applying fuzzy AHP to determination of optimum selection method for economic cocoon traits improvement in silkworm breeding Meysam Shaverdi & Barzin Parakhat Bringing Strategy Back into Financial Systems of Performance Measurement: Integrating EVA and PBC Arabella Mocciaro Li Destri, Pasquale Massimo Picone, Anna Minà The Use of Reported Cash Flows versus Earnings to Predict Cash Flows: Preliminary Evidence from Qatar Helmi Hammami Local banks and private equity: cultural and organizational challenges in light of the international financial crisis Massimo Arnone & Alessandra Bechi Regional Innovation Systems: A Literature Review Giorgia M. D'Allura, Marco Galvagno, Arabella Mocciaro Li Destri Revitalising the Outsourcing Discourse within the Boundaries of Firms Debate Lucia Marchegiani, Luca Giustiniano, Enzo Peruffo, Luca Pirolo Strategic Management and “Complex Products”: some notes about an interpretative model for business policies Lucia Aiello, Gaetano Fausto Esposito, Maria Antonella Ferri Smart Energy Management. A Viable Systems Approach perspective Francesco Polese, Luca Carrubbo, Primiano Di Nauta "Ranking-based Ties" Social Networks. An illustration based on a system of Fashion Capital Cities in the world Ignacio Martínez de Lejarza & José Rodolfo Hernández-Carrión Controlling hazards and safety in complex systems: a multi-layered part-whole approach to system safety Luca Pazzi Expansion Economies Fernando Buendía

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Business Systems Review

ISSN: 2280-3866 Volume 1 – Issue 1

Editorial Note “Why Does Systems Thinking Matter?” Gandolfo Dominici, Ph.D., Editor in Chief Tenured Ass. Professor of Business Management, University of Palermo, Italy Received April 18, 2012/ Accepted May 2, 2012 / published online June 1, 2012 DOI: 10.7350/bsr.a02.2012 – URL: http://dx.medra.org/10.7350/BSR.A02.2012

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The social and economic complexity of our times triggers intense transformations in the competitive logics of markets and, broadly speaking, of business systems. Business scenarios today are typified by dynamism, connectivity, nonlinearity, and emergent properties—in other words by “complexity”. Asserting that the world, and consequently business systems, are complex means that it is impossible to understand them by considering their individual elements separately, and that there is no option of predicting the future, but only of grasping and proactively influencing future scenarios. Reductionist models are unable to fully depict, or to allow us to deeply understand, new complex and dynamic business scenarios. Today more than ever, it is necessary to recognize the need for a paradigm shift that can carry science beyond the analytical reductionist approach, and towards a more comprehensive systemic perspective. This, of course, does not imply rejecting all the discoveries and benefits that the reductionist approach has brought to science, but it does mean going further, being aware that the analytic way alone is not sufficient for obtaining a deeper understanding of complex phenomena. Hence, without rejecting the old paradigm, we must move ahead to embrace a systemic view of social and economic facts. Growing complexity calls for new systemic skills, capable of giving directions to the management of firms. It is necessary to move beyond the mere application of models and algorithms. Managers and consultants need to develop the ability to grasp the “sense of events”, instead of merely classifying them into predefined patterns. In other words, they must learn to think in terms of the “possible”, and to deal with the “emergent”. The management of firms must be proactive in order to shape their activity, and to influence the business environment; managers and entrepreneurs must be able to decode the signs of continuous change, and to move fast enough to turn these into opportunities. In today’s “liquid” society, intangible and irrational aspects manifest prominently in consumer choice. The very existence of marketing implies that the consumer does not choose as a “homo oeconomicus” who considers tangible costs and benefits, but who instead thinks and chooses according to the emotional and symbolic values of goods. This has implications for the whole value-creation process, and consequently for managerial practice. The firm cannot be conceived as an isolated system. Each time we use reductionist logic to identify a system, we make a distinction between what is inside and what is outside the system. The systemic approach highlights the complexity of the relations between the system and the environment, and the constant interrelation and exchange of matter, energy, and information between the system and the environment. Another relevant aspect for the management of firms in complex scenarios is the characteristic of “emergency”. An emergency, in a complex system, is a manifestation of something “new and unpredictable” from the point of view of the planner.

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Business Systems Review, ISSN: 2280-3866 Volume 1, Issue 1, 2012

To deal with emergencies, it is important to consider that the position of the firm in its business environment is the result of different levels of relations, which create both internal and external dynamic hierarchies. These cannot be crystallized into a single pyramid; they evolve and coevolve with mutual relations at different levels. This allows the firm to have more chances of dealing with emergent patterns. To be viable, a firm needs to be able to redefine itself continuously, changing its structure. We can refer to the new concept of dematerialized (liquid) structure, according to which firms can be considered as value constellations of intangible assets. This implies that twentyfirst century enterprises depend much more on their portfolio of intangible assets than they did in the past. According to this view, the firm is not a static entity that can be produced with predefined functions, but can be seen as a tool for planning future scenarios. To manage this conceptual paradigm shift, we need to use and develop new tools based on fuzzy logic and nonlinearity. These are the reasons I think Systems Thinking matters in Business Science, and the challenges that I wish BSR to be able to face. BSR does not aim to be just one of the thousands of open-access journals on management and economics. My aim in these pages is to gather together authors who can bring us new ideas, new tools, and new theories that will expand the frontiers of Business Science. I am aware this is an ambitious project, but I believe that beginning a project without ambition means to fail in advance. I hope that many researchers from all fields will take up this challenge, and will contribute their ideas to help us make this journal a place of discussion and confrontation among bright minds full of bright ideas, who are not afraid to be proactive in the advancement of business science. REFERENCES 2

Barile, S., Calabrese, M. (2011). A New Frontier in Consulting. The VSA Consulcube. In Barile S. Bassano C. Calabrese M., Confetto M., Di Nauta P., Piciocchi P., Polese F., Saviano M., Siano A., Siglioccolo M., Vollero A. (eds), Contributions to theoretical and practical advances in management. A Viable Systems Approach, pp. 245-282. International Printing. Bauman, Z. (2000). Liquid Modernity. Blackwell Beer, S. (1972). Brain of the firm. Penguin Press. Dominici, G. (2012). Consulting of the XXI Century. Coping with Complex Business Systems. Nuova Atlantide, 3, 69–77. Dominici, G., Levanti , G. (2011). The Complex System Theory for the Analysis of InterFirm Networks. A Literature Overview and Theoretic Framework. International Business Research, 4(2), 31-37. doi: 10.5539/ibr.v4n2p31. Espejo, R., Reyes A. (2011). Organizational Systems: Managing Complexity with the Viable System Model. Springer. Luoma M. (2006). A play in four arenas: how complexity can serve management development. Management Learning , 37(1), 101–123. doi: 10.1177/1350507606058136. Shaw, P. (1997). Intervening in the shadow systems of organizations: Consulting from a complexity perspective. Journal of Organizational Change Management, 10(3), 235-250. doi: 10.1108/09534819710171095. Snowden, D. (2002). Complex acts of knowing: paradox and descriptive self– awareness. Journal of Knowledge Management, 6(2), 100–111. doi: 10.1108/13673270210424639.

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Editorial Note Enzo Scannella, PhD, Co-Editor in Chief Assistant Professor of Banking and Finance, Faculty of Economics, University of Palermo, Italy received April 18, 2012/ accepted May 2, 2012 / published online June 1, 2012 DOI: 10.7350/bsr.a01.2012 - URL: http://dx.medra.org/10.7350/BSR.A01.2012

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I am delighted to take over as Co-editor of the Business Systems Review and to do so with a brilliant team of Associate Editors. We have rounded up a highly qualified Editorial Board. The Business Systems Review is the official publication of the Business Systems Laboratory. It will publish twice a year. There will be also one or more special issues per year. The special issues will be commissioned by the Editor on topics of particular interest, each with a strong Guest Editor. The Business Systems Review aims to provide a place of exchange of ideas for the mutual association of persons with an interest in the systemic approach for business, encourage research from areas of business, and improve public understanding of management and financial problems. Given the scope and mission of the Business Systems Review, we will publish qualitative and empirical papers across all the major fields of management, marketing, banking, and financial research. It will be a specialized forum for the publication of research in the area of general management, innovation management, knowledge management, banking and finance, marketing, economics of organization, and services. The Business Systems Review will publish research and literature review papers, both established and newly developing fields. In particular, the Business Systems Review will focus on: studies that synthesize and evaluate critically the literature in business, management, social science, banking and finance. These papers should examine a theoretical, methodological, or policy issue from the perspective of a particular discipline or from an interdisciplinary perspective; studies that examine important theoretical works and shed light on domestic and international issues; studies that examine important empirical issues, using a different set of data, and different empirical and theoretical frameworks; business case studies that analyse theoretical or empirical issues; paper presented at international or national conferences in the business, management, and finance fields. The Business Systems Review also welcomes cross disciplinary research which examines interaction among different fields that bridges the gap between theory and policy. Three criteria are really important to publish papers in the Business Systems Review. First, papers must advance knowledge, theory, and practice. Second, the content of papers must be accurate. Third, papers must be well written, clear, well organized, and stylistically correct. A paper submitted for publication to the Business Systems Review must be original and not under consideration for any other publications. We particularly encourage submissions of original research papers from research students (especially PhD students) emerging scholars and early career researchers.

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Business Systems Review, ISSN: 2280-3866 Vol ume 1, Issue 1, 2012

In addition, we will seek to attract papers in specialized areas critical to the development of Business Systems Laboratory’s aims and scope. In brief, Business Systems Review takes the approach of broad coverage across all business, management, and finance related areas. The Business Systems Review’s emphasis is on theoretical studies. It strives to be an outlet for your research. Please consider submitting your best work to Business Systems Review. Enzo Scannella Co-Editor in Chief

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Complexity and Systemic Models: Tools to understand and manage crises Premise to the International Symposium: The Economic Crisis. Time for a Paradigm Shift ~ Towards a Systems Approach. Valencia (Spain), January 24-25, 2013

Charles François Honorary President of GESI (Grupo de Estudio de Sistemas Integrados), Argentina Honorary President of ALAS (Asociación Latinoamericana de Sistémica) Norbert Wiener golden medal for Cybernetics, 2007 e-mail: [email protected] Invited article. Received July 27, 2012. Published July 31, 2012 DOI: 10.7350/BSR.A06.2012 – URL: http://dx.medra.org/10.7350/BSR.A06.2012 1. INTRODUCTION

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We sometimes face critical situations and frequently try to handle them without a good understanding of their complexity. A dissociated and even fragmented approach, often rules in our management of politics, economics, education and business. Only some limited aspects are taken into account, out of context and even omitting sometimes very basic features of the affected entity. This reduced approach contaminates also the time dimension. In many cases only short time oscillations are taken into account and extrapolated as trends without considering medium and long term natural and automatic corrections. In such cases so-called human “controls” may turn untimely, incoherent, useless and even damaging. Such critical situations can become worse when resulting from a multiplication or acceleration of interactions. Within this complexity, organizations and structures can emerge spontaneously. They may interfere and interact in unexpected ways and produce a kind of background noise for each other even in international and intercontinental electronic communication. When we busy ourselves with the study of systems and their multiple relations with their environment, we should try to discover and use some efficient ways for their management. If we consider systemic modelisation, we notice the existence and multiplicity of hypercomplex entities and situations, mostly man-made or, at least, widely modified and made more complex by human activities. Examples are the vast economic systems for production and distribution of goods, as well as the numerous and very diverse local, national and transnational ones, private or public, concerned with a wide variety of specific subjects, scientific, technical, economical, political, social, etc… Most of those originally natural and more or less cyclical ones (water, forests, soils, human as well as vegetal and animal populations, etc…), have been widely modified by ever increasing human interferences, deepened in turn by technological progress. An impressive example is the explosive human demography. At the beginning of the 20th Century the human population of the

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planet was 1.650 million people. Presently, we are more than 6 billion, many of whose are living in dire and alarming poverty. Moreover, many other situations are evolving, and mostly worsening: - Local, regional and now global climate change. - Expansion of deserts. - Massive contamination of soils and water. - The probably unsustainable massive use of fossil fuels. - The foreseeable exhaustion during the present century and in many regions of useful sources of water, potable and, or available for irrigation. Obviously, we should urgently attend the need for a better understanding and adequate management of all kinds of complex systems, natural as well as man-modified. This would be possible only through a new conceptual synthesis, in order to gain a general and coherent integration of our enormous, but scattered and globally ill-interconnected specialized knowledge. None of the enormous technological advances of the more recent centuries can free us from the need to respect our basic physical and biological life conditions; our dependence of our vital environment (soils, water, air, vegetal and animal life) and our all embracing social way of living. Nearly the whole of our present technocratic civilization rests on our close and absolute dependency of fossil fuels: coal, oil and gas. We are well on our way to consume within short decades non renewable resources slowly accumulated during geological eons. We do not use even a small part of this geological treasure trove to try to finance and develop new – and for now costlier – sources of energy. We contaminate – evermore massively – continents and oceans. We are on our way to globally warm our planetary atmosphere and modify its composition by the use of fossil fuels, without having any concern for possible, and massive climatic consequences. Formerly, the small traditional rural and urban communities were obeying more stable ways of life. Societies were evolving slowly, or not at all: the forefathers’ knowledge, acquired through long experience, remained valid for their grand- or even great grand children. Old age was viewed as the age of wisdom, at secular scale. However, we have now obviously reached the era of a planetary community, with new ways for learning, knowledge, communication and organization. These unavoidable changes brought disorientation, doubt and disorganization to all traditional societies, particularly so in the socalled “developing countries” (a soothing expression that easily conceals numerous contradictory and even non compatible trends). Of course, not all new situations are complex and unmanageable: urban massive and complex vehicular traffic can be quite well controlled through a system of simple and easy understood rules. However, during the most recent decades, new and intricate problems emerged, as results among others of great urban concentrations, new technologies and numerous new types of undertakings including multiple and variously interacting elements and actors. Many of the resulting changes are not clearly understood – or even perceived! – and, still less, correctly managed. 2. THE URGENT NEED FOR NEW MODELS For anyone worried about the society to which he/she belongs, the need for a new class of models becomes ever more obvious in order to take into account and understand the various aspects of our complex reality. We should accept the consequent necessity and permanent disposition for adaptive change. In fact, occasional and unplanned jumps from one state to

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another will not do. The well-known British cybernetic Stafford Beer, in his famous lecture “The substitute world we do manage” (1973), warned us to become more cautious in our ways to act, guiding us by dubious or even utterly simplified and possibly incorrect models of reality. He urged to admit, that if reality does not accept to conform to our models, what we should do is correct these models in spite of- in Beer´s terms- stamping reality, trying to submit it to our wishes. Beer proposed a continuous process of monitoring and verification of the effects of our action on factual situations. He emphasized that any relation between our perceptions, our modelization and our action should be permanently auto-corrective, according to their effects and the reactions of the entity that we try to manage. This is of course a true and typical cybernetic process of feedback at the mental level. To begin with, we should not let our goals dazzle and confuse our mind. We need to acquire a wider and deeper view of the matter at hand…which in many cases brings us back to common sense. Let us thus consider some examples of the systemic-cybernetic approach:

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a) “The whole is more than the sum of the parts”: this means that any “whole” offers its own emergent properties, which should be discovered and considered. b) “The whole is less than the sum of the parts”: any element incorporated within an organized total entity, loses some of its proper characteristics. Or at least, these remain occult or limited in their effects c) “Structures”: any complex system presents internal structures that correspond to the needs and conditions of its workings (processes). James Miller, the American systemic biologist and pioneer of the International Society for the Systems Sciences (ISSS), stated that any system possesses an “envelope” which separates it- more or less!- from its environment. In his systemic classification he calls it a “boundary”, which is always the locus for any exchanges between the system and its environment. d) “Processes”: a process is a flow through two or more structures corresponding to inputs, internal transformations and outputs. e) “Any action can produce reactions through feedbacks”: .many are obvious, but others are not. It is very important to discover them and evaluate their workings. f) “Feedbacks can be positive or negative” (accelerating or braking processes): there is a frequent complementarity and alternance between both types of feedbacks. g) “Structurating dissipation” (concept introduced by René Bénard and Ilya Prigogine): it considers generation of “forms” as a result of the injection of an excess of energy in a system. h) “Auto-genesis”: this model- introduced by the hungarian systemist Vilmos Csanyi, shows how interconnections among elements formerly loose, may turn from casual to repetitive and finally acquire a functional and permanent character. i) “Web and gregariousness”: this model completes the auto-genesis one. Casual interactions among formerly loose elements, may turn repeated and produce a weblike organization of mutual communication. j) “Growth laws”: lineal, asymptotic, parabolic, hyperbolic and periodic growth, should be clearly identified and distinguished k) “Waddington´s Creode”: this British physicist proposed a general growth curve produced from a set of self-similar curves of shorter periodicity and lesser amplitude. This curve also

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l) m)

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u)

v)

corresponds to the “renormalization equation” introduced by the german mathematician Karl Weierstrass. It describes a global function which integrates a superposition of harmonic ones “Morphogenesis”: the limitative effect of reciprocal interactions among various functions in an a-forming system, tends to transform some processes into permanent ones, generating in turn more or less stables forms. “Systems tend towards dynamic stability” (i.e. homeostasis): Prigogine did establish the general thermodynamic principles of dynamic stability (with his theorem of minimum entropy production). Thus has been eliminated the absolute contradiction that seemed to oppose the 2nd principle of thermodynamics and the progress of complexity in living and social systems. “Adaptability is a superior way of adaptation”: it is a dynamics of successive adaptations. “Principle of required variety”: (this concept has been introduced by Walter Ross Ashby) an entity (system) may be able to maintain its autonomy- i.e. a more or less ample ability to manage itself- only if able to adapt a variety of its states to the variations of its environment. “Threshold of maximum or minimum activity”: any complex entity offers a superior and an inferior level of activity acceptable for its basic processes. “Stress: the concept of critical tension” (i.e. the maximum acceptable one). “Short, medium or long term process”: a repetitive short term process may- through accumulation- produce medium and/or long term effects (within a defined time-scale). “Catastrophes”: this systemic notion was introduced and developed (in mathematical terms) by René Thom. The notion implies “sudden discontinuity” i.e. the sudden jump in the trajectory from a process to another. “Fractals”: the existence of similarities between structures or processes at distinct dimensional scale allows for some previsibility (i.e. a general determinism more or less affected by limited randomness at lesser scales). “Communication”: between an emitter (or various ones) and a receptor (or various ones), it signals the transmission of some type of information (“message”) through some shared system of coded signs. Communication is easily perturbed by “noise”. This can be in principle prevented by “redundancy”, i.e. repetition of the “message”. “Information”: information is generated if and when a signification corresponds to some emitted signal (as much as possible in a bi-univocal way). This implies of course the existence of a stable code agreed among participants in the process of communication

Confucius insisted on the need for “correct designation”. This implies creditworthy data, free of ambiguities or even unconscious doubtful interpretations. In this last case, we should better speak about “disinformation”. As to “models” they are merely conceptual representations of concrete systems: such representations are unavoidably always merely partial and should be used in specific cases and well as defined situations. Any model always necessarily discards some properties of the concrete system. However, and at least, the use of systemic models helps us to avoid the mismanagement of concrete real situations and to acquire a better awareness of the ways our perceptions can lead our understanding astray. For example, members of the Latin American systemic societies (integrated into ALAS – Asociación Latinoamericana de Sistémica and members of the International Society for Systems Sciences (ISSS) and the International Federation for Systems Research (IFSR)) did express, in a message about the global planetary ecological crisis, that

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such crisis is basically the result of our inadequate use and irresponsible administration of planetary and human resources. As systemists, we understand and point out that a better and more global paradigm for governance is urgently needed. Accordingly, we need to urgently revise our specialized and limited views about all human concerns and their place within nature as a whole. Our traditional reductionist, fragmented and merely (so-called) “practical” views and ways are clearly leading us into dead ends, at a more global scale. We definitely should adopt a wider systemic embracing world paradigm and translate it into our practical everyday activities. We should use it to create more advanced and better integrated and more coherent models. Systemic and cybernetic methods are obviously adequate and useful tools for such an endeavor. REFERENCES Ashby,W.R. (1996). Introducción a la Cibernética. Buenos Aires: Nueva Visión. Conway, J.H., A series of articles on “Game of Life” of Conway, by Martin Gardner. Scientific American, from 1970 to 1976. François C. (1976). Markovian models for non-linear complex systems – 3rd European Meeting for Cybernetics and Systems Theory. Vienna François C. (1976b). Systèmes complexes: modélisation intégrale et systèmes markoviens. Cybernetica, 19 (3). 9

Hopkins, F. S. (1974). Prometheans and Epimetheans. The Futurist, 8(3) Letov, A.M.(1969). Stability theory, in Zadeh, L.A., Polak, E. (eds). Systems Theory. New York, McGraw Hill. Mesarovic, M., Macko, D., Takahara, Y. (1970). Theory of hierarchical multilevel Systems. NY, Academic Press. Steinbuch, K. (1961). Die Lernmatrix. Kybernetik, 1(1), 36-45. Thom, R. (1972). Structural Stability and Morphogenesis. NY, Benjamin. Thom, R. (1974). Modèles mathématiques de la Morphogénèse. Paris, Union Générale d´Éditions. Varela, F., Maturana, H.R., Uribe R.(1974). Autopoiesis: The organisation of living Systems: its characteristics and a model. Biosystems, 5, 187-196 Vendryes, P. (1975). Hacia la teoria del hombre. Buenos Aires, El Ateneo. Von Neumann, J. (1956). Probabilistic logics and the synthesis of reliable organisms from unreliable components, in Shannon, C.E. & Mc Carthy, J. (eds.). Automata Studies. Princeton University Press. White, M. (1955) The age of analysis. NY, Houghton Mifflin Co. Wiener, N., Schadé, J.P. (1963). Nerve, brain and memory models. Amsterdam, Elsevier.

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A Test of Strong-Form Efficiency of the Nigerian Capital Market Oke, Micheal Ojo, Ph.D. Department of Banking and Finance, Faculty of Management Sciences, Ekiti State University, Ado Ekiti, Nigeria. e-mail: [email protected]. Corresponding author Azeez B.A. Department of Banking and Finance, Faculty of Management Sciences, Ekiti State University, Ado Ekiti, Nigeria, Received May 28, 2012 / Revised June 21 / Accepted July 3 / published online July 10, 2012 DOI: 10.7350/bsr.a03.2012 – URL: http://dx.medra.org/10.7350/BSR.A03.2012

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ABSTRACT This study tests whether the Nigerian capital market exists in the strong-form efficiency. It is necessitated on the belief that investors and firms can outperform the market. The empirical analysis is done employing the Autoregressive Conditional Heteroscedascity (ARCH) and Generalized Autoregressive Conditional Heteroscedascity (GARCH) models. Data were collected mainly from the Nigerian Stock Exchange, Central Bank of Nigeria Statistical Bulletin and other published sources. The study covers a period from 1986 to 2010. The findings reveal that the Nigerian capital market is weak-form efficient, suggesting that current market price of securities reflect past or historical information. The study recommends among others that the Nigerian Stock Exchange (NSE) should be closely monitored to achieve an optimal maturity level, greed and bad choices should not take the place of risk management capacity and market discipline and the Securities and Exchange Commission (SEC) should take a leading role in regulating abnormal financial activities. Keywords: Nigerian Capital Market, Strong-form Efficiency, Autoregressive Conditional Heteroscedascity (ARCH), Generalized Autoregressive Conditional Heteroscedascity (GARCH) 1. INTRODUCTION Capital market is defined as the market where medium to long-term finance can be raised (Akingbohungbe, 1996). In another direction, Ekezie (2002) noted that capital market is the market for dealings (that is, lending and borrowing) in longer-term loanable funds. Mbat (2001) described it as forums through long-term funds are made available by the surplus to the deficit economic units. It must, however be noted that although all the surplus economic units have the same easy access to it. The restriction on the part of the borrowers is meant to enforce the security of the funds provided by the lenders. In order to ensure that lenders are not subjected to undue risk, borrowers in the capital market need to satisfy certain basic requirement. It has very profound implication for socio-economic development of any nation. Companies can finance their operations by raising funds through issuing equity (ownership) or debenture/bond borrowed

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as securities. Equities have perpetual life while bond/debenture issues are structured to mature in periods of years varying from the medium to the long-term of usually between five (5) and twenty-five (25) years. Capital market offers access to a variety of financial instrument that enable economic agents to pool price and exchange risk. Through assets with attractive yields, liquidity and risk characteristics, it encourages savings in financial form. This is very essential for government and other institutions in need of long-term funds and for suppliers of long-term funds (Nwankwo, 1991). The stock market generally is the centre point of traders, purchasers and sellers who trade in securities of different forms and life spans. When money is parted with, into the stock market, it is done with the aim of generating a return on the capital market. Many investors try to make a profitable return, but also to outperform or beat the market. When a market is operationally efficient, it means there is little or no friction in the trading process (Mabhunu, 2004). Information on prices and volumes of past transactions is widely available and price sensitive information is both timely and accurate, thus information dissemination is fast and wide. Liquidity is such that enables market participants to buy or sell quickly at a price close to the prior (last traded) price. Also, there is price continuity, such that prices do not change much from one transaction to another unless significant new information becomes available. According to the Efficient Market Hypothesis (EMH), an operationally efficient stock market is expected to be externally and informational efficient; thus “security prices at any point in time are an unbiased reflection of all the available information” on the security’s expected future cash flows and the risk involved in owning such a security (Reilly and Brown 2003). Such a market provides accurate signals for resources allocation as market prices represent each security’s intrinsic worth. Market prices can at times deviate from the securities’ true value, but these deviations are completely random and uncorrelated. Prices changes are only expected to result from the arrival of new information. Given that there is no reason to expect new information to be non-random, period-to-period price changes are expected to be random and independent. In other words, they must be “unforecastable if they are properly anticipated, that is, if they fully incorporate the expectations and information of all market participants” (Lo, 1997). It is expected that the more efficient a market, the more random the sequence of its price movements, with the more efficient market being the one in which prices are completely random and unpredictable (Fama, 1965; Lo, 1997). In an efficient market information gathering and information based trading is not profitable as all the available information is already captured in the market prices. This may leave investors with no incentive as to the gathering and analyzing of information, for they begin to realize that market prices are an unbiased estimation of the shares’ intrinsic worth. In the Nigerian context the capital market has opened the floodgate to relatively inexpensive fund surpassing the possibility of self- financing available to indigenous enterprises. Such funds are usually used for expansion of existing business or to cushion the effect of inflation so that businesses may continue as going concerns. It also affords indigenous enterprises and entrepreneurs the opportunity to be introduced into the economy in general through entry into the securities market. This enables shares that have been privately held to be offered to the general market or international markets for inflow of foreign investment. The entering of an indigenous company into the capital market enhance its prestige and reputation, especially its products and credit worthiness in the eyes of the public as conferred upon it by the new status. (Bayero, 1996). The capital markets in Nigeria create a free entry and exist for investors. It is a known fact private company that it is not easy for an investor (shareholder) to with draw capital invested

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without upsetting the company capital structure. But for public quoted company, it does work not like that. As long as an investor’s broker can find a prospective investor to buy the clients’ shares the process is done. One of those important functions of the capital market is to encourage indigenous enterprises to develop its peculiar technologies, through accessibility to funds and expertise through international connection. This it has achieved tremendously. Moreover, most of the Nigeria enterprises benefited from the implementation of the Nigeria Promotion Acts and the privatization policies through the market. Both policies promoted indigenous enterprises which are the main engine of economic growth and development in an economy. Despites the capital market laudable performance and benefits, it is still beclouded with some weakness in Nigeria. The bureaucratic system of the Securities and Exchange Commission is a hindrance to smooth processing of application submission is a hindrance to smooth processing of application submitted to it. The private sector to which most enterprises belong is not used to the “leap and tumble” system of the public sector, operates by leaps and bounds. The fee charge by the exchange are unreasonably high and constitute a great burden on enterprises/companies for whose sake the second tier Securities markets (SSM) was established in 1985. If it is realized that the engine of economic growth and development in Nigeria rest in this sector, which is endowed with the capacity to create jobs for the unemployed, then the charges should be moderate and not appear to be punitive. Likewise the cost of hiring the services of stock brokers, registrars and issuing houses in the capital markets is getting higher every now and then, but their efficiency is not commensurate to the high cost, this gives room for complaints and mistrust. The imposition of all forms of taxes by the three tiers of government on companies and businesses is especially discouraging, and add to the number of weakness that undermine the capital market as the engine room and pivot for economic growth and development in Nigeria. This paper seeks to test specifically for the strong form efficiency of the Nigerian capital market. The study is motivated on the need to ascertain whether an investor or frim can outperform in the Nigerian capital market and if previous or current information influences market prices. The study reviewed the period from 1986-2010. The rest of the paper is structured as follows: section two provides the literature review, section three discusses the research method, section four presents the empirical results and discussion and section five provides the conclusion and recommendations. 2. LITERATURE REVIEW 2.1 The Efficient Market Hypothesis {EMH} Efficient Market Hypothesis {EMH} asserts that in an efficient market, prices at all times fully reflect all available information that is relevant to their valuation (Fama, 1970]. EMH argues that competition between investors seeking abnormal profits drives prices top their “fair value”. This implies that prices should incorporate information in the market. The ability of a stock market to incorporate information into prices determines its level of efficiency. Fama [1970] stated that the sufficient but not necessary conditions for efficiency are; there are no transaction costs in trading securities, all information is costless available to markets participants and all agree on the implication of current information for the current price and distribution of future prices of each security. The EMH can more specifically be defined with respect to the information item available to market participants. Fama (1970) classified the information items into three levels depending on how quickly the information is impounded into price; (1) weak-form EMH (2) semi-strong form EMH, and (3) strong-form EMH. However, studies over the years have showed

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that concept of Efficient Market Hypothesis may almost certainly be false due to various abnormalities and anomalies (Malkiel 2003, Schwer 2003 and Shiller 2003), such anomalies include the evidence of volatility of returns on investments (Lo and MacKinlay 1990), size effect (Banz 1981 and Reinganum 1981), the weekend effect (French 1980), the value effect (Basu 1977) and the momentum effect (Fama and French 1996) among others. 2.2 The Strong-form EMH In its strongest form, the EMH says a market is efficient if all information relevant to the value of share, whether or not generally available to existing or potential investors, is quickly and accurately reflected in the markets price. It is the most satisfying and compelling form of EMH in a theoretical sense, but it suffers from one big drawback in practice. It is difficult to confirm empirically as the necessary research would be unlikely to win cooperation of the relevant section of the financial community insider declares. The financial points hold in the strong-form EMH: I.

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Share prices reflect all information and no one can earn excess returns.

II.

To test for the strong form efficiency, a market needs to exist where investors cannot consistently earn excess returns over a long period of time. When the topic of inside trading is introduced where an investor trades on information not yet publicly available. The idea of a strong-form market seems impossible.

III.

If there are fund managers who have consistently beaten the market, then it cannot be described as being strong-form efficient. Common sense and empirical evidence suggest that stock markets are unlikely to be strong form efficient.

2.3 The Semi-strong form EMH In a slightly less rigorous form, the EMH says a market is efficient if all relevant publicly available information is quickly reflected in the market price. If the strong form is theoretically the most compelling, then the semi-strong form perhaps appeals most to our common sense. It states that no investor can earn excess returns from trading rules based on publicly available information .If the market is semi-strong form efficient, then stock price reacts so fast to all public information that no investor can earn an above normal return (higher than the market or return on the S&P 500 index) by acting on this type of information. Tests of semi-strong form efficiency have shown that no investor can earn an above normal return on publicly available information such as annual accounting reports block trades(Fama, Fisher, Jensen, and Roll,1969), earning announcements, stock split announcements, dividend announcements, and repurchase of stock announcement .Example of public information include stock splits, dividend increases, and repurchases .For example, if an individual buys the stock on the announcement date and still does not make an above normal return, the market is semi-strong form efficient. Under the semi-strong form EMH; the following are assumed: I.

Share prices adjust instantaneously and in an unbiased manner to publicly available new information so that no excess returns can be earned by trading on that information.

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II.

Semi-strong form efficiency implies that fundamental analysis will not be able to produce excess return.

III.

To test for it, the adjustments to previously known news must be of a reasonable size and must be instantaneous. If there are consistent upward or downward adjustments, it would suggest that investors had interpreted the information in a biased manner and hence in an inefficient way.

2.4 Weak-form EMH In the least rigorous form, the EMH confines itself to adjust one subset of public information, namely historical information about the share price itself. New information must by definition be unrelated to previous information; otherwise it would not be new. It follows from this that every movement in the share price in response to new information cannot be predicted from last movement or price. The future price cannot be predicted from the last movement or price. The future price cannot be predicted from a study of historic prices. As for the weak form EMH, it states that:

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I.

No excess returns can be earned by using investment strategies based on historical share prices or other financial data.

II.

Weak form efficiency implies that technical analysis will not be able to produce excess returns.

III.

To test the weak form efficiency, it is sufficient to use statistical investigations in time series data of prices. In a weak form efficient market, current share prices are the best, unbiased, estimate of the value of the security. News is generally assumed to occur randomly, so share price changes must also therefore be random.

2.5 Review of Previous Studies Information plays a very important role in security markets. It aids in the establishment of security prices and, with these prices, helps the individual investor in the selection of an optimal portfolio. The relationship between security prices and information made available to the market has been explained by the efficient market theory (EMT), which states that publicly available information is always fully reflected in share prices. Any new information of economic value subsequently becoming publicly available is instantaneously impounded in an unbiased manner. This is the semi –strong form of the EMH. The primary role of the capital market is the allocation of ownership of an economy’s capital stock. In general terms the ideal is a market in which prices provide accurate signals for resource allocation, that is, a market in which firms can make production investment decisions, and investors can chose among the securities that represent that ownership of firms’ activities under the assumption that security prices at any time “fully reflect” available information is called “efficient”. As already mentioned economists have undertaken considerable research into EMH in developed market and reach a consensus on the validity of the weak and semi- strong forms of EMH. On the other hand, few studies of EMH in emerging markets have been carried out, and the conclusions reached in those studies have been mixed. Dickinson and Muragu (1994) studied the weak- form efficiency of the Nairobi stock market and concluded that the market is not efficient; Osei (1998) arrived at a similar conclusion in his study on the efficiency of the Ghana Stock Market. Matomi (1998) examined the behaviour of the

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Namibian stock market. Overall, there is more evidence of inefficiency than efficiency from studies on African capital market. Similarly, the few studies of market efficiency in the Nigerian capital market have generally focused on test of the weak- form efficiency. These include Ayadi (1984), Omole (1997) and Adelegan (2004). Most of the studies conclude that the Nigerian stock market is weak- form efficient. Tests on the semi- strong form are even fewer. Using monthly prices, Olowe (1998) investigated the reaction of the Nigerian stock market to stock splits. His study centred on monthly data of 86 stock splits involving 59 quoted companies between 1981 and 1992, and found that statistically and economically abnormal returns could earn on the Nigerian stock market. Oludoyi (1999) looked at the impact of earnings announcements on share prices In Nigeria around annual general meeting (AGM) dates between 1986 and 1994. His study, which was undertaken in the period before the cap on share price movement was expanded, used weekly stock prices and movements for a period of 21 weeks around the event window. He showed that the Nigerian capital market is not efficient in the semi- strong form as share price still drift ten weeks after corporate earnings have become public information. Three have been several economic policy changes affecting the stock market since then, however, such as the promulgation of the Nigeria Investment Promotion Decree of 1995, which fully opened the stock market to foreign investors and the abolition of the capital gains tax in 1998. Many studies have also established that the announcements of unexpected changes in divided payments provide information affecting the market values of the companies making the changes especially in UK and USA. These include: Petti, 1972; Charest, 1978; Bernard and Thomas, 1990; Healy and Palepu, 1988; Asquith and Mullins, 1983; Christie, 1990, Dhillon and Johnson, 1994; Michalely et al; 1995, Amihud and Murgia, 1997 and Naranjo et al; 1998. The results of most of these studies showed that market reaction to dividend announcements is biased. One strand of literature found evidence for immediate and post announcement market drift as a result of dividend changes (Healy and Palepu, 1988; Asquith and Mullins, 1983; Michalely et al. 1995).Healy and Palepu (1988) examined companies that initiated dividend payments for the first time, as well as those that completely omitted their dividend payments and found significant two-day abnormal stock return of3.95% and -9.5%, respectively. Overall, this research found that the short-run price impact of dividend omissions is negative and that of initiations is positive. Michalely et al. (1995) studies markets reactions to dividend initiations and dividend omissions in the USA and found that those omission announcements are associated with a mean price drop of about 70%and initiations with a price increase of over 30% around the event day. These studies indicate that dividend changes convey information from corporate decision makes to the investing public. Some other studies also studies also provide evidence to support post dividend announcement drift. (Michalely et al, 1995: Charest, 1978; Christie, 1990). Charest (1978) found small but significant price drift after dividend changes. That is, excess returns are positive in the months following the announcement of a dividend increase, but are negative in the month following the announcement of a dividend cut. The conclusion was supported by Christie (1990). Michaely et al. (1995) investigated dividend omissions and initiations to see whether there are subsequent excess returns after the market has had a chance to react to the announcements of a change in divided policy. They found significant long term drifts following announcements of initiations and omissions. Prices of firm that omit dividends drift down after the immediate reaction to the omission, and prices of firms that initiate dividends drift up. In 22 out of the 25 years examined in the study, the combined initiating and omitting firms’ drift results in abnormal profit. Bernard

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and Thomas (1990) also advanced evidence for the post –earning announcement drift (or underreaction). This research showed that when firms made surprising quarterly earnings announcements, prices continued to move in the some direction for the next three quarters, especially on the days surrounding the next quarterly earnings announcement. Since dividend omissions and initiations are similar to earnings surprises, one might expect a similar drift in the prices following a change in dividend policy. A second strand of literature provides some reasons to expect exactly the opposite pattern of prices. Numerous studies found evidence for over-reactions or mean reversion in prices. (Brenner and Sweeny, (1991) documented that those firms on the New York Stock Exchange (NYSE) that exhibit the most extreme price movement tend to display mean reverting excess returns in the subsequent time period. This tendency is stronger for losers than for winners. Similarly results were obtained by other researchers in the USA and in other markets for different time periods. The literature on why one might expect excess returns following a dividend initiation or omission is in support of the clientele effect. This research showed that dividend initiations or omission would give rise to excess returns if it causes a change in the type of stockholders owning the company. The clientele effect may occur because some individual stockholders prefer cash payments, while others dislike cash dividends for tax reasons (Black and Scholes, 1974). Similarly, some institutions may have a preference for dividends or be required by chart to own stock only in dividend paying companies. Findings of some studies of the effect of dividend changes on stock and bond prices have led to a distinction between the information content and wealth redistribution hypothesis. Information content implies that when a dividend increase is announced, bond price should increase, while a dividend reduction is expected to bring about a reduction in bond prices. Handijinicolaou and Kalay (1984) analyzed bond returns and dividend changes and reported that bond prices react to dividend reductions but are not affected by dividend increases. They argue that their data support the information content hypothesis. Woodridge (1983) obtained similar results. Thus, the bulk of the existing literature supports the information content hypothesis, and the evidence for wealth transfer is scanty. Wealth redistribution implies that bond prices should fall when dividend increases are announced, and this will in turn lead to wealth redistribution between bondholders and stockholders. Dhillon and Johnson (1994) analyzed stock and bond prices and dividend changes and reported that there was a positive reaction to large dividend increases in the stock market and a negative price reaction in the bond market, which is consistent with the wealth redistribution hypothesis. Researchers have used several approaches to test for evidence of the dividend signaling effect. Some studies use actual reported earnings after dividend announcements to proxy for the change in expected future cash flows and their conclusions are mixed. Healy and Palepu (1988) report that companies have significant changes in their annual earnings, in the year of the announcement of dividend changes and at least one year thereafter. Bernartzi et al, (1997) find no change in actual reported earnings after dividend changes and conclude that dividend signaling does not appear to be occurring for the companies in their sample. However, the dividend signaling hypothesis holds that a change in dividend signals a change in current expectations of future cash flow and not necessarily changes in future realizations of them. Instead of using changes in actual future realizations of earnings as a proxy for changes in expectations of future cash flow, some authors use a more direct proxy. Yoon and Starks (1995) use analysts’ earnings forecasts to test the signaling power of changes in dividends. This is more direct measure of changes in current expectations because earnings analysts specialize in helping

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the market set those expectations. They reported that unexpected changes in dividends are positively related to abnormal earnings forecast revisions. Another strand of literature made a distinction between the effects of dividend announcement on share prices of announcing firms (announcers) as well as share prices of non-announcers. Two main distinctions underpin the two alternative types of information transfers documented in the literature. The first refers to industry-wide information commonalities that engender a contagion hypothesis. The industry-wide commonalities influence is expected to affect all firms within that industry in a directionally similar manner. In contrast, the competitive shift scenario indicates changes in competitive structure which implies that within a given industry, some firms will benefit while others will lose. Accordingly, the contagion hypothesis through industry-wide influences predicts positive correlated information transfers and therefore a positive price impact for non-announcing firms in the same industry. In contrast, the competitive hypothesis predicts negative correlated information transfers and hence a negative intra-industry price impact (Otchere, 2002). Some researchers have explored the possibility that a company’s announcements could affect the market value of its competitors. The evidence generally indicates an industry-wide information transfer via announcements previously thought of as company specific. Lang and Stulz (1992) report that bankruptcy announcements reduce the market value of rivals over a two-day announcement period by 1% on average-a phenomenon termed the contagion effect, as the rival companies have caught an infectious disease from the announcing company. This suggests that changes in dividends may provide important information regarding rivals’ cash flow in addition to potentially signaling inside information about cash flows of announcing companies. Some other researchers have structured the potential linkage between the information conveyed by changes in dividends and the effect that is transferred from one company to its rival. Firth (1996) examines the effect of relatively large dividend changes on the stock market reactions and earnings forecast revision of announcing companies and their rivals. His results show that dividend increases produce a significant positive effect on stock prices while dividend reductions produce negative effects on stock prices and forecast revisions of both the announcing companies and their rivals. On the other hand, Laux et al. (1998) study the stock market reactions of rivals to dividend changes by announcing companies and are unable to confirm Firth’s findings. Caton et al. (2003) examine whether information embedded in dividend omission affect the cash flow expectations of rivals. They examine abnormal stock return and abnormal earnings forecast revisions of rivals surrounding announcement s of dividend omission by announcing companies (announcers). Their result are consistent with those of Firth (1996) and inconsistent with that of Laux et al. (1998) .They found both significant negative stock returns and significant negative earnings forecast revisions for rivals to dividend omissions of announcers. The regression results reveal a significant positive relationship between stock return and earnings forecast revisions of rivals. 3. RESEARCH METHOD This study hypothesized that the Nigerian capital market is not strong-form efficient. The econometric techniques are the Autoregressive Heteroscedacity (ARCH) introduced by Engel (1982) and the Generalized Autoregressive Conditional Heteroscedacity (GARCH) introduced by Bollerslev (1986) will be employed to investigate the strong-form efficiency of the Nigerian Stock Market. The appeal of the GARCH (1, 1) model is that it allows for a time-variant conditional variance and non-linearity in generating mechanism. Also it captures both volatility

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clustering and unconditional return distribution with heavy tails. Secondary sourced data were utilized for this study. These sources involve annual market capitalization on the Nigerian stock exchange, government development stock, annual all share index and the value of transaction at the Nigerian stock exchange between 1986-2010. The data were collected from CBN Statistical Bulletin, data from Nigerian Stock Exchange, Textbooks, Journals, and from the Internet. The estimation procedures are to determine whether the Nigerian Capital Market is strongly efficient is or not, or in case of overshooting this can be seen as the presence of outrageous level of volatility. The presence of volatility is determined by summing up the root of the autoregressive model of α+β. This is referred to as the rule of the thumb, in this case if: α+β1, no efficiency or inefficient market

3.1 Model Specification The analytical methodology consists of a system of equation which is made up of endogenous and exogenous variables specified as follows: Model 1 MC=f (GDS, VT, ASI)………………………............... ….….(1) MC=β₀+β₁GDS+β₂VT+β₃ASI+µ…………………………... (2) 18

σt2=ῶ+α∑²t+βσ²t-1……………….………………………… (3) Model 2 ASI=f (GDS, MC, VT)……………………………………….. (4) ASI=β₀+β₁GDS+β₂MC+β₃VT+µ….………………………… (5) σ²t=ῶ+α∑²t+βσ²t-1………………………………………….... (6) Where; MC=Market Capitalization GDS=Government Development Stock VT=Value of transaction at the stock exchange ASI=All Share Index σ²t=Conditional Variance ∑²t=ARCH (news about volatility from previous period) σ²t-1=ARCH term (variance of last period forecast) α= the Coefficient of ARCH β= the Coefficient of GARCH β₀, β₁, β₂, β₃, ῶ are parameters and µ=Stochastic error term

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3.2 Limitation of methodology of the Study Although the GARCH model employed in this study has the advantage of measuring volatility in financial time series such as the stock market, there has being a serious challenge which pose a limitation to its usage since its discovery. This limitation has to do with all kind of variation on the original model; however the GARCH (1,1) model which allows for a time-variant conditional variance and non-linearity in generating mechanism is employed for this analysis. 3.3 Expected Result For the Null Hypothesis to be valid or accepted, it is expected that the summation of the coefficient of ARCH (α) to the coefficient of GARCH (β) to be less than one; meaning that the Nigerian capital market is not strongly efficient. Mathematically, this can be represented as: α+β>0.5 4. EMPIRICAL RESULTS AND DISCUSSION The models formulated for the study revealed the following: Model 1; shows market capitalization to be the explained variable, while government development stock, value of transaction and all share indexes are the explanatory variable. Model 2; shows all share index to be the explained variable, while government development stock, market capitalization, value of transaction are the explanatory variable. 19

4.1 Empirical Results of the First Model (Analysis of the ARCH and GARCH Results) Market capitalization (MC) is used as the dependent variable, while government development stock (GDS), the value of transaction (VT) and all share index (ASI) on the Nigerian stock exchange are used as the independent variables. From the estimated results: The coefficient of ARCH (α) is given as 0.849742 The coefficient of GARCH (β) is given as -0.088944 The summation of α and β, α+β=0.760798 Since the summation of the two coefficients is greater than 0.5, but less than 1, we therefore say that the Nigerian capital market is not strongly efficient. Rather we say it support the weak form efficiency. Test for the Analysis of R² The R² which measures the goodness of fit of the model is given as 0.920831 which implies that about 92% of the total variation in the dependent variable is being explained by the v variation in the independent variable, while the remaining 8% is explained by the error term. Test for the Overall Significance of the Model 1 (F-Test) MC=β₀+β₁GDS+β₂ASI+β₃VT H₀:β₁=β₂=β₃=0 the model is not overall significant H₁:β₁≠β₂≠β₃≠0 the model is overall significant From the estimated results, F-statistic=34.89356 while the F-tabulated is 3.07. We therefore reject the null hypothesis and conclude that the model is overall significant. The Durbin-Watson test for autocorrelation also shows that there is no autocorrelation.

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4.2 Empirical Analysis of the Model 2 (Analysis of the ARCH and GARCH Results) Here, all share index (ASI) on the Nigerian stock exchange is used as the dependent variable. While, government development stock (GDS), market capitalization (MC), and the value of transactions (VT) are used as the independent variables. From the estimated results: The coefficient of ARCH (α) is given to be 1.129768 The coefficient of GARCH (β) is given to be -0.227140 The summation of α and β, α+β=0.902628 Since the summation of the two coefficients is greater than 0.5, but less than 1. Therefore say that the Nigerian capital market is efficient only in the weak form, but not in the strong form. Test for the Analysis of R² The R² which measures the goodness fit of the model is given as 0.885623 which implies that about 89% of the total variation in the dependent variable is being explained by the independent variables, while the remaining 11% is explained by the error term. Test for the Overall Significance of the Model 2(F-Test) ASI=β₀+β₁MC+β₂GDS+β₃VT H₀=β₁=β₂=β₃=0; the model is not overall significant H₁≠β₁≠β₂≠β₃≠0; the model is overall significant

20

From the estimated result, F-statistics is given as 23.22904 while the F- tabulated is 3.07, thus we reject the alternative hypothesis. The Durbin-Watson test for autocorrelation also confirms the absence of autocorrelation.

4.3 Discussion of Findings In both models, the analysis of ARCH and GARCH results shows that the summation of the two coefficients is greater than 0.5 but less than 1. The R² which measures the goodness of fit of the models were considerably high in both models and this means that the regression line gives a good fit to the observed data. The F-test indicated that the models were overall significant, while the Durbin Watson test for autocorrelation revealed that the models are free from autocorrelation. This implies that the Nigerian Capital Market is not strong form EMH as there is randomness in the market. The main contribution of this study to the existing knowledge is that, the empirical findings of the study revealed that the Nigerian capital market is weak efficient as a result of some crises witnessed in the market in the past few years, which has given rise to declining investors’ confidence, declining share value, rising malpractices, crisis-ridden market and declining all share index, declining market capitalization among others. It must be noted that the major indices used in measuring the performance of any market include but not limited to market capitalization and all share index. Though, in recent times the Nigerian capital market has been recording consistent strong growth and has joined the league of emerging markets with best returns to investors. Reasons for this include the massive funds availability following the recapitalization and consolidation of the banking sub-sector as well as increasing awareness of the high returns that the market has been offering to investors. The heightened market upsides, which is largely a consequence of banking sub-sector recapitalization-induced and liquidity-driven demand pressure provided some

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alternative to keeping money in commercial banks where the interest rates (returns) are usually much lower. A closer look that the market today depict that whatever gain the NSE had recorded, have almost been wiped out within two years of the global financial crisis. 4.4 Implication of Findings

21

Overall results from the study suggest that the NSE is not efficient in the strong-form, but only efficient in the weak-form. The acceptance of weak-form efficiency is consistent with the studies of Olowe 1999, Ayadi (1983) and Amoo and Raji (2006). While Olowe used a set of data consisting of an end of the month quoted stock prices of 59 randomly period from January 1981 to December 1992 on the Nigeria stock exchange and employing a sample autocorrelation test, Ayadi employed a non-parametric tests in testing the hypothesis that successive weekly price changes are independent in a sample of 30 quoted companies on the Nigerian stock exchange. Amoo and Raji (2006) on the other hand market focused their study on market indices in local currencies rather than prices of individual stocks and employed both parametric and nonparametric test in determining the efficiency of the Nigerian stock. Even though this study adopts a unique approach, the finding is consistent with previous studies. A major economic implication of this evidence for investors of the NSE is that stock returns are not predictable, in the short horizon, either from historical returns or from volume traded. On the other hand, it is also possible for the investors to beat the market based on privately available information with them. For the firms, it implies that the securities of firms cannot outperform the market and the present market price is more or less a true reflection of the present situation of their security. 5. CONCLUSIONS AND RECOMMENDATIONS The study tested whether the Nigerian capital market is strong-form efficient. Using ARCH and GARCH, the main finding emerging from this study indicates that the Nigerian capital market is weak-form efficient, which led to the acceptance of the null hypothesis. This signifies that the capital market follows the random-walk hypothesis, implying that current stock prices fully reflect historical information. The policy implications of this analysis are that the NSE, as an emerging market, must be closely monitored to achieve an optimal maturity level. Greed and bad choices should not take the place of risk management capacity and market discipline. Investors must be aware that, in inefficient stock markets, heavy gains are just as likely as heavy losses. Furthermore, the Securities and Exchange Commission should take a leading role in regulating abnormal financial activities. In the meantime, an inefficient market could suffer over inflated stock prices, speculation, and insider trading, all potentially intensified by herding behaviour. Several policy challenges need to be confronted to enhance the efficiency of the NSE, including (and not limited to): − Increase market activities through reduction in transaction costs and increase in membership of the NSE. − Establishing a stock exchange news service, which will be responsible for early, equal and wide dissemination of price sensitive news such as financial statements and other information that are material to investors’ decision. This will ensure that participants and investors have equal access to high quality and reliable information.

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− Minimize institutional restriction on trading of securities in the Market. This will allow the market to flow as a deregulated market. − The NSE and SEC also need to strengthen their regulatory capacities to enhance market discipline and investors’ confidence. This will involve training personnel to enforce financial regulations, perform market surveillance, analytical and investigative assignments. − Improvements in the trading system i.e. the NSE should adopt advanced trading technology. REFERENCES Adelegan, O.J. (2004). How efficient is the Nigerian stock market? Further evidence. African Review of Money, Finance and Banking, 143–65 Akingbohungbe, S. S. (1996). The Role of the Financial System in the Development of the Nigerian Economy. Paper Presented at a Workshop Organized by Centre for Africa Law and Development Studies. Amihud, Y. & Murgia, M. (1997). Dividend, taxes and signaling: Evidence from Germany. The Journal of Finance, 52(1), 397–408. Amoo, B.A.G. and Raji, C.J. (2006). Analytical Framework and Empirical Analysis of Transaction Costs and Efficiency in Nigerian Capital Market. Central Bank of Nigeria: Research and Statistics Department. 22

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Reinganum, M.R. (1981). Misspecification of capital asset pricing: empirical anomalies based on earnings’ yields and values. Journal Financial Economics 9(1), 19-46 Schwert G.W. (2003). Anomalies in market efficiency. In Costantinides, Harris, Stulz (Eds.). Handbook of Economics of Finance. Elsevier Science Shiller R.J. (2003). From efficient market theory to behavioural finance. Journal of Economic Perspective. 17(1), 83-104 Woodridge, J.R. (1983). Dividend changes and security prices. Journal of Finance, 38(5), 16071615. Yoon, P.S. Starks L. T.. (1995). Signaling, investment opportunities, and dividend announcements. Review of Financial Studies, 8(4), 995–1018.

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APPENDIX COMPUTATION OF DATA

26

YEAR

MC (N’000)

GDC (N’000)

VT (N’000)

ASI (N’000)

1986

6800

6.2

497.9

1,797.80

1987

8200

5.7

382.4

2,123.00

1988

10000

13.7

850.3

2,529.70

1989

12800

8.0

610.3

3,286.40

1990

16300

33.9

225.4

5,083.90

1991

23100

37.2

242.1

8,059.40

1992

31200

37.2

491.7

11,172.20

1993

47500

37.2

804.4

14,748.30

1994

66300

32.1

985.9

22,958.70

1995

180400

1.1

1838.8

45,781.40

1996

285800

23.5

6979.6

71,461.70

1997

281900

0

10330.5

91,663.10

1998

262600

428.9

13571.1

71,542.50

1999

300000

1146.6

14072

63,170.30

2000

472300

115.7

28153.1

80,414.10

2001

662500

115.7

57683.8

122,220.90

2002

764900

115.7

59406.7

139,582.40

2003

1359300

0

120402.6

186,718.70

2004

2112500

0

225820

296,863.80

2005

2900100

622.4

262935.8

274,520.60

2006

2900100

439.15

470253.4

304,122.60

2007

13294600

420.3

1076020.4

585,279.70

2008

95630000

494

603069.9

605,096.42

2009

7030800

451.2

2149343.7

277,098.55

2010

9962800

455.2

1276144.7

489,158.20

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Imbibing Social Entrepreneurship in Biotechnology Mousumi Majumdar, Ph.D. Vanguard Business School, Bangalore. India. e-mail: [email protected]. Vasanth Kiran, Ph.D. Vanguard Business School, Bangalore. India. e-mail: [email protected]. Corresponding author received June 7, 2012 / revised July 12 / accepted July 17 / published online July 23, 2012 DOI: 10.7350/BSR.A04.2012 – URL: http://dx.medra.org/10.7350/BSR.A04.2012

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ABSTRACT We are in the era of globalization where innovation in every field is essential due to the changes in the society and continuous demands for the betterment of life. In such a climate around, one needs to be creative, selfless, have qualities of businessman and be scientific in thoughts. An entrepreneur who works for the welfare of the society without profits as a sole motive is a social entrepreneur. Biotechnology as such is the field which has grown tremendously over the years now and has helped people spot a ray of hope with its applications in the field of Medicine, Agriculture, Food, Industrial and many more. We found out that there is large scope and need for social entrepreneurs in this sector who can contribute remarkably to the society. This paper peaks into the topic to show the need of social entrepreneurs in Biotechnology field and how it can bring about sustainable development. Keywords: Biotechnology, Social Entrepreneurship, Sustainable Development, Environment, Agriculture, Medicine. “How selfish soever man may be supposed, there are certainly some principles in his nature, which interest him in the fortunes of others, and render their happiness necessary to him, though he derives nothing except pleasure from seeing it.”. Adam Smith. (1761). The Theory of Moral Sentiment. Edinburgh: A. Millar. p.1 1. INTRODUCTION Biotechnology, globally recognized as a rapidly emerging and far-reaching technology, is aptly described as the “technology of hope” for its promising of food, health and environmental sustainability by Department of Bio-technology, Government of India. The recent and continuing advances in life sciences clearly unfold a scenario energized and driven by the new tools of biotechnology. The biotechnology revolution is “something much broader than genetic engineering. What we are living through today is a revolution in the underlying science of biology” (Fukuyama, 2002, p. 19). Innovation happens, every nano second in all the corners of the world. Biotechnology can deliver the next wave of technological change that can be as

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radical as it could and even more pervasive than that brought about by IT (Henderson, 2007). Generating employment, creating intellectual wealth, expanding entrepreneurial opportunities, augmenting industrial growth are few of the compelling factors that warrant a focused approach for this sector resulting in benefit to the society in large. Biotechnology is a technology with knowledge drive, which needs to be driven by a constant flow of new ideas and innovative concepts for the development of new tools in research, new processes for manufacturing and innovative business models. But, the progress of biotechnology as a successful sector or industry throws many challenges related to research and development (R&D) which is an integral part, creation of investment capital, technology transfer and absorption, patentability and intellectual property rights, price affordability, regulatory issues and public confidence. There are two key factors to bear in mind is: affordability and accessibility to the products of biotechnology. Policies that strike a balance between sustaining innovation and facilitating technology diffusion need to be put in place. The strength of a biotechnology company lies in scaling up number of proven technologies, diagnostics, vaccines, products, and processes for fine-tuning and large-scale production says XI Five Year Plan Report, Government of India while again the ability of accessibility and affordability is questioned. Indian biotechnology industry is strong in product development and marketing for commercial benefits, however still the challenge remains in building infrastructure to take up research and development (R&D) in the niche areas like molecular modeling, protein engineering, drug designing, synthetic biology, immunological studies, preclinical studies, stem cell studies, clinical trials etc. The two major areas of biotechnology which is capturing the attention of the world are industrial biotechnology and medical biotechnology. 28

1.1 Industrial biotechnology. At present, a wave of biotechnology – industrial biotechnology – is strongly developing. Industrial biotechnology (also referred to as white biotechnology) uses biological systems for the production of useful chemical entities. This technology is mainly based on bio catalysis and fermentation technology in combination with recent breakthroughs in the forefront of molecular genetics and metabolic engineering. This new technology has developed into a main contributor to the so-called green chemistry, in which renewable resources such as sugars or vegetable oils are converted into a wide variety of chemical substances such as fine and bulk chemicals, pharmaceuticals, bio-colorants, solvents, bio-plastics, vitamins, food additives, bio-pesticides and bio-fuels such as bio-ethanol and bio-diesel. The application of industrial biotechnology offers significant ecological advantages. Agricultural crops are used starting raw materials, instead of using fossil resources such as crude oil and gas. This technology consequently has a beneficial effect on greenhouse gas emissions and at the same time supports the agricultural sector producing these raw materials. Industrial biotechnology frequently shows significant performance benefits compared to conventional chemical technology. Focus in industrial biotechnology will be on reducing chemical and toxic load in our effluent streams, developing non-fossil fuels that are eco-friendly and developing green technologies in Industrial processing. a. Encourage public-private partnership to promote investment in this sector. b. Promotion of industrial biotechnology in strategic areas of manufacturing and developing green technologies.

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1.2 Medical Biotechnology Human beings have been using nature and its products throughout history. We can define biotechnology as the use of living organisms or parts of them to provide goods or services. Medical biotechnology is applied to the diagnosis or treatment of a disease (Bhardwaj and Macer, 2003). Use of technology in living organisms has resulted in great innovations in which the role of Medical Biotechnology has been pivotal. Medical biotechnology offers a significant possibility for Indian industry to establish a strong pharmacy sector, a growing number of small and medium biotechnology companies, a large network of universities, research institutes, and medical schools and low cost of product evaluation. The medical biotechnology sector annually contributes over 2/3rd of the biotechnology industry turnover (Department of Biotechnology, Government of India, 2010). The Indian vaccine industry has highlighted India’s potential by emerging as an important source of low cost vaccine for the entire developing world. Further, economic opportunities through contract research and manufacturing through global partnerships are large if supported by enabling government policies and incentives. 2. OBJECTIVE OF THE STUDY

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As the world’s largest democracy with more than half the population below middle class, there are many infrastructural problems that face developing countries, such as bureaucratic structures, corruption, and lack of universal health care access. Above all the lack of funds for medical care experienced by so many people is dominant for a developing country and limits the choices open to its citizens (Azevedo and Cerqueira, 2002). As United Nations (UN) Secretary General Kofi Annan has rightly pointed out in the WEHAB Initiative (2002) that water and sanitation, energy, agricultural productivity, biodiversity and ecosystem management, and health are the five priority areas which are directly connected to the sustainable development of the country. These areas can develop through the technological uplift in the field of Biotechnology. Again, social entrepreneurs have a direct role to play in these fields for the betterment of the society. The objective of this study is to show the importance of social entrepreneurs to get imbibed in the field of biotechnology and become the real change makers of the society. The paper is organized as follows. Section 3 discusses how biotechnology sector leads to sustainability followed by the performance of this sector in India in section 4. Section 5 describes the social entrepreneurship as the solution. Section 6 provides the policy recommendations. Section 7 concludes. 3. BIOTECHNOLOGY LEADING TO SUSTAINABLE DEVELOPMENT The Biotechnology is the science that leads to sustainable development. Top Indian policy makers argue that biotechnology will provide food security to the hungry (Sharma, 2003) but do not explain as to why should hunger exist at all in India with its overflowing food stocks, if the issue was only supply! 3.1 Ensure agricultural competitiveness Biotechnology is necessary to maintain our agriculture competitiveness and make it remunerative. It is also essential to achieve nutrition security in the face of major challenges

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such as declining per capita availability of arable land; lower productivity of crops, livestock and fisheries, heavy production losses due to biotic (insects pests, weeds) and abiotic (salinity, drought, alkalinity) stresses; heavy post-harvest crop damage and declining availability of water as an agricultural input. Investment in agricultural related biotechnology has resulted in significantly enhanced R&D capability and institutional building over the years. Regulatory efforts with regard to BT cotton (Bacillus Thuringiensis Cotton) in India are proposed, but the officials of the Department of Biotechnology, Govt. of India admitted their lack of knowledge regarding the long-term safety (Scoones, 2003). However, progress has been rather slow in converting the research leads into usable products, and this is where the social entrepreneurship can play a vital role.

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3.2 Solution to Environmental problems Biotechnology has tremendous potential for application to a wide variety of environmental issues including conservation and characterization of rare or endangered trees, afforestation and reforestation. It can help in rapid monitoring of environmental pollution, eco restoration of degraded sites such as mining spoil dumps, treatment of effluents discharged by industries (oil refineries, dyeing and textile units, paper and pulp mills, tanneries, pesticide units etc.), treatment of solid waste, and so on. Also, most challenging is the continuous strive for re-use of treated wastewater. Indeed, water shortage is emerging in an increasing number of countries all over the world and necessitates the short cycling of water. Finally, biotechnology has a key role to play in the novel approaches to design wastewater treatment based on decentralized sanitation and reuse (DESAR) (Grommen & Verstraete, 2002). A number of technologies have already been generated and demonstrated in the country. The real challenge is their adoption by the industry, which has been somewhat uneven. In general, corporate groups have not been overly enthusiastic in adopting biotechnologies even where they have proven efficacy. The reasons may be several: industry is usually not involved at the planning stage of experiment; enforcement of environmental laws is not always strict or uniform at the ground level and offenders can often escape with impunity; manufacturers frequently change their production schedules based on demand profiles resulting in varied streams of effluents, but microbial consortia specifically designed to one set of effluents may be ineffective in breaking down the changed pollutants. The goal of environmental biotechnology would be to provide cost-effective and clean alternatives for risk assessment and quality monitoring, eco-restoration of degraded habitats, conversion of toxic recalcitrant chemicals into harmless byproducts, bioremediation of wastes, value-added products from biomass, control of biological invasion through biotechnological interventions, greener process technologies, and effective ex situ conservation strategies. These can be fulfilled through a deeper understanding - and engineering - of the metabolic pathways for degradation of toxicants, environmental genomics and proteomics, and other molecular techniques. 4. BIOTECHNOLOGY IN INDIA. Biotechnology is perceived as a revolution throughout the world. Biotechnology considered with its widest meaning encompasses all practical applications of properties of living organisms to create value. The Indian biotechnology sector is one of the fastest growing knowledge-based sectors in India and is expected to play a key role in shaping India's rapidly developing economy. With numerous comparative advantages in terms of research and development (R&D) facilities,

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knowledge, skills, and cost effectiveness, the biotechnology industry in India has immense potential to emerge as a global key player. 4.1 Characteristics of Biotechnology firms The Biotech industry being capital intensive in nature has historically relied on venture capital from public and private sources (Greenwood, 2011). India needs to provide active support through incubator funds, seed funds and provision of various incentives in order to develop the biotech sector. In a highly competitive and fast moving business environment, innovative capacity is an important determinant of the ability to create a continuing pipeline of new products and processes. Innovation covers knowledge creation (R&D), knowledge diffusion (education and training) and knowledge application (commercialization). Innovation is not a onetime event; instead, it has to continuously respond to changing circumstances for creating sustainable growth. Innovation is measured in terms of external / domestic patent applications; human capital devoted to R&D, government expenditure on R&D proportionate to country’s GDP, business funded expenditure on R&D, indigenous technologies standardized, demonstrated and transferred to industry for commercialization; and the number of spin off companies created (Joshi, 2006). Clear government policies for promotion of innovation and commercialization of knowledge will propel the growth of the biotechnology sector. “Biotechnology is only one tool, but a potentially important one, in the struggle to reduce poverty, improve food security, reduce malnutrition, and improve the livelihoods of the rural and the urban poor” (Persley, 1999, P.19). 31

4.2 Biotechnology Market in India Combined with rising public interest in this sector, growing investment by traditional business houses, tax incentives and the significant foreign investment available, the Indian biotechnology sector has emerged as a significant force on the global biotech map (India Economic News XII, Winter 2002/03). It is also promising to see the growth in market share that India has captured over period of time and again its ray of light towards positive sector (fig.1). Figure 1. Percentage of Country wise Market Share

Source: Bio Spectrum, June 2011, 9(6), p. 14) (All figures in INR. 10 Million)

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The Indian biotechnology industry is represented by the following five segments: I. BioAgriculture – The BioAgriculture sector comprises plant-derived pharmaceuticals, biotechnological development in crops and livestock, marine science, and forests. II. BioIndustry – The BioIndustry sector comprises biotechnologically developed products such as enzymes, bio-instrumentation and bioprocess equipment. Bio-instrumentation includes surgical and medical instruments. III. BioInformatics – BioInformatics or computational biology refers to the use of multiple techniques, including applied mathematics, computer science, information technology, and statistics to solve problems encountered in the biological domain. Information Technology is used in multiple research areas such as comparative genomics, gene expression analysis, high-throughput image analysis, modeling of biological systems, protein expression analysis, sequence analysis, structure prediction, etc.

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IV. BioPharmaceuticals – Biopharmaceuticals may be defined as medical drugs that are produced by biotechnology. Biopharmaceuticals usually comprise macromolecules, which are created through genetic manipulation of living organisms using gene cloning, recombinant DNA (gene slicing) or cell fusion technologies. The major thrust areas in biopharmaceuticals are diagnostics, monoclonal antibodies, oligonucleotides, recombinant proteins and vaccines. V. BioServices – BioServices comprises research services provided by contract research organisations (CRO). Examples of such organizations operating in India include Quintiles, Syngene and SiroClinpharm. Figure 2. India Biotech Industry (2006-2011)

Source: Bio Spectrum, June 2011, 9(6), p. 26) (All figures in INR. 10 Million)

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5. SOCIAL ENTREPRENEURSHIP IN THE FIELD OF BIOTECHNOLOGY. Analyzing the condition of the biotechnology industry and its contribution to the society which is of utmost importance and can help the people in need like agriculture, medical, industrial and environmental sectors to use the application of biotechnology and here is where the social entrepreneurs can play the key role. Social entrepreneurship is about applying practical, innovative and sustainable approaches to benefit the society in broad sense, with an emphasis on those who are marginalized and poor. Thompson, 2002: pg 413 ) extended the definition of social entrepreneurs to include: “people with the qualities and behaviors we associate with the business entrepreneur but who operate in the community and are more concerned with caring and helping than ‘making money’”. A social entrepreneur is a different kind of social leader who identifies and applies practical solutions to social problems by combining innovation, resourcefulness and opportunity (Elkington, Hartigan, 2008, Pg 256) which results in developing a new product, a new service, or a new approach to a social problem. A social entrepreneur identifies and solves social problems on a large scale. Just as business entrepreneurs create and transform whole industries, social entrepreneurs act as the change agents for society, seizing opportunities others miss in order to improve systems, invent and disseminate new approaches and advance sustainable solutions that create social value. Identifying and solving large-scale social problems needs a committed person with a vision and strong will to persist in the face of daunting odds. Ultimately, social entrepreneurs are driven to produce measurable impact by opening up new pathways for the marginalized and disadvantaged, and unlocking society's full potential to result in social change. 33

5.1 Characteristics of Social Entrepreneurs Entrepreneurial characteristics include spontaneous creativity, the ability and willingness to make decisions in the absence of solid data, and a generally risk-taking personality. An entrepreneur may be driven by a need to create something new or build something tangible. But social entrepreneur’s first and foremost focus is on social value creation through innovation (Schumpeter, 1951; Drucker, 1985) and in that spirit, is willing to share openly the innovations and insights of the initiative with a view to its wider replication. He doesn't wait to secure the resources before undertaking the catalytic innovation. A social entrepreneur is a specific type of leader, distinctive from the myriad of well-meaning and creative individuals and their organizations that work in the field of ‘development’. Apart from the above mentioned characteristics, a social entrepreneur is embraced with certain other specific qualities which are discussed below. 5.1.1 Ambitious: Social entrepreneurs tackle major social issues, from increasing the college enrollment rate of low-income students to fighting poverty in developing countries, it includes all. These entrepreneurial leaders operate in all kinds of organizations: innovative nonprofits, social purpose ventures such as for-profit community development banks, NGOs and hybrid organizations that mix elements of nonprofit and for-profit organizations. Setting of a goal and stay undeterred about problems faced is the kind of ambitious character one possesses. 5.1.2 Mission driven: Generating social value and not wealth is the central criterion of a successful social entrepreneur. While wealth creation may be part of the process, it is not an end in itself but a result. Promoting systemic social change remains the focal objective.

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5.1.3 Strategic: Like business entrepreneurs, social entrepreneurs see and act upon what others missed opportunities to enhance systems, create solutions and innovate new approaches to create social value. ‘The process is never more important than when a social enterprise is developing its strategic marketing plan’ says Boschee (2006). And like the best business entrepreneurs, social entrepreneurs are intensely focused and hard driving even relentless in their pursuit of a social vision. 5.1.4 Resourceful: Social entrepreneurs operate within a social context rather than the business world. So they have limited access to capital and traditional market support systems. As a result, social entrepreneurs must be exceptionally skilled at mustering and mobilizing human, financial and political resources. Dr. David Rendall rightly calls social entrepreneurs ‘tightrope walkers’ because they are constantly hovering in mid-air between their social purpose and marketplace realities mentions Petit (2009). 5.1.5 Results oriented: Ultimately, social entrepreneurs are driven to produce measurable returns. These results transform existing realities, open up new pathways for the marginalized and disadvantaged, and unlock society’s potential to effect social change.

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Whether they are working on a local or international scale, social entrepreneurs share a commitment to pioneering innovation that reshape society and benefit humanity. Quite simply, they are solution-minded pragmatists who are not afraid to tackle some of the world’s biggest problems. 5.2 Need for Imbibing Social entrepreneurship in biotechnology. Our research on the societal aspects of the biotechnology firms’ started from the assumption that social networks have a key role in the process of creation and early development of the new firm, facilitating entrepreneur’s access to critical technological resources. The transformation of a technological opportunity into a marketable technology, product or service and its commercialization requires the combination of technological and non-technological competences and resources (Autio, 1997; Mustar et al, 2006). The person who establishes a new biotechnology firm is usually a scientist who tries to develop his innovation/discovery into a commercial opportunity. Scientific entrepreneurs often lack managerial competences as well as industrial experience and contacts (Ensley and Hmieleski, 2005), even if teams sometimes integrate members with a managerial background. Thus, this type of firms will typically need to resort extensively to the environment, in order to acquire non-technological assets and they may also be less well prepared to identify and select the more adequate sources and to negotiate their access (Colombo and Piva, 2008; Costa et al, 2004). But the mobilization of external resources may raise particular problems in the case of firms operating in emerging fields, given the high levels of uncertainty (both technological and market) associated with their business (Yli-Renko et al, 2001). Thus the degree and quality of the assistance that entrepreneurs find in the environment is critical to successful firm formation (Van de Ven, 1993; Stuart and Sorenson, 2003). The conditions found in less advanced contexts may make the external search for resources more complex for technology intensive companies in emerging fields. In fact, these contexts are likely to be less effective in providing a set of resources and competences that are critical for this type of firms, such as capital, market-related resources, specialized services and

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business intelligence (Mustar et al, 2006; Druilhe and Garnsey, 2004; Degroof and Roberts, 2004). Solutions to certain social problems, such as sustainable alleviation of the constellation of health, education, economic, political and cultural problems associated with long-term poverty, often demand fundamental transformations in the political, economic, and social systems that underpin current stable states. Social entrepreneurship brings change in the social dynamics and systems that created and maintained the problem. Social entrepreneurs identify an unfulfilled opportunity to fix a problem or fill a void. They use business skills and knowledge to create enterprises that accomplish social purposes in addition to being commercially viable (Emerson and Twersky, 1996). Social entrepreneurship emphasizes the innovative character of the initiative. Replication or expansion of existing services is also a valuable solution to a social problem. When the resources or capacities to duplicate existing services for poor and marginalized groups are not available, creative initiatives that reconfigure existing resources or services for more effective or wider delivery are imperative to serve wider populations (Uphoff, Esman, and Krishna, 1998). Such creative initiatives represent social entrepreneurship. Therefore it can be argued that the strategies for network building followed by the biotechnology firms in this type of contexts will combine behavioral aspects that are typical of biotechnology entrepreneurs, with other that are a response to the conditions found in their particular environment. These strategies will be strongly influenced by sectoral and environmental determinants, whose impact will be felt at the level of the social capital built by entrepreneurs and at the level of the need of and scope for mobilizing this capital and/ or creating new relationships. However, the firms’ ability to identify, search for and activate or build the set of formal and informal relationships that can facilitate the access and effective use of available resources and competences will obviously be the critical element. 6. POLICY RECOMMENDATIONS The policy goal is to accord high priority to basic and applied research. Innovation should be supported through new granting mechanisms to support interdisciplinary networks and public private partnerships. The policy should be framed by highlighting the contribution of the social entrepreneurs around the world emphasizing the priority areas for sustainable development. For the diffusion of biotechnologies to be successful the following measures should be put in place: a. Ensuring effective and closer horizontal linkages between research workers and the user corporate groups; b. Public-private partnership in research and application of clean technologies; c. Strict enforcement of the ‘polluter pays’ principle. This would require interaction with law enforcement agencies; d. Capacity building and training, through workshops, of law enforcement officials, municipal workers, state government functionaries and corporate groups on role and relevance of biotechnology in waste treatment; e. Steps to encourage small and medium business companies in producing eco-friendly products, microbial consortia etc. for wider usage; f. Building greater awareness for protection of proprietary rights of microbial consortia through appropriate methods (e.g., process patent, trade mark etc.); g. Educate the agricultural dependent community (farmers), to use the tools and techniques of Biotechnology and enhance the productivity and ensure food security.

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7. CONCLUSIONS

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The common dynamics of economic development is related to the value creation through the advancement in Biotechnology. This evolves as techno-economic dynamics in the development process. A healthy population is essential for economic development. It is important to synchronize the technology and products with the local needs of the health system and to facilitate technology diffusion into health practice. New directions in manufacturing and delivery are emerging. Rapid responses are demanded to meet the challenges as they proceed and there is a requirement for specialized and skilled personnel and excellent laboratories for R&D. Biotechnology is India’s latest pursuit for domain expertise in knowledge-intensive sectors. It is promising to see the growth in market share that India has captured over period of time and again its ray of light towards positive sector. In recent years, this sector has seen the active interest and involvement of industry, academic institutions and government, with a vision of attaining global competitiveness and attracting global investments into India. India is already being globally recognized as a manufacturer of economical, high-quality bulk drugs and formulations. With a huge base of talented, skilled and cost-competitive manpower, and a well-developed scientific infrastructure, India has great potential to become a leading global player in biotechnology. A good managerial team provides the necessary skills for the day-to-day management and coordination of scientific, technical and commercial operations, and also projects a good external image of the firm. Hence, one key aspect where social entrepreneur have major role to play is in the commercialization of research results of the biotechnology sector thus, ensuring sustainable development. A working regional innovation system with respect to the links between firms and knowledge organizations can ensure the ability of implementation. The social entrepreneurship firms combine the use of entrepreneurs’ social capital, typical of entrepreneurial start-ups, with a sometimes extensive effort to build up new relationships that enable them to expand the scope of their technology search, frequently also using the social capital to facilitate this task. Confusion about the nature and role of social entrepreneurship limits their potential to contribute fully to positive social change. Thus, while many social entrepreneurs achieve some degree of social transformation in their local communities, the potential for further spread falls short of what it could be. REFERENCES Autio, M. (1997). New technology-based firms in innovation networks sympletic and generative. Research Policy, 26(3), 263–281. Azevedo, E. S and Cerqueira E. M (2002), Decisions in Circumstances of Poverty. Eubios Journal of Asian and International Bioethics, 12(3), 105-107. Bhardwaj, M and Macer, D.R.J. (2003), Policy and ethical issues in applying medical biotechnology in developing countries, Medical Science Monitor, 9(2), 49-54. Biospectrum,(2011). The Business of Biotech, 9 (6), 14-26. Biotechnology in India – a promising future, India Economic News XII (Winter 2002/03), cited in S. K Patra and P. Chand, (2005). Biotechnology research profile of India. Scientometrics 63(3), 477-489.

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Boschee, J. (2006), Strategic Marketing for Social Entrepreneurs. Institute of Social Entrepreneurs, Social enterprise report.USA, pp. 2-11. Colombo, M., Piva, E. (2008). Strengths and Weaknesses of Academic Startups A Conceptual Model. IEEE Transactions on Engineering Management, 55(1): 37-49. Costa, C., Fontes, M., Heitor, M. (2004). A methodological approach to the marketing process in the biotechnology-based. Industrial Marketing Management, 33(5), 403- 418. Dees, J. Gregory (1998). The Meaning of ‘Social Entrepreneurship. Comments and suggestions contributed from the Social Entrepreneurship Funders Working Group. Degroof, J.J. and Roberts, E.B. (2004). Overcoming Weak Entrepreneurial Infrastructures for Academic Spin-Off Ventures. The Journal of Technology Transfer, 29(3-4): 327-352. Department of Biotechnology, Ministry of Science and Technology, Government of India’s (2012). Draft Report on National Biotechnology Development Strategy, http://ec.europa.eu/research/biosociety/pdf/nbds_india.pdf accessed on April 30, 2012. Druilhe, C., Garnsey, E. (2004). Do academic spin-outs differ and does it matter? Journal of Technology Transfer, 29(3-4), 269-285. Drucker, P. F (1985). Innovation and entrepreneurship. New York: Harper & Row, Publishers Emerson, J. Twerksy F. (1996). New Social Entrepreneurs: The Success, Challenge and Lessons of Non-Profit Enterprise Creation. San Francisco, The Roberts Foundation, Homeless Economic Development Fund. 37

Ensley, M.D., Hmieleski, K.M. (2005). A comparative study of new venture top management team composition, dynamics and performance between university-based and independent start-ups. Research Policy, 34(7), 1091–1105. Fukuyama, F. (2002). Our Posthuman Future. New York: Farrar, Straus and Giroux. Grommen, R., Verstraete, W. (2002).Environmental Biotechnology: The ongoing quest. Journal of Biotechnology, 98(1), 113–123. Greenwood, J. (2011). Unleashing the Promise of Biotechnology. Biotechnology Industry Org, USA. Henderson, A. (2007). IT, Stem Cells, and Poverty: Modernity and the social impact of technological innovation in India. ATLIS, USA. Elkington, J., Hartigan, P. (2008). The Power of Unreasonable People. Harvard Business Press. Joshi, R. (2006). Biosafety and Bioethics. Isha Book Publications. Mustar, P., Renault, M., Colombo, M., Piva, E., Fontes, M., Lockett, A., Wright, M., Clarysse, B., Moray, N. (2006). Conceptualising the heterogeneity of research-based spin-offs: a multidimensional taxonomy. Research Policy, 35(2): 289–308. Persley G.J. (1999). Agricultural Biotechnology and the Poor: Promethean Science. http://www.cgiar.org/biotech/rep0100/persley.pdf (accessed on 25 April 2012). Petit, P.U. (2009). Creating a New Civilization through Social Entrepreneurship. The Goi Peace Foundation Publishing.

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Schumpeter, J. A. (1951). Essays: On entrepreneurs, innovations, business cycles, and the evolution of capitalism. R. V.Clemence (Ed.). Cambridge: Addison-Wesley. Scoones, I. (2003). Regulatory manoeuvres: the Bt cotton controversy in India. Working Paper 197, August, Institute of Development Studies, England. Sharma, D. (2003). Bt Cotton Fiasco: Turning a Blind Eye. www.biospectromindia .com/content/:columns/103102002.asp (accessed on 15 April 2012) Smith A. (1761). The Theory of Moral Sentiment. Edinburgh: A. Millar. Stuart, T., Sorenson, O. (2003). The Geography of Opportunity: Spatial Heterogeneity in Founding Rates and the Performance of Biotechnology Firms. Research Policy, 32(2), 229253. Thompson, J. L. (2002). The World of the Social Entrepreneur. The International Journal of Public Sector Management, 15(4/5), 412-431 WEHAB Working Group (2002). A Framework for Action on Water and Sanitation. Geneva: UN, 2002 Uphoff, N, Esman, M.J, Krishna, A (1998). Reasons for Success: Learning from Instructive Experiences in Rural Development. West Hartford, Connecticut: Kumarian Press. Van De Ven, A.H. (1993). The Development of an Infrastructure for Entrepreneurship. Journal of Business Venturing, 8(3), 211-230. 38

Yli-renko, H., Autio, E., Sapienza, H. (2001). Social Capital, Knowledge Acquisition and Knowledge Exploitation in Young Technology-Based Firms. Strategic Management Journal, 22(6-7), 587-613

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Insurance as Credence Goods: On the Allocation of the Burden of Proof Mahito Okura Associate Professor, Faculty of Economics, Nagasaki University, Japan. e-mail: [email protected] . Corresponding author Yunho Lee Professor, Department of Finance & Insurance, Daegu University, Korea. e-mail: [email protected] received May 15, 2012 / revised June 29 / accepted July 21 / published online July 28, 2012 DOI: 10.7350/BSR.A05.2012 – URL: http://dx.medra.org/10.7350/BSR.A05.2012

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ABSTRACT The purpose of this study is to consider the following two questions by examining insurance products as credence goods. First, whether the insurance firm chooses the truth telling when it sells good-type or bad-type insurance product? Second, what is the effect of the allocation of the burden of proof between insurance firm and consumer? First, there are two types of equilibrium in the model. The insurance firm always chooses the truth telling when it sells good-type insurance product in both types of equilibrium. The second type of the equilibrium realizes when the ratio of good-type insurance products is relatively low. Second, what the insurance firm bears a greater burden of proof is not desirable because it lowers the probability of truth telling. This result is not consistent with the general opinion that the insurance firms should bear a greater burden of proof for protecting the consumers. Keywords: Insurance, Game theory, Credence goods, Burden of proof, Asymmetric information. 1. INTRODUCTION When the consumers purchase the insurance products, they may not be able to judge whether the insurance products they purchased is really suitable for their needs. Actually, they purchase the insurance products by relying on the insurance firms’ integrities. However, many insurance products, especially complicated insurance products include high-leveled financial technologies, are more difficult for average consumers to understand. Thus, there is asymmetric information in relation to the insurance products between the insurance firms and consumers in the market. This asymmetric information brings strong incentives for insurance firms’ opportunistic activities (Villeneuve, 2000 and 2005; Andersson, 2001). For example, the insurance firms may offer unnecessary coverage to the consumers and they may not choose truth telling about the type of insurance products in order to receive more profits. In order to prevent such activities, governments seek to remedy the disadvantages from the asymmetric information by monitoring and regulating insurance firms’ marketing activities. However, in many countries, distribution channels are deregulated and the business scope of insurance firms is expanded in recent years.

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These trends are likely to contribute to achieve more efficient insurance market, but they are also likely to lead the lemon problem for consumers in the insurance market. To protect consumers from the lemon problem, transaction rules with definite rights and duties of the contracting parties have to be established. Although the rules are well prescribed in the insurance business law, it might not be sufficient to protect consumers who bought complicated insurance products such as variable life insurance products where the final amount of insurance payment depends on the investment returns. In this case, if the investment returns are poor, consumers cannot obtain a sufficient insurance payment. Then, consumers sometimes argue that the insurance firm has a responsibility to compensate them for their lower insurance payment because the insurance firm did not fulfill its obligation to explain the insurance products before sale. However, it is not easy for consumers to obtain compensation because they bear the burden of proof that the insurance firm misrepresented its insurance product. Moreover, many kinds of insurance firms’ sales explanations would be fully or partially unobservable for a third party including the court. Thus, the finding the solutions of the problem occurred by the asymmetric information in relation to the insurance products is not easy and this study mainly focuses on considering this problem because there are a few economic studies regarding the burden of proof in the insurance market. 1 With respect to these problems, discussions of the credence goods give this study some of the ideas. Generally, the credence goods have the characteristic that the consumers cannot judge the type of the goods before they purchase and then they finally know the type of the goods after they purchase. The same is true of the insurance products. Insurance consumers cannot get and understand enough information about the insurance products before they purchase and they generally know the utility of the insurance products when the accident occurs or the insurance period is expired. Sellers act as experts determining the customers’ requirement in this kind of a market. Therefore, the most of studies about the credence goods focus on fraudulent sellers or experts. Darby and Karni (1973), Wolinsky (1993,1995), Emons (1995, 1997) discuss how market conditions and technological factors affect the amount of fraud. Pitchik and Schotter(1987) show that the expert randomizes between either explanations truthfully or not. Tayler(1995) adopts a framework where he can analyze inefficiencies arising in the level of maintenance of the durable goods. Pesendorfer and Wolinskky(2003) analyze potential inefficiencies in the amount of effort provided by an expert to makes an diagnosis. But previous papers have assumed that fraud is costless and the only source of inefficiency is the cost of getting a second opinion. Then lying is not inefficient. By contrast Alger and Salanie(2006) allow for fraud costs and show conditions leading to equilibrium overtreatment. But it is difficult to introduce intact ideas into our framework, because our main concern is how the allocation of burden of proof and the accountability affect on seller and consumers behavior, not the fraudulent behavior of experts. The purpose of this study is to consider the following two questions by examining insurance products as credence goods. First, whether the insurance firm chooses the truth telling when it sells good-type or bad-type insurance product? Second, what is the effect of the allocation of the burden of proof between insurance firm and consumer?

1

There are many economic studies on the allocation of burden of proof for accident prevention. For example, see Sanchirico (1997) and Hay and Spier (1997).

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This study is organized as follows. Section 2 builds the model in which the asymmetric information in relation to the type of insurance products exists. The equilibrium is derived in Section 3. Section 4 considers how the allocation of the burden of proof affects the equilibrium. Section 5 provides some concluding remarks. 2. THE MODEL Assume that there are one insurance firm and one consumer in the market. Also suppose that there are good and bad insurance products in this market. Although the insurance firm can distinguish between both types of insurance products, the consumer cannot because of asymmetric information. In this market, the consumer only knows the ratio of good and bad insurance products. Denote the ratio of good (G) and bad (B) insurance products as π and 1 − π , respectively. In this situation, both the insurance firm and consumer face the following four-stage game. In the first stage, the insurance firm announces the type of insurance product to the consumer before sale. Because the consumer cannot distinguish between the two types of insurance products, the insurance firm can mimic the type. Thus, the insurance firm can announce B-type (G-type) to the consumer, despite actually selling G-type (B-type) insurance product. For example, there is a consumer who wants to prepare full coverage, but does not have sufficient knowledge about insurance products. In this case, insurance product without (with) deductible can be interpreted as G-type (B-type) insurance product. Let ei ( i ∈ {G, B} ) be the selling costs

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and assume that 0 < eG < e B < ∞ . This inequality indicates that selling the bad insurance product is more difficult and costly than selling the good insurance product. Also assume that selling costs only depend on what the insurance firm announces because selling costs mainly depend on the amount of the explanation about the insurance product. Thus, in the model, the insurance firm has to pay e B even if the real insurance product is G-type. In the second stage, the consumer chooses whether to purchase the insurance product. If the consumer chooses to purchase, the insurance firm invests a part of the insurance premium and the game proceeds to the third stage. In contrast, if the consumer chooses not to purchase, the game ends at this stage. In this case, the consumer’s payoff is M > 0 , while the insurance firm’s payoff is − ei . This means the consumer can receive the amount M > 0 by investing in a no-risk asset (such as a time deposit) that represents constant (expected) payoff without any insurance products, while the insurance firm only ends up paying the selling costs. In the third stage, nature decides whether the investment is a success or a failure. Here, qi denotes the probability of a successful investment when the insurance firm sells i-type insurance product and assumes that 0 < q B < q G < 1 . If the investment succeeds, the consumer receives the revenue and the game ends. In contrast, if the investment fails, the game proceeds to the fourth stage. In the fourth stage, both the insurance firm and the consumer take court action to allocate the responsibility for the failure of the investment. Assume that the insurance firm’s winning probability with truth telling is higher than with false telling in the first stage. If the insurance firm loses, they have to pay compensation to the consumer. Here, X ijk and Yijk (where j ∈ {T , F } and k ∈ {S , F } ) defines the insurance firm’s and consumer’s payoff when the insurance firm sells i-type insurance product and chooses truth telling ( j = T ) or false telling ( j = F ) with

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investment success ( k = S ) or failure ( k = F ). Using the game situation described, we construct the game tree in Figure 1. Figure 1. The Game Tree.

42

In Figure 1, N, I i and C i are the nodes of nature, the insurance firm, and the consumer when itype insurance product is sold. µ and γ are the probabilities that the consumer believes the insurance firm chooses truth telling when the insurance firm announces G-type and B-type, respectively. The expected payoffs for the insurance firm before subtracting the selling costs and the consumer are represented by X ij and Yij , respectively. We can then calculate X ij and Yij as follows:

X ij = q i X ijS + (1 − q i ) X ijF

(1)

Yij = qi YijS + (1 − qi )YijF .

(2)

In addition, we set three assumptions: X GT > X GF , X BF > X BT and YiT > M > YiF . The first assumption is that the insurance firm that chooses truth telling can receive a higher expected payoff than false telling when the insurance firm sells G-type insurance product and the consumer always purchases it. The second assumption is that the insurance firm that chooses false telling can receive a higher expected payoff than truth telling when the insurance firm sells B-type insurance product and the consumer always purchases it. The third assumption is that the consumer wants to purchase the insurance product when the insurance firm chooses truth telling regardless of the type of insurance product and vice versa.

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3. DERIVING THE EQUILIBRIUM Because this game is categorized in dynamic game with imperfect information, the perfect Bayesian equilibrium (PBE) is the most suitable equilibrium concept. To start with, it is easy to verify that the insurance firm always chooses truth telling when it sells G-type insurance product because eG < e B and X GT > X GF . Next, consider the case where the insurance firm announces Gtype. In this case, there are two possibilities: namely, truth telling and false telling. Here, r denotes the probability of the consumer purchasing the insurance product when the insurance firm announces G-type. If the consumer purchases this insurance product, its expected payoff is µYGT + (1 − µ )YBF . In contrast, if the consumer does not purchase, its payoff is M . Then:

r =1

if µ ≥

M − YBF , YGT − YBF

r =0

if µ ≤

M − YBF , YGT − YBF

r ∈ [0,1] if µ = (Case 1) µ ≥ 43

(3)

M − YBF . YGT − YBF

M − YBF YGT − YBF

In this case, the consumer always purchases the insurance product when the insurance firm announces G-type. Given that consumer’s response, we consider the insurance firm’s decision when it sells B-type insurance product. Here, s denotes the probability of choosing truth telling when the insurance firm sells B-type insurance product. If the insurance firm chooses truth telling, its expected payoff is X BT . In contrast, if the insurance firm chooses false telling, its expected payoff is X BF . Because X BF > X BT , the insurance firm chooses s = 0 . Thus, the insurance firm chooses truth telling only when it sells G-type insurance product. In order to maintain belief consistency, µ = π must be satisfied. Also, we can confirm that any γ becomes the equilibrium both even in the case of surely purchasing and not purchasing because X GT > X GF > −e B and X BF > X BT > −e B .2 Thus, if π ≥

M − YBF is satisfied, YGT − YBF

(Case 2) µ ≤

  M − YBF , ∀γ  becomes the PBE. r = 1, s = 0, µ ≥ YGT − YBF  

M − YBF YGT − YBF

In this case, the consumer never purchases the insurance product when the insurance firm announces G-type. Then the insurance firm chooses s = 1 . In order to maintain belief consistency, 2

In this case, information set on the belief γ is off equilibrium path. In this case, this information set is not restricted by the belief consistency and just compute the belief that satisfies both G-type and B-type insurance firms announce G-type. In details, for example, see Section 4.2 in Gibbons (1992).

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µ = 1 must be satisfied. However, µ = 1 contradicts µ ≤

(Case 3) µ =

M − YBF . Thus, there is no PBE. YGT − YBF

M − YBF YGT − YBF

In this case, the consumer is indifferent to purchase the insurance product when the insurance firm announces G-type. If the insurance firm chooses truth telling, its expected payoff is X BT . In contrast, if the insurance firm chooses false telling, its expected payoff is rX BF − (1 − r )eG . Thus, the response function can be written as: s =1

if X BT ≥ rX BF − (1 − r )eG

s=0

if X BT ≤ rX BF − (1 − r )eG

s ∈ [0,1]

if X BT = rX BF − (1 − r )eG .

(4)

(Case 3–1)

44

In this case, the insurance firm always chooses truth telling. In order to maintain belief M − YBF consistency, µ = 1 must be satisfied. However, µ = 1 contradicts µ = . Thus, there is YGT − YBF no PBE. (Case 3–2) In this case, the insurance firm never chooses truth telling. In order to maintain belief consistency, µ = π must be satisfied. Also, we can confirm that any γ becomes the equilibrium in the same manner of Case 1.   M − YBF M − YBF , ∀γ  becomes the PBE. It is easy Thus, if π = is satisfied, ∀r , s = 0, µ = YGT − YBF YGT − YBF   to see that this equilibrium is a special case of Case 1. (Case 3–3)

X BT + eG . In order to know whether the X BF + eG PBE exists, we must check the belief consistency. Using Bayes’ rule, the belief can be written as:

In this case, the consumer’s response is certain as r =

µ=

M − YBF π = . π + (1 − π )(1 − s ) YGT − YBF

From the equation (5), we show:

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(5)

Business Systems Review, ISSN: 2280-3866 Volume 1, Issue 1, 2012

s=

M − YBF − π (YGT − YBF ) . (1 − π )(M − YBF )

(6)

Because s ≥ 0 , the following equation must be satisfied.3 M − YBF − π (YGT − Y BF ) ≥ 0 .

(7)

Then,

π≤

M − YBF . YGT − YBF

(8)

In this case, in order to satisfies the belief consistency of γ , γ = 1 must be satisfied because consumer surely finds the insurance firm must be B-type when the insurance firm announces Btype. M − YBF Thus, if π ≤ is satisfied, YGT − YBF

  X BT + eG M − YBF − π (YGT − YBF ) M − YBF ,s = ,µ = , γ = 1 becomes the PBE. r = X BF + eG YGT − YBF (1 − π )(M − YBF )  

45

Roughly speaking, there are two types of equilibrium in this game (Case 1 and Case 3-3). Which of these equilibriums is realized depends on the ratio of good and bad insurance products denoted by π . Case 1 depicts the first type of equilibrium. This equilibrium is realized when π is relatively high. This equilibrium implies “the insurance firm never chooses truth telling when it sells Btype insurance product”: that is, the insurance firm announces the true type only when it sells Gtype insurance product. The consumer always purchases the insurance product regardless of the announcement. Case 3–3 depicts the second type of equilibrium. This equilibrium is realized when π is relatively low. This equilibrium implies “the insurance firm randomly chooses truth telling when it sells B-type insurance product”: that is, the insurance firm always announces the true type when it sells G-type insurance product and it randomly announces the true type when it sells Btype insurance product. The consumer also randomly chooses whether it purchases insurance product when the insurance firm announces G-type. 4. ALLOCATION OF COURT ACTION COSTS. Court action brings higher costs for both the insurance firm and the consumer. Thus, the allocation of court action costs is one of the factors that characterize the equilibrium. In this section, we consider the effect of the allocation of court action costs. Suppose that the court action costs takes place in the fourth stage. For simplicity, the amount of court action costs is constant regardless of any previous decisions. Here, θ ∈ [0,1] denotes the ratio that the insurance firm burdens the court action costs. Thus, the insurance firm has the full

3

s ≤ 1 is always satisfied because M − YBF − π (YGT − YBF ) ≤ (1 − π )(M − YBF ) ⇒ M ≤ YGT .

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burden of proof when θ = 1 , while the consumer has the full burden of proof when θ = 0 . Using the results in the previous section, the degree of θ affects the following variables.

s∗ ≡

π∗ ≡

M − YBF , YGT − YBF

(9)

r∗ ≡

X BT + eG , X BF + eG

(10)

M − YBF − π (YGT − YBF ) . (1 − π )(M − YBF )

(11)

These variables contain X BF , X BT , YBF , and YGT .4 Thus, we have to investigate the changes in each of the four variables when θ changes. To start with, because court action costs are only realized when the investment fails in the third stage, X ijF and YijF are a function of the amount of court action costs. We can then compute the following derivatives, X ij ' and Yij ' .

X ij ' ≡ Yij ' ≡ 46

∂X ij

∂θ ∂Yij

∂θ

= (1 − q i )

= (1 − qi )

∂X ijF ∂θ

∂YijF ∂θ

,

(12)

.

∂X ijF

(13)

∂YijF

< 0 and Yij ' > 0 because > 0 . Because ∂θ ∂θ the amount of court action costs is constant regardless of any decisions, then X BF ' = X BT ' and YBF ' = YBT ' . In addition, the probability of the insurance firm’s winning with truth telling is higher than with false telling. Thus, we can derive the following relationship.

It is easy to understand that X ij ' < 0 because

YBj ' = YGj ' ⇒ Y BF ' = YBT ' > YGT ' ⇒ Y BF ' > YGT ' .

(14)

Partially differentiating π ∗ , r ∗ , and s ∗ with respect to θ , Y ' (M − Y BF ) + Y BF ' (YGT − M ) ∂π ∗ = − GT F =0.0000 PROFITABILITY: DEPENDENT VARIABLE Explicative Variables

Estimates (ß)

Standard Error

t-ratio

TDRSRomagna

-.0024776**

.0011461

-2.16

TDRSLombardia

-.0021535**

.0005541

-3.89

TDRSPiemonte

.0020658

.0012354

1.67

TDRSVeneto

.0000291

.0006221

0.05

TCRSRomagna

-.0031443

.017865

-0.18

TCRSLombardia

.0327432**

.0158114

2.07

TCRSPiemonte

.018349**

.0045764

4.01

TCRSVeneto

.0428178

.0219142

1.95

CFRSRomagna

.0075852**

.0020401

3.72

CFRSLombardia

-.0012612**

.0006273

-2.01

CFRSPiemonte

.0286654**

.0083221

3.44

CFRSVeneto

-.0057621**

.0024579

-2.34

DRSRomagna

-.4008466

.5214546

-0.77

DRSLombardia

1.844903**

.3346828

5.51

DRSPiemonte

-.0011445

.0023021

-0.50

DRSVeneto

.5601624

.9866148

0.57

Costante

.7300348

.0078625

92.85

138

F(70,268) =

5.52

Prob > F = 0.0000

** the estimates are significant with at a confidence level α of 5% i

To conform with Italian regulations on academic publishing, we attributet hecontribution of each author as follows, even though the article is the joint work of both authors: Massimo Arnone, sections: 1, 3, 4 and 5 - Alessandra Bechi, section: 2.

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Business Systems Review

ISSN: 2280-3866 Volume 1 – Issue 1

Regional Innovation Systems: A Literature Review Giorgia M. D’Allura Assistant Professor of Business Management. University of Catania, Catania, Italy. e-mail: [email protected]. Marco Galvagno Assistant Professor of Marketing. University of Catania, Catania, Italy. e-mail: [email protected]. Arabella Mocciaro Li Destri Associate Professor of Business Management. University of Palermo, Palermo, Italy. e-mail: [email protected]. Corresponding author Received September 4, 2012 / revised October 4 / accepted October 26 / published online October 29, 2012. DOI: 10.7350/BSR.A12.2012 – URL: http://dx.medra.org/10.7350/BSR.A12.2012

139

ABSTRACT Though various authors have offered reviews of the Regional Innovation Systems (RIS) literature and some have described their personal intellectual voyage amongst the building blocks that constitute this area of scientific enquiry (for example, Cooke 2008), these often illuminating illustrations are nonetheless subjective and, thus, suffer from biases which pertain to the actor performing the analysis. The study proposed in this paper aims to overcome the aforementioned limitation by elaborating an objective review of the main contributions to the RIS field of research, highlighting the main themes studied and the principal approaches followed. The analysis has been conducted following the Author Co-citation method, applied to the literature regarding RIS present in the Social Science Citation Index (SSCI) of Thomson-ISI in the time span from 1990 to 2009. The results allow to trace an overview of how the RIS research area is actually composed, identifying six main research themes which characterize the field and varied approaches according to which each theme has been analyzed. Main contributions are positioned against each other in order to foster an increase in efforts from future research. Keywords: Regional Innovation Systems, Co-citation

1. INTRODUCTION Over the past two decades, studies regarding regional innovation systems (RIS) have gained increasing attention on behalf of academics, practitioners and policy makers. This surge of interest has been paralleled by widespread dissemination of the theme in academic literature. Though most of the contributors to this field of study share the broad underlying idea that

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140

territorial agglomeration provides the best context for an innovation-based globalizing economy because of localized interactive learning processes and “sticky” knowledge grounded in social interaction, the approaches followed, the theories used as conceptual building blocks and the design of empirical analyses show a significant degree of heterogeneity. The variety of theoretical and empirical approaches to the study of RIS may be justified by the range of cultural backgrounds which distinguish the many authors whose work contributes to the development of the field – who range from economic geographers and management analysts to sociologists and political scientists. Though, on the one hand, the rich array of perspectives used to study RIS poses the basis for fruitful cross-fertilizations between different theoretical approaches, on the other, it enhances the utility of taking a step back and drawing an overview of how the research area is actually composed, identifying the main research trends which characterize the field, as well as its boundaries and the core subject matters treated within it. This type of research is aimed to deliver a conceptual basis which may clarify the main characteristics of a field of study in order to foster an increase in the returns from future research efforts (Priem and Butler 2001). The aforementioned research may be conducted following a subjective approach, based on a qualitative analysis of the literature. Though this kind of analysis is often very illuminating, the more a field of study is differentiated the more it becomes difficult to keep abreast of the current trends and developments which are continuously taking place within it. Also, this approach often leads to studies which are influenced by the researcher’s cognitive barriers and biases - which, in turn, reflect their education, their experiences and the social groups to which they belong (Acedo et al. 2006). Thus the subjective approach has two main drawbacks as, in first instance, it may lead to incomplete representations of the field analysed (Bettis and Prahalad 1986) and, in second instance, it tends to meld the description of what the field is with the prescription of what the field should be (Casillas and Acedo 2007). In order to overcome the limitations of the subjective approach, in this paper we adopt an objective approach to the study of the area of research regarding RIS based on a bibliographical analysis of the scientific works that can be included within the field. In particular, at the basis of the Author Co-citation Analysis (ACA) (Small 1974; White and Griffith 1981) is the idea that both journal articles and books contain the knowledge which makes up the research field and, further, that the references of any scientific work are indicative of the theoretical and empirical bases on which the new scientific contribution rests. Thus, an analysis of the references and cross-references between authors allows to identify networks of authors and papers belonging to the same school of thought, trend or perspective. This method is a powerful procedure to study the structure of a scientific discipline and its main trends, and has been applied to many fields of research (Culnan 1986; Pilkington and Liston-Heyes 1999; Knight et al. 2000; Acedo et al. 2001, Ramos-Rodríguez and Ruíz-Navarro 2004; Acedo et al. 2006; Casillas and Acedo 2007; Nerur et al.. 2008; Distefano et al. forthcoming;). Given the variety of approaches and perspectives which distinguish the research area regarding RIS, we apply the ACA method in order to provide a panoramic view of the structure of the main contributions to the field, highlighting the main themes that are being scrutinized, the way they talk to each other and the links between them, whilst showing possible “research holes” which may orient future research endeavors. Finally, we hope this study may represent a user-friendly reference that may allow researchers who are new to RIS studies to gain rapid acquaintance with the field. The rest of the paper is organized as follows: the following section introduces the concept of RIS and describes the variety of approaches which interact within the RIS literature. The third

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section, describes the ACA method and how it works and, then, proceeds to illustrate its application to the RIS literature. In the fourth section the results of the application of the ACA method to the RIS field are illustrated. The results obtained are discussed in detail in the fifth section, whilst the sixth section draws from the results obtained to sketch a number of issues which are open for future research. The final section contains the main conclusions of the study.

2. THE ANALYSIS OF REGIONAL INNOVATION SYSTEMS AS A FIELD OF STUDY

141

Among academics, entrepreneurs and policy-makers consensus has long suggested that innovation is a crucial factor in generating economic growth and development. Equally, there is widespread evidence regards the uneven spatial distribution of innovative behavior between different geographical areas and, in particular, between different regions in the world. These recurrent patterns have brought social scientists and policy-makers to pay increasing attention to regions as designated sites of innovation and competitiveness in the globalizing economy (Florida 1995; Cooke et al. 1997), pushing research to focus on the interrelationships between technology, innovation and industrial location. The surge of interest regards the factors and dynamics underlying regional competitiveness in fields as diverse as political science, economic geography and business economics, has resulted in the emergence of a number of concepts which, in different ways or with different emphasis, underscore the processes and dynamics underlying the localization of innovative activities within confined territorial areas. Amongst these it is possible to recall the following: “learning region”1 (Morgan 1997; Florida 1995); “innovative milieu”2 (Maillat 1998); “industrial district”3 (Becattini 1992; Scott 1988); “local productive system” (Courlet 2001); “cluster”4 (Porter 1990, 1998, 2003; Maskell 2001; Iammarino and McCann 2006); “technopole”5; “regional innovation

1

The learning region (Morgan, 1997; Florida, 1995) is a region that functions as a collector and repository of knowledge and ideas, and provides an underlying environment or infrastructure which facilitates the flow of knowledge, ideas and learning. The critical elements defining the learning region concept are knowledge, customers and suppliers, inter-firm relations and networks, and a high degree of rivalry between actors. Main dimensions of the learning region are the infrastructures that produce, foster and share knowledge. 2 The innovative milieu (GREMI study group; Crevoisier, 2001; Maillat, 1998) is a concept which stems from the idea of localized learning and innovation processes, and explores the sociological and cultural dimensions of local competitive advantage. The basic assumption of this approach is that the environment (the milieu) is an essential component of innovation. Main dimensions of the innovative milieu are firms and know-how. 3 The industrial district (Beccattini, 1992; Scott, 1988) concerns a particular form of agglomeration characterized by a localized thickening of inter-industrial relationships that is reasonably stable over time. In this view, firms are small, specialized, and rooted in a given territory. Innovation and learning result from cooperation, mutual dependence, and trust among local actors. Main actors of the industrial district are small and specialized firms. 4 The cluster (Porter, 1990, 2003; Maskell, 2001; Iammarino and McCann, 2006). Clusters are intended as the geographical agglomeration or co-location pattern of firms, organizations and institutions interconnected and interdependent in their activities directed to the production of goods and services. The focus of the cluster literature is however on the concentration of inter-dependent and rival firms within the same or adjacent industrial sectors in a small geographic area – ie. on firms which operate in the same or correlated industries. Other actors are considered only if (and to the extent to which) they represent a stimulus to the upgrading of the cluster firms’ performance. 5 The technopole (Technopolis project in Japan and the Tecnolpolis policy in France) is an institutional infrastructure aimed to proactively foster industrial innovation activities and technology transfer, providing opportunities for institutional cooperation within and between university and industry. Main actors of the technopole are universities and industrial firms.

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systems” (Cooke et al. 1997; Cooke 2001, 2004; Asheim and Isaksen; 2002; Malberg and Maskell 2002; Ashiem and Coenen, 2003; Wolfe 2003). In this complex maze of partially overlapping theories, the relevance gained by the RIS literature may be justified in consideration of the capacity of its framework to embrace in a systemic manner and correlate a relevant number of the other concepts considered. Furthermore, in consideration of the fact that the establishment and formation of RIS plays a strategic role in the development of the endogenous capacity of regions to innovate in order to create competitive advantage, the full comprehension of the RIS concept has been considered a necessary passage towards the elaboration of effective RI policies and, thus, has increased the attention towards this field of research. It is not surprising, therefore, that the field under scrutiny presents a large range of different perspectives and approaches. Until today, the analysis of the intellectual structure of the RIS field has been conducted according to a subjective and qualitative approaches (Cfr. for example, Karlsson and Andersson 2002; Carlsson 2003; Doloroux 2004; Boschma and Frenken 2005; Doloroux and Prato 2005; Cooke 2008). The study conducted in this paper uses objective tools of analysis, based on the ACA method of bibliometrics. The aim of the analysis that follows is to highlight the main trends within RIS studies, underscoring the different theoretical and empirical backgrounds which characterize the various streams of research, in order to complement the outlook provided by the subjective analyses of the RIS area of research.

3. METHODOLOGY: THE AUTHOR CO-CITATION METHOD 142

As stated above, in order to explore the structure of the RIS research domain so as to better understand its origins, current state of development, and future trends, in this paper we conduct a literature review according to the author co-citation analysis (ACA) methodology. ACA methodology is a bibliometric technique used to analyze publication patterns in a field or body of literature. Co-citation analysis makes it possible to map research on a topic and to identify the dominant approaches in the field, thus shedding light on social structures and uncovering the “vast interpersonal network that screens new ideas in terms of central theme or paradigm, permitting some a wide audience and consigning many to oblivion” (Crane 1972). In co-citation analysis the data compiled are counts of the number of times two documents are jointly cited in later publications6. The analysis is based on the premise that authors cite papers they consider to be important to the development of their research. As a result, heavily cited articles are likely to have exerted a greater influence on the subject than those less frequently cited (Sharplin and Mabry 1985; Culnan 1986). It is assumed, first, that “highly” cited papers represent “important” concepts and methods in science; second, that “frequently” co-cited papers are related by content. A graphic representation of published works that tend to be cited together by researchers helps identify research streams and other cluster of scholarly work. Studies focusing on cited works try to establish the general structure of the discipline (what types of works are dominant), as well as the discipline’s boundaries and relations to other disciplines. Identifying co-citations can tell us, 6

Cited references for a paper A would include scholarly publications appearing in any journal that cites the paper A. Each cited reference has a unique identifier that forms the basis to record the co-citations between a pair of papers. A co-citation occurs between two papers, say A and B, when a cited reference to paper A (which could have been published in any journal) also cites paper B. That is, the number of cited references of A that match the cited references of B gives the frequency of co-citations between A and B.

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143

through factor analysis7 for example, what the major factors and groups are within the field and how they vary across journals and over time. We can also graphically illustrate what the most influential citations are for each of the factors, how they are related, how strong their relationships are, and how far removed they are from, or central they result regards, the factor groups they belong to. Co-citation studies can show us what topics, authors, journals, and research methods were central, and peripheral, to the field, and how they may have changed over time. Our analysis, following the method prescriptions (McCain 1990), comprises six steps: (1) selecting the unit of analysis; (2) retrieving co-citation frequencies; (3) compiling the raw cocitation matrix; (4) converting the raw co-citation matrix into a correlation matrix; (5) multivariate analysis; and (6) interpreting the findings. The unit of analysis can be defined in terms of articles or authors, depending on whether the analysis aims to identify the structure of specific or broad fields of inquiry (Culnan 1986). In particular, for the studies targeted at specific research areas (as in our case), it is preferable to analyze articles in order to avoid the results being biased by the fact that the same author may have published in different fields (Acedo et al. 2006). In the work that follows, this method allows us to identify the connections between the most influential contributions regarding the concept of Regional Innovation Systems (RIS) in order to represent them systematically within a unitary framework, underscoring the way these scientific contributions relate to each other. Also, this kind of analysis will highlight the presence of fragmentation and specialization between different research streams if these are present, providing indications for future research which may foster the development of unifying perspectives within the RIS field. We based the analysis on the Social Science Citation Index (SSCI) of Thomson-ISI, with a time span from 1990 to 2009, available on the on-line database and consistent with the aim of our analysis. This database, which covers over 1,700 of the world’s leading scholarly social sciences journals in more than 50 disciplines, provides access to bibliographic information, author abstracts, and cited references. The analysis was performed in September 2009. Given the aim of our analysis, we defined a criterion to search for papers. The criterion adopted considered three keywords: “RIS”, “Regional Innovation System(s)s” and “Regional System(s) of Innovation”. The search was performed by selecting the papers whose title, abstract, and keywords matched our criterion. By screening the Thomson-ISI SSCI database according to the above search criteria, we obtained a set of 211 contributions. Among these, we selected only published articles (excluding proceedings, or working papers) and only journals whit impact factor in the fields of business, management, economics, and geography. Given our interest in defining the hard core of the discipline, and following the example of previous works with similar time spans, we selected all those articles that have been cited at least 30 times8. This resulted in a total of 13 articles. So as to avoid the risk of excluding important articles, and to cover all the developments within the research field, it seemed preferable in this stage to form a core of works as large as possible, while ensuring that this core is made up only of documents that can truly be considered as shaping the knowledge in the RIS field. Thus, it was decided to add other papers which could 7

Factor Analysis is based on seeking a linear combination of variables such that the maximum variance is extracted from the variables. It is by far the most common form of factor analysis and it is generally preferred for purposes of data reduction (translating variable space into optimal factor space). 8 This practice’s main weakness is the use of a relevance criterion that favours older documents to the detriment of more recent ones that might have had a greater impact on the theory. This entails a static view of the theory, and does not capture the new trends being shaped in the most recent years.

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be considered important to the development of the research subject analyzed, by searching for those articles that: (a) had cited Freeman (1995), or Cooke et al. (1997), or Cooke (2001) (as an a priori indicator of their link to the RIS research field)9, or (b) had cited two of the 13 articles in the initial set, and (c) had been cited more than 30 times in the 1990–2009 period (relevance criterion). In this way, 24 articles were selected to serve as the starting point for subsequent analysis (see Table 1).

144

Table 1: The set of articles Freeman C., Cambridge Journal of Economics, Feb. 1995 (P1) Cooke P., Uranga M. and Extebarria G., Research Policy, Dec. 1997 (P2) Cooke P., Industrial and Corporate Change, Dec. 2001 (P3) Carlsson B., Jacobsson S, Homen M. and Rickne A., Research Policy, Feb. 2002 (P4) Acs Z.J., Anselin L. and Varga A., Research Policy, Sep. 2002 (P5) Cooke P. Uranga M. and Extebarria G., Environment and Planning A, Sep. 1998 (P6) Asheim B.T. and Isaksen A., European Planning Studies, Jun. 1997 (P7) Muller E. and Zenker A., Research Policy, Dec. 2001 (P8) Rantisi N.M., Regional Studies, Aug. 2002 (P9) Asheim B.T. and Coenen L., Research Policy, Oct. 2005 (P10) Oinas P. Malecki E., International Regional Science Review, Jan. 2002 (P11) Sternberg R., European Planning Studies, 2000 (P12) Humphrey J. and Schmitz H., Regional Studies, Dec. 2002 (P13) Cantwell J. and Janne O., Research Policy, Mar. 1999 (P14) Malmberg A., Progress in Human Geography, Sept. 1996 (P15) Romijn H. and Albaladejo M., Research Policy, Sep. 2002 (P16) Lawson C. and Lorenz E., Regional Studies, Jun 1999 (P17) Malerba F., Research Policy, Feb. 2002 (P18) Bunnell T.G. and Coe N.M., Progress in Human Geography, Oct 2003 (P19) Wolfe D.A., Gertler M.S., Urban Studies, May 2004 (P20) Coe N.M. and Bunnell T.G., Global Networks, Oct 2003 (P21) Sydow J. and Staber U., Regional Studies, May 2002 (P22) Boscham R.A. and Frenken K., Journalo of Economic Geography, Jun 2006 (P23) Boscham R.A., Regional Studies, Dec. 2004 (P24) Each of the 24 articles was paired with every other author in Table 1 and the co-citation frequency of each pair was computed from the total references in the Social Sciences Citation Index (SSCI) online. The result of this procedure was a 24 by 24 matrix of co-citation counts, an extract of which is presented in table 2. This co-citation matrix is symmetrical and its diagonal values are zero, since no paper can cite itself. In order to standardize the data, as well as decreasing the number of zeros, the Pearson correlation matrix was estimated (Moya et al. 1998; Rowlands 1999). It serves as a matrix of inter-article “proximities”10. 9 This choice is justified as Freeman (1995), Cooke et al. (1997) and Cooke (2001) are the three articles mostly cited among those identified in the first round of the retrieving process. 10 Here the correlations are defined as measures of similarity: the higher the positive correlation, the more similar two papers are in the perceptions of citers (McCain, 1990).

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Following analogous studies (Culnan 1986; McCain 1990), we continued to apply three multivariate statistical techniques: multidimensional scaling (MDS), cluster analysis, and factor analysis. Table 2 – Sample co-citation matrix.

Freeman, 1995 Cooke et al., 1997 Cooke, 2001 Carlsson et al, 2002 Acs et al., 2002 Cooke et al., 1998 Asheim, Isaksen, 1997 Muller, Zenker, 2001 Rantisi, 2002 Asheim, Coenen, 2005 Oinas, Malecki, 2002 Sternberg, 2000 Humphrey, Schmitz, 2002

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Freeman, 1995 9 14 1 7 1 6 4 1 2 0 0 2 1

Cooke et al., 1997 14 13 10 11 4 6 7 1 7 2 9 0 1

Cooke, 2001 1 10 8 2 0 7 7 0 1 1 3 0 2

Carlsson et al, 2002 7 11 2 12 2 2 2 1 1 0 2 0 0

Acs et al., 2002 1 4 0 2 4 0 1 0 0 0 0 1 0

Cooke et al., 1998 6 6 7 2 0 7 6 0 1 1 1 3 0

Multidimensional Scaling consisted in projecting the papers on map, using the data from the correlation matrix as input data. The values obtained exhibit a good fit (STRESS=0.12 and RSQ=0.93) and permit us to state that the map is a good approximation of reality (see Figure 1 in Appendix). The purpose of this analysis is twofold. On the one hand, MDS shows co-citation links among contributions. Points positioned at the center of the map represent contributions linked to many different schools of thought and thus with heterogeneous citation profiles. On the other hand, MDS reduces the data space, by positioning the articles on a bidimensional space, making it easier to interpret the relative positioning of the clusters of contributions. Next to MDS a hierarchical cluster analysis was applied to the data. This technique allows to obtain a series of groups (or clusters) of significantly related documents. Hierarchical clustering determines the belonging to a group by analyzing the distance between pairs of documents in the multidimensional co-citation space. In our study applied to RIS literature, cluster analysis clearly shows five groups of papers. In order to better visualize and frame them in a conceptual space, the clusters were superimposed on the MDS graph. Along with the two previous techniques, we also employed a correspondence factor analysis of the co-citation matrix in order to reveal the “hidden” subject matter. Factor analysis can give us yet another piece of information on the structure of the field. If a structure is present in the data it will show by being decomposed in its constituent factors (i.e. sub-fields of research or areas/perspectives). The relevance of Factor Analysis in this context is based on the notion that papers which are related to one another will, in general, be repeatedly cited together in subsequent publications, while works which are rarely or never cited together will not. If this assumption is true, then Factor Analysis can use the co-citation entries to determine which contributions are grouped together and therefore share a common element. It does so by producing a number of “factors”, each of which captures a common element of the documents that are grouped together. It is also capable, by producing numerical indicators of the relevance of the factors (i.e. eigenvalues), of telling us something about the relative importance of these

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underlying elements11. This analysis was carried out using the varimax rotation, following previous works (Rowlands 1999). The rotation of the axes carried out in the process of factor analysis aims to obtain factors endowed with theoretical significance, as well as to achieve the simplest possible factorial structure (Hair et al.1999). 3.1 Results Table 3 shows the publishing journals for the 24 most co-cited works in the Regional Innovation System research domain. Table 3: The set of articles Journal Research Policy Regional Studies Progress in Human Geography European Planning Studies Others Total

Number of articles 8 5 2 2 7 24

% 33% 21% 8% 8% 29% 100%

The inspection of the journals on which the most cited papers are published reveals various interesting points: 146

1. A management journal, Research Policy, is the most influential in the field. One third of the most important articles has been published there; 2. One third of the articles has been published in geography journals as Regional Studies (1/5 of the total) and Progress in Human Geography; 3. There is a strong prevalence of conceptual articles and qualitative methods. Results of the analysis are depicted in Figure 1 (in Appendix) where the Multidimensional Scaling Map and the five groups of papers obtained through the clustering procedure are shown. The grouping of the authors represented on the graph elaborated through multidimensional scaling was obtained on the basis of the results generated from the cluster analysis (using Ward’s hierarchical method). The map shows: 1) positions of papers with respect to the map’s axes; 2) identifiable paper groups which represent research topics/lines of research; 3) location of these groups with respect to each other; 4) proximities of papers within groups and across group boundaries (“border papers”). Commentary on each point follows. 1) Although the construction of the axes is arbitrary, the position of the papers on the map suggests a meaning for the axes. In the RIS field of studies, the framework obtained seems to suggest that the horizontal axis refers to the “level of analysis on which the paper focuses regards the study of the production of innovation”. In particular, the levels of analysis range from the

11

Although the use of cluster and factor analysis may prove to be redundant, each one of them possesses a specificity that allows us to grasp additional aspects of the relationship between the papers. The strength of factor analysis can be found in its ability to detect common, underlying dimensions on which variables or objects may be located, while the strength of the cluster analysis method lies in its ability to indicate group membership. In relation to this paper, we use cluster analysis to identify different topics inside the RIS literature, while we use factor analysis to highlight the different research approaches used to study these issues.

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more micro or individual level of analysis on the left side of the graph, to the more macro or social level of analysis which characterize the papers located on the right side of the framework. With respect to the vertical axis, the works located in the quadrants above the horizontal axis analyze the “Regional Innovative Capacity”. While those below the horizontal axis, are mostly related with “Firm Innovative Capacity”.

147

2 and 3) through cluster analysis, papers are grouped together on the basis of correlation relationships; thus generally papers within each group share the same topic or issue. Figure 1 (in Appendix) depicts the five major groups found. Papers within group boundaries share similar cocitation profiles. This ‘relationship’ only means that papers address the same broad questions, without necessarily agreeing with each other on their findings. Furthermore, papers and groups of papers near the external areas of the map are generally related, through co-citation, to fewer neighbors. Clearly the similarity among papers also depends on how they were perceived by the authors who have, for one reason or another, cited the papers together. Given these premises, the proximity between the papers within group boundaries can provide interesting information. Starting from the bottom right area and proceeding clockwise, the groups identified are the following: − Group A is focused on Systems of Innovations (Lundvall 1985). It is composed of eight articles, which are generally strongly cited, but their position in the map indicates that they cannot be identified as central in the RIS literature. Actually they deal with a wide range of innovation systems, from National Innovation Systems (Freeman 1995) to Regional Innovation Systems (Acs et al. 1997; Cooke et al. 1997; Asheim and Isaksen 2002), from Technological System (Carlsson et al. 2002) to Sectoral Innovation Systems (Malerba 2002). Papers in this group are focused on the idea that understanding the linkages among the actors involved in innovation is key to improving technology performance. An analysis of the main contributions to this group suggests that innovation and technical progress are the result of a complex set of relationships (i.e. a system) among actors producing, distributing and applying various kinds of knowledge. Papers in this group are not recent (7 out of 8 have been published between 1995 and 2002) and generally focus on definitional issues. Of particular interest is the position of the group with respect to the axes. Most papers are in fact located on the right hand side of the map, the main theme treated pertaining to the characteristics of the different systems of innovation. Regards the authors, it is worthwhile saying that all are economists, with Freeman and Cooke being among the founders of the systems of innovation field of research. − Group B assembles three papers focused on Regional Systems of Innovation, from a regional science and economic geography perspective. The analysis of the main contributions suggests that the idea and content of RIS follow discoveries made by regional scientists, economic geographers and innovation analysts and are conjugated with three fundamental dimensions. The first dimension is related to local specificity. They try to understand the effect of local specificity of a region on economic development. The second dimension focus on institutions. In particular, local institutions play a fundamental role on economic development. The third dimension is about knowledge flows which take place inside formal relationships among local private and public institutions. Interestingly, the group is also characterized by a significant homogeneity in terms of approach (institutional approach) and all authors are geographers. Furthermore, the group has a central position in the map meaning that papers within this group are generally evenly cited by all the other groups. From these findings it is clear how the recent but constantly growing interest for regional development

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and innovation issues pushed scholars to broaden the traditional span of research on location and agglomeration theories by drawing on typical subfields of the innovation literature. − Articles in group C, the most numerous with nine papers, seeks to move beyond existing conceptualizations of Systems of Innovation in two key respects. First, by introducing a nonterritorially bounded dimension to the study of innovation and by emphasizing a network perspective and the significance of innovative networks that extend beyond firms. Second, by focusing on the tacit knowledge flows that take place among individuals beyond any formal relationship. Articles in this group represent very well the main trend that is emerging in the latest years: the interest regards the extra-regional side of regional innovation. In this vein, external relations of actors are key elements that transcend all existing systems of innovation. This group contains relatively recent contributions and can be considered as the integration of the evolutionary economic geography approach with the knowledge and organizational learning perspective, originating from the management field. Among the authors belonging to this group, Bunnel and Coe are present with two articles, both dealing with networks that extend beyond firms and physical place as the locus of innovative activity. − Group D is composed of two articles written by Boschma (2004) and Boschma and Frenken (2006). These contributions focus on regional competitiveness. They both apply an evolutionary approach and argue that the competitiveness of a region depends on intangible, non-tradable assets based on a knowledge and competence base embedded in a particular institutional setting that are reproduced and modified through the actions and repeated interactions of actors. − Finally, group E, includes two papers that attempt to understand the role of different types of knowledge in favoring the firm’s learning and innovation processes. For this thread of research, since the single firm represents the main object of analysis, it is important to recognize the role of regional and local interactions in the creation of firm’s innovative capability. Empty regions in the two dimensional space represent two types of significant information: differentiation or dissociation between clusters on the one hand, and/or the significant absence of objects on the other hand. The former reveals the existence of large differences among groups; the latter means that certain themes have been overlooked by almost all authors. For example, it is interesting to note that there is a vast empty region on the lower central portion of the MDS map. This seems to suggest the need for more in-depth research on the firm’s innovative capacity and its proactive role within the overall system of innovation. 4) Articles having positive correlation with other papers across group boundaries deserve further study. The papers in question create a bridge between two research themes and often borrow new ideas from other groups to improve or extend the research of the groups they belong to. Often, new research areas are created across the boundary of different research groups. In particular, factor analysis allows us to identify the factors explaining most of the variance observed and to identify groups of strongly correlated papers in order to allow us to define the structure of the field of research. We have considered that a contribution should be included in a trend when its loading is equal to or greater than |0.5|, and if the loading is greater than |0.7| then the paper is of great relevance within the corresponding paradigm. Table 4 (in Appendix) shows the results of this analysis. As can be observed, all of the information is summarized in six factors (explaining 78,5% of the variance). All 24 papers, but one (Muller and Zenker 2001) loaded on at least one factor. Significantly, most of the contributions are loaded with a weight greater than |0.7|, corroborating the relevance of these works within their respective paradigms.

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Likewise, it can be observed that one article (Cooke et al., 1997) exhibits considerable loading on more than one factor (greater than |0.5|). This work is of even greater interest, as it represents a bridge between paradigms, thus helping us to understand their evolution and the ties that have been forming between the different research trends. The interpretation of the factor analysis is based on what the papers represent in terms of scholarly contribution and intellectual association. If the cluster analysis showed five, well recognizable, broad topics that characterize research on Regional System of Innovation, factor analysis is useful to interpret the intellectual connections among papers as well as their epistemological and theoretical backgrounds. Factors can be interpreted as the “approaches” or “interpretative lens” adopted as a basis for the elaboration of a piece of research. Thus the results of the factor analysis, presented in Table 4 (in Appendix), reveal how and to which perspectives the RIS literature is intellectually indebted. By analyzing the loadings on each factor, it was possible to infer the perspectives they represented. The careful scrutiny of the papers considered for each factor suggests the identification of the 6 factors according to the following definitions: (1) Regional Science; (2) Economics of Innovation; (3) Social Embeddedness; (4) Evolutionary Economic Geography; (5) Knowledge and Organizational Learning; (6) International Business.

4. THE RIS FIELD OF RESEARCH: AN OVERVIEW

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The results obtained from the author co-citation analysis conducted above reveal a number of distinct traits which characterize the RIS field of research. Firstly, the discipline appears varied in relation both to the particular themes treated and to the interpretative lenses adopted to study RIS, reflecting to some extent the multiple backgrounds of the authors who have contributed to this body of literature. The MDS map and the cluster analysis performed vividly illustrate the richness of themes treated - which range from the definitional issues underlying the RIS concept and the comprehension of the linkages between the different actors within RIS, to more “spatial” and social studies in which the specific institutional characteristics of territories are highlighted, to analyses whose focus is on the different types of knowledge which characterize a territory and how this feeds firm innovative capacities, to the evolutionary focus on knowledge and competences embedded in particular territories, and finally the network approach that extends RIS reasoning to the linkages between different territories. The position of the different papers within the clusters along the axes of the map also illustrates that the themes treated are often further enriched by a variety of approaches according to which each one is considered, which range from micro to macro level perspectives and from major focus on regional innovation to firm innovation. This array of themes and approaches which characterize the RIS literature may be considered positively, as the interface and confrontation between different stances often fosters a more through explanation of phenomena than single monolithic approaches. However, in order to take advantage of the richness of perspectives within the field there is the necessity to avoid excess fragmentation, whilst facilitating mutual fertilizations between diverse approaches. In this regard, the presence of a number of works (Malberg 1996; Asheim and Coenen 2005; Cantwell and Janne 1999) in the central area of the MDS map is to some extent comforting, as they represent pieces of research that serve as a basic reference for the field. However, these papers, rather than being eclectic in their approach or unifying for the entire branch of studies, are each one strongly representative of a part of the field, highlighting the main blocks of research that are present in the RIS literature: in particular, the institutional approach of the economic geographers; the definitional positivist perspective of the economists; and the

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extension on the RIS reasoning beyond self-contained territories that emerges from the fusion between evolutionary perspectives in economic geography with organizational learning studies. Thus, though the central area of the map is not void, there is still the need for the elaboration of unifying research which may serve as a platform of mutually shared concepts and theories for the entire RIS field of enquiry. The factor analysis shows that although RIS studies are intended as an independent area of research, its intellectual roots are wide spread, rendering it an interdisciplinary field of research in which insights are drawn from social, economic, cultural and political sciences. The six factors identified show the presence both of approaches which, to different extents and in diverse ways, underscore the role of social structure, institutions and contextualization in “real places” – regional science, social perspective and international management – and those which are more abstract and formal, or less “social”- knowledge based view and organizational learning, economics of innovation approaches, and the evolutionary approach. The intellectual heritages identified are diverse also regards their implicit behavioral assumptions – i.e. the agent rationality assumption –, ranging from the more rational utilitarian approach of the economics of innovation strand to the more rule guided behavior of the social and regional science studies. Finally, these approaches are different also regards their static or dynamic nature, ranging from the more dynamic stances of the evolutionary approach to the static economics of innovation studies. The consideration of the significant epistemological diversity of the intellectual foundations of the major contributions to the RIS field suggests their reciprocal incommensurability. However, the scrutiny of the development of the field of studies in time suggests that there is a progressive shift of attention and approach and that the actual interchange of ideas is potentially greater than expected. In particular, the less recent works are mainly located to the right hand side of the map and are divided between the more socially oriented regional scientist and economic geography studies, on the one hand, and the more abstract and rational economics of innovation studies, on the other hand. As the evolutionary approach begins to surface the field, there is a progressive meld between the definitional concepts and ideas elaborated in the field ‘till then and the more dynamic study of the role of knowledge and competences, allowing for the emergence of different strands of research which bridge static conceptual building blocks into more process oriented theories, both at the micro level of analysis - which are located on the far left hand side of the map -, and at the more macro level of analysis regarding the connection between different RIS and the opening of local networks in order to maintain the dynamic efficiency of the system. Amongst the most interesting aspects of the analysis is the presence of a relevant empty area on the bottom right hand of the MDS map. This empty space suggests the absence of research which adopts a holistic view regards the role of single focus firms in the development of RIS. The area’s position seems to suggest the need for an understanding regards the characteristics of the different RIS and the way these influence the capacity for single firms to contribute significantly to the emergence and performance of specific territorial systems. Recent studies regarding the anchor tenant hypothesis and their correlation with RIS studies could perhaps be an intriguing phenomenon to enrich this aspect of the economics of innovation.

5. CONCLUSIONS Though various authors have offered reviews of the RIS literature and some have described their personal intellectual voyage amongst the building blocks that constitute this area of scientific

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enquiry (for example, Cooke 2008), these often illuminating illustrations are nonetheless subjective and, thus, suffer from biases which pertain to the actor performing the analysis. The study proposed in this paper aims to overcome the aforementioned limitation by elaborating an objective review of the main contributions to the RIS field of research, highlighting the main themes studied and the principal approaches followed. The analysis has been conducted following the Author Co-citation method, applied to the literature regarding RIS present in the Social Science Citation Index (SSCI) of Thomson-ISI in the time span from 1990 to 2009. The initial data set counted 211 contributions, but the application of criteria which allow to screen out the research pieces which actually characterize and shaped the field left 24 foundational papers. The use of the ACA method of analysis has allowed to trace an overview of how the RIS research area is actually composed, identifying the main research themes which characterize the field, the varied perspectives adopted, as well as its boundaries and the core subject matters treated within the different clusters of research. This conceptual frame aids to clarify the main characteristics of the RIS field of study in order to foster an increase in the returns from future research efforts. The clear cut representation of the different research themes and approaches, as well as the temporal distribution of the scientific contributions, allows a user friendly introduction to the field for those who are new to it and hint towards fruitful areas of future research also for those who are more acquainted with this literature. The analysis we propose is an initial study, which no doubt has much to gain from further development. In fact, given the rapidity with which studies regarding RIS evolve and the unremitting interest for this field of intellectual endeavor, future reviews are bound to include new trends which are constantly emerging. Also, the ACA method carried out in this paper delivers a static representation of the field as it is up to a specific date. It is of interest to understand the evolution of the field of studies from its genesis. In order to gain such a dynamic representation, multiple ACA studies could be conducted selecting smaller time spans (within the general 1990-2009 time period) and confronting the results obtained progressively. Further, the sociology of scientific communities and the influence they exert on the directions towards which the field moves, could be better understood through a systematic analysis of the backgrounds and perspective which characterize editorial board members of the principal journals on which foundational studies are published.

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Ramos-Rodríguez A. R., J. Ruíz-Navarro (2004). Changes in the Intellectual Structure of Strategic Management Research: A Bibliometric Study of the Strategic Management Journal, 1980-2000. Strategic Management Journal, 25(10), 981-1004. Rowlands, I. (1999). Patterns of author co-citation in information policy: Evidence of social, collaborative and cognitive structure. Scientometrics, 44(3), 533-546. Scott A. J. (1988). New Industrial Spaces, London, UK: Pion. Small H. (1974). Co-citation in the Scientific Literature: A New Measure of the Relationship Between two Documents. Essays of an Information Scientist, 2(1), 28-31. White H. D., Griffith B. C. (1981). Author Co-citation: A Literature Measure of Intellectual Structure. Journal of the American Society for Information Science, 32(3), 163-171. Wolfe, D. (2003). Clusters Old and New: The Transition to a Knowledge Economy in Canada’s Regions. Kingston: Queen’s School of Policy Studies,.

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APPENDIX Figure 1 - Multidimensional scaling and cluster

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Table 4 – Rotated factor analysis - articles loadingsa Perspectives REGIONAL SCIENCE

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Asheim and Isaksen, (1997) Cooke, Uranga and Etxebarria (1998) Malmberg (1996) Cooke (2001) Freeman (1995) Sternberg (2000) Malerba (2002) Carlsson et al., 2002 Acs, Anselin ND Varga (2002) Cooke, Uranga and Etxebarria (1997) Sydow and Staber (2002) Humphrey and Schmitz (2002) Rantisi (2002) Coe and Bunnell (2003) Lawson and Lorenz (1999) Boschma and Frenken (2006) Boschma (2004) Romijn and Albaladejo (2002) Asheim and Coenen (2005) Wolfe and Gertler (2004) Oinas and Malecki (2002) Cantwell and Janne (1999) Bunnell and Coe (2001)

ECONOMICS SOCIAL EVOLUTIONARY KNOWLEDGE INTERNATIONAL

OF

INNOVATION

,850 ,828 ,741 ,709 ,602 ,595

,598

,930 ,884 ,769 ,711 ,830 ,753 ,744 ,640 ,579 ,943 ,936 ,803 ,771 ,705

a

Rotation converged in 7 iterations. Extraction Method: Principal Component Analysis. Rotation method: Varimax with Kaiser normalization.

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,841 ,819 ,655

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Revitalising the Outsourcing Discourse within the Boundaries of Firms Debate Lucia Marchegiani Assistant Professor of Management. University Roma Tre, Rome, Italy. e-mail: [email protected]. Corresponding author Luca Giustiniano Associate Professor of Management. LUISS Guido Carli, Rome, Italy. e-mail: [email protected] Enzo Peruffo Assistant Professor of Management. LUISS Guido Carli, Rome, Italy. e-mail: [email protected] Luca Pirolo Assistant Professor of Management. LUISS Guido Carli, Rome, Italy. e-mail: [email protected]

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Received September 5, 2012 / revised October 26 / accepted October 27 / published online October 31, 2012. DOI: 10.7350/BSR.A13.2012 – URL: http://dx.medra.org/10.7350/BSR.A13.2012

ABSTRACT Despite outsourcing has been at the core of managerial practice and literature for a long time, still authors do not agree on a clear understanding of the overall outsourcing process. This article answers two main questions, relevant to researchers and practitioners: 1.What are the main findings so far in outsourcing literature? 2. What do we still need to learn? Through a comprehensive review of the literature, we offer systematization of the existent body of knowledge on outsourcing, its implications on firms’ boundaries, and the theoretical challenges. In conclusion, implications for managers are drawn. Keywords: Outsourcing, Boundaries of Firms, Transaction Cost Economics, Resource-based View.

1. INTRODUCTION Outsourcing, which is broadly recognized as an important and multi-faceted strategic choice, has not yet been consistently defined, studied or put into practice. A recent publication by the OECD STAN database1 confirmed that outsourcing reached the peak of its popularity during the late 1

Release as of December 2011: OECD countries - time-period 1970-2009 (www.oecd.org).

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1980s and 1990s, boosted by the rush of corporate downsizing and the reengineering bandwagon effect. However, it continued to grow at a rate of 30-35 percent (revenues per year) until 2007, and it is expected to return to similar growth rates by 20122. Experts have not only predicted resurgence in outsourcing practices but also suggested that outsourcing needs to be redefined and better understood (Outsourcing Center, 2011). This paper responds to the fact that, despite almost 30 years of research and practice, the field of outsourcing still suffers from ambiguous definitions and lacks guidelines for strategic implementation. Moreover, although outsourcing practices were once embraced favorably by the public, the widening of their scope has inevitably clashed with the priorities of some internal and external stakeholders (e.g., employees, unions, banks). To clarify the underlying concepts and to show the main concerns about implementation, we reviewed the literature in the field of management by assessing whether the established research can explain the recent trends in outsourcing. This paper refers to a recognized framework for a comprehensive survey of the existing literature and the principal mainstream theories. Through a critical review of the main hypotheses and limitations of the literature, this paper aims to foster new insights for both academics and practitioners by answering two main questions: a) What are the main findings in the existing literature on outsourcing? And b) What are the implications for managers? We propose a research model to investigate outsourcing decisions that address the limits in the existing literature. In particular, we call for an integrated and longitudinal approach.

2. WHAT ARE THE MAIN FINDINGS ON OUTSOURCING?

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2.1 Definitional Aspects Outsourcing practices have varied over the years, covering a diverse range of services from support activities to core managerial processes and from service-based activities to productive processes, such as modular production (Brusoni & Prencipe, 2001; Prencipe, Davies, & Hobday, 2003). Because of these different applications, the management literature still lacks a clear definition for outsourcing that would incorporate all of its possible implementations. Broadly speaking, outsourcing refers to a firm’s external acquisition of inputs, services, or processes (Amiti & Wei, 2004; Boldea & Brandas, 2007). More specifically, some authors define outsourcing as an element of a firm’s overall strategy or a firm’s decision not to make a service or product internally, but to purchase it externally (e.g., Quinn & Hilmer, 1994; De Fontenay & Gans, 2008). Other scholars focus on global sourcing and define outsourcing as the integration and coordination of production and marketing (Kotabe, 1990; Murray, Kotabe, & Wildt, 1995). In this paper, we refer to outsourcing as the procurement of supplies or services related to a value chain activity from legally independent firms. “Domestic” outsourcing occurs when the firm sources from suppliers of the same (home) country, and offshoring occurs when the outsourced business functions are done in another country, typically where the costs of resources are low. These definitions can help to distinguish outsourcing from divestiture strategies, which refer to a firm’s adjustments of its ownership and business portfolio structure (Brauer, 2006).

2

Despite a frictional slow down in 2008 and 2009 (annual growth of 20 percent), forecasts from the field (e.g., Sequoia Capital and ValueNotes) depict a reversal in momentum by 2011.

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2.2 The Model Overview

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The debate about outsourcing is central in multiple fields of research and, along with the general question of firms’ boundaries, has received much attention over the years. Many studies have investigated outsourcing, a hot topic in firm strategy, from diverse perspectives that range from economics to finance or, more generally, management (Mayer & Salomon, 2006; Rothaermel, Hitt, & Jobe, 2006). The only noteworthy exception may be found in Wolter & Veloso (2008), although it is focused on the relation between innovation and vertical integration. As a result of these diverse definitions in research, studies often produce contradictory results (Kotabe & Swan, 1994; Mol, van Tulder, & Beije, 2005) and, in the best case, face unanswered questions (De Fontenay & Gans, 2008). To disentangle the main issues in outsourcing, this paper aims to clarify the different approaches offered by the literature. This clarification aims to resolve the disputes of prior works by identifying the dominant patterns and gaps in the existing literature. Our review shows that, among the different theoretical lenses used in this field of research, Transaction Cost Economics (TCE) and the Resource-Based View (RBV) are the most widely applied frameworks (Espino-Rodríguez & Padrón-Robaina, 2006; Mayer & Salomon, 2006; Reitzig & Wagner, 2010). Based on the seminal work of Coase (1937) and Williamson (1975), TCE assesses the choices between self-producing (internal transactions) and outsourcing activities (market transactions) by comparing the internal costs (hierarchy) and the costs of “using” the market (Jones & Hill, 1988). Subsequent research has shown that TCE may overrate rationality in firms’ behaviors due to a lack of cognitive capacity to assess appropriability (Oxley, 1997; Pisano, 1990) or observability (Holmstrom, 1979). Additionally, outsourcing literature shed little light on the possible ambiguities related to the assessment of the actual dynamics of transaction costs (Chen, 2009; McCarthy & Anagnostou, 2003). For instance, differences in culture, language, and business laws may have a great impact on transaction costs and thus limit the generalizability of prior studies across national governance systems. However, the RBV provides some useful insights to avoid these limits of “over-rationality”. The application of RBV to the analysis of outsourcing strategy shows that the decision to outsource is taken according to a firm’s capabilities compared with those of its suppliers. Espino-Rodríguez and Padrón-Robaina (2006) divided this perspective into two categories: first, a focus on “the propensity” to outsource and, second, the “relation” between the decision to outsource and organizational performance. Combining the TCE and RBV, Mayer and Salomon (2006) found that “contractual hazards” provide firms with an incentive to internalize, independently of firm capabilities; however, in the presence of weak technological capabilities, it is more likely that firms will outsource. Therefore, RBV complements TCE in the treatment of outsourcing by focusing on the positive aspects of in-house strategic activities (Espino-Rodríguez & Padrón-Robaina, 2006) and resources (Prahalad & Hamel, 1990). The International Business (IB) approach does not constitute a theoretical framework; still it is a necessary part of our literature review on outsourcing. From the IB perspective, outsourcing is influenced or co-determined (among other factors) by the following: the “multinationality” of firms, the frequency of cross-border communications, and the differences in asset costs across borders (Mol et al., 2005). Research on international business has proposed many potential, often overlapping, definitions of outsourcing: international outsourcing (Levy & Dunning, 1993), multinational sourcing (Birou & Fawcett, 1993), offshore sourcing (Frear, Metcalf, & Alguire, 1992; Kotabe & Swan, 1994), offshore outsourcing (Bertrand, 2011), and international economics (Lommerud, Meland, & Straume, 2009).

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3. A MODEL FOR CATEGORIZING RESEARCH ON OUTSOURCING Three major research questions have a central role in outsourcing research: a) Why should a firm decide to outsource?; b) What are the effects of outsourcing?; and c) How should the process of outsourcing be managed? We developed a framework of 10 boxes to classify the existing studies on outsourcing (Johnson, 1996) into three streams: i) antecedents, ii) process management, and iii) outcomes. Figure 1 Classificatory Framework

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The antecedents include: 1) Environment; 2) Industry Characteristics; 3) Firm Characteristics; and 4) Outsourced Areas (Boxes 1 to 4 in Figure 1). The process concerns include 5) Arrangements; and 6) Management of Outsourcing) (Boxes 5 and 6 in Figure 1); and the outcomes include 7) Economic and Financial; 8) Strategic; and 9) Organization and Governance (Boxes 7 to 9 in Figure 1). Within this framework, we can identify two types of study on outsourcing. The first group contains studies that fit a specific box; in general, these studies describe the relevant phenomenon or variables. The second group consists of studies that explore the links between the boxes and highlight the relations between variables or concepts. As a result, we can offer a comprehensive view of the literature and its main findings on outsourcing. Our systematization of the literature is also useful for identifying the research that is still needed in the field. 3.1 Antecedents The search for the antecedents of outsourcing, alternatively called “reasons” or “drivers”, is probably the topic that has driven most of the research on outsourcing. When it comes to answering why a firm should outsource, the literature identifies a wide range of causes and drivers, which we grouped into four main contingency factors (antecedents) that influence firms’ decision making: 1) Environment; 2) Industry characteristics; 3) Firm characteristics; and 4) Outsourced areas.

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3.1.1 Environment Despite the extensive range of entities and phenomena that could be related to the external environment, our analysis focuses on the most relevant factors pointed out in the recent literature. The external environment has been considered in general terms by referring to macroeconomic drivers, such as the size of the home country and economy, currency fluctuations, the level of foreign direct investment, and the presence of foreign companies. These factors have been taken in consideration either directly (though the inclusion of such variables in the models, e.g., Swamidass & Kotabe, 1993) or indirectly (by choosing sample from countries with specific characteristics, e.g., Mol et al., 2005)3. Other scholars suggest that environmental dynamism has a moderating effect on the relationship between outsourcing intensity and firm performances (Gilley & Rasheed, 2000). Studies that adopt a pure transaction cost perspective tend to translate the impact of the external environment in terms of general uncertainty (Aubert, Rivard, & Patry, 2004), volume (market) uncertainty, and technological uncertainty (Aubert et al., 2004; Walker & Weber, 1984, 1987) or, alternatively, to contractual hazard (Duncan, 1998; Mayer & Salomon, 2006). In sum, some scholars have considered three main dimensions of the external environment: i) rights protections and corporate governance systems; ii) markets; and iii) technology.

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i) With respect to rights protections and corporate governance systems, the unionization and the general defense of workers’ jobs seemed to act as an important antecedent of outsourcing. Lommerud et al. (2009) explained the trends of deunionization and increased international outsourcing in many countries. They assume that firms do not outsource any activity if they can obtain it at a lower price in the “domestic” market. From this perspective, the decision to outsource any part of production is determined not by in-house production costs, but rather by the reserve wage of domestic workers. They affirmed that stronger unions imply higher collective bargaining power and increase job security. Thus, although domestic wages are higher, stronger unions lower the possibility for employers to introduce international outsourcing. Kotabe, Parente, and Murray (2007) drew similar conclusions and distinguished between wages to a firm’s labor force and the strength of its unions in detail. ii) As far as market characteristics are concerned, the literature provides some insights on international business. In this field, the “home market” dimension has been adapted to outsourcing from the literature on Multinational Companies (MNCs) (Mol et al., 2005). Studies assume that the degree of outsourcing is negatively related to the size of the focal country and shift the focus from size to foreignness and domestic matters (such as the degree of importexport and the quality of domestic supply) (Coucke & Sleuwagen, 2008; Murray, Kotabe, & Wildt, 1995; Swamidass & Kotabe, 1993). Considering size and the idea of extended enterprise, McCarthy and Anagnostou (2004) followed a slightly different approach and focused on the value-adding network of the focal organization. Another aspect of the market is related to the pace of change in customer needs, which is evaluated in terms of both speed and heterogeneity. On one hand, some studies identified the uncertainty surrounding the demand as an antecedent for outsourcing (Quélin & Duhamel, 2003); on the other hand, it seems that a greater change in customers’ needs and a greater degree of heterogeneity leads to more outsourcing (Kotabe et al., 2007).

3

In this sense, the unusual distinction between domestic firms and subsidiaries of MNCs made by Coucke and Sleuwagen (2008) could help lead to a better understanding of the underlying phenomena.

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iii) The technological dimension is viewed in terms of its impact on manufacturing activities. Specifically, the possibility of switching from an in-line integrated internal supply chain to a modular production gives firms the opportunity to outsource intermediate products and some value-chain sub-activities (Brusoni & Prencipe, 2001; Kotabe, 2007; Kumar, van Fenema, & von Glinow, 2008; Parmigiani & Mitchell, 2009; Prencipe et al., 2003; Tiwana, 2008). Thus, all the studies seem to agree that, given this technological opportunity, outsourcing and offshoring could guarantee sustainable competitive advantages. Nevertheless, technological evolution could also be considered an environmental pressure for outsourcing (Quélin & Duhamel, 2003). Technology can also be considered a contingent antecedent for outsourcing due to the enabling potential of Information Technology (IT) as a coordination mechanism. Jean, Sincovics, and Cavusgil (2010) classified IT resources in IT advancement and electronic integration to explain how IT solutions could foster outsourcing relations between customer firms and suppliers. This study showed that the proposed classification of IT resources can identify different types of information exchanges and knowledge-related activities in customer-supplier relations. A glance at the present situation —where companies can outsource, control and manage remote activities—clarifies how IT could support the remote purchasing of both primary and support activities. 3.1.2 Industry Characteristics Many studies on outsourcing have dealt with specific industries as case studies to ground theories and verify hypotheses. By decoding the assumptions of the main studies, we can identify some general industry-related findings: 162

i) In knowledge-intensive industries (e.g., pharmaceutics, biochemistry, and healthcare), selective outsourcing could occur in favor of specialized and focused suppliers and in business-related activities (Quinn, 2000); or in hybrid business models (Marchegiani et al., 2012). ii) In manufacturing complex products (e.g., automotive, aerospace, and software production), the modularity of components and subcomponents could require forms of joint development and the execution of primary activities related to the entire supply chain system (Arnold, 2000; Brusoni & Prencipe, 2001; Tiwana, 2008). iii) In information-intensive industries (e.g., banking, insurance, editing), the outsourcing of IT should involve reliable partners because information is a critical asset in these fields. 3.1.3 Firms’ Characteristics Many authors focused on firms’ size and argued that large firms are more likely to outsource due to their larger bargaining power, which contributes to lower prices for services and products. This hypothesis is supported by the assumption that, in international outsourcing, large firms may have access to more suppliers that can contribute to their international development by working in several target markets. Subsequently, the introduction of the RBV to explain outsourcing decisions (Bettis, Bradley, & Hamel, 1992; Quinn, 1992) enabled scholars to examine a common managerial practice that peaked during the 1990s. At that time, the idea of core competencies, coined by Prahalad and Hamel (1990), was a successful theory that suggested that firms should keep core activities and competencies in-house and outsource non-core services and functions. The identification of non-core activities and their potential “outsourceability” has been associated with many factors, such as the following: a) lack of capital and know-how; b) need for flexibility (through the reduction of fixed costs); and c) shorter delivery time. Some

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studies focused on the idea of “asset specificity” (Lyons, 1995) or recalled the impact of path dependence on sourcing decisions (Barney, 1999). However, the pioneering work of Heikkilä and Cordon (2002) shed additional light on the idea of core and non-core competencies in relation to outsourcing. In particular, the study suggested that core competencies related to activities that should not be outsourced can be classified into three types (p.188-9): 1) distinctive competencies, key capabilities allowing the firm to excel; 2) essential competencies, activities that are needed for profitable operations; and 3) protective competencies, related to activities that could be risky if not properly managed. Espino-Rodríguez and Padrón-Robaina (2006) proposed that the following resources and capabilities are associated with a lower chance of being outsourced: a) more valuable and specific (heterogeneous) for the firm; b) more nonsubstitutable and unique; and c) allowing for higher rents. In contrast, “outsourcing the activities or business processes not forming part of the firm’s core competences (complementary and noncore) to specialist suppliers increases organizational performance” (p. 65). Luftman (2003) considered the IT area critical for strategy improvement and extended some considerations by Loh and Venkatraman (1992) to combine the idea of core/non-core competences (Prahalad & Hamel, 1990) with the impact of underlying activities as a critical factor for firms (Porter, 1985). Hence, companies should outsource services that are not related to their core competencies. At the same time, they should reassess and redeploy core competencies allocated to activities that are not related to critical factors. In contrast, Quinn (2000) showed that even activities that are potential sources of competitive advantage should be outsourced if the firm cannot develop them in the time frame required by the market. When core competencies are embedded in proprietary technologies, companies could benefit from the internal sourcing of activities and components that involve a high level of proprietary technologies (Murray, Kotabe, & Wildt, 1995). Mayer and Salomon (2006) made a similar argument, although it is adjusted for the (internal) phenomenon of “technological capability”. In reviewing the field of outsourcing, business and corporate strategies could be considered in the general setting of firms’ characteristics. In particular, Gilley and Rasheed (2000) attempted to explain performance related to outsourcing in the context of firm strategy by considering that, at a SBU level, cost leadership and differentiation (Porter, 1985) could moderate these decisions differently. The dual consideration of customer and supplier organizations as a source for the effective implementation of the outsourcing decisions requires researchers and practitioners to also consider information sharing and the quality of communication as firm characteristics that could impact firm performance (Lee & Kim, 1999). 3.1.4 Outsourced Areas The neo-classical make-or-buy decision process leads to the traditional use of an accounting perspective to assess the areas/services that firms could have purchased externally to reduce costs. In the late 1980s, attention moved from support to the primary activities of Porter’s value chain (1985) (Ford & Farmer, 1986; Saunders, Gebelt & Hu, 1997). More recently, a survey conducted by Quélin and Duhamel (2003) showed that, among large European companies, the areas that the following areas are the most affected by the decision to outsource: office IT, industrial maintenance, waste management, logistics, and telecommunications. IT-related services remain the most important activities outsourced by firms, regardless of firm size. In fact, outsourcing contracts range from mega-deals, typical of large companies, to spot sourcing, which is practiced by smaller firms (Cheon, Grover, & Teng, 2001; Lacity & Hirschheim, 1993) in a diverse range of industries (Lacity & Willcocks, 1995; Loh & Venkatraman, 1992).

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Many scholars have also focused on R&D. Quinn (2000) showed that in research-oriented and technology intensive-industries, such as the pharmaceutical and biochemical industries, earlystage research and advanced development could be subject to selective outsourcing if the firms can select and engage highly specialized, focused and committed partners. Similar considerations could be made for “smart sourcing” (Earl, 1996) and concurrent sourcing (Parmigiani & Mitchell, 2009), which support the traditional make-or-buy decisions (Aubert & Weber, 2001; Lacity & Hirschheim, 1993; Lacity & Willcocks, 1995). 3.2 Process The literature on outsourcing does not provide many insights into the idea of “process”, defined as the decisional and operational bridge connecting antecedents and outcomes. Specifically, studies have treated outsourcing design and organizational formula differently. Some focus on the potential effectiveness of alliances, on the threat of such contracts or, alternatively, on the general idea of partnership quality, with the aim of depicting “winning combinations” (Saunders et al., 1997).

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3.2.1 Arrangements Kakabadse and Kakabadse (2000) was a valuable milestone in terms of arrangement of outsourcing process because it classified possible sourcing configurations. Despite being limited to the centralization of shared services, the paper clearly distinguished the sourcing configurations in the following: a) contract sourcing, b) sourced service consortia, c) insourcing, and d) spin-off sourcing. This configuration choice seems to have been driven by six factors: 1) matching sourcing configuration with enterprises’ development requirements; 2) selecting partners; 3) strengthening or enlarging the host enterprise’s core business; 4) harnessing synergies related to the exploitation of internal or external economies of scale; 5) assessing the return on investments; and 6) appreciating the nature of commitment. In this scenario, IT solutions could sustain the transactions between partners if firms moderate their competition and aim for well-integrated consortia, which are compatible with a scale economy-based philosophy and capability-building capacity objectives (Kakabadse & Kakabadse, 2000). 3.2.2 Management of Outsourcing The contribution of Jean et al. (2010) is uniquely valuable in assessing the management dimension of outsourcing. The study explored three governance mechanisms. First, Cooperativeness is the outcome of the interaction between two (or more) exchange partners; this mechanism goes beyond the mere presence of joint activities (Obadia, 2008) and embeds the acceptance of relational rules (Cannon & Perrault, 1999). Second, in Output monitoring, the focus is on service-level agreement and evaluation of the deliveries. Third, Behavior monitoring focuses on the use of power and influence. Additionally, we propose two more elements connected to the management of outsourcing: 1) location and 2) product life-cycle. 1. Location. According to the evidence of MNCs and international business literature, (Buckley & Pearce, 1979) the internationalization of sourcing should adhere to the following trends: i) inversely related to the size of the (parent) country (Ruigrok & van Tulder, 1995; Wyckoff, 1993); and ii) more frequent for foreign subsidiaries than for domestic firms, given the strength of the home supply bases (Birou & Fawcett, 1993; Monczka & Trent, 1991; Murray, Kotabe, & Wildt, 1995; Swamidass & Kotabe, 1993).

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2. Product life cycle. Product life cycle has been related to outsourcing in two ways. The first idea relates the marketing product life cycle to outsourcing in terms of market volumes and future development. The second interpretation includes some industry-level studies that have tried to link the international product life cycle (Vernon, 1979) to international sourcing by arguing that the volume of local sales influences choices about sourcing (Swamidass & Kotabe, 1993). 3.3 Outcomes Although only a few strategy scholars have reviewed the studies on the outcomes of outsourcing, we can identify some general indications of the effects of this strategy on firms. First, these outcomes can be ascribed to different perspectives, ranging from an economic or financial view to a broader management vision. Second, an analysis of the studies on this topic shows that, in studies on economic and financial performance, the implications of outsourcing have been assessed both at an early stage, connected to the simple announcements of the decision to outsource, and at a later stage, connected to the implementation of this decision. In other words, outsourcing generates outcomes both at the moment of the decision and after its implementation.

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3.3.1 Economic and Financial Outcomes Economic and financial performances, deriving from outsourcing strategies, mainly refer to the reactions of the financial market to the announcement of an outsourcing strategy and its effects on a firm’s value (Bryce & Useem, 1998). Oh et al. (2006) analyzed market perceptions in reaction to IT outsourcing announcements. This study showed that investors react favorably to outsourcing when the level of transactional risk is low, but react negatively to outsourcing arrangements that pose high transactional risk. In other words, investors understand the potential transaction risks that accompany IT outsourcing decisions. Hayes, Hunton, and Reck (2000) used a similar approach and focused on the impact of information systems outsourcing announcements on the market value of contract-granting firms. Specifically, Hayes et al. (2000) found positive and significant market value gains for smaller compared to larger firms and services compared to non-service industry firms. In sum, the results support the notion that smaller and service firms can benefit from strategic outsourcing, which can be an effective strategy to achieve superior performance. This finding stands in partial contrast to the studies classified as dealing with firm characteristics as antecedents for the outsourcing decision. Reitzig and Wagner (2010) also focused on the technology-based industries and drew on patent data for approximately 500 firms over 20 years to provide evidence of a relationship between firm performance and vertically related activities in its value chain that is driven by knowledge. They affirmed that the rate of outsourcing upstream activities is negatively related to a firm’s downstream performance. Moreover, ceteris paribus, similarity in knowledge bases and underlying upstream activities performed internally and externally increases a firm’s downstream performance. 3.3.2 Strategic Outcomes Strategic outcomes generated by the implementation of outsourcing strategy can be analyzed from both an empirical and a theoretical point of view. For example, Insinga and Werle (2000) affirmed that outsourcing strategy is motivated by the growing pressure on management to remain competitive by “accomplishing more with less”. In this view, outsourcing is a means to

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achieve efficiency, effectiveness, and, in turn, greater productivity, through strategies such as restructuring, downsizing, and reengineering activities. The empirical contributions on the effects of outsourcing have usually focused on specific industries. For example, Rothaermel et al. (2006) focused on the global microcomputer industry. This study developed a large panel of longitudinal data, documenting over 35,000 products, to investigate the relationship between strategic outsourcing and vertical integration, their effects on a firm’s product portfolio and product success, and, in turn, their impacts on competitive advantage and overall performance. The baseline proposition was that balancing vertical integration and strategic outsourcing enriches a firm’s product portfolio and product success and, in turn, contributes to competitive advantage and overall firm performance. Building on these findings, Bettis et al. (2006) conducted research on firms in North America, Europe, and Asia to identify how the proper use of outsourcing can build competitive advantage and affirmed that the improper use of outsourcing can destroy the future of a business.

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3.3.3 Organization and Corporate Governance Outcomes The organizational outcomes and the effects of outsourcing on corporate governance have been analyzed from a worker’s perspective. In this view, Brooks (2006) focused on the potential effects of outsourcing on IT workers and their environment. Specifically, the potential results of outsourcing have an impact on the employers who change organizations after the implementation of the outsourcing strategy and on those who remain at the firm. IT workers shift organizations, change jobs, or exhibit different work-related behaviors (such as changes in motivation, involvement, or commitment) according to the impact of outsourcing on individual perceptions of job alternatives and job-related satisfaction. In contrast, workers can decide to be loyal to their organization depending on the impact of outsourcing on their perception of the profession, career-related opportunities, and ability to change careers. In sum, if negative perceptions of outsourcing supersede the individual's level of satisfaction and commitment, then the potential loss in performance, productivity, and innovation could be detrimental to the firm. Lommerud et al. (2009) also analyzed the impact of outsourcing on individual workers and found that it leads to increased wages for the remaining in-house workers. 3.4 Linkages Our review also aimed to highlight the findings of studies that we classify as “linkage studies” (see Figure 1). From a statistical point of view, the main relations investigated in the research on outsourcing concern the link between a firm’s characteristics and the outcomes of the decision to outsource. According to numerous authors, certain firm characteristics seem to be the key to understanding outsourcing decisions and, ultimately, their effect on firm performance. Along this path of study, some works (Hayes et al., 2000) have focused on firm size and suggested that smaller companies, compared to larger ones, can benefit more from outsourcing strategy. Firms’ competitive strategy is also treated as a key predictor of outsourcing success. Numerous studies have investigated the role of outsourcing strategy in pursuing or enhancing competitive advantage. Gilley and Rasheed (2000) showed that firm strategy mediates the relationship between outsourcing and performance. Specifically, whereas cost leadership fosters a positive relation between peripheral outsourcing and financial performance and between core outsourcing and innovation performance, differentiation shows a negative relationship. Similar to competitive strategies, researchers have also analyzed corporate and functional strategies in exploring the link between outsourcing decisions and expected outcomes. With respect to corporate strategy,

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Quélin and Duhamel (2003) studied the motives of corporate management in large European manufacturing firms to engage in outsourcing and the risks they perceive to be associated with strategic outsourcing operations. In a study of functional strategies with a focus on production and innovation activities, Murray et al. (1995) hypothesized a moderating effect of productrelated factors (product innovations, process innovations and asset specificity) on the relationship between global sourcing strategy and the financial dimension of product market performance. Finally, following a traditional resource-based approach, it is appropriate to include a firm’s capabilities in the analysis of boundary decisions. Barney (1999) assumed that it is costly for a firm to create a particular capability on its own and argued that firms in rapidly evolving hightechnology industries prefer to access capabilities through non-hierarchical forms of governance. In other words, outsourcing strategy is strictly connected to the benefits that an outsourcing partnership can generate. Furthermore, firms’ characteristics have been analyzed to explore their link with the arrangements of outsourcing strategy. For example, De Fontenay and Gans (2008) adopted a resource-based approach combined with bargaining theory to analyze outsourcing strategy. Specifically, they analyzed whether a downstream firm with upstream production resources or assets would choose to outsource to an independent or established firm upstream. The downstream firm faces a trade-off between lower input costs caused by independent competition and a higher resource value associated with the firms that can consolidate their upstream capabilities. According to De Fontenay and Gans (2008), this trade-off is resolved in favor of outsourcing to an established firm. Research on the characteristics that can explain or predict the success of outsourcing has not been limited to “internal” features but has also included some “external” factors, such as the quality of the relationship between a firm and its partners. To link this factor to outsourcing outcomes, Lee and Kim (1999) conducted an in-depth study to investigate whether partnership is an effective way to improve economies of scale and scope in traditional modes of organization. Their study emphasized that partnership does not guarantee a desirable outcome. To reach such an outcome, firms must pay careful attention to the quality of partnerships that result from outsourcing and ensure they are positively influenced by factors such as participation, communication, information sharing, and top management support. In the research on firm characteristics, various authors have focused on the outsourced areas to identify the functions that might produce more positive outcomes for outsourcing strategy. The majority of the literature in this area is concentrated on IT, which is seen as the area where outsourcing strategy can be easily implemented with high potential benefits. Among the studies on this issue, Oh et al. (2006) produced fruitful insights by finding evidence that investors’ reactions to IT outsourcing announcements are strongly connected to investors’ perceptions of the risks involved in IT outsourcing strategy. Although most of the studies that connect outsourcing areas to expected outcomes have focused on IT, we can identify some works on other sectors. For example, Quinn (2000) assumed that innovation and R&D activities play a strategic role in outsourcing strategies and suggested that a firm can derive higher innovation returns from outsourcing the entire business process or process design activities that are not core competencies of the firm. Leiblein and Miller (2003) have also investigated the link between innovation, viewed as a possible functional area for outsourcing, and the outcomes of this decision. They found that firms with more experience with a particular technological process are more likely to internalize manufacturing activities than are firms that lack such production experience. Similarly, firms with high levels of sourcing experience are

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more likely to outsource their production than firms that do not have such experience. In a similar study focusing on the global microcomputer industry, Rothaermel et al. (2006) explored how strategic outsourcing and vertical integration enrich a firm's product portfolio and product success. Some indications can also be traced to production activities, which support the main findings of the research on the links between innovation and outsourcing. Along this path of study, the contribution of Parmigiani and Mitchell (2009) argues that concurrent sourcing of complementary components becomes more common when firms have relevant knowledge about the components in conjunction with suppliers (interfirm expertise) and within the firm (withinfirm shared expertise). Research on outsourced areas has also addressed the competitive environment in which firms act. For example, Walker and Weber (1984) showed that comparative production costs are the strongest predictor of make-or-buy decisions and that both volume uncertainty and supplier market competition have small but significant effects. The management of outsourcing strategy influences the strategic outcomes a firm can attain. Insinga and Werle (2000) argued that the business environment pushes companies to conduct several functions in house and the rest through aggressive outsourcing. Nevertheless, this strategic choice creates some dependencies that, in turn, can lead to unforeseen strategic vulnerability. Thus, Insinga and Werle (2000) shifted the focus to the dependencies that outsourcing can create and considered the negative effects of the links that connect firms to external actors.

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4. DISCUSSION AND CONCLUSIONS The framework illustrated in Figure 1 highlights some particularly important points for future research. We thus sketch a tentative future research agenda that considers both theoretical and empirical factors. In terms of theory development, the existing literature can be classified according to the underlying theoretical framework illustrated in Table 1 (in Appendix). As first evidence, we note that the reviewed papers recall mainly two theoretical frameworks, namely TCE and RBV. On this basis, we can point out three main issues. 1) Our first suggestion for further research grounded on TCE is that it should shed more light on the actual dynamics of transaction costs. First, for example, the mere existence of a regional trade agreement (e.g., NAFTA, Mercosur) or international mesa-institution (e.g., UE) might not automatically reduce transaction costs (Coucke & Sleuwaegen, 2008; Kotabe et al., 2007; Mol et al., 2005). Second, differences in culture, language, and business laws still have a major impact on transaction costs4 and thus limit the generalizability of prior studies across national governance systems. Whereas the outsourcers’ production costs may decrease (Rangan, 2000), transaction cost levels rise with the distance between the two or more markets due to the differences that may occur in language, culture and other institutional items. We call for an institution-based analysis of the outsourcing phenomenon (Peng, Li Sun, Pinkham, & Chen, 2009) that should focus on how formal and informal institutions influence transaction costs. Third, outsourcing may generate a separate type of transaction cost (in itinere) that has been neglected so far (i.e., the costs associated with the management of the outsourcer-outsourcee 4

The concept of “regional outsourcing” arises from the presence (involvement) of two or more partners from different countries belonging to the same free trade region or regional international agreement.

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relationship and other control mechanisms). Future research should pay more attention to the implementation of outsourcing choices. Furthermore, some limits of “indirect assessment” and a lack of rigor in measurement characterize the translation of Williamson’s original idea of “specificity”: object specificity (Arnold, 2000), asset specificity (Aubert et al., 2004), and brand specificity (Chen, 2009). 2) Despite the consistent amount of papers using RBV to complement TCE, we have a general caveat for the outsourcing process. The literature focuses either on the propensity to outsource or on outsourcing’s relation to organizational performance (Espino-Rodríguez & Padrón-Robaina, 2006) but often ignores the implementation dynamics (process). The idea of “governance capability” that was developed by Mayer and Salomon (2006) can be viewed as an important milestone leading to a deeper understanding of the practical organizational drawbacks. Mahnke (2001) solely suggested an evolutionary perspective on vertical dis-integration. The Author contributes to the literature by considering the switching costs that impact the scope and speed of the process of vertical dis-integration, and by adding a long-term perspective.

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3) The reviewed contributions did not properly consider corporate and business strategies as antecedents of the decision to outsource. Partial exceptions could be found in the model developed by Trent and Monczka (2003), which identified several forms of international sourcing as different stages of global sourcing. Other exceptions are the studies that directly (Kotabe & Swan, 1994; Mol et al., 2005) or indirectly (Kotabe et al., 2007) refer to the classification introduced by Bartlett and Ghoshal (1989) to analyze the relation headquartersubsidiaries as a potential source of contingent antecedents (i.e., frequency in communication, availability of local resources, knowledge transfers). We suggest adopting a systemic vision that embeds outsourcing strategies in a firm’s overall strategic decision path. Considering the empirical factors, we can highlight two main controversial points in the literature. A first concern relates to the assessment of the strategy implementation, which cannot be assessed if the intended goals are undeclared or unclear. Despite the emphasis on performance improvement in most of the literature (e.g., Lee & Kim, 1999; Leiblein & Miller, 2003; McCarthy & Anagnostou, 2004; Mol et al., 2005), many studies evaluate this variable through perceptions of advantages, cost cutting and efficiency, market share, and overall exports (Bertrand, 2011; Frear et al., 1992 Kotabe, 1998; Kotabe & Swan, 1994; Scully & Fawcett, 1994). Nevertheless, some studies mentioned indicators of financial or market performance, but measured through “comparison with competitors” (Gilley & Rasheed, 2000; Mol et al., 2005) or through indirect measures of outsourcing success (Lee & Kim, 1999). Therefore, we believe that future research should rely on a new set of quantitative performance indicators to be observed both ex ante and ex post outsourcing decisions. A second concern is connected to the poor attention that is often given to crucial organizational aspects. Although the literature provides some ideas on this topic, we believe that future research on outsourcing should focus more on several specific aspects: a clear definition of the scope, the outsourcer-supplier relation, the firm’s attitude to collaboration, and IT as an enabling factor. Outsourcing covers a range of activities, both in the manufacturing and service industries. Therefore, studying a limited range of activities (scope) seems an increasingly limited approach to firms’ decisions. In particular, it is difficult to generalize models obtained from the following specific fields: franchises and supplies (Walker & Weber, 1984, 1987), components (Kotabe & Omura, 1989; Kotabe & Swan, 1994; Swamidass & Kotabe, 1993), complementary components (Kogut & Zander, 1992; Milgrom & Roberts, 1990), intermediate products (Mol et al., 2005),

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intermediate goods (Lommerud et al., 2009), modular productions (Brusoni & Prencipe, 2001; Prencipe et al., 2003), interfirm modularity (Tiwana, 2008), strategic modularization (Kotabe et al., 2007), firm complementarity (Parmigiani & Mitchell, 2009), intertask interdependence (Kumar et al., 2008), the degree of standardization of production and product innovation (Murray et al., 1995), support activities (Tettelbach, 2000), or selected primary activities (Ruiz-Torres & Mahmoodi, 2008). As for the outsourcer-supplier relationship, many studies simplify the decision to outsource by gathering the counterparts (suppliers/outsourcers) into fictionally homogeneous entities (Bettis et al., 1992; Quinn & Hilmer, 1994). However, evidence shows that both large and small enterprises engage in outsourcing relations with heterogeneous partners. Therefore, the outsourcee’s characteristics should be included among the reasons for outsourcing (e.g., competences, knowledge, general similarity, or other elements that can be considered valuable for strategic partnership). This type of analysis is also useful for exploring a firm’s attitude toward collaboration. In fact, outsourcing is often viewed as the “consequence” of a firm’s ability to search for and evaluate suppliers (Mol et al., 2005; Rangan, 2000; Webster & Wind, 1972), or it is viewed as influenced by previous merger and acquisition (M&A) experience (Mol et al., 2005)5. Despite some distinguished work on partnership quality (Lee & Kim, 1999), most of the existing research has treated the general attitude of partners to collaboration as a marginally important antecedent for outsourcing. However, we appreciate that recent studies have shown that the governance of these relations can include cooperativeness, output monitoring and behavior monitoring (Jean et al., 2010). Finally, there is a clear gap in the literature on the significant role of IT in the implementation of outsourcing decisions. Although scholars in the Management of Information Systems (MIS) field have paid extensive attention to outsourcing, many of their contributions lack an explicit theoretical perspective6, which creates some problems for the empirical verification of Information Systems’ expected role as an enabler.

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Walker, G., Weber, D. (1984). A transaction cost approach to make or buy decisions. Administrative Science Quarterly, 29(3), 373–391. Walker, G., Weber, D. A. (1987). Supplier competition, uncertainty and make or buy decisions. Academy of Management Journal, 30(3), 589-596. Webster, F., Wind, I. (1972). Organizational buying behavior. Englewood Cliffs, NJ: PrenticeHall. Williamson, O. (1975). Markets and hierarchy. New York, NY: Free Press. Wolter, C., Veloso, F. (2008). The effects of innovation on vertical structure: Perspectives on transaction costs and competences. Academy of Management Review, 33(3), 586-605. Wyckoff, A. (1993). The extension of networks of production across borders. Science, Technology and Industry Review, 13(4), 61–87.

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APPENDIX Table 1: Positioning of reviewed papers Theoretical perspective

Transaction cost economics

Resource-based view

177

The outsourcing model Antecedents Chen, S. (2009); Mayer & Salomon (2006); Arnold (2000); Lacity & Willcocks (1995); Aubert, B.A. & Weber R. (2001); McCarthy, I.P. & Anagnostou, A. (2004); Lyons, B. (1995); Chen, S. (2010); Hayes, D. C., Hunton, J. E., & Reck, J. L. (2000); Walker, G. & Weber, D. (1984); Walker, G. & Weber, D. (1987) Mayer & Salomon (2006); Arnold (2000); Parmigiani & Mitchell (2009); Heikkila J., & Cordon C. (2002); Espino-Rodríguez T.F. & Padrón-Robaina V. (2006); Quinn J.B., & Hilmer F.G. (1994); Aubert B.A., Rivard S., & Patry, M.(2004); De Fontenay & Gans (2008); Oh, Gallivan, & Kim (2006); Gilley, K.M. & Rasheed, A. (2000); Barney, J.B. (1999)

Process

Outcomes

Chen, S. (2010)

Chen, S. (2010); Hayes, D. C., Hunton, J. E., & Reck, J. L. (2000)

De Fontenay & Gans (2008); Insinga, R.C. & Werle, M.J. (2000)

Bettis, Bradley, & Hamel (1992); Oh, Gallivan, & Kim (2006); Insinga, R.C. & Werle, M.J. (2000); Gilley, K.M. & Rasheed, A. (2000)

Dynamic capabilities

Rothaermel, Hitt, & Jobe (2006)

Rothaermel, Hitt, & Jobe (2006)

Knowledgebased View

Tiwana, A. & Keil, M. (2007); Tiwana, A. (2008)

Reitzig & Wagner (2010); Tiwana, A. (2008)

Information technology

Loh & Venkatram (1992); Lacity, M. & Hirschheim, R. (1993); Earl, M. J. (1996); Lee, J. & Kim, Y. (1999); Kotabe, M., Parente, R., & Murray, J. Y. (2007)

International business/MNC

Lommerud, Meland, & Straume (2009); Mol, M.J., Van Tulder, R.J.M. & Beije, P.R. (2005);Coucke, K., & Sleuwaegen, L. (2008)

Industrial organization

Ford & Farmer (1986); Cheon, M., Grover, V. & Teng, J. (1995); Oh, Gallivan, & Kim (2006)

Contingency theory

Murray, J.Y., Kotabe, M. & Wildt, A.R. (1995)

Kotabe, M., Parente, R., & Murray, J. Y. (2007) Jean, R., Sinkovics, R. R., & Cavusgil, S. (2010); Bertrand, O. (2011) Kakabadse A., & Kakabadse N. (2000)

Brooks (2006); Lee, J. & Kim, Y. (1999)

Kotabe, M. (1990); Bertrand, O. (2011)

Oh, Gallivan, & Kim (2006) Murray, J.Y., Kotabe, M. & Wildt, A.R. (1995)

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Strategic Management and “Complex Products”: some notes about an interpretative model for business policies Lucia Aiello, Ph.D Universitas Mercatorum, Rome, Italy, e-mail: [email protected], Corresponding author Gaetano Fausto Esposito, Lecturer, Universitas Mercatorum – Secretary General, Italian Chambers of Commerce Abroad, Rome, Italy, e-mail: [email protected] Maria Antonella Ferri, Associate Professor of Business Strategy, Universitas Mercatorum, Rome, Italy, e-mail: [email protected] Received September 4, 2012 / revised October 25 / accepted November 5 / published online November 9, 2012. DOI: 10.7350/BSR.A14.2012 – URL: http://dx.medra.org/10.7350/BSR.A14.2012

ABSTRACT 178

This paper compares some studies in the field of economics and management in order to identify an innovative model of strategic management in reference to complex products. The work starting from (after having taken a critical look at) a critical analysis of structuralist studies, highlights the need to move from industry analysis to business analysis to define strategies, later on it offers a new definition of Product - increasingly made up of good /goods + service/services and subsequently seen as commodities - as well as a new definition of Consumer - as a person searching for characteristics in products and then seen as “usumer”. Such definitions underlie a model that allows the analysis of both market structure and market “soul”. The structuralism’s limitations – thanks to a brief analysis of literature – are considered outweighed by business models, among which one in particular is Abell’s model defining the (SBA) Strategic Business Areas. This study, after considering complex products and usumer, aims to complete Abell’s model and to provide a revision of it, in order to suggest new guidelines and interpretations mainly aimed to complex products such as the “Made in Italy”. Keywords: Complex Products, Usumer, Made In, Business Models, Business Unit, Interpretative model for business policies.

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1. INTRODUCTION: THE LIMITS OF STRUCTURALISM IN STRATEGIC ANALYSIS

179

Studies on strategic behavior of companies are generally “structural” - based since they examine the characteristics of the structure of a particular industry in order to enable the development of a specific strategy. This strategy is considered to be functional to the definition of performance (business results), neglecting other aspects related to both influence of environmental, social (Oliver, 1997) and institutional (Bresser & Milloning, 2003) factors, and strong connections and interactions with customer demand. This approach originated in a period of great market, consumption tastes and preferences’ stability, but it seems less appropriate in circumstances of rising market turbulence and of growing interconnection between business and institutional factors, in a time of growing spread of information and communication networks (Teece, 2010; Hunt & Arnett, 2004; Hunt & Morgan, 1995) as well as in the case the product is defined by "unconventional" inputs such as the image and culture of an area, or the very active action of consumers. Yet interdependence in consumption has been being analyzed for a long time as part of the economic analysis and dates back to the studies of Duesenberry (1949) and Leibenstein (1950). This is likely due to the fact that the standard search approach comes from industrial economy and Industrial organization studies, where the strategic interaction is traditionally studied (Tirole, 1991) with reference to oligopolistic markets, through the use of more or less sophisticated versions of the game theory (both one shot and repeat form, with complete information or asymmetric, etc.) (Rumelt, Schendel & Teece, 1991). In all these cases, the function of enterprises’ reaction considers essentially no more than the supply side and the target variable of reference is represented by price, through a continuum (sometimes exaggerated) of reactions to the behaviour of competitors (Rumelt, Schendel & Teece, 1991). New studies, paying particular attention to the theory of organizations, of contracts and therefore of transaction costs (Milgrom & Roberts, 1992; Williamson, 1990), have increased the amount of variables to be considered, introducing more realistic assumptions on the interaction among different actors, but still remaining at a very strong level of stylization. A first step towards supply analysis taking a look at demand within the process of strategic analysis was accomplished through strategic management research, which has better focused the concept of strategy, placing it in relation to the concept of competitive advantage, even if sometimes it is not clear what exactly is meant by this term (Klein, 2001), trying to break away from the overly abstract view in economics study, while aiming to enhance some aspects in terms of method (Rumelt, Schendel & Teece, 1991) . A strategy aims to: “drive management decisions in order to achieve excellent results through the search of a competitive advantage [...] it is a vehicle for both communication and coordination within the organization.” (Grant, 1999, p. 13). This definition connects competitive advantage to its impact within the company, but still an essentially little dynamic view which is tied to a very well defined reference frame seems to remain. In fact, the most well-known patterns of competitive analysis, basically derived from studies on industrial organization by Bain, Scherer and Caves-Porter, use as reference paradigm the one known as Structure-Behaviour-Performance, therefore business behavior/strategy is determined by market structure (simply measured in terms of elasticity of demand and economies of scale), and this defines company's results. It is essentially a model of neoclassical origin (Silva, 1995), which not accidentally is eligible for an allocative and mechanistic approach, strongly characterized by cause and effect sequences. Within this branch of research

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180

perhaps the most widespread model, straddling economics studies and management studies, is the one of Michael Porter (founder of the market based view), known as the "five forces" (Porter, 1979), since it identifies five leading, relevant and perspective forces, identifies the rivalry between competitors, considers aspects on customer and supplier (bargaining power of buyers, bargaining power of suppliers, existence of substitute products, the threat of new products, besides that for potential competitors). The focus is represented by the industry sector (and its barriers), with the aim of carrying out a perimeter of "relevant" market, rather than identifying its specific characteristics in terms of demand, its attributes and methods through which enhance it and then capture its value (Teece, 2010; Rumelt, Schendel & Teece, 1991). In the same way, the "life cycle of the industry" model, with the passage of a market through different stages, responds to this structural logic, introducing in addition a kind of automatism in the transition from one stage to another, that is appropriate for a Fordism paradigm, but inconsistent in a post-fordism frame1. The structural limit is, in many ways, maintained in the proposals focusing on elements that are closest to the analysis of entrepreneurial behavior, for identifying (and/or make result) different strategies. That is what happens when you identify a product portfolio (particularly in multibusiness firms) as in the elaboration of the Boston Consulting Group’s matrix, which defines product strategies through the use of two fundamental variables: market shares and development rate; or also of the General Electric-McKinsey matrix that, though in a more articulated way, distinguishes different business (in a Strategic Business Unit logic) based on the power of competition and on the attractiveness of the industry, although both read on the basis of complex variables. Even if these models’ efforts, as well as more advanced ones’, were intended to make sure customer role was given a greater consideration, ultimately the result seems to keep focus on product, or at the most on company behavior, maybe even considering its internal reflections (as it happens in Milgrom, Roberts & Grant, 1999) and their implications on corporate organizational variables. Similarly, studies in the field of strategic management based on the resource-based perspective (Barney, 1991; Collis & Montgomery, 1995; Grant, 1991) which have the advantage to emphasize the role of company’s distinctive capabilities and the various forms and combinations of tangible and intangible capital, but they conceive the strategic approach substantially as a way to align resources and business skills with market opportunities (Grant, 1999, p. 139), playing on an approach that is mainly internal to the company2 and not very customer-driven, within a logic also contributing to the creation of the product3. In addition, as noted by Williamson (1999), the reference to the concept of competence is likely to introduce 1 Insofar knowledge circulation and transmission is relevant, rather than its incorporation into defined goods, and as a process of "propagation” of the same starts - as argued by Rullani (2010), it is not possible to identify precise sequences from a "strategic" point of view, as some "steps" may be missing and others may even be skipped. 2 From this point of view it may appear almost a paradox the statement of Grant (1999, p. 141) according to which reference to internal resources is a response to the volatility of consumers’ preferences and identities and to technology changeability. 3 There have been some attempts aimed to improve the resource-based model. Probably among the most interesting ones, there is the approach of Hunt and Arnett (2004) which represents an attempt to integrate the resources within an approach of competitive advantage and, for this reason, it takes into proper account the elements of imperfection, heterogeneity and discontinuity in demand and in the set of available information that we put in the introduction (Hunt and Morgan 1997), or those directed to identify a competitive advantage in the activity of relationship with other companies and to identify a sort of relational income resulting from business alliances and from interorganizational activities (Dyer, Singh 1998), or even trying to integrate this approach with aspects concerning the circulation of learning and actions and the management function (Mahoney 1995).

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an ex post explanation of business success (if not also to have a tautological nature: the company has been successful because it had good skills), unless it refers to a very broad meaning including, from an analytical point of view, assets, skills and business routines - basically integrating different aspects highlighted by Edith Penrose (1959), up to the contributions of Nelson and Winter (1982) on the role of business routines, going through the approach of contracts4. In our view, the increase of market complexity and of consumer preferences, as well as the rise of strong interaction between preferences and, generally, the need to take account of the social environment and of its influence on business and consumption variables (Manski, 2000), require the use of strategic management approaches taking into account some aspects, also highlighted in literature of both economic and business derivation: − difficulty in assessing the quality and variety of goods due to the existence of asymmetric information that affects consumer (Stiglitz, 1990), as well as the tendency of many goods/services to be the result of a process of co-production with the company; − the role institutional factors, membership in social groups holding certain rules of behaviour (Akerlof & Kranton 2012)5, can play in interacting with strategic management, because of the impact they may have on the success and survival of an organization (Bresser & Milloning 2003).

2. METHODOLOGY AND OBJECTIVES

181

The methodology consists of an analysis of literature on the following main topics: industry analysis, strategic management, business analysis, in order to identify new methodological opportunities representing the business areas in reference to the match between supply and demand. Let's start with redefining the concepts of product and consumer, as well as with a brief analysis of literature on marketing to find the passage from what Kotler defines marketing 1.0 to 3.0. A comparison of economics and management main theories and reflections about issues related to strategic analysis and management show that supply cannot ignore the "real” knowledge of the market of reference moreover consumer demand has mainly become a demand for complex products. The aim of this study is – according to the opportunities and limitations encountered in the literature on the topics discussed – to propose a model of business analysis which can effectively match the new management needs. For that reason, the following work: 1. 2. 3. 4.

defines the concept of complex product; states the overcoming of structuralism; sets the business model as the overcoming of the standard model; defines the concept of consumer, resuming the definition of usumer;

4

For an overview of the different strategic approaches and their theoretical matrices we refer in any case to Teece, Pisano and Shuen (1997). 5 In particular, it is possible to identify the endogenous interactions occurring when the behaviour of a person depends on the behaviour of the group in which he identifies, the contextual interactions when variability of behaviour depends on factors outside the group and lastly the related effects, when people in the same group tend to have a similar behaviour because they have similar personal characteristics or face the same institutional environment. The first two cases show a strong influence from the social environment, while the third case expresses events of extra-social type (Manski 2000, p.24).

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5. proposes a new interpretive model for analyzing corporate policies for complex products such as the "Made in Italy” ones.

3. A PRODUCT DEFINITION (GOOD+SERVICE): COMPLEX PRODUCTS

182

The first limit mentioned at the end of the previous paragraph is particularly relevant. In fact, the most part of the contributions to strategic management have been developed for companies that produce products (goods or services) uniquely and clearly defined in their characteristics. They were the result of a Fordist approach, which found its most typical expression in the mass goods market and in a low differentiation of consumer tastes and trends. Far-back economic literature, starting from the contribution of Nelson (1970) has showed the strong diffusion of goods whose characteristics can be recognized and/or tested only after their consumption (experience good) and, in several cases, especially in the field of service, neither in this situation (credence good, let’s think, for example, to medical services, or to car repairs)6, as opposed to search for goods, whose characteristics are clearly defined at the time of purchase (Sloth & Philipsen, 1998). This introduces many difficulties in the standard models used to examine the consumers’ behaviour and in particular highlights even more the lack of realism of the assumptions underlying perfectly competitive markets, since it includes consumers’ need to evaluate the search costs when buying certain goods (and the importance of advertising variously held Nelson, 1974; Milgrom & Roberts, 1986). In presence of asymmetric information, as demonstrated by Stiglitz (1987), the price of the product does not assume an informative content for consumer choice any more, but it becomes itself an indicator of quality of the product, through incentive effects on consumer. The products available today are mainly considered "complex products" because they are constituted by elements of a different nature, which are connected to different types of production (of cultural and territorial contiguity). Typical is the case of the so-called "Made in Italy" productions that have a high social content, because they reflect the relationships in the area where they were produced, knowledge, human resources and symbols (Rullani, 2004b) which are present and settled over time, even with the constant activity of local networks of relationships (Becattini, 2009; Lipparini, 2002). This applies today to a growing complex of production, and in particular for those appearing closely related to the specificities of a region, a culture, a community, and resulting from interactions among these specificities and consumers, tourist products, cultural heritage, technological products are some examples, but also other consumer goods and durables. At present we see more and more products consisting of goods and services. Formerly “distinction between products and services was relevant, however in recent years this distinction has lost its meaning that is because every good and service is composed of several elements and each product (for the most part of cases) consists of both goods and services. The prevalence of the goods or services criterion is not enough to characterize a product [...]. The term product can be used to refer to goods or services at the same time [...]. Subsequently consumer becomes Usumer (user + consumer).” (Ferri & Aiello, 2009). The term usumer proposed in 2009 6

The category of the credence goods was introduced after contribution from Nelson, Darby, Karni (1973), in all cases recovering the original contribution of Stigler (1961) concerning information economy. In particular, we are nowadays observing an increase of those goods in relation to which the consumer may develop a sense of disappointment in regarding the relation between utility and / or expected benefit, and utility and / or real benefit, in the case of durable goods or services can then decay or even give rise to forms of discomfort, as argued by Hirschman (1982).

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indicates the "new concept" of consumer who is both user/consumer of services and consumer of goods. The meaning also includes the concept of prosumer (producer + consumer) as the idea that consumer is also involved at the time of production is now acclaimed, and this is even more evident in reference to service. Table 1. The product: system of goods and services Need to satisfy Meal for the first breakfast Night' passing Transport Wellness

183

Cases Kellogg's

Product Good: cereals Service: alimentary advising (web-site) Good: bed Service: concierge's room

Best Western Fiat

Good: car Services: ABS, Satellite Navigator

Jacuzzi Source: Ferri & Aiello, 2009, pp. 10.

Good: bath Service: jacuzzi

Product thus consists of a set – which is to be defined by consumer - goods and services in relation to the needs to be met, as showed in the chart. “The cases showed in the chart represent only some examples of complex product and concern all areas, whatever kind of needs to satisfy. When we say product we want to refer to good and service at the same time. This is explained by the fact that marketing steps – analysis, strategy and policy – have the same rules, this is a result of the environmental evolution.” (Ferri & Aiello, 2009, pp.11). Telling in advance what we will say later on, product is complex when resulting from an “extended" production process, which includes not only traditional factors (such as use of capital and employment of specialized labor), but requires a larger process of production which is also achieved through consumer behaviour, as well as through interaction with social environment. In a complex product, then, one can find all characteristics we mentioned earlier in this work: search, experience and credence. To make things simpler, we can say that complex productions are particularly characterized by: 1. a component of "functional" nature which tends to satisfy needs we can define "elementary", as solution of a specific need (eating, dressing, producing a specific object, etc.); 2. a cross-sectoral component, represented by a combination of aspects related to both manufacture and service; 3. a component of emotional nature, linked to composite factors of cultural nature, and often to ability to evoke images and specific places, mainly resulting from "social production". Together, these elements combine to define product: their interaction produces a continuous process of innovation, but the second contribution has been gradually increasing over time and highlights the need to set production into a comprehensive system of local and global relationships being based on very active role played in the process of consumption. Often these products result from a system of interactions with other firms, between businesses and consumers. In that case, another aspect is relationship, not only (or not so much) intended in the sense of relational good (which also implies a strong emphasis on spontaneity and mutuality

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of performance (Donati & Solci, 2011), but as a kind of asset, of resource concerning the quality and the amount of relationships between supply and demand. The construction of strategic models subsequently needs to consider the implications of this situation, coming through the idea describing products, even differentiable ones, as a definite or easily definable set, not considering product’s interaction with the processes of consumption.

4. TOWARDS A CRITICAL OF THE STRUCTURAL MODEL

184

Amit and Zott (2001, pp. 493) define the business model as “the content, structure, and governance of transactions designed so as to create value through the exploitation of business opportunities.” Afuah and Tucci (2003) consider a business model as a system that is made up of components, linkages between the components, and dynamics You can easily perceive that literature on the subject has been growing since the late nineties/early two thousand. Zott and Amit (2009, pp. 216-238) affirm “the business model defines the structure of the value chain […] Some scholars have explicitly pointed to boundaryspanning nature of business models by emphasizing the need to consider activities performed for the focal firm but outside its boundaries by partners, suppliers or customers. This allows the focal firm to rely on the resources and capabilities of third parties, and harness external ideas and technologies through “open business models”. Indeed, in some instances entire key activities such as product development are shifted outside the firm, but they remain a central part of the firm’s business model.” These definitions of business model are consistent with considerations made so far, showing how business models respond better to evolution of economy, of market, of consumers and of supply itself. 4.1. The business model as a review of the standard models The variability in the concept of 'standard' product, the emergence of the network economy and the spread of internet, introduce the need to integrate the standard concept of strategy with the one of business model. There are several ways of understanding this concept (Zott, Amit & Mass, 2010), which according to some (Teece, 2010) have no defined theoretical matrix either in economics or in management. For that reason it is likely to move towards a more complex and complete approach. However, a unifying element might be found in the firm’s ability to build and make better use of its resources to offer its customers more value and consequently improve their profitability. In some respects, a more dynamic and even more relational concept becomes apparent against a complex market, which is not merely driven by actual and/or potential competitors. And this goes hand in hand with complexity concerning products and their manufacturing process. The concept of a business model emphasizes the overall aspects of value creation, the partnerships and joint creation of value for all potential stakeholders of the company as an organization. Focusing on the business model helps to give greater consideration to the company’s relations with all entities of reference, including those that belong to society including institutional context (second limitation of conventional strategic management), and particularly emphasizes customer relationships and the chance to take value from the demand for goods and services, which may present itself as the result of a complex process of interaction of relational type, while the traditional concept of strategy focuses mainly on the role of competition and acquisition of a competitive advantage then translated in terms of profit.

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The analysis of supply is therefore enhanced by other values, for example, on how the company can better meet the needs of customers, taking value from this activity (Teece, 2007). Moreover, in reference to the business model the assumptions of reference considering the possibility of limited and / or distorted knowledge, take proper account of the problems of asymmetric information mentioned earlier in the text. Referring to the contribution of review of Zott, Amit and Massa (2010, p. 18) we can probably say that the literature on business model is especially useful to highlight the limits of the traditional strategic approach, and then to highlight the features more advanced models should consider, entering the following criticisms: 1. there is no linear (predetermined) mechanism of value creation that goes from the company to its customers, but the interaction is much more complex and requires the relationship among many actors; 2. the strategic position of an enterprise cannot be defined only in terms of product differentiation or cost leadership in reference to certain activities, as well some doubts remain about the precise business areas delimitation; 3. the emphasis on the strategy’s impact in terms of internal organization should be overcome (from Chandler’s definition and that in many ways is also suggested by Grant).

185

Perhaps the most important point of criticism concerns the fact that customers’ needs are as important as company’s needs when conducting a strategic analysis – a perspective which is rare in the literature on the subject – according to a more relational approach in reference to both the firm and the environment/institutions. The evolution of literature in the field of marketing clearly highlights this issue, in fact the transition from Marketing 1.0 to the 2.0 and then to the 3.0 has determined the passage from "product-centric marketing" to "consumer-oriented marketing" to "value-driven marketing ", where the concept of " value " leads and directs marketing policies and should direct and lead strategic models themselves, as represented by Kotler in the table below. Into the perspective of Marketing 3.0 it is positioning the e-business, that is, in according to Dominici (2010, pp. 5), “the mere application of the business model in a digital business environment.” Specifically, the value of the investigation on product’s content and various aspects seems to transform the concept of the good required itself, which in many cases becomes the result of a process of transformation where the consumer/user is actively involved. Recent contributions on marketing approaches’ evolution (Kotler, 2011) show, as already remarked, the complexity inherent the concept of product (Ferri & Aiello, 2009). It is a perspective recently pointed out by contributions belonging to the branch of research of the so-called Resource-Advantage Theory (Hant & Arnett, 2003, 2004). The above-mentioned approach Resource-Advantage Theory highlights that a successful business strategy must consider the nature of competition in reference to the market segments the company is competing for. There are two main factors that determine the market positioning (Hunt & Arnett, 2004, p. 19): the perception of consumers about the market value in comparison with the one of competitors and the comparative costs (to other competitors) of resources required by companies for production.

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Table 2. Comparison of Marketing 1.0, 2.0, and 3.0 Marketing 1.0

Marketing 2.0

Marketing 3.0

Product-centric

Consumer –oriented

Values-driven

Marketing

Marketing

Marketing

Objective.

Sell products.

Satisfy and consumers.

Enabling forces.

Industrial Revolution.

Information technology.

New wave technology.

Mass buyers with physical needs.

Smarter consumer mind and heart.

Whole human with mind, heart, and spirit.

Key marketing concept.

Product development.

Differentiation.

Company guidelines.

Product specification.

Corporate and positioning.

Functional.

Functional and emotional.

Functional, emotional, and spiritual.

One-to-many transaction.

One-to one relationship.

Many-to-many collaboration.

How companies market.

see

marketing

Value propositions. Interaction consumers.

with

retain

the

with

Make the world a better place.

Values. product

Corporate mission, vision, and values.

Source: elaboration on Kotler, 2010, pp. 6

186

However it seems that this dual consideration does not take into account the complexity characterizing competitiveness into the different market segments, particularly with regard to the characteristics of demand and to the role that consumers/families can play for goods/services’ production. Hence the opportunity to make use of a strategic analysis, highlighting the main aspects, and thus useful for interpreting and classifying reality through interpretative models which are intended to overcome a purely descriptive approach, without ignoring variables considered to be significant. Moving then to the field of strategic management modelling it seems to us that the contribution of Abell is the one taking more into account aspects related to the demand flexibility and to the value. As we know this author, when considering the elements of a Business Unit, focuses on the customer component in order to identify customer target, its actual needs and methods of satisfaction. The business unit is a logical element or segment of a company (such as accounting, production, marketing) representing a specific business function, and a definite place on the organizational chart, under the domain of a manager; also called department, division, or a functional area (www.businessdictionary.com). “The relationship between competitive scope and the value chain provides the basis for defining relevant business unit boundaries. Strategically distinct business unit are isolated by weighing the benefits of integration and de-integration and by comparing the strength of interrelationships in serving related segments, geographic areas, or industries to differences in the value chains best suited for serving them separately. If differences in geographic areas or product and buyer segments require very distinct value chains, then segments define business units. Conversely, strong and widespread benefits of integration or geographic or industry interrelationships widen the relevant boundaries of a business unit to encompass upstream or downstream activities, while weak advantages to integration imply that

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each stage is a distinct business unit. Similarly, strong advantages to worldwide coordination of the value chains imply that the relevant business unit is global, while strong country or regional differences largely distinct chains imply narrower geographic business unit boundaries. Finally, strong interrelationships between one business unit and another may imply that they should merge into one. Appropriate business units can be defined, then, by understanding the optimal value chain for competing in different arenas and how the chains are related.” (Porter, 1985, p. 58). Grunig & Gaggl (2003, pp. 32) state: “for the definition of the existing strategic businesses the steps: 1. identifying and classifying of existing market offers; 2. determining the strategic business units; 3. grouping business units into business fields according to market and/or re source interdependencies. Possible upgrading of business units to business fields.” The definitions of business unit as well as the detection methods do not fully satisfy the reflections concerning the development of analysis models conducted so far, it is essential to overcome the close connection to the concept of segmentation, being too restrictive and anchored to the product (for example, the segmentation of the market carried out to define the characteristics of the product, colour of the car or performance) in favour of the new concept of market and marketing 3.0 putting on the same level supply analysis - and internal resources - and demand analysis - and external relations. Although this approach is much more demand based than earlier ones and less anchored to a structuralism view, it should all be integrated with an enhanced analysis of consumer behaviour, with particular reference to those types of demand which appear very complex, as their formulation is characterized by the presence of variables related to values and perception, features characterizing in particular "Made in" products. 187

5. IMPROVING DEMAND ANALYSIS In this chapter, we will try to use a heterodox approach to analyse strategic behaviour, aiming to integrate an economic direction with aspects of strategic management. From this perspective, it is necessary to improve demand analysis as well as the analysis of complex goods production . In particular, referring to some goods more closely related to the concept of Made in Italy (Esposito, 2005) we need to consider the micro-economic approach, connecting consumers/families demand and supply, within a broader process of enlarged production characterized by a more complex system of interaction between goods, values, territories, ability to relate to others. The traditional economic approach simplifies the problem of choice too since it tends towards balance, and putting itself into a logic of allocative type, considers as data just some essential parameters on consumption choices: the reference to traditional notions of demand elasticity to price and income does not explain the complexity of consumption relationships because it ignores the many components playing into consumers’ function of preference, connecting them to the best representation of business groups. At this stage, the study aims to consider two contributions representing, although independently developed, a significant input to the development of an alternative view of consumer demand compared to the standard one: they are the theory formulated by Gary Becker and the one by Kelvin Lancaster. Both of these theories consider consumption as a "productive" process, but Becker focuses on the role played by family, as well as on the importance of time factor and on aspects of social interaction, whereas Lancaster’s theory facilitates a better articulation of business groups,

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focusing on the concept of product as a set of features. For our purposes, these theories offer complementary aspects being useful for enhancing a strategic management approach 5.1. Goods or commodities?

188

Becker’s theory recovers some structural elements in order to define preferences, it places traditional analysis into a wider system of influences and constraints on consumer choices (Becker, 1974) and highlights the aspect related to the inter-temporal regularity of choices. This analysis lays into a neoclassical approach of maximization, but regardless of its methodological implications7, for our purposes it is crucial to identify the complex process that involves the development of a system of preferences, joining production elements and consumption elements (Becker, 1965) and where the latter depends on flow variables (such as income), but also, and especially, on stock variables, which are collected and produced both inside the family and through interactions with the social system. Besides such a theory shows that the income to which to refer to for consumption analysis is not only monetary income, but it must include additional variables, including the allocation of time (a measure of monetary income which was failed or lost), as well as other elements related to values and/or status identifying what the author describes as social income8. The focus of the process of consumption is not represented (and cannot be represented) by single goods, with well-defined specifications and features as assumed by studies on strategic management and in particular by those focusing on market view, but by the so-called commodities, designed as complex economic goods produced by families (Becker, 2000) and to the production of which a certain contribution results from the goods purchased, as well as from the time of transformation (defined as a price similarly to the market price of goods (Becker, 1965; Mattila-Wiro, 1999), and especially by the human resources which are available in a family: these are constituted by the sum of personal capital, which includes consumption and other past experiences, and of social capital, which refers to the influence on consumption choices of those with whom an individual comes into contact9 and coming from the network of relationships in which the individual, or the family are integrated10 (Becker 1974). Personal 7

For this theory, which could deny the creative and procedural characteristic of consumption we refer to Sassatelli (2004). We underline, however, that the approach used here draws on the analytic concept of Becker, but it clearly did not accept its neoclassical basis, according to which consumption practices are modelled as instrumental personal choices. The aspects of the emotional type in fact are not generally considered in neoclassical models, according to which individuals choose on the basis of expected utility (Compte, Postlewaite 2004). 8 Defined as sum of personal income and the monetary value of social interactions. 9 Social capital can be defined as the set of social relations an individual or a collective entity has at any given time. It is therefore a strictly relational concept as social capital makes available cognitive resources, such as information, or regulations, such as trust, which allow achieving objectives that are otherwise impossible or difficult to achieve (Esposito 2010). 10 Becker's theory defines a function of commodity production including the characteristics of other persons who may influence the characteristics of the commodity. However, this approach opens the way to highlight the role that social networks may play in the production of social capital, and not the general willingness to cooperate or the existence of the trust (Coleman 1990). The social capital according to some (Donati, Solci 2011) emerges as a kind of relation of production that does not belong to individuals, but result from relationship. .Moreover, the concept of social capital (and its influence) is certainly related to a kind of post-Fordist economy, as the Fordist did not consider the role of networks of relationships, but the regulatory mechanisms (at a micro-level) are the organizational capacity of the company and (at a macro level) of regulation of demand and market stabilization. This concept also has an increasing importance in the analysis of strategic corporate decisions, so that it also refers to organizational capital. For a review see. Lipparini (2002). In all cases, the central element is that the concept of social capital involves the reference to social networks (Lipparini 2002).

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capital and social capital are therefore the overall stock of human resources affecting consumption choices. In synthesis, the value of a commodity is defined as:

Z i = fi ( X 1i , X ki ..., t1i , tli , S1 ,...S j , , Yi ), i = 1...m Where Zi indicates the commodities entering the utility function, fi is the function of production of the i-th commodity, Xji indicates the amount of good and / or service used for the production of the i-th commodity, tji represents the contribution in terms of time of the jth individual, Sj stands for human resources (sum of personal and social capital which includes the effects of social interaction), and Yi represents all other factors (Stigler & Becker, 1977). Commodity is configured as a complex object of production/consumption, in which many factors come into play. It is a key element allowing us to retrieve the active role played by subjective elements, such as the influence coming from personal conditioning, the education system and values, as well as the time11 dedicated to the transformation of single goods (Becker, 1965). So consumer's utility refers to commodity, and not to single material goods, therefore the price/cost relevant to the consumer is not about single purchase (and in many ways the intermediate good of production), but the commodity’s cost of production, which matches its "shadow price" and at the margin it is equivalent to the marginal cost needed to produce one more unit of commodity (Stigler and Becker 1977). Accordingly, it is equal to: w − Aj CPtmj 189

where w is the wage rate, C is the amount of consumption capital of the commodity (which in turn depends on the time for the production and on human resources (personal and social), which enter the production function, P is the price and A quantifies the so-called "effect of dependence", that is saving future time input on capital deriving from the production of C at time j on capital of later consumption. In this way it becomes possible to identify a form of relationship for which the stock of consumption capital collected for a specific commodity also influences future consumption. Beyond its further implications this approach gives emphasis to different aspects of great interest in reference to goods having complex feature: by linking the demand characteristics to experience, it indicates that purchasing process is influenced by a set of elements and particularly that favourable dependence12 of current consumption on future consumption can be established, for that reason an increase in current consumption of an asset also entails an increase in its future demand, at the same time, since it contributes to increase the consumption capital, it reduces the commodity’s shadow price and therefore (in some respects) makes it more convenient. In addition, this approach emphasizes the need to take into account the characteristics of other 11

Becker (1993, p.386) , his first theory was developed in 1965, recently pointed out that nowadays time is the main constraint, because while commodities continue to rise, the availability of time, despite the progress of medicine and the lengthening of life expectancy, is a resource difficult to expand beyond certain limits, so as goods become more abundant, time acquires greater value in relative terms 12 Stigler and Becker (1977) show that there may also be harmful dependency, in which the relationship between human capital and commodities appears to be negative, in contrast to what generally happens in the case of convenient dependency, in which this relationship is positive.

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people influencing the production of commodities, in particular it is necessary to pay attention to both (Becker, 1974, pp. 1067 et seq.) the characteristics of the social environment and the individual’s effort/behaviour (therefore his income) spent to influence other people. That means the more important is the contribution of social environment on an individual’s social income, the more his overall well-being (and thus his consumption capital) is determined by the attitudes and behaviours of other people, rather than by its monetary income. Therefore, the more an individual’s (social) income is determined by the importance he confers to social environment the greater the percentage change of its contribution to the formation of the characteristics of other people will be. Social interaction implies a lower elasticity to income than individual consumption and then situation in which there is no interaction. Greater or smaller presence and sensitivity to what we have identified as social capital, modifies the consumption function (and in particular the sensitivity of goods to the component of social influence). In conclusion, Becker’s contribution makes it possible to add a useful specification to the three variables identified by Abell, and aims to better define the needs people want to be satisfied. It introduces the prospect of a co-production of the good, the time variable in the process of co-production and the role of social interaction with its related effects of substitution between goods consumed and the share of social consumption, so it also opens the way for a better specification of the satisfaction of customer needs/demand, because it involves a greater use of relational channels, which affect the personal and social capital, as well as less use of time by the consumer and therefore in the commodities’ production. 5.2. From product to product features 190

In order to describe the variable concerning the group of companies, we can refer to the theory formulated by Lancaster (1966), allowing us to focus even better on the consumption function in close connection with the production function. The author has introduced the concept of quality difference between products, defining their heterogeneity. The consumer does not maximize any more the amount of product purchased, but he will try to maximize the diversity of the products themselves. In this way, the demand for products is derived from the demand for the different features required by consumers (Lancaster, 1990) and consumption is configured as a real activity where products are the inputs having as output a set of characteristics (Lancaster, 1966, p. 133). Even in this case, as for Becker, the process of production involves the consumer who puts together the different characteristics of products13. In order to achieve this result he will use the "technology and consumption matrix", in all cases in which he handles composite products. According to Lancaster: (Lancaster, 1966, p. 4). In the chart the x-axis lists the possible characteristics of a product (1...m) and the y-axis indicates the different consumption activities realizing the consumption demand (1...n). Three situations are possible where the number of available goods is equal to, less than or greater than 13

In general, according to Lancaster, a single product can present a set of features and many features can be shared among multiple products.

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the number of characteristics. Lancaster considers the third as the more complex situation, but it is actually interesting to consider the second situation, which may be typical of goods referring to "Made in". Lancaster argues that the consumer looks for a set of utilities in a good, that is to say an optimal mix of different features maximizing utility compared to his disposable income. Lancaster (1966) particularly identifies the following assumptions: 1. features are observable and objectively measurable 2. the characteristics have the property of linearity, so that a double amount of the asset corresponds to twice the amount of the characteristic considered; 3. the characteristics are additive. Figure 1. Technology and consumption matrix

Goods

Features 191

Source: Van Der Borg, 2009, pp. 18

Starting from the consumption function, it focuses on the qualitative characteristics of the goods, which can be represented by a set of features offered by different company groups, so the utility function dimension is linked to the consumer behaviour, to the company groups’ dimension, by entering a mode of segmentation (differentiation in the language of economics: Lancaster 1990) based on what he describes as intrinsic commodity group (Lancaster, 1966, pp. 144), which identifies a group characterized by a close relationship among the characteristics resulting from 'consumption activities, which are not connected with any other feature, it is consequently possible to separate this set of characteristics and activities from others inserted into the technology matrix. Products belonging to this group will not be affected by changes in the price of other groups, so it is possible to build on them targeted segmentation strategies14.

6. AN INTERPRETATIVE MODEL FOR BUSINESS POLICIES As mentioned earlier Abell’s approach is, among the most popular patterns of strategic analysis, the one paying more attention to demand factors, as it focuses on the following three decision variables: 1. Who are customers we want to satisfy (customer groups). 14

Even this approach has been object of a critical review: in particular, while emphasizing its validity, it has been highlighted its "static" characteristic in the sense that it does not pay attention to what happens after consumption (James 1983). However, it has been much more radically criticized by others (as Bowbrick), in relation to some of its constitutive aspects.

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2. What needs we want to satisfy (customer needs). 3. How customers’ needs can be satisfied (core competencies). These three decisions are crucial to define business strategies since they represent the source of competitive advantage over competitors as well as a tool directing the company’s efforts towards competitiveness in business or in industry sector. This model still places itself into a delimitation logic, it tries to define and represent the SBU15 or Business Unit to identify competitive pressures through an approach marking the transition from sector analysis (of static type) to dynamic business analysis by considering some of the elements that underlie the construction of the business model. Business is consequently defined by the simultaneous presence of the three above mentioned elements, translated in the following demarcation lines of the competitive area: 1. customer groups (segments of demand); 2. the utility function the product performs; 3. the technology used for production. Moreover it allows us to get a precise view of management profitability, identifying the revenue responsibilities for different product/market combinations (SBU) through the following threedimensional pattern16. Figure 2. Abell’s SBU Model FUNCTION USE

192

GROUPS OF CUSTOMERS

TECHNOLOGY

Source: elaboration on Abell, model of ASA.

The strategic business units (SBU) are both "revenue" and "responsibility" synthesis units - SBU Strategic Business Unit – presenting an economic structure that is independent and managed in competitive areas clearly identified by means of a differentiated strategic management: to each SBU usually corresponds a competitive system. From a theoretical point of view, the definitions of market as well as the definition of SBU require a conceptualization through the definition of 15

The concept of ASA has, in literature and business practices, two different meanings. The first one, to define a distinctive area of the company’s environment / market .The second one as a unit or the activities serving a specific environment / market. 16 The concept of strategic business unit was used for the first time by General Electric in the late Sixties’ as a tool to give autonomy of decision and responsibility of results to the manager of a large group broadly diversified (at the time GE was divided in 200 centers and 145 departments unified in 10 groups). Hofer (1975) defines the business unit as the level of organization to which one is responsible for formulating strategies for a single functional area or the competitive arena of a product / market

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alternative criteria. Among the various criteria17 – from the supply perspective beforehand, from the demand perspective afterwards – Abell’s model has the advantage to lie at an intermediate level in reference to supply and demand perspective, it consequently incorporates the suggestions and empirical and theoretical methods of other criteria. The stages that specifically allow us to determine the strategic business areas are: 1. 2. 3. 4.

identification of criteria for the classification of the three dimensions; identification of the aggregation criteria; construction of the product / market matrix; collection of products / market combinations and induction of SBU.

6.1. The "productive" role of consumer through Becker and Lancaster’s contributions

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The model has been adapted, according to a logic of demand enhancement, in order to propose a management tool fitting both the complexity and the heterogeneity of demand for products / services as the "Made in Italy" ones, that, as mentioned in paragraph 2, result from a complex production process involving the consumer/family. The underlying motivation is to highlight, on a three-dimensional area, the product’s main components resulting from an internal and external analysis of the product-company/territory system. In light of the above reflections we propose an adaptation of Abell’s model, on the basis of new guidelines borrowed from Becker and Lancaster’s models. At this stage of the work, it would be appropriate to provide a definition of the SBU: it is an area defining the dimensions of company/sector-market relationship, providing a representation of the complexity of the business market/area-sector. Becker’s approach recovers some structuralist elements to define consumer preferences, adding to the traditional analysis of purchase behaviours a larger system of influences and constraints on consumption choices. For our purposes, the relevant thing is that pattern identifies a complex process involving the development of a system of preferences which combines elements of both production and consumption and where the latter depends on flow variables such as income and on stock variables collected and produced within the family through a set of interactions with the social system as well as on the transformation time variable. Consumption focuses on commodities entailing a reference to forms of experience and appearing as complex object of production/consumption, in which a number of factors – related to influence coming from individual behaviour, educational system, and values system – may come into play. The utility function is not defined on the basis of parameters under influence, but with reference to motivational/experiential factors depending on the economic and social system of reference. Through Lancaster’s model it is possible to derive a function of business groups, since it highlights the quality of each product/company’s characteristic, pushing consumer to choose those products appearing closer to the set of characteristics they are requiring. And the entity to be taken as a reference can be represented, from an operational point of view, by consumer willingness to pay (willingness to pay), which is the expression of demand for those attributes18.

17

For a deepening on the taxonomy of the criteria for market definition and SBU, among the various authors, see Valdani and Ancarani (2009). 18 The willingness to pay also provides a measure of the eventual consumer’s surplus. The Company's ability to take/extract this rent through policies of differentiation is entirely consistent with the studies of strategic management, since it identifies the objective of the strategy in the continuing search for a surplus (Mahoney 1995). The concept of surplus is intended, however, also in terms of resource usage, in fact the objective of the resourcebased theory is to achieve this surplus against other competitors (Oliver 1997). However, it remains the fact that

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In other words, this model retrieves a dimension of demand segmentation, resulting from the variety of products, which is a further means of taking into account the phenomenon of heterogeneity in consumption (Hunt & Arnett, 2004)19. It is now suitable to consider some specific aspects concerning the motivations driving consumers to purchase goods and by which we can identify different types of customers that should be considered for further segmentation. As a result SBU grows as a function of: 1. purchase motivations defining customer groups; 2. utility function/utility assumed by Becker’s function; 3. company groups; complexity of goods (characteristics), borrowed from Lancaster.

194

Together these different aspects concur to the construction of a three-dimensional model for positioning and complex products/services policies, which considers several important dimensions of the phenomenon. It tries to take into account both aspects of micro-economic type (resulting from consumer choices) and of competitive analysis, more directly related to strategic analysis (as the concept of SBU itself). The aim is to make the use of competitive tools more dynamic in order to overcome (at least in some measure) static limitations inherent in structuralist models, as well as to inspire policies of products promotion to be implemented not only into business logic, but also into an institutional one. Figure 2 shows all three dimensions described. By connecting these dimensions it is possible to draw the "pyramids of the competitive area." This model analytically shows three "areas". The first one is “the supply area " and originates from the connection between groups of companies and purchase motivations (customer groups). This area is particularly affected by Lancaster’s concept of consumption process, according to which a better analysis of "features" and of consumption process (actions), of its "technology", produces a more precise segmentation of relevant markets and subsequently highlights the possible set of choices made by company. This area comprises policies playing on the supply of products/services in terms of companies’ characteristics and ability to catch purchasing positive trends20. The second area is the demand area, connecting the different functions of use and the motivations of consumption. In this case, they are factors relating to policies aimed to affect motivational aspects as well as on consumers’ capacity/ability to produce commodities. The reference to the concept of commodity entails, when activating the strategic drivers, the need to take into account all "factors of production" involved, in particular, consumers’ personal capital and social capital and transformation time. For that reason a positioning strategy cannot ignore a new product affects consumer “social" income and may vary consumer’s preference between direct consumption and "social" consumption. In the case of a strong propensity for social interaction and its variables, a new product just considering the product’s function of use and its price may not achieve the expected results as consumers may award the social component of greater sustainability and increases of the company’s revenue (regardless of its method of measurement) are obtained by trying to "extract" as much as possible from the consumer’s income. 19 These authors also argue that the activation of the segmentation process will increase the overall well-being of an economic system, as opposed to a neoclassical perspective that is based on the homogeneity of tastes and preferences of consumers. 20 Lancaster’s concept of intrinsic commodity group is particularly important in this context. According to this author, the introduction of a differentiated product can be interpreted as the inclusion of a new product into an existing group. It is possible to verify the way new commodities are obtained. There may be cases where new commodities present characteristics across different groups.

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preference and consequently penalize the new product. Similar considerations relate to the time of consumption, not surprisingly the new products are characterized by a friendly usage, just to economize on a factor (the time) which is a resource that cannot be increased. Finally there is a third dimension that we have defined as policy dimension, referring to interventions that can be carried out by institutions in order to direct the overall goods market, acting both on the company component and on the crucial aspects of commodities production (that is to say the consumption component). Depending on the importance (we can even say the size) of the three areas it is possible to draw specific pyramids of competitiveness, which identify with their size and location into the threedimensional space the various combinations resulting in a clearly identifiable SBU. Figure 3. Directrices of the SBU for complex products

195

The A pyramid (continuous lines) represents those products constituted by a complex set of different goods and services, even belonging to different sectors, however, against a low number of consumer’s motivations as well as a function of simple use, an example is the event of the Olympic Games or the football championship, when reasons are simple and closely linked to the passion for the event, the function of use of the event itself is simple because the consumer just watch the games into the appropriate sites. Yet behind a single event there is a complex group of companies - public and private organizations, sports clubs and associations, sponsors, sports centres, hotels, transport companies, other. Conversely, in the case the viewer of the event has also tourist-cultural motivations the base of the pyramid could be considerably enlarged even though the product is the same. The B triangle (dotted lines) refers to a product consisting of a small number of groups of companies and of a set of motivations driving the consumer to buy the product; an example is a tour package in a holiday park. Between these two extremes there may be countless pyramids, for example, in the figure the C pyramid (dashed/dotted lines) represents a product with a low level of groups of companies and of motivations too but with a

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complex function of use, that is the case of a sophisticated or luxury car. The D pyramid (dashed lines) refers to a product with a low level of groups of companies and functions of use but having a sophisticated set of motivations, an example may be a luxury good, jewel or watch. Obviously it is not the product itself that defines the SBU but the mix of the three dimensions, in fact the same product for different consumers can be represented in different ways, for example, in the case a participant in the event of the Olympics is motivated not just by "being a fan and passionate but also by other aspects such as "cultural visit", "gossip", "curiosity", "other", the base of the pyramid A would be much larger. This statement applies to any other product.

7. MANAGERIAL IMPLICATIONS: INTERVENTIONS POLICIES’ RANGE IN THE INTERPRETATIVE MODEL. This way of reconstructing the interpretive model of SBU seems to present the following advantages, in comparison to traditional strategic management perspectives:

196

1. it allows us to correctly take into account the greater complexity characterizing the consumption process and at the same time, by referring to factors concerning the production of commodity, it introduces some components (such as personal and social capital) mainly playing a prominent role with reference to the process of purchase of many goods having a strong emotional component; 2. it provides a more advanced method to perform market segmentation; 3. it allows us to enter the role played by public policies in promotion in the field of strategic management; 4. it shows that this role cannot be played only by acting on the supply (that is possibly through the traditional policies concerning the company’s factors), but also acting on factors relating to the production of commodities (that are mainly individual capital, human capital and transformation time). These last two aspects are probably the most innovative ones, or at least the ones we need to highlight in this context. The attention paid by strategic management literature on institutional factors, and therefore on promotion policies performed by public sector, was usually very slight. Some authors (Bresser & Milloning, 2004; Oliver, 1997) recently tried to integrate institutional aspects in the context of models generating a competitive advantage, though not with particular reference to the action of specific public policies. The aim is to underline the need and the more recent propensity of literature to consider the "institutional capital” along with corporate resources, the former thought as a set of specific conditions within an institutional framework allowing the creation of a competitive advantage (Brasser, Milloning 2004, p. 229). Our model, inasmuch as it pays attention to public policy, takes into account this dimension, though not referring to its most general meanings, but to the ones more directly related to the role of institutional actors in promoting certain products (including abroad promotion). The definition of an SBU must also consider these aspects. And the way in which public policies can be involved precisely comes out from the construction of the model. These actions must take into account the complex demand-supply interaction and therefore the interaction between motivation and ability to produce commodities. In reference to the production of commodities, public policies must specifically: 1. intervene in the creation of personal and social capital and support the shift of personal consumption and sensitivity towards "social consumption" in order to create an appropriate

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environment for the consumption of this kind of goods, gaining value when inserted into a cultural context capable, on the one side, of enhancing the features of distinctiveness and creativity, and on the other side, of encouraging a process of contamination of those cultural aspects allowing consumers to extract value from goods, through an accurate process of transformation into commodities; 2. affect the time of transformation, trying to minimize (through awareness and information campaigns, and paying attention to search costs’ reduction) the time to be used for these goods’ finding and for the appreciation of their characteristics. All that affects the way a company creates its strategy as well as the way it takes into account the subsequent impact of this strategy in terms of competitive advantage. Moreover, this way of defining a competitive strategy produces a positive impact on specific actions achieved by institutions, particularly in the field of internationalization policies. The volume of the pyramid also detects the intensity needed in public, private and joined policies. From the height-volume-base width intersection we can draw the following conclusion: the higher the pyramid is the larger the opportunity for policies affecting the supply will be (supply range), the larger the pyramid is the larger the opportunity for policies affecting the utility function will be. Briefly, the model helps the study of product positioning in international competition from a three-dimensional perspective of supply and demand. Moreover, the complexity of the underlying variables may help to understand why most of the public policies focusing on supply have not achieved significant results. It has happened because public policies persist in focusing on just one aspect among significant others and ignore the interactions among variables. 197

8. FINAL REMARKS, RESEARCH LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH The model here proposed clearly undermines the opportunity to embrace absolute statistical and mathematical models of analysis in the field of management; after all, this is an important advantage: letting management seek for consumers’ own characteristics. In this new era of marketing where spiritual and relational aspects are becoming increasingly important, it is suitable to move from an absolute perspective to a relative one. Furthermore, economic literature (Lancaster, 1998; Kahn, 1998) has been pointing out for a long the difficulties that companies have to face in their decisional process when dealing with asymmetric information referring to consumers who express a very high variety demand otherwise a range of purchase options depending on complex motivations, among which there is the desire to insure themselves against future uncertainty about their preferences too (Kahaneman, Snell 1992). The 2008-2011 crises showed that no mathematical model, based on assumptions of rationality, is able to have a predictive function, without focusing on market effectiveness and on complex psychological and social variables underlying consumers’ choices, as well as on competitors which can be synthesized into definition of animal spirits (Akerlof & Shiller, 2009). In many cases, consumers’ expectations result from a cognitive process which is different from the one related to decision: in fact in the first case “people probably engage themselves in some mental forms of experience simulation relating to consumption different options. (...) In a decision making people refer to a rational value-seeking and choose the higher value option without imagining its future outcome.” (Hsee, 1999, pp. 599). In fact, as stated by the Nobel Prize for Economics Daniel Kahaneman: “No one ever seriously believed that all people have rational

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beliefs and make rational decisions all the time.” (Kahaneman, 2003, pp. 162). A key point of this study is that companies need to recover a role that is typically entrepreneurial (dating back to the theories of Schumpeter on entrepreneur and to the so-called Austrian School): it is the role relating to the constant exploration and discovery of market and of its effective opportunities (Kirzner, 1997), since in all actions of real economy all actors are always entrepreneurs. The effectiveness of the model lies in supporting management activities for the definition of the business area, by giving equal and integrated importance to both supply and demand component so that companies can put real and complex products on the market in view of real and complex. demand. In conclusion, some remarks about limitations and plans for future research are due. With reference to the research’s limitations: it would be appropriate to enlarge he "applicability" of the considerations made for a specific type of products "related to territory, culture or community" – such as the Made In – to all types of product "universally" identified into a special collection of goods and services’ characteristics. Moving to future directions that this research can take, they are numerous, including its application to specific case studies that will be intended to provide empirical support to theories and conclusions arising from this analysis.

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Smart Energy Management. A Viable Systems Approach perspectivei Francesco Polese Associate Professor of Business Management, Department of Medicine and Surgery, Salerno University, Salerno, Italy. e-mail: [email protected] Luca Carrubbo Ph.D. in Business Management, Department of Economics and Law, Cassino University, Cassino, Italy. e-mail: [email protected]. Corresponding author Primiano Di Nauta Assistant Professor of Business Management, Department of Economics, Foggia University, Foggia, Italy. e-mail: [email protected] Received September 30, 2012 / revised November 9 / accepted November 10 / published online November 11, 2012. DOI: 10.7350/BSR.A15.2012 – URL: http://dx.medra.org/10.7350/BSR.A15.2012

ABSTRACT Energy is a complex issue to deal with, and the paper’s purpose is to decline a systems theory reflection capable of interpreting complex phenomena in order to better design and manage future energy agendas. Achieving an efficient matching of energy demand and supply needs, 202 introducing a market mechanism for the allocation and pricing of energy resources especially take the specific requirements of energy producers and consumers into account. Moreover, many other actors ought to be taken into considerations; among these for certain all world population and future generations. It seems that energy is a socio-economic topic that needs to be approached with network and complexity theories due to the number of interested parties and the numerous perspectives with which it can be viewed and analyzed. Furthermore, Smart Energy Grid requires continuous improvement in the interactions among system elements in order to optimizing resource allocation, collaborative advantages and cooperative strategies, indeed for the systemic equilibrium within the complex service systems related the energy services provision. The new logic of co-creation of value is win-win, which considers the interaction among several entities represented by a number of Service Systems, and the desire to gain a collective mutual satisfaction, in which the active contribution is multiple, the integration is maximal, complementarity is crucial. The paper suggests that the Viable Systems Approach (VSA), a methodological key based on systems theory and relationships, useful for the interpretation of complex phenomena, might be promising to support world community discussion upon energy, both in terms of value cocreation processes and of the general behavior of nowadays smart service systems.

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For the energy issue, one of possible solution can be the implementing of Demand-SideManagement (DSM), able to allow distributed energy storages and advanced communication technological network for renewable generations in the grid. VSA, in fact, focuses on the analysis of relationships among socio-economic actors in search of viable interacting conditions, and this may support the valorization of all interested parties expectations, giving voice to all the actors interested in the energy topic. Keywords: Viable Systems Approach; Smart Energy Grid; Complex Service Systems; Energy Agenda; Demand Side Management.

1. INTRODUCTION

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Everything that exists is configured as a system, or as part of a system. Systems are in nature, society, science, in computer tools, in economics, are inside the human mind, organizations, etc. Studies on the characteristics of the system are useful for understanding and then trying to manage complex phenomena of various kinds (including those relating to the service). System studies and theories increase knowledge about multiple perspectives, linking components, connective functions and practical applications of complex phenomena (as service exchange). These led to the evidence on concept of dynamics, boarders, structures and relationships of actors. Systems are in nature, in society, in business, within socio-economic contexts. They are not only peculiar of individuals and their human mind. They may be identified also within organizations, districts, etc. Every system is different from every other system. Also considering the same entity carrying out iterative operations, and comparing during a defined time similar involving situations, we can observe relevant differences (in operations, effects, base-logics). Through systems thinking (ST) we can investigate organization behavior, allowing the analysis of links, nets, balances, and processes. Dynamics; with ST various standpoint can be chosen to underpin resources, goals, needs/expectations. ST supports the interpretation of complex phenomena, both from a holistic and from a reductionist perspective. Systems studies and theories increase the knowledge about multiple perspectives (informatics, managerial and organizational) and structuring capacities, linking components, connection functions and practical applications. Systems are in nature, in society, in science, within informatics tools and in economic sides. They are inside the human mind, organizations and general behavior. Through Systems Theories we may observe: − “a system as a complex of interacting elements.” (Von Bertalaffy, 1956); − “a system as an entity that is adaptable for the purpose of surviving in its changing environment.” (Beer, 1975); − “system elements are rationally connected.” (Luhmann, 1990); − concepts of many part compositions (Parsons, 1971), boundaries, connections and different relationship levels show certain signs of systems relevance and allow an interpretation of its own capabilities as being critical and influential, and its relations with correspondent suprasystems and sub-systems; − “sub-systems focus on the analysis of relationships among its own internal components while supra-systems focus on the connections between the analysis unit and other influencing systemic entities in their context.” (Golinelli, 2005);

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− “a structure can be studied (What is it? How is it made?), a system should only be interpreted (How does it works? What logics does it follow?).” (Barile, 2008). In this direction, the contribution aims to deal about the relation between systems and the energy management topic, highlighting how a systemic perspective can support and valorize it. Then, the first part of the paper is addressed towards the recovery of the concepts on the contributions coming from systems theories and approaches, and then focusing particularly on the Viable Systems Approach (VSA). The second part is oriented to the topic of the contribution and implication of systems approaches to value co-creation and competitiveness. The third part deals with the energy as a global issue, proposing an interpretation of the energy management issue through the lenses of Viable Systems Approach (VSA). The forth and last part proposes a path towards the identification of solutions for the governance of energy as a complex context, the demand side management. 1.1 Advances in Systems Thinking, contributions from Service Research

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In the last decades, many international contributions occurred with the aim to improve systems thinking considerations. Many discipline were involved about, a number of relevant advancements were shared. The evolving Service Research was one of them, proposing worldwide several reflections on service systems, and their evolution of smart service systems. Scholars, practitioners and researchers start from a new concept of service that may support to identify a shift in perspective in which goods no longer represent the only object of transaction, but rather, an instrumental element (an appliance) to service provision, considered the effective protagonist of inter-part relations and agreements (Vargo, Lusch, 2006; 2008; 2011). In general, for them the service is related to the value co-creation among actors, the Service view improves positive interaction between entities in reticular systems, service co-creation involves many actors within a dynamic process, and service exchanges need evolving expertises and competences. According to Service Science (Maglio, Spohrer, 2008) a service can be considered as a system made of parts interacting and interdependent between people, technologies and commercial activities (Sporher er al., 2007), continuously seeking the possibility of relating itself (Sampson, Froehle, 2006), in order to use the distinctive capabilities that they own to get a competitive and lasting advantage (Chesbrough, 2005). According to the S-D logic (Vargo, Lusch, 2006; 2008) the service is seen has “the application of competences, through actions, processes and performance, with the benefit of another entity”; it represents “the increase of value for physical goods” (Vargo, Lusch, 2006; 2008). In general “services are intangible activities customized according to the single request of well-known customers” (Pine, Gilmore, 2000); the relative customizations take to coproduction relationships, considering the customers as the real participant of the process and the real key component able to distinguish a specific model of service system from the traditional economic one. These considerations affect the configuration, the behavior and the interpretation of any service system. Emerging service systems studies show how and how much any specific kind of system can be “read” as something, following first of all service logics. According to recent studies on Service Research, we understand that service systems represent value-co-creation configurations of people, technology, value propositions connecting internal and external service systems, and shared information (e.g., language, laws, measures, and methods) (Spohrer, Maglio, Bailey, Gruhl, 2007; Maglio, Srinivasan, Kreulen, Spohrer, 2006). Every service system is both a provider and client of service that is connected by value propositions in value chains, value

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networks, or value-creating systems (Normann, 1991;Vargo, Maglio, Akaka, 2008); service system can simply be a software application, or a business unit within an organization, from a project team or business department, to a global division; it can be a firm, institution, governmental agency, town, city or nation; it can also be a composition of numerous collaboratively connected service systems within and/or across organizations (Qiu, Fang, Shen, Yu, 2007; Qiu, 2009). Service systems therefore act as resources integrators, understandable in terms of elements of a work system” (Spohrer, Anderson, Pass, Ager, 2008), “within the organization and through the network enduring resource specialization, those operand and operant such as knowledge, skills, know-how relationship, competences, people, products, material money, etc.” (Vargo, Lusch, 2006). A service system is any number of elements, interconnections, attributes, and stakeholders interacting in a co-productive relationship that creates value, in which principal interactions take place at the interface between the provider and the customer (Spohrer, Vargo, Maglio, Caswell, 2008). Service systems are socially constructed collections of service events in which participants exchange beneficial actions through a knowledge-based strategy that captures value from a provider-client relationship. Service Systems are defined as work systems in which service providers and service customers share knowledge and information within dynamic networks and a specific value chain (Alter, 2008). 1.2 The Viable Systems Approach (VSA)

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The VSA represents, nowadays, a scientific proposal that can be described as the key methodology for the analysis of complex phenomena (Golinelli, 2000; Barile, 2008; Barile et al., 2012b). It is focused on original representations of behavioural entrepreneurial approaches and on the related interactions between the company, here meant as a system, and its own referring context (theoretical approach). The VSA is inevitably connected with the network studies and it is based on the systems general theory, the social sciences and on many others disciplines concerning cognitive spheres completely different from economy (the main actual application), such as natural and IT sciences. The VSA can be used for the formulation of definitions and postulates which determine the nowadays company behaviour that is basically aimed at achieving a unique final common goal: the survival. This important interpretation allows the analysis, the interpretation and the management of determinant factors from a particular point of view, which differs from those ones that have been consolidated in economy; the consideration of the entity object of the study (a company, an individual or any other existing organism) from a systems point of view, allows to find out the critical elements (also the environmental ones) with whom it has to deal in order to succeed in facing the numerous external and internal changes that, especially in long terms, can influence its actions. From this point of view any organization action is contextualized in a dense group of relationships which are branched off within the structure of a company-system (so considering that also its sub-components – sub-systems), stretching to its external side and relating itself to all the possible system over-structure (significant or not – supra-systems) that, in a direct or indirect way, can influence the action, the strategies and the outcomes of an organization (Saviano, 1999; Barile et al., 2012b). The VSA, which is developed from an interdisciplinary interaction between the holistic and the reductionist theories (von Bertalanffy, 1956), is based, according to the systems thinking and to the related implications in terms of relationships, on the system concept, and it is oriented toward the interpretation of its construction and organization, of its behaviour and evolution, of its relationships and interactions. The system we study, therefore, can be meant as a micro-ambient

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made of several associated parts (Parsons, 1971), made of a series of elements which are interconnected in order to achieve a common goal. VSA enables an analysis to be made of the relationships that exist among an enterprise’s internal components, as well as an analysis of the relationships between enterprises and other systemic entities in its environmental context. Recently, a set of main fundamental concepts was synthesized, trying to cluster theoretical principles affecting the VSA, as represented in table 1. According to the VSA, the relational development between system entities is referred to the consonant and resonant relationships which can be found in the long term; nowadays the competitive behavior is strictly connected to the ability of identifying and managing functions, communicational channels, informative streams, rationalizing and harmonizing a sustainable development, adjusted to the iridescent external ambient (Christopher, 2007; Barile, Di Nauta, 2011; Barile, Polese, 2011; Barile, Saviano, 2011a; 2011b). VSA proposes a deep analysis of the Structure – Systems dichotomy when introducing that every system represents a recognizable entity emerging from a specific changing structure (set of individual elements with assigned roles, activities and tasks performing in compliance with rules and constraints). System origins then from its own structure, this kind of evolution derives from the dynamic interactive activation of static existing basic relationships. Starting from the same system features, a comparison between their performance effects certainly highlights some differences. We have to consider many aspects and factors for a behavior system analysis, like experience, knowledge improvement, previous mental constructions, abilities, personal competences, tacit or codified procedures, specific operations of doing things, from the potential application of internal specific competencies to the external effective manifestations on real patterns capable of evaluation. Each system, to be so defined, must be able to manage its relationships with the outside, respecting the rules, the roles and the shared responsibilities, in an attempt to succeed in satisfying the common interests of the system entities involved in its process of value creation (Golinelli, 2000; Barile, Montella, Saviano, 2011). In reference to the distinction that exists between the static structure, which is the basis of any organization, and the dynamic system that originates from it after the activation of the relationships existing between the component elements, according to the VSA, the consonance represents the basic compatibility between two system entities, the potential harmony of a relationship that can be related exactly to the structure (Golinelli, 2000; Barile, 2008; Barile et al., 2012a); on the contrary, the resonance concerns the effective harmonic and dynamic interaction between two systems, as consonance ideal evolution (its acceleration, its second derivative, Barile 2008), fundamental for a synergic one-to-one union, aimed at favoring the common satisfaction of a collective behave.

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Table 1. The ten fundamental concepts (FCs) of VSA (Source: Barile, Polese, 2011).

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1.3 Complex Systems, Smart Service Systems and Viable Systems

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Through the development of modern interpretations of service systems, we have seen the centrality of customers in the process of service creation and delivery, reinforcing the iterative and cyclical mechanism of contemporary service provision. In this direction, a new generation of complex systems which are capable of describing and analyzing a situation and taking decisions based on the available data in a predictive or adaptive manner can be defined as Smart or Viable. Recent developments in Service Science Research have led to a new concept of service systems, arriving at a definition of the characteristics of Smart Service Systems (SSS). SSS combine advances in IT tools with the evolution in thinking about system dynamic interactions, adaptive skills, sustainable development, enhanced learning, reconfiguration capacities and service innovation (IfM, IBM, 2008) in complex environments (Basole, Rouse, 2008; Demirkan, Gaul 2006), all converging toward something more “smart” than that we are used to considering, generally referable, going up to a sort of Smarter Planet (IBM, 2010). The evolving and increasing role of interconnections, enablers, measures, standard quality and procedures represents the theoretical evidence of this evolution; intelligent utility networks and metering, intelligent transportation, consumer driven supply chains, intelligent oilfields, manufacturing productivity, instead, are the nowadays practical applications (Barile, Polese, 2010) as systems capable of serving customers better (this could be applied to water consumption and use, electricity distribution and management, public transportation, education, healthcare, etc.). In order to stimulate thinking about smarter concepts (soon referred to as the Specific, Measurable, Agreed, Realistic and Timely phenomenon), Service Science researchers have investigated every potential application of service research “on stage”, referring to practical evidence about something really iterative, interactive, instrumented, interconnected, intelligent, i.e. a smarter planet. In this sense the intelligence of smart service systems derives not from intuition or chance, but from systemic methods of learning, service thinking, data collection, rational innovation, social responsibility and networked governance. Applying a smart context, smart practicalities, smart cities, smart organizations, smart operations and smart outcomes to modern service “events”, we can enjoy several important changes in our life. VSA, instead introduced the concept of “viable” as something different form the “living” or “vital” one, remarking it is not referred to something that in a specific moment can live, but to something that is autonomously able to grow its own survival possibilities. In the VSA, the word “viable” refers just to the capability of building the adequate relationships with the surrounding ambient and of running all the actions which are necessary for the organization survival, especially in the long period (Golinelli, 2000; Barile, 2008; Barile et al., 2012a). VSA synthesize that: any viable system lives, its aim is to survive within a context which is populated by other (viable) systems; − every context is subjectively perceived by a viable system’s top management (the decisionmaker) from analyzing its environment (a macro-system in which the decision maker is immerged) distinguishing and identifying its relevant supra-systems (resources owners) in relation with its objective; −

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− context is the synthesis of a reticulum of viable systems, within which it is possible to distinguish a certain number of systems (relevant supra-systems), which are able to condition top management decisions; − the system’s structural definition and the level of consonance between its evolved components (interacting supra and sub systems), define a given system’s grade of elaboration; − a viable system has the capability of dynamic adjusting (auto-regulation) its structure: hence we may refer consonance to the system’s attempt to correctly interpret contextual signals, and resonance to the concretization of the consequent competitive behavior in order to maintain stability (if the system satisfies external expectations and needs) displayed by relevant supra-systems.

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A system is made viable from the behavior adopted (also in the value creation point of view): more strategic, more reactive, more adaptive, and more intelligent. The qualification and the valorization of the relationships, the new planning of the organizational configurations, the complexity management, the common participation to the value creation process, are all elements that identify a successful system. Matching Service Research and System Thinking, we can highlight the relevance of system configurations (function of the designed structure and the ability to evolve, adapt, be intelligent and smart); and system interactions (indicative of the ability to implement relationships, collaboration for mutual satisfaction effectively, win-win logic). In general complex systems improve quality of life, creating more opportunities for win-win interactions, resulting in measurable resource access and value-co-creation for multiple stakeholders. In every social system, contextual consonance and the search for resonance are firmly linked to the capacity to create value and consequently, to the capacity of creating competitive advantage. As a result, the co-evolving of the system, favoring processes of harmonious development and reciprocal satisfaction, enhancement of long term relationships with (more or less relevant) supra-systems of references, cannot and should not be analyzed regardless of the potential of the context for competitiveness. Summarizing: − “Greater odds for survival of the system depend on the organization’s capacity to update value propositions in line with the external changes (contingences) and context needs.” − “Modern service systems, regardless of specific value propositions, are inspired by structure concepts and organization in systems thinking logics.” − “A link exists between the viability and the concept of ‘smart’, both are bound by the system vision and characterized by adaptive actions.” Energy Management issue can be interpreted as a system, a set of elements interacting to catch a final goal in terms of efficiency of communication and of results for consumptions. The need to know and organize the flows of information leads the managers to think and implement smart tools and instruments. In this direction, Energy Management can be fostered to improve the performances of the system as a whole. Energy Managers look for solutions in order to support different levels of users in the exchanging process of useful data in real time. The theoretic background given by Demand Side Management techniques could represent an innovative proposal to face the issue of energy consumption integration. Energy Management techniques are based on the automatic reduction of energy supply operated by the remote management in order to smooth the daily demand trend.

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2. SYSTEMS THEORIES’ IMPLICATIONS FOR VALUE CREATION AND COMPETITIVENESS

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New reflections on value creation models in Systems Thinking illustrate that their form or nature do not depend wholly on contributions from interest groups (such as participants) in value generation processes but highlight on the contrary, improved interaction in the relational dynamics of system elements and the relevance of resource allocation and collaborative advantages, not to mention the importance of alliances, roles, rules and cooperative strategies. VSA underlines the systemic nature of value creation processes; the firm as an isolated entity totals little value taking into account it is a part of the value creation processes jointly and contextually with its specific interlocutors. It follows that value has to be considered in its dynamic capacity as well as in its multidimensional (economic, social, competitive) form. The implication is a process of knowledge governance which takes into account the weight of and effective role played by each interested party with the firm. In terms of context, the governing body selects the entities by virtue of which and due to their effective relevance, it qualifies as a potential participant in the dynamics of value creation; in other words, as co-creators and coresponsible for the satisfaction of mutual needs and expectations. Value creation is the result of the interactive dynamics in play between systems, also underlines how components, activities and processes are relevant in providing services to others (i.e. consumers) in order to obtain mutual value (i.e. providers). In line with the relational view (Gummesson, 1993; Prahalad, Ramanswamy, 2000) of business performance, network theories consider all the actors involved as dynamic, ‘operant’ and active resources that facilitate networked interaction (Lovelock, Gummesson, 2004; Achrol, Kotler, 2006), and organizations and their activities are enclosed in various relationships (Gummesson, 2008). In this perspective, system relationships drive business components, behaviour, strategies, policies, and organizations; these relationships are then consciously determined and finalised to mutual satisfaction (Womack, Jones, 2007; Lusch, Vargo, O'Brien, 2007). In terms of VSA, system viability is strictly linked to the relational and cognitive skills that are capable of generating “calculated consensus” (differential) through interaction thus exalting processes of collaboration, cooperation and sharing aimed at the co-creation of value; in other words, favoring interaction between systems that share their own resources in a win-win relationship to manage component dynamics, especially with reference to the variation between internal “characteristics” and external “opportunities”. Emerging relationships are very much related to individuals who interpret and fulfill business missions, strategic actions, and management practices through their values and cultural identity (Golinelli, 2010). This kind of social relations can be defined as a relational pattern that characterizes each individual in a business scenario and involves personal, business and stakeholder relations (Polese, 2009; Polese, Minguzzi, 2009; Polese, et al., 2009; Polese, Russo, Carrubbo, 2009; Polese et al., 2010); in social relationships, consequently, consensus is favored when systems are constituted by cohesive, interpersonal, fiduciary, long-term relationships based on values rather than rules. In the close link between new service and system considerations and modern interpretations on the creation of value, the process, seen in the Service Research and System Thinking perspective, in practice follows a pathway a) starting from the traditional value chain (Porter, 1980), b) arrives at real value constellations (Normann, Ramirez, 1995), where customers are no longer viewed as “destroyers” of the value proposed by the firm, but rather as core elements (Moeller, 2008).

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In terms of service science logics, customers (and the other stakeholders) deliver a crucial "surplus value" both as concerns the production (and co-creation) of value, translated in the sense of core to achieving and sustaining competitive advantage (Woodruff, 1997). The levers illustrating the shift in paradigm clearly indicate that the new models of value creation are closely related to the new concept of service precisely because of the co-creation mechanisms that all the stakeholders sharing in the process of value generation, inevitably set in motion. Similarly, the value attributed to all the stakeholders involved has shifted attention to a new way of thinking, not simply linear or unidirectional, but also crosscutting, iterative, self-sustaining, of a many-to-many type. This means that the transaction, on which the competitive strategy rested initially, has been replaced by adaptive, evolutionary, viable behavior characterized by dynamic systems interaction. From the value-centered perspective of innovative service, it is evident the extent to which consumers are interested not only in the goods or services as such, but rather in terms of solutions to their needs (Zeithaml, 1988; Maglio, Spohrer, 2008). Consequently, the consumer does not obtain value directly from the product itself, but from its use, processing or consumption (Lusch, Vargo, 2006). If it is true to say that the value of a product consequently, derives from the benefits that underlie the service (Venkatesh, Peñaloza, Firat, 2006) and seeing as companies have no option but to formulate their product offerings to satisfy the market, then it is evident that value is not created in the production process or reflected in the selling price, but follows a more sophisticated process of co-creation (Prahalad, Ramanswamy, 2004; Ballantyne, Varey, 2006; Mele, 2007). Value in other words, is derived from a complex process of co-production, co-design, comarketing involving different entities (not least end users, Vargo, Maglio, Akaka, 2008); by sharing information, resources, skills, needs and risks (Möller, 2006) in conformity with the network theories and the systems approach to corporate governance (Gummesson, Polese, 2009; Mele, Polese, 2011; Polese, Di Nauta, 2012). As concerns the end user, value is created by means of a personal “consumption” process, stemming from the constant interaction with other parties in the relevant service system (Spohrer, Vargo, Maglio, Caswell, 2008). In this perspective, perceived value, (i.e. the potential value proposition) becomes concretized (i.e. effectively co-created through the process of customer satisfaction) and the firm is seen as integrator (and manager) of the resources necessary (Polese, Carrubbo, 2008) in a prospect of mutual satisfaction, blending the value co-created with the comparative appreciation of a mutual service” (Lusch, Vargo, O’Brien, 2007). The value is considerable an improvement in the system, as perceived by the system itself or on the ability of the system to integrate into its environment. Value creation takes place as a potential resource is converted into an actual specific benefit. The logic of co-creation of value is a win-win, which considers the interaction between different entities represented by a number of Service Systems and the desire to gain a collective mutual satisfaction, in which the active contribution is multiple, the integration is maximal, complementarity is crucial; economic exchange is ultimately voluntary, and reciprocal use of resources for mutual value creation through two or more interacting systems. The service systems of today (so smart and viable) are not defined only by simple relations and interactions between resources: some resources must be operating, must be ensured to propose, agree and assess the processes of co-creating value, often if not always reticular in nature. The supply chain is re-conceptualized as a network of service systems and therefore has a configuration cannot be defined a priori, but rather can be changing, to adapt and evolve in relation to changing contextual conditions. The contribution of knowledge, application skills, the

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ability to configure and re-configure itself, the desire to weave long-standing relationships with individuals representing all considered to be strategic elements of a systemic way to be adaptive. The value is perceived and co-determined by the customer based on value in use (Consumption process), so something to be defined ex-post ex-ante but achievable mainly through the contribution of the recipients concerned in the process of co-creation of value. The service can be seen as an end, rather than opens as a means of creating in the process! Then: − the consumer is no longer seen exclusively as a target (value destroyer); − companies have a right only to make its own proposal (value proposition); − consumers are considered real factors of production (value co-creator) within a complex system of service delivery (service system); − consumers are able to benefit not only from the products purchase, but also for processing, use and consumption of the same (value in use), revealing their role as active (participant) in the value generation process; − the business competition is very influenced by that because, as you are able to create value more competitive you are, as you are able to engage in co-creative purposes, greater sustainable will be your value proposition.

3. ENERGY AS AN EMERGING GLOBAL ISSUE 3.1 The energy agenda development 212

Energy is a complex issue to deal with. It is complex for the related continuous technical innovation, for the balance that needs to be reached among renewable energy sources, for the shortage of traditional energy sources such as gas and petroleum. Achieving an efficient matching of energy demand and supply needs introducing a market mechanism for the allocation and pricing of energy resources all take the specific requirements of energy producers and consumers into account. Moreover, many other actors ought to be taken into considerations; among these for certain all world population and future generations. Is seems that energy is a socio-economic topic that needs to be approached with network and complexity theories due to the number of interested parties and the numerous perspectives with which it can be viewed and analyzed. Furthermore, Smart Energy Grid requires continuous improvement in the interactions among network elements in order to optimizing resource allocation, collaborative advantages and cooperative strategies indeed for the systemic equilibrium within the complex service systems related the energy services provision. Energy is a Global Issue, because of its need to be approached with systems, network and complexity theories; multiple actors are involved in its production, transportation, consumption, management, all referable to the new concept of service. Energy market needs a mechanism for the allocation and pricing of resources that especially takes the specific requirements for producers/providers and consumers/users; energy organizations require continuous improvement in the interactions among network elements in order to optimizing resource allocation, collaborative advantages and cooperative strategies. The complexity management and the general diffusion of the service logic may attempt to useful solutions for the efficient matching of energy demand and supply. Despite their relevance and the number of actors involved, to find shared policies and strategies to deal with energy production/consumption, as well as with a sustainable development of human

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socio-economic activities, more efforts need to be placed. Researchers, politicians and opinion leaders, in fact, cannot easily find a solution to such complex phenomena; to carry out an efficient plan of activities we have to reach the elements for a better Energy Agenda and we need a long-term goal to shape a scientific and policy agenda aimed at smart, sustainable and inclusive growth. The priority goals in the agenda have to be oriented to rationalize consumption, diversify the energy portfolio, reduce emissions of greenhouse gases and increase energy efficiency. Today we can easily assume that energy management and sustainable development are two of the most challenging and important issues we are about to face in the new millennium; issues that may affect the length and the quality of human life in the world. The management and the measurements of energy consumptions is today of fundamental importance not only for charging purposes, but also to coordinate the energy flows aimed at rationalizing and reducing consumptions, both in industrial activities and in the commercial and domestic activities. From the point of view of measurement issues, the evaluation of flows of energy is among the most difficult aspects of metrology without any doubt, both for the impossibility to perform direct measures, and for the difficulty of ensuring the most accurate metrological traceability in traditional form and the certification of instruments used for this purpose. 3.2 Systems theories insights for the energy agenda VSA,

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a methodological key, focuses on new approaches to representations of entrepreneurial behavior and the interactions between the firm, considered as a system, with its own environment (theoretical approach) in an attempt to suggest innovative interpretations on business strategies, organization and management (practical approach). Then the study of systems and the VSA in particular may support energy research & development and energy decision makers, policy makers and opinion leaders. In order to design and manage future energy agendas, the VSA can be adopted to decline opportunities and constraints expressed by the involved actors, looking for wise decision making and sustainable (viable) behavior of producers, consumers, politicians, researchers and so on. This may be accomplished since the VSA, based upon ten fundamental concepts (FCs) (Barile, Polese, 2010b) introduces the issues such as: i) systems approach; ii) systems hierarchy; iii) reductionism and holism; iv) open systems and systems’ boundaries; v) autopoiesis, homeostasis, and self-regulation; vi) structures and systems; vii) Consonance and resonance; viii) system viability; ix) adaptation and relationship development; x) complexity and decision-making. It can be interesting to highlight what is happening at an international level to energy matter, considering it is a crucial topic in the economic scenario. Think, for example, of the repercussions on financial markets related to the variation of the price of oil the consequent periodic energy crises. Therefore, the measurement and control of energy have a significant importance both in domestic industrial activity and in the international one. Nevertheless the complex measurability of greatness energy still makes little economic transparent exchange of goods and energy services. Consider the accounts of fossil fuel (petrol, oil, natural gas, etc.) performed yet by volume (liters, barrels, etc.) or the measurement of electricity and heat made respectively with electrical and thermal counters not yet submitted in Italy to review by the legal metrology, or even the almost total absence of meters for taking into account energy consumption in apartment buildings with central heating systems. To make it even more complex and critical, the liberalization of Italian and European electricity and gas market contributes to

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this situation. But the accounting is not the only technical aspect that must be taken into consideration when it comes to measure because of the need to continually transform energy from different forms makes it necessary to know, certify and monitor periodically the complex systems responsible for that purpose, and hence provide a reliable measurement of energy flows in transit and energy efficiency. The increase in trade has also given rise to the need to perform many more measurements. These trends are trampling today’s measurement technology, which is further hampered by a lack of effective and precise standards under which to calibrate measuring instruments. In this context of technological changes and innovations regulatory changes are included too, such as those described in the new 2004/22/EC of the European Parliament and Council of March 31, 2004 (MID). Figure 1 – VSA Foundational Concepts and their relation with the Energy Agenda (Source: Authors’ elaboration on Barile, Polese, 2011) vSa Foundational Concepts

Fit with Energy Agenda

System hierarchy

Different levels of management, check, efficiency improve

Holism and reductionism

Environmental effects and single sub-systems organization Law, institutions, needs, technologies, opportunities to develop

system’s boundaries

214 14

Consonance and resonance

Complexity and Decision Making

Users, producers, providers, storer, manager behaviours agreeble with each other Demand Side Management

Despite the importance of energy issue, in the past scarce attention has been given to problems such as calibration and traceability of gauges of electricity and heat, so that, at least as regards Italy, more than 70 million meters of energy (electrical and thermal) are active and apply tariffs without a proper metrology mark. As for electricity, calibration of meters is carried out according to the UNI CEI 13.4 standard, by comparing the estimate of electricity measured by the meter under test with the measurement made by an energy meter reference. Significant changes were envisaged in regulation, as the complete reform and liberalization of the electricity market and implementation of Directive 2004/22/EC on measuring instruments (MID). With the goal of creating a single market, the MID has defined harmonized rules regarding procedures for the marketing of special measuring instruments, and between the counters of electricity. The MID sets out requirements to be met by measuring instruments related to the specific directives adopted on the basis of Directive 71/316/EEC in relation to their marketing and/or put into service. The counter global energy could solve these issues by implementing even an embedded low-cost instrument capable of carrying out the calibration as required by MID and following the guidelines outlined by industry standards, and communicate data measure to a calibration thanks

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to current communication technologies (Power Line Communication, Communicatio Wi-Fi, Wi Bluetooth, GSM, etc.). All these seem to fit with energy and to be able to support the related system critical deepening. VSA supports energy research and energy decision ecision makers, policy makers and opinion leaders since the scientific proposal is able to analyze and manage complexity and the role of many actors (also including ending users), naturally involved in co-creation co creation exchanges characterizing energy production and consumption. The general comparison can be found as follow, highlighting the connections existing between the main focus of VSA and the application to energy complex systems. Table 2. VSA Foundational Concepts and their relation with the Energy Complex Systems (Source: Authors’ elaboration on Barile, Polese, 2011)

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4. IN SEARCH FOR OPERATIONAL SOLUTIONS: DEMAND SIDE MANAGEMENT For Energy complexity interpretation and management, future EU measures will be implemented encompassing revision of the existing Energy Services. “Measurement” will have to focus on the establishment and functioning of the internal market, securing EU energy supplies, energy efficiency and renewable, reticular interconnection energy networks. The renewable generations in the grid could be reachable with the distributed energy storages and advanced communication technological network, by implementing Demand-SideManagement (DSM) application (Strbac, 2008). In particular: 1. DSM seeks to reduce energy demand or shift it to times that better suit supply; 2. Consumers can be provided with the necessary information for a more effective use; 3. Reaching an active and flexible management requires devices for communication in real time, as smart meters and electronic box, using two-way communication between intelligent agents located on the grid for a smart energy management. The DSM techniques implementation allows a consistent reduction of (Kirschen, 2003; Mohsenian-Rad et. al. 2010): − costs related to energy distribution networks, due to an optimization of dimensions; − costs of energy, thanks to a reduction of demand peaks; − energy consumptions of demand side, which becomes even more responsible thanks to this innovative contract. 216

The modular architecture would be ensured through the use of the well-established technologies based on the development of appropriate web services that enable access to information of interest through standardized protocols and platforms independent of the particular hardware/software solutions adopted. To achieve this result, the “smart” sensors will consist of modules including special sections for sensing, transduction, development and digital transmission (Vojdani, 2008). To this aim, standard protocols, typical for implementing web services, will be adopted. This technology will allow the development of cooperative applications that can be easily carried out by distributed systems composed of suitable computer networks (Rau, Narayan, Wan, Yih-heui, 1994). Through this option, if necessary, introduction of new sensors and/or replacement of existing sensors with different devices will not require significant changes to system architecture. Indeed, a web service is a ‘class’ that allows a machine to invoke ‘methods’ that reside on other machines, using shared data formats and communication protocols (Lund, 2007). In this sense, the connection with one of the most important stakeholder of energy provision (the demand) improved by producers and managers, and the willingness to involve the final user within the process of energy distribution/consumption, sounds so close to systems approach reflections about the logics of systems’ boundaries and hierarchy (VSA FC2 and FC4). Indeed, the presence of many actors operating for DSM solution helps in the definition of the limits of the system; the several steps and the multi-part contributions to the system efficiency support the levels configuration. The development of a model that works on data collected on field should include the use of quantities measured (directly or indirectly), which means that the model should be strong enough to work properly with data affected by uncertainty or with unevenly time spaced.

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The model, therefore, must use directly measurable parameters, such as: absorbed/generated electric power, gas flow, hot water flow obtained by estimates, energy consumption in various forms provided for the type of user, availability of the market for the various sources, price of energy for different sources, other relevant information to the operation, weather forecasting, types of absorption/generation, special events, etc. The model then, has to combine completeness and execution speed so that it can be implemented on a normal Workstation (Donnelly et al., 1996). Therefore, the objective function is a mathematical function with as input parameters the energy past consumptions of the various system loads and prices for the various sources; the actuation quantities as independent variables and overall energy of the system home/small-medium enterprise as output. Future EU measures will be implemented through adequate legislative instruments, including a legislative proposal encompassing revision of the existing Energy Services and Combined Heat and Power Directives, focusing on the establishment and functioning of the internal market, securing EU energy supplies, energy efficiency and renewable, reticular interconnection energy networks. The renewable generations in the grid could be reachable with the distributed energy storages and advanced communication network. Accommodating renewable power needs managing the increased volatility of electricity supply achievable, by implementing DSM (Strbac, 2008). The studies and the applications developed in recent years, however, concern the solution of specific problems without addressing the problem of integration of the various forms of energy. The latest theories on the management of energy consumption, instead, are pushing towards the integration of systems for remote reading devices, that allow the setting of the characteristics of the supply (partialization of energy loads), that can be remotely controlled. Assuming that they are connected to a bidirectional communication network coordinated by a central unit for the information collection and command transmission, the system would be able to apply the most modern techniques of “Demand Side Management” to the integrated management of energy sources (Kirschen, 2003; Mohsenian-Rad et. al. 2010). The DSM allows: − the collection of readings/information by electronic devices; − the simultaneous issuance of the invoice; − the possibility to collect, store and transmit further information to processing centers (alarm signals, such as tampering and leak-detection events, or events stored locally as the period or rate of use of the supply by the individual user) and mainly to remotely control the characteristics of supply. This energy management system makes more useful and effective the communication capabilities featuring the newest and innovative both domestic and industrial energy consuming devices, as well as the adaptive behavior of building automation systems, which would be used for reconfiguring devices to match the demand reduction operated by management (Donnelly et al., 1996; Lund, 2007; Rau, Narayan, Wan, Yih-heui, 1994). Such an integrated flexible management system of the whole energy supplies (electric, gas and hot water) would be possible if were designed and realized the following items: − energy supply reduction actuators;

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− measurement, elaboration and control local units featured with analog and digital output/input modules, and multi standard communication modules for transmitting measurements and receiving commands to/from a remote central management unit; − a suitable ad hoc data network. The proposed energy management system would find applications for industrial and commercial users. In fact, small industries, which usually do not have the support of an energy manager, could get significant energy savings by means of held down investments. The system proposed centralizes the energy management entrusting it to an information system implementing management rules codified by a pool of experts and helping management to take decisions on the basis of data coming from users, energy market and user specifications (Donnelly et al., 1996).

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The web services are implemented in the ‘NET Framework’, where the method calls are performed using the Simple Object Access Protocol (SOAP), based on XML, which describes how to mark the requests and answers so they can be interpreted by the browser. As a result, through the SOAP protocol, applications transmit data according to a standardized format with the consequent advantage that the implementation of specific web service (in terms of data format, programming language, operating system and hardware platform) does not create any bond against the ‘client’ who is using the service. For these reasons, this proposal would build and characterize a distributed monitoring system based on the ‘NET Framework’ platform (Rau, Narayan, Wan, Yih-heui, 1994). In particular, for the monitoring system, a hierarchical architecture is proposed: the web sensors would communicate with web servers (located at short distance) which are responsible for data base coherence in respect with each single measurement domain (Lund, 2007). Information about measurement will be sent to a concentrator capable of ensuring reliability and robustness through the study of correlations and properly exploiting the existing redundancies. The resulting information will be made available to ‘remote clients’, in the form of ‘web services’. The detection of the most appropriate strategy to optimize consumption, through the implementation of a software management system that, starting from data coming from the field, automatically provides the rules for the loads management. In this direction, the software would implement a procedure for the optimization: it would be based on the definition of an objective function, which defines the analytic relationship between costs and benefits, and its minimization, by an optimization algorithm. The objective function is a mathematical function, a scalar function and thus with values in the field of real numbers, which describes the behavior the system from an energy point of view; it would take into account the involved parameters, such as measuring and control (or actuation) parameters. It would also be defined, so that the optimum situation for the system would correspond to its minimum value: therefore, in order to optimize energy performance of the system, the objective function has to be minimized with an optimization algorithm. DSM seeks to reduce electricity demand or shift it to times that better suit supply. Consumers can be provided with the necessary information for a more efficient use. The achievement of an active, smart and flexible management requires devices able to communicate in real time, as smart meters and electronic box, using intelligent two-way communication between intelligent agents located on the grid. In order to design and manage future energy agendas, the VSA can be analyzed in order to decline opportunities and constraints expressed by the involved actors, looking for wise decision making and sustainable (viable) behavior of producers, consumers, politicians, researchers and so on.

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5. CONCLUDING REMARKS

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The management system will consist of (i) a set of smart sensors, (ii) local servers for measuring the quantities of interest, (iii) a central server and (iv) a communication system. According to the proposed scheme, the resulting system for DSM will be able to carry on realtime acquisition for the quantities of interest in different geographical areas to timely suggest appropriate action for demand optimization. A key aspect in designing a distributed measurement system relates to the development of hardware and software interfaces for data transmission, from sensor nodes to local concentrators and data throughout wide area network. As a consequence of the development in digital signal processing and corresponding low-cost device manufacturing, the design and implementation of distributed smart data acquisition systems are now feasible. In particular, local measurement systems can execute data acquisition as well as data storage, data processing and data encoding allowing a concise and complete information set to be transferred to the central unit. Equally, important is the choice of the architecture for transmission network, dislocation of nodes and data compatibility, regardless of platform, as well as the choice of communication protocols for data exchange, qualification of transmission equipments and security in accessing to system resources. The complex measurability of the quantity energy still makes opaque economic exchange of energy products and services. Consider the accounting of fossil fuels (gasoline, oil, natural gas, etc..) performed yet in volume (liters, barrels, etc.); or consider the measurement of electricity and heat carried out respectively with heat and electricity meters still not submitted in Italy to control of legal metrology; or even to the almost total absence of measures for the accounting of energy consumption in apartment buildings with central heating systems. Liberalization of the Italian and European market for electricity and gas make even more complex and critical this situation. But billing is not the only technical issue that must be taken into consideration when it comes to energy measurement as the need to continually transform energy from different forms makes it necessary to know, certify and monitor periodically the complex systems responsible for this purpose,, and thus to provide a reliable measurement of energy flows in transit and energy efficiency. The increased trade has also given rise to the need to run many more measurements. Phenomena related to power quality such as harmonic distortion, noise and transients, in addition to the holes and surges generated by new, sophisticated electronic equipment have increased the degree of difficulty in making precise measurements. From the perspective of the measurement problems, the energy estimate and the definition of calibration problems connected with it are undoubtedly among the most difficult aspects of metrology, either for the impossibility of direct measurements and for the challenge of achieving the most accurate metrological traceability in traditional forms. So we must first understand what quantities are directly measurable, taking into account the various problems of specific measurement for each of the quantities of interest. In a second phase, energy consumption will be linked to directly measurable quantities. In a third phase there will be a study on the quality of energy in order to bring into account the quality parameters in the billing to both reward and penalize users. Today we can easily assume that energy management and sustainable development are two of the most challenging and important issues we are about to face in the current millennium. These issues may affect the length and quality of human life in the world. Despite their relevance, and the fact that many actors (participants involved in energy system processes enhancement) are struggling to find shared politics and strategies to deal with energy production/consumption, as

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well as with a sustainable development of human socio-economic activities, more efforts need to be placed. Researchers, politicians and opinion leaders, in fact, cannot easily find a solution to such complex phenomena. Energy is a real complex phenomenon to deal with (because of related services, networks, organizations, policies, strategies, etc.); due to this so strategic issue, it is very important to define and maintain a good sustainable energy agenda, especially for renewable sources solutions. Systems Theories may support its interpretation, governance and management of relations is a fundamental concept both for service paradigm sciences as well as for network and systems theories, therefore, also VSA, for the improvement of energy performances and fosters a smart energy management. There are several methodological concepts described by VSA that could be useful to synthesize energy approaches. This paper focuses on just a few of these concepts and contribute offering to decision makers, who strive to achieve survival for their organizations, a new and useful perspective in order to observe and interpret energy dynamics within wider complex systems. Demand-Side-Management represents a possible solution to check, measure and evaluate energy flows, in order to manage the efficiency and the productivity.

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To conform with Italian regulations on academic publishing, even though the article is the joint work of all the authors and they share responsibility for the entire work, we attribute the contribution of each author as follows: sections 1 and 5 to Francesco Polese, sections 3, 3.1 and 3.2 to Primiano Di Nauta, sections 1.1, 1.2, 1.3, 2 and 4 to Luca Carrubbo.

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“Ranking-based Ties” Social Networks. An illustration based on a system of Fashion Capital Cities in the world Ignacio Martínez de Lejarza Associate Professor of Applied Economics. Faculty of Economics, University of Valencia, Spain. e-mail: [email protected]. Corresponding author José Rodolfo Hernández-Carrión Associate Professor of Applied Economics. Faculty of Economics, University of Valencia, Spain. e-mail: [email protected]. Presented at the First Business Systems Laboratory Discussion Meeting – 10-11 September 2012 – University of Palermo - Italy / revised November3 / accepted November 13 / published online November 14, 2012. DOI: 10.7350/BSR.A16.2012 – URL: http://dx.medra.org/10.7350/BSR.A16.2012

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ABSTRACT Our paper aims to apply a non-conventional Social Network Analysis to a network generated from an initial sorting of data with mere order. The aim is to test whether and how one relationship set "conveniently" generated by the ranking is able to provide a coherent system of interactions with possible practical and theoretical utility. We consider a system of city distributions where we focus on “Ranking-Based Ties” social networks, considering a system of "objects" of the same class that would be able to interact. The objects in question are ordered according to their "performance" in a particular ranking. According to a survey developed by Global Language Monitor, there is a ranked number for every capital that could be considered important among the world’s most fashionable cities. Using the rank of scoring average we construct a fashion cities network in order to analyze the dynamics and the topology of the system following a gradual process of clustering or densification of relationships consistent with key network statistics analysis. Keywords: Fashion cities, Fashion Capitals, Social Networks, SNA, Ranking-based Ties, System of cities.

1. INTRODUCTION Our purpose is to offer the beginnings of a new line of inquiry into social networks, to apply a social network analysis to the core group of global fashion cities. The question motivating our inquiry is whether and how social network effects have spillovers and connect each other; we are going to consider a system of cities distribution where we focus on “Ranking-based ties” social networks. In our paper we would start a discussion which is still “ongoing”. We consider a system of “objects” of the same class that would be able to interact. The objects in question are ordered

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according to their “performance” in a particular ranking. That “performance” will be, ultimately and therefore this ranking, which is cause-effect and reason-consequence, the root of all relationships that would exist among them. These relationships are realized through mechanisms such as competition, imitation, leadership, monitoring, differentiation, etc. These are mechanisms all of which can be at least partially driven by this ranking. Let be S=< E, R > an ordered system with a set of individual E, E={e1,e2,…,en} and a totally order relationship R with the usual properties, that means being reflexive, anti-symmetric and transitive . Over this structure we consider the ranking function R as a map from the set E to the Real Space, R : R: E
R / R(ei) = Ri with: ∀i : Ri ∈ Q being Q, the Set of rational numbers, Ri >Rj ⇔ ei precedes ej by the order R , max{ Ri} ≤ N and min { Ri} ≥ 0

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On such structures may induce a binary relation between each two of the elements E, so that both link according to some criterion consistent with the relationship. The ultimate goal and purpose of our work is to see whether it is possible to extract a set of viewable and analyzable interactions with SNA resources, from a initial sort of order, so as to facilitate research in areas where it is conceivable that this order relation is capable of generating interactive behaviors of interest. Several examples of these situations could be the following: the presence of various firms in the same market segment; the competition between election candidates; competition between countries, regions, or even companies in the market of a product; organization of events; and supremacy at commercial, sports, economic or military environment. This will be the goal in the case study in which we get a binary relationship that grows with some measure of the discrepancy between the two orders of the two elements of E considered, and it is also growing with some measure of relevance or importance of both. We want to analyze a particular case, the relationships of influence among fashion cities or capitals (The Global Fashion Capitals). We get a triennial ranking from The Global Language Monitor (GLM) which is an Austin, Texas-based company that collectively documents, analyzes and tracks trends (www.languagemonitor.com and en.wikipedia.org/wiki/Fashion_capital). From these raw data we would establish different relationships meaning competitiveness, gravitation, emulation, imitation, differentiation, leadership, servility, etc. We want to check if these relationships that determine the ranking can be useful to explain which fashion-city network works from a linkage perspective. We assume as work methodology that ranking and network relationships mutually define, or codetermine, each other. Any ranking is based on the best-worst performance of individuals or nodes on a set of values, traits, attributes, variables, etc. Furthermore consideration of dynamics or structure interactions (at a given time) of the system comprising the set of individuals would let us to consider a quite different set of relationships among those individuals who in one way or another are induced or have been the cause of this sort.

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In our paper we approach this relationship by using the conceptual and methodological apparatus of Social Network Analysis (SNA). According to SNA standpoint methodology, ties among individuals induced by a ranking may be: − Uni-directional or bidirectional (Oriented-Not oriented) − Valued or not valued Figure 1 shows an outline: Figure 1: Typology of Networks

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On the other hand if we consider the case valued and the strength associated with the links and how can depend (be caused / or cause) of the organization and ranking of the relative position between nodes (individuals), there would be a lot of possibilities that are summarized and shown in Table 1. Therefore, following that line, in one-directional ranked-based network, the ties between two nodes reach values from the best to the worst one (B-W) or in the reverse direction (W-B). Moreover, considering the strength of valued ties, the relevance of each node should play an important role that we still have not developed. The current state of our research does not allow consideration of all cases and we only have explored some of these possibilities in the case of Fashion Cities. We have considered the classification as given, and not lose sight of that once obtained some results, perhaps it might be interesting to compare them with empirical studies that present data from the fashion industry itself, its agents and professionals, through objective economic indicators and statements of professional opinion.

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Table 1. Different kinds of Ranking-based Networks ONE WAY NON-VALUED

Creasing

VALUED

Decreasing

Creasing/ Decreasing

B-W Leadership Prevailing position Imitated / Emulated by Inspiring Differentiatio n from Looking for own way An integrated set of relations

BIDIRECTIONAL W-B

Followship Subordinating

NotSignificant

Imitation / Emulation to Be inspired by

Watchfulness Competition Cooperation

Competition for the best position

Gravitation. (each other) Consideration

An integrated set of relations

An integrated set of not valued relations

2. THE SYSTEM OF THE TOP FASHION CAPITAL CITIES IN THE WORLD

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According to a survey developed by Global Language Monitor, there is a ranked number for every capital that could be consider important among the world’s most fashionable cities. Global Language Monitor, or GLM, is a media analytics company that documents, analyzes and tracks cultural trends in language the world over, with a particular emphasis upon Global English (http://www.languagemonitor.com). GLM's main services include Narrative Tracker which is based on global discourse, providing a real-time, accurate picture about any topic, at any point in time. Narrative Tracker analyzes the Internet, blogosphere, the top 75,000 print and electronic global media, as well as new social media sources as they emerge (en.wikipedia.org/wiki/Global_Language_Monitor). We can define fashion capital as a city which is a major center for the fashion industry and in which many activities including the production and retailing of fashion products, fashion important events (such as fashion weeks and awards) and fashion related trade fairs generate quite significant economic output. A fashion capital will generally show an active, vivid, strong and unique subculture, an environment capable of inspiring not only fashion professionals, but also the citizens of the whole city, turning its street style and street culture into essential characteristics to consider. A fashion capital will also usually have a broad mix of business, entertainment, culture, and leisure activities and be internationally recognized for having a unique and peculiar identity. There are currently widely regarded as being four principal fashion capitals in the world, known as “the big four”: London, Milan, New York City and Paris. An annual ranking of the leading fashion capitals is produced by Global Language Monitor. Berlin and Singapore broke in 2011 into the Top Ten, which is the core whole reference (www.languagemonitor.com/fashion/londonovertakes-new-york-as-top-global-fashion-capital). In 2010 world fashion capital moved from Europe continent to United States of America (www.languagemonitor.com/fashion/new-yorkregains-fashion-capital-crown-from-milan), and in 2011 London regained this top score for Europe again, being New York the one holding longer this position in recent years.

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Rank of scoring average “Ri” of these cities has been obtained from the fashion city annual ranking from 2009 to 2011 by subtracting 50 from the average position. Table 2 (in Appendix) shows the cities ordered by ranking average. It should be noted that some cities are labelled with “N” meaning its absence in the ranking for the considered year.

3. THE NETWORK OF FASHION CAPITAL CITIES Considering this ranking scores we initially thought that the elements of the adjacency matrix could be: Aii = 0 ∀i Aij =

Ri max(2, Ri − R j )

Ri in other case Rj

In this way, the ties between cities link two nodes with a strength that should be proportional to the relevance of both cities (the geometric mean) and, as well, the greater relative position between in and out nodes, the greater strength. However, this valuation favored too much the ties between far (but not relevant) cities. This inconvenient was avoided dividing by the factor max (2, |Ri-Rj|). Finally, the proposed network could be summarized with an adjacency matrix with: 229

Aii = 0 ∀i Aij =

Ri max(2, Ri − R j )

Ri in other case Rj

Figure 2 shows this final complete network, and an enlargement of the central area is displayed in Figure 3. Blue circles represents European cities, black ones North American cities, gray ones are AsianPacific cities, violet ones are Latin American cities, red ones are from Middle East, deep green is the color for African cities and the light green one represents Moscow. It is remarkable that the central position in display is in consonance with the relevance of each city. Central core is compound by the constellation of the great four London, Paris, Milan and New York; including as well, Los Angeles and Hong Kong, with some more additional cities surrounding the main ones.

4. PROCESSING ALL INFLUENCES AND CONNECTIONS AMONG EACH OTHER FASHION CAPITALS We have selected the resulting networks of consider only intensity ratios exceeding decreasing values. In this way we would be able to visualize how influences are configured according to a particular topology, in order to provide several relevant clues about how transmission of innovations, guidelines, criteria, styles, etc. works in the fashion world connecting all different centres of influence.

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Considering only the relations with values of strength greater than 23 network, we reach the maximum intensity network where we are able to find only the five major world capitals of fashion, although comprising only incomplete connectivity influences as from New York to Paris, Milan and London, and London to Hong Kong (this one perhaps because of post-colonial continuity as a potential explanation). This first step is shown in Figure 4 (in Appendix). When decreasing the influence intensity threshold up to 20 (Aij>20), we find that the “core constellation” of fashion capitals constitutes a highly connected network. Even if it is still an incomplete network, we get a very high density connected network. Only connections in both directions from New York to the cities of Los Angeles and Hong Kong fall below the threshold (Figure 5, in Appendix). Only by lowering the threshold to 19 (Aij> 19), is when the first links between cities of second level cluster may be shown (Figure 6). Specifically we can appreciate the influence of Sydney over Barcelona and of Barcelona on Tokyo (interestingly, the main cluster connectivity is not increased). As we reduce the threshold of significance, it seems that more cities or fashion capitals are incorporated into this second-level cluster network; but pretty slowly (well, with a threshold of 18, only Rome and Shanghai are influenced by Tokyo) and after that the process gets more speed (Figure 7). Upon reaching a minimum intensity of 13 (Aij>13) (Figure 8, in Appendix), the network shows two clearly differentiated clusters with high degree of connectivity, although not complete, in neither of both cases. If we consider a somewhat lower level of intensity as the threshold we get a third cluster of axial arrangement around the core emerging fashion city of Mexico. This third cluster contains only two-way interactions, Mexico-Mumbai and Mexico-Bali. In addition it is remarkable that the two main clusters interact for the first time through the influences of Los Angeles and Hong Kong in direction to Sydney (which recreates the Pacific Connection) (Figure 9, in Appendix). Related to the third cluster which appears at this level of strength, it is not reasonable to consider that it matches relations of an actual imitation, emulation, differentiation, cronyism, etc. and looks more like a sub-net spuriously generated by its own (by the relative position and variations thereof in these three years considered). Interestingly, despite the fact that we have simply assumed that the order of the ranking of cities should be consistent with the set of relations of influence really produced, until we get to this level, all the relationships that had been appearing were intuitively quite realistic. Going down to an intensity level of 7 (Aij> 7), we get a fourth cluster of interconnected cities with medium density which constitutes another group of fashion cities competing in a lower division or league. There we find some important cities economically relevant at a regional or even global level (as Chicago) but without so much tradition in the fashion industry that only recently have started to look for presence in the fashion world. Moreover, in this level of intensity the basic framework of the very most relevant fashion capitals (the mean core) is already built thanks to the emergence of new influences between primary and secondary constellation; as influences between Paris and London to Sydney, or Los Angeles and Hong Kong to Barcelona (Figure 10, in Appendix). Upon reaching the threshold intensity 5, there is not any isolated cluster found any more. The global network of fashion capitals is already constituted as such. However there are some isolated nodes, not integrated in any network, that are identified as the cities of Atlanta, Caracas, Medellin, Frankfurt, Krakow, Antwerp and Abu Dhabi (Figure 11, in Appendix).

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Now, we have got a network not only consolidated or quite compact, but also because of the density of the relationships, that has been increased considerably. By the other hand, remains a higher density of connections within the initial clusters, more than among the different clusters. If we reach a threshold of 3, the entire network has been established; Caracas and Krakow are the only cities which remain as isolated nodes. The primary and more important two clusters have already formed a compact and high density core of relationships (Figure 12, in Appendix). The hierarchy gets dissolved almost reaching this level of quite reduced level of influence. It is important to remark that a ranking is a hierarchy. And a hierarchy is an absolutely linear network, nothing heavy or dense. If the hierarchy of fashion cities creates dense relationships is because it is something dynamic and competitive. Finally, considering the intensity threshold of 1 (Aij>1), we have already completed the network of relationships with relevant or important influence that we had initially considered. We reach the whole network in which Caracas is also incorporated. The network has clearly two areas of maximum density relationships (the two main clusters) which are also highly related between them (Figure 13, in Appendix). As we will see, this gradual process of clustering or densification of relationships is consistent with the key network statistics analysis.

5. GEOGRAPHICAL ANALYSIS OF FASHION-CITIES NETWORK

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The relations among the different cities in the network display a typical performance of interaction in a globalized world. However, strong polarizations towards privileged regional areas could be verified in the graphic above (Figure 14, in Appendix) which shows the mean intensity of all ties between cities of each geographical area to each other. Influences, from and to, North America and West Europe are clearly greater than the rest. And a lesser relevance of African cities is also evident. Relations among cities of different geographical areas are reproducing a globalized world with very distinct polarizations which can be identified in the average values of the intensities of these influences: If we only consider the ties with relevant strength, the geographical analysis would be more illustrative. In fact, considering the number of main interactions, the number of interactions with strength greater than one, as it is shown in the following figure, some conclusions could be obtained: − The maximum number of main interactions is between cities groups from West Europe and Asia-Pacific (21 and 15, in one and the other direction). − These two regions, jointly with North America, constitute a triad that becomes the fundamental core of the fashion-cities main relations with a number of 79 (21+15+11+15+12+5) relations, while the other areas hold many fewer relations and Africa has none. The following graph (Figure 15, in Appendix) shows the number of relevant intensity influences (greater than 1) among the various geographical areas.

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6. STATISTICAL ANALYSIS OF THE MAIN NETWORK NODES In this section we carry out a global analysis of fundamental features for nodes (fashion capital cities) in the network considering ties of strength superior than one and extending analysis to the whole network. For each raw identifying a city, Table 3 (in Appendix) displays its regional attributes: area, country, cultural tradition, as well as the principal indicators of the fundamental network features as neighbourhood, closeness and between-ness. “Degree” of a node is the number of links that involve this node, so it indicates the cardinality of neighbourhood nodes. Obviously the greater degree the more relevant the node is. Maximum value of degree is “n-1”, being “n” total number nodes being minimum value as 0 (when node is absolutely isolate). Initially being n=53; by excluding the impact relationships below 1, the number of “important nodes” becomes n= 47 and the maximum 46. Between-ness of a node is the number of paths among different nodes that pass through that node. This indicator informs us about how important the node is. It means intermediation as a measure of how easily a node can connect with other nodes. Finally, “closeness” is a reciprocal measure of the (harmonic) mean distance between the considering node and all the rest. Being l (i,j) the distance between the nodes i and j, the number of links we can found across the shortest path that ties i with j, the (harmonic) closeness of the node i is:

δi = 232

n −1 ∑ i ≠ j l (i, j )

At the final results table, we see how the degree is descending from the maximum value (46 for cities belonging to the main central cluster in orange colour), as has been described in former epigraph. Subsequently, a second best value appears for Barcelona and Sydney with a degree of 43, constituting a transition from the former group to the second cluster (pink colour), with a degree of 42, with an epigone group integrated by Dubai, Moscow and Rio de Janeiro. From here it is shown a smoothing descendent degree for several cities from Buenos Aires to Frankfurt. Finally, the last cities have no important relations (strength ≥ 1) and so their degree has value 0. As expected, the three centrality indicators (degree, between-ness and closeness) display similar performance for the different cities showing a hierarchical clustering of decreasing centrality or relevance. Colour layout could help to perceive it. 6.1 The degree distribution Another usual element in the statistical analysis of networks is the degree distribution study, the analysis of the frequency distribution of the degree values and its comparison with standard significant distributions. Typically interest is focused to the possibility of fitting a Pareto or Poisson distribution. Poisson distribution is the performance that should show a merely random network. On the other extreme, a potential Pareto distribution is the typical scale-free distribution with an accelerated decreasing frequency (in potential way) with the increasing degree. Figure 16 shows the degree distribution of the cities degree. Comparing with the Poisson and standard Pareto distributions graphics (Figure 17 and Figure 18 in Appendix) we can clearly conclude that the distribution is so far from one as from the other, so its performance is not stochastic but is not scaling-free.

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Kolmogorov-Smirnov tests results (Table 4, in Appendix) show an evident misfit to Poisson or Normal distributions; and misfit to Pareto distribution is obvious since the distributions graph. Differing from the scaling-free distribution indicates that this structure lacks “strategic points” and also indicates that is remarkably distributed spite of having been generated by an ordinal relation. In fact, it indicates now a high degree of intercommunication.

REFERENCES Andersson, M., Karlsson, C. (2004). Regional innovation systems in small & medium- sized regions. Paper No. 10, CESIS Working Paper, KTH Royal Institute of Technology. Barabási, A. L., Bonabeau E. (2003). Redes sin escala. Investigación y Ciencia, Julio, p. 58–67. Barabási, A.L. & Albert, R. (1999). Emergence of scaling in random networks, Science, 286, 509–512. Jackson, M.O. (2008). Social and Economic Networks. Princeton University Press. Newman, M. E. J. (2005). Power laws, Pareto distributions and Zipf's law. Contemporary Physics, 46, 323–351. Retrieved: 01/08/2012 from: http://arxiv.org/abs/cond-mat/0412004v3 Serrano, M. A., Boguñá, M., Vespignani, A. (2007). Patterns of dominant flows in the world trade web. Journal of Economic Interaction and Coordination, 2, 111–124.

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APPENDIX Table 2: Ranking of fashion capitals RANKING FASHION CAPITALS Ranking 2011

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New York London Paris Milan Los Angeles Hong Kong Sydney Barcelona Tokyo Shanghai Rome Las Vegas Singapore Madrid Monaco Sao Paulo Berlin Miami Melbourne Amsterdam Dubai Moscow Rio de Janeiro Buenos Aires Bali Mexico City Mumbai Florence Vienna Copenhagen Johannesburg Santiago Stockholm Prague Warsaw Cape Town Toronto

2 1 3 4 5 6 11 7 9 14 13 16 8 12 15 25 10 26 17 19 27 18 23 20 21 22 24 31 35 29 41 30 28 48 33 46 34

Ranking Ranking Ranking average score Ri 2010 2009 1 2 48,33 3 5 47 4 3 46,67 6 1 46,33 5 4 45,33 2 7 45 7 9 41 9 14 40 14 12 38,33 12 14 36,67 22 6 36,33 16 10 36 15 20 35,67 10 21 35,67 N N 35 13 8 34,67 18 19 34,33 8 13 34,33 11 25 32,33 17 N 32 21 11 30,33 20 22 30 19 20 29,33 24 24 27,33 32 N 23,5 29 31 22,67 28 30 22,67 N N 19 27 N 19 34 N 18,5 25 N 17 31 39 16,67 33 40 16,33 26 29 15,67 36 N 15,5 23 N 15,5 38 N 14

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Bangkok Chicago New Delhi San Francisco Dallas Austin Abu Dhabi Antwerp Atlanta Frankfurt Medellin Seoul Krakow Caracas Montreal

32 36 39 38 37 40 42 44 45 43 N N 47 50 49

35 37 30 N 40 N N 41 40 43 44 45 39 42 N

42 N 43 N N N N N N N N N 50 N N

13,67 13,5 12,67 12 11,5 10 8 7,5 7,5 7 6 5 4,67 4 1

Table 3: Regional attributes and fundamental network features of fashion cities Culture tradition New_York N_America Ang-Saxon London European Union Ang-Saxon Milan European Union Italian Paris European Union French Hong_Kong Asia-Pacific Asian Los_Angeles N_America AngSaxon Barcelona European Union Hispanic Sydney Asia-Pacific AngSaxon Amsterdam European Union Eur Berlin European Union Eur Las_Vegas N_America AngSaxon Madrid European Union Hispanic Melbourne Asia-Pacific AngSaxon Miami N_America AngSaxon Monaco European Union French Rome European Union Italian Sao_Paulo Latin America Hispan Shanghai Asia-Pacific Asian Singapur Asia-Pacific Asian Tokyo Asia-Pacific Asian Dubai Middle East Muslim Moscow East Europe Eur Rio_de_Janeiro Latin America Hispan Buenos_Aires Latin America Hispan Bali Asia-Pacific Asian Mexico City Latin America Hispanic City

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Regional Area

Country Degree Betweenness Closeness USA UK Italy France China USA Spain Australia Holland Germany USA Spain Australia USA Monaco Italy Brasil China Singapur Japan Dubai Russia Brasil Argentina Indonesia Mexico

46 46 46 46 46 46 43 43 42 42 42 42 42 42 42 42 42 42 42 42 41 41 41 40 38 36

29,415 29,415 29,415 29,415 29,415 29,415 9,915 9,915 5,54 5,54 5,54 5,54 5,54 5,54 5,54 5,54 5,54 5,54 5,54 5,54 4,44 4,44 4,44 3,657 2,365 1,365

358 358 358 358 358 358 361 361 362 362 362 362 362 362 362 362 362 362 362 362 363 363 363 364 366 368

Harmonic Closeness 46 46 46 46 46 46 44,5 44,5 44 44 44 44 44 44 44 44 44 44 44 44 43,5 43,5 43,5 43 42 41

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Mumbai Florence Vienna Copenhaguen Johannesburg Santiago Cape_Town Stockholm Prague Toronto Warsaw Bangkok Chicago New_Delhi San_Francisco Dallas Austin Abu_Dhabi Antwerpen Atlanta Frankfurt Caracas Krakow Medellin Montreal Seoul

Asia-Pacific European Union European Union European Union Africa Latin America Africa European Union European Union N_America European Union Asia-Pacific N_America Asia-Pacific N_America N_America N_America Middle East European Union N_America European Union Latin America European Union Latin America N_America Asia-Pacific

Asian Italian Eur Eur AngSax Hispan AngSax Eur Eur AngSax Eur Asian AngSax Asian AngSax AngSax AngSax Muslim Eur AngSaxon Eur Hispanic Eur Hispanic French Asian

India Italy Austria Denmark SAfrica Chile SAfrica Sweden Czech Rep Canada Poland Tailhand USA India USA USA USA Abu Dhabi Holland USA Germany Venezuela Poland Colombia Canada SCorea

36 31 31 30 30 29 27 27 27 27 27 25 25 24 24 23 20 8 6 6 6 0 0 0 0 0

1,365 0,069 0,069 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

368 373 373 374 374 375 377 377 377 377 377 379 379 380 380 381 384 396 398 398 398 2704 2704 2704 2704 2704

41 38,5 38,5 38 38 37,5 36,5 36,5 36,5 36,5 36,5 35,5 35,5 35 35 34,5 33 27 26 26 26 0 0 0 0 0

Table 4: Kolmogorov Smirnov’s goodness-of-fit tests Kolmogorov-Smirnov test for DEGREE DISTRIBUTION

FIT TO NORMAL DISTRIBUTION N Normal Parameters

EXTREME DIFERENCES

mean Standard deviation

degree 52 30,6154 14,82731

Absolute

,200

Positive Negative Kolmogorov-Smirnov Z Asymptotic significance. (bilateral)

,150 -,200 1,446 ,031

FIT TO POISSON DISTRIBUTION

degree

N

52

Poisson parameters

mean

30,6154

EXTREME DIFERENCES

Absolute

,403

Positive Negative Kolmogorov-Smirnov Z

,173 -,403 2,904

Asymptotic significance. (bilateral)

,000

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Figure 2. The complete network

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Figure 3. Enlargement of central area of the network

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Figure 4. Five major world capitals of fashion, maximum intensity network

Figure 5. Influence intensity threshold up to 20 cities

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Figure 6. Lowering the threshold to 19 (Aij> 19)

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Figure 7. With a threshold of 18 (Aij> 18)

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Figure 8. With a threshold of 13 (Aij> 13)

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Figure 9. Third cluster appears while the first two ones interact through the Pacific Connection

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Figure 10. Level of 7 brings a fourth cluster and some relevant connections

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Figure 11. The global network of fashion capitals is already constituted

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Figure 12. The entire network has been established with a threshold of 3

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Figure 13. The global network with two main clusters defined

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Figure 14. Mean intensity links between geographical areas

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Figure 15. Number of influences of maximum intensity between geographical areas

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Figure16. Degree distribution and descriptive

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Figure 17: Poisson distribution

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Figure 18. Pareto distribution

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Controlling hazards and safety in complex systems: a multi-layered part-whole approach to system safetyi Luca Pazzi Assistant Professor of Information Elaboration Systems. Department of Engineering "Enzo Ferrari". University of Modena and Reggio Emilia, Modena, Italy. e-mail: [email protected] Received September 30, 2012 / revised November 14 / accepted November 15 / published online November 16, 2012. DOI: 10.7350/BSR.A17.2012 – URL: http://dx.medra.org/10.7350/BSR.A17.2012

ABSTRACT

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The behavior of complex dependable systems poses severe safety issues due to hazards which may result from incorrect and unpredictable behavior. In order to prevent such hazards, system behavior has to be specified and checked incrementally, in order to defeat the overall system’s complexity. Modularity in system design is however not trivial due to the intrinsic monolithic nature of the control loop, typical of such systems. An additional problem is given by the fact that the current modeling paradigm tends at introducing additional interactive complexity due to the direct communication and synchronization mechanism among decomposed modules. It can be shown, however, that modular decomposition is feasible by revising the current communication and interaction paradigm. Physical interactions in physical systems denote in fact less evident conceptual structures, which host the overall interaction and synchronization knowledge among the component parts. By introducing additional system entities with the aim of hosting such knowledge in a localized and compact manner, we obtain a part-whole hierarchy of systems, called holarchy. Such systems are, at the same time, both parts and wholes within a holarchy, thus giving a formal characterization to Koestler’s holons. Keywords: System-safety, Holonic frameworks, State-based modeling, Statecharts, PWStatecharts.

1. INTRODUCTION Three different kinds of systemic failures, which in turn may become system accidents, are possible: “faults”, “failures” and “errors”. A fault is a primary error within a system component. An error is a deviation from the expected behavior of the system, which may result in a global system failure. Since the joint behavior of components make the system behavior, it is evident that any progress in system-based safety calls for a deep understanding of the way systems, whether natural or

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artificial, are made up of components. Typically, system components interact in order to achieve a global task. It is therefore plausible to hypothesize that system structure play a crucial role in understanding how components’ faults propagate emergent system behavior (Smith 1989) and may therefore result in a global system failure (Hammer 1980). The paper addresses such hypothesis and shows that well known fault management techniques may be framed into a hierarchical context. Such hierarchical arrangement, allows to bring new light into both safety related methodologies and, at the same time, into the very nature of controlled systems. Holons, introduced by Arthur Koestler in his book “The Ghost in the Machine” (Koestler, 1976) are entities which are, at the same time, both parts and wholes. Accordingly, complex phenomena and entities can be decomposed into part/whole hierarchies, named holarchies, with holon nodes at each level. The main interest in the holonic approach lies in the fact that it reconciles both the holistic and the reductionist view in systems analysis. Aim of this paper is to show their usefulness in partitioning and reducing the complexity of dependable behavior in safety-critical systems employed in energy production systems. By the reductionist view, which dates back to Descartes, a complex system can be analysed by “reduction” to its fundamental parts. Analytic reduction is the main weapon system scientists possess in order to control system complexity by dividing it into less complex distinct parts. Three important assumptions underlie the reductionist process, in order for it to be effective both in the analysis and synthesis phases (Leveson, 2011):

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1. The division into parts will not distort the phenomenon being observed; 2. Components are the same when examined apart as when playing their part in the whole; 3. The interactions among the components are separate from the behavior of the components themselves. Although the assumptions above are reasonable for most observable systems, they still pose at least two open problems when such systems have to be modelled within a computer-based context. The first problem consists in finding the exact system boundary, in order to have self-contained systems, which behave in the same way when taken apart and when assembled into more complex systems. The second problem deals instead with providing assembled system models by suitable modular constructs, in order to host separately the component subsystems and the interactions among them. The third assumption of the reductionist approach states indeed that mutual interactions amongst systems do not belong to the interacting systems: this is a reasonable requirement, otherwise the reduction into parts will necessarily produce subsystems which are not the same when taken alone or within a larger whole, thus contravening the first requirement. The subtle point in solving both problems is essentially that, – as pointed out by the third reductionist requirement – “interactions” have to be modelled separately from the behavior of the component themselves. In other words, the joint behavior which pertains the aggregation of separate systems has to be modelled separately by a specific behavioral construct. This in turn requires that systems have to be free from the behavioral information pertaining their aggregation in a specific whole. In other words, the only behavioral information modelled within a system has to be the one pertaining such a system. In order to achieve such a result, structural guidelines easily follow. On one hand modelled systems have to expose an interface to outer composition contexts which allows external behavioral constructs to act on them; on the other hand, system models have to host not only component systems, but also a specific construct which specifies the behavioral semantics pertaining their composition.

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Figure 1. Aggregation of 3 objects modelling

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In figure 1, the aggregation of three objects can be modelled implicitly by three mutually referring objects (a). Behavior is depicted within objects by geometric shapes. Triangles represent the associative behavior spread through the objects. The same aggregation can be modelled also by a holarchy of four holons (b), where holon W gathers the global associative (triangle-shaped) behaviour. Current modelling paradigms fail in achieving such a separation. In the rest of the paper it is observed indeed that either: (a) the behavioural information pertaining aggregation is spread into the aggregated parts or (b) it can be hosted within the system having the aggregated systems as parts. In the latter case the whole is said to be modelled explicitly, which in turns means that both the whole and the constituent parts are easy to understand, reuse, extend and so on. Figure 1 compares the two approaches. 1.1 Implicit versus explicit system modelling A physical system is assembled from a set of physical components, which exercise physical control one upon another. For example, consider a simple heating appliance pilot light, which is a small flame used to start a furnace, which is controlled by a thermocouple. The ignition process starts by a button being pressed, which closes an electrical circuit an in turn charges a condenser while keeping, at the same time, an electrically-operated gas valve open. As soon as the condenser is charged a spark is emitted and the pilot flame is possibly lit. In case the flame is not lit, the process may be repeated different times by having the condenser recharge. When the pilot light is lit, the thermocouple produces a voltage, which keeps open the main supply valve that feeds gas to the heating appliance. So long as the pilot flame remains lit, the thermocouple remains hot, and the pilot gas valve is held open. In case the pilot light goes out, temperature in the thermocouple falls, causing the voltage to drop and the valve to close. A set of mutually related devices may, globally, exhibit a system behavior by having direct physical, typically mechanical, interactions. The pilot flame example depicts physical entities, which interact through physical processes (mechanical, electrical, thermo-electrical). Such processes cause state changes in related components. Chains of component state changes are at the basis of the global system behavior. However, a different view is possible, since each chain

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of state transitions at the component level may be seen as a single state transition at the system level. In the same way, the state changes in the system before and after each casual chain of state changes can be seen as a single state change. With the advent of electromagnetic devices, control has been exercised by voltage in electrical circuits, as in the case of the electromechanical valve of the pilot light example. The subsequent advent of digital controllers and field buses allowed actuating physical state changes by digital signals. Conversely, specific devices called sensors, which generate digital signals accordingly, can sense state changes in the environment. The consequence of technological advance is therefore that a system of interacting components may be implemented by a set of devices that act one upon the by directly exchanging signals embodying both messages and state information. Direct communication among system components is however not the only way to implement a system behavior. In [] it is shown in fact that the same system behavior may be modelled either as above, by direct communication among system components, or through an explicit additional entity representing the system being modelled, which has the system components as parts and hosts the system behavior as a whole. The two approaches have been named implicit versus explicit system modelling. It is possible to view systems interactions as being the primary structure of a system. By the former view, the system is simply a network of mutual interactions among the subsystems making it. Such a view emphasizes interactive complexity and tight coupling of system control modules, each residing within a single component of the system. Such an approach has been named implicit modelling in system design. Implicit modelling brings evident problems in software engineering terms. Each component typically hosts a single software controller. In order to achieve a useful system behavior the different controllers have to synchronize by mutually exchanging control signals, which encode event and state information. In Pazzi (1999) it is shown that direct communication, albeit inspired by natural systems, is not the only way to implement a digitally controlled system. Although it is presumable that a system modelled by direct interactions can be equivalently modelled by an explicit structure hosting its behavior as well as its component parts, the explicit approach has notable advantages in terms of quality factors, which defeat its intrinsic complexity. Cognitive psychology established that the perception of complex structured entities as a single entity firmly depends on the observer’s point of view and affect the overall performance in a problem solving context (Norman, 1993). Similarly Woods (1995) claims that there are no neutral representations, since different representations either increase or decrease the overall problem complexity. Interactive complexity represents a threat to safety since the level of interactions reaches the point where failures cannot be planned, understood, anticipated, and guarded against (Leveson, 2011). Such systems can be expected to have many such unanticipated interactions, each potentially leading to a failure, and eventually making them vulnerable to accidents (Perrow, 1999). On the other hand, systems which make use of little or no knowledge of the behavior of other separate components have a minor impact on each other in case of failure. If what happens in one part has little impact on another part, the system is said to be “loosely coupled”, while it is said “tightly coupled” in the opposite case. This paves the way for a modular concept of safety. 1.2 Towards a modular concept of safety Ensuring safety means “reducing accidents throughout the life cycle of a system” (Storey, 1996; Leveson, 2011), which in turn means preventing, eliminating and controlling hazards (Becker et

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al., 2006), i.e., situations that have the potential to pose threat to life, health, property, or environment. Safety deals with the limitation of hazards and the management of their effects, and depends on system failures, that are failures due to the mutual arrangement and interactions of the components of the system. Such components may, possibly but not necessarily, have failed on their turn. It is customary in the literature to distinguish between failures of the whole system and failure due to single components, called faults. Faults are underlying defects, imperfections, or flaws that have the potential to cause system failures. A fault is something within a system component, which may cause the system not to meet one of the functions for which it has been designed, resulting in a deviation from the expected system behavior and possibly in a system failure. The failure of a system can be seen as a fault in the context of the larger system of which the system is component. Safety should not be confused with “reliability”. Reliability is the property of a system to perform a specific function over a definite period of time, such function being part of the specification of the systemic correct behaviour (for example: “the lamp must turn on once the switch closes a circuit”). Apparently, the more reliable a component is, the more reliable the system having that component as part should be. It can be observed, instead, that even a system assembled from reliable (working) components may undergo a systemic failure, due to unforeseen interactions among its components. A safe device may, therefore, be harmful once it interacts incorrectly with other reliable devices. Two switches arranged in series within a circuit give a trivial example of systemic failure with no fault components. Pupils learn that, in the series case, sometimes one of the two switches does not affect the light bulb, even if the two switches and the other components of the circuit work correctly. A more complex example is given in (Pazzi & Pradelli 2008) where an assemblage of medical devices, consisting of a blood pump, a valve and a patient’s pressure monitor, fails under specific circumstances, even if its components work perfectly. In other words, a system is safe if, recursively: 1. It is assembled from safe components; 2. Its components interact in a safe manner. Safety is both a hierarchical and a behavioral property of systems. Safety is a hierarchical property since safety of subsystems impacts on the safety of super systems, along chains of partof hierarchical arrangements. Safety is, additionally, a behavioral notion since, as observed, not only a system may be unsafe due to the interaction of different safe/reliable subsystems, but, on the opposite, unsafe/unreliable subsystems may be arranged within a system in such a way to be safe, typically by adding redundant components. Understanding dynamical relationships among systems arranged in part-of hierarchies is, therefore, a basic step in understanding how safety management policies can be effectively implemented. Moreover, as first observed in (Pazzi & Pradelli, 2010) different safety management policies (Carter et al., 1987) fit naturally at different hierarchical levels. 1.3 Structure of the paper Aim of this paper is to investigate whether a sound notion of system modularity drastically reduces the complexity of safety management policies. Section 2 discusses and compares two general principles of entity composition, interaction and synchronization. Such a distinction calls for the modelling of explicit entities in place of the

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observed mutual behavioral relationships. Part- Whole Statecharts can be shown to implement the concept of Holon, thus satisfying such a requirement. Such formalism is used, through the case study in dependable energy production systems of Section 3, in order to allow a clean and effective modelling of hierarchical fault management strategies at different hierarchical level.

2. FROM SYSTEMS TO HOLONS

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Arthur Koestler coined the term holon for a part-whole construct that can be seen, at the same time, as a component of one or more higher level systems or as whole which has other lower level holons as parts. Holons have been used as an effective paradigm for modelling flexible (Dominici, 2012; Dominici & Palumbo, 2012) and multi-agent production systems (Dominici et al. 2010). In this Section it is shown that holonic modularization can be introduced effectively in statebased control paradigm, by revising the communication mechanism amongst interacting entities along two main directions. On one hand it is suggested to forbid any mutual communication amongst peer modules. Such a requirement springs from basic software engineering considerations, requiring modules to be self-contained and represents the fundamental notion over which the explicit approach in the modelling of wholes is based (Pazzi, 1999). On the other hand, the previous requirement implies to introduce additional “bridging” systems in order to allow communication amongst basic systems, which are forbidden to communicate directly. Such systems become the right place in order to host the semantics of interaction. In other words, the need to express the semantics of interaction brings to new entities, often not readily apparent. Section 2.1 describes such a modularization process in state-based control. Such entities are nothing but holons playing the role of wholes, linking the original systems, which become holons playing the role of parts. For example in Figure 3-(a) different subsystems interact by exchanging command events: such an interaction models the global behavior of the system, namely the alternate timed behavior of two counter-rotating engines. As shown in Section 2.2, such a behavior can itself be described by a state machine having two states and two state transitions linking them. In general, the emergent behavior involving different interacting systems can be hosted in holons playing the role of wholes, while the original systems become holons playing the role of parts. Finally, parts have to be logically independent from emergent wholes. This requires holons to implement interfaces in order to be controllable when playing the role of parts. On the other hand, parts do not have to host details concerning the whole, in order to allow full compositionability in different, unforeseeable, contexts. This introduces an asymmetry in the vertical, whole to parts, composition process, since parts do not know the whole, but the whole must be able to know the parts in order to control them. 2.1 Modularization of the control loop State-based control is achieved through a closed loop, such as the one depicted in Figure 2-(a), where a plant, that is a physical system, is sensed and acted through sensor and actuator devices, through the exchange of events and the knowledge of the current state of each device (Kopetz, 2011). Each device is associated to a state machine, acting as an interface to the underlying hardware. Such interfaces show the current state of the device to which they are associated,

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together with the available actions that can be acted on it and the resulting state of such actions, if successful. Figure 2: Modularization of closed loop control

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In figure 2: modularization of closed loop control (a) requires to keep into account not only the existing subsystems in the physical plant (b), but also to introduce specific modules in order to host mutual interactions among them, such as cW in (c). In other words the interface of a device is a state diagram, and the device behavior can be abstracted as the one belonging to a state machine. Any of such state diagrams should be also able to signal to the controller not only its current state, but also to signal other events that may be related to the behavior. For example, a “smart” lamp should be able to signal not only its faults, but also maintenance or substitution requests. The state machine hosted within the state-based controller changes its state according to the signal emitted by the system through the sensors; vice versa the controller issues signals towards the system, which changes its physical state through actuators. Control is therefore achieved through state machine interactions: the controller state machine sends command events towards interface state machines, which, on their turn, send feedback events to the controller. It is possible to view the current state of the sensors and the actuators as representing the global state of the plant: by such a view the controller takes control decisions depending on the current global state of the plant. The problem with the approach of Figure 2-(a) is that it is monolithic, that is, it is not clear how to divide the controller into modules in order to partition its complexity. The customary approach towards modularization consists in distinguishing subsystems in the physical plant and having a corresponding control module in the state-based controller. This seems reasonable, since most systems have parts that are naturally distinguishable, for the reason

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that either they are assembled from standalone devices or they perform some function. It seems therefore realistic to structure system control around physical or functional parts. The problem consists in the fact that subsystems are not isolated, that is they exhibit necessarily, as part of the system, some sort of coordinated behavior. Consider for example figure 2-(b), where two systems A and B interact at the physical level (consider for example a cogwheel A acting on a cogwheel B). The two corresponding state-based interfaces associated to the control of A and B have therefore to take into account not only the control of the corresponding physical entities, but have also to synchronize their internal behavior in order to mimic the physical interaction among A and B. As shown in figure 2-(b), the two controllers have therefore to exchange synchronization messages mAB and mBA. If, on one hand, either a mutual interaction is observed among two systems, A and B, having two different state machines or such an interaction has to be enforced among them, having two corresponding modules on the control side of the loop, and enforcing control through them, may incur to the problems discussed above. The problems observed may be solved by adopting an explicit modelling approach (Pazzi, 1999). As shown in figure 2-(c), we forbid the two controllers cA and cB to exchange synchronization messages (a solid line is placed between them, in place of the dashed one). By providing instead each controller state machine with a suitable interface, we decouple controller modules one from another by adding an additional controller module cW. Such a module is again a state machine, which provides control to the subsystems A and B, and can be controlled on its turn through its own interface. Since controller cW models the physical interactions amongst A and B, it seems evident that an additional systems W, embodying the former interacting two systems A and B, has some level of objective existence, although it may not be readily visible. Figure 3. The modelling of the behavior of two alternate counterotating engines by traditional Statecharts (a) and by Part-Whole Statecharts (b).

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2.2 Holons implemented by Part-Whole Statecharts

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Part-Whole Statecharts (Pazzi, 1997; Pazzi, 2000) (shortened either as PW Statecharts or PWS) were created with a radical commitment towards state-based modularity. The idea behind their introduction was to have a formalism which encapsulates a compound behavior, forcing the modeller to expose an interface representing the composed behavior as a whole. Such a behavior is annotated by state propositions which are verified directly in the specification phase (Pazzi, 2008). In the paper a brief account of PWS syntax and semantics is given through the running example in the next Section. Part-Whole Statecharts require making explicit the interaction among the behavior of parallel state based processes, i.e. to introduce an explicit module containing the state diagram depicting such a behavior. A Part-Whole Statechart diagram consists of two main sections, as shown in figure 3-(b), the upper one hosting a set of component state machines, the lower one a single state machine representing the global system behavior, named “whole” (referred to in the rest of the paper as either the whole or the whole section of the PWS). By such a “connecting behavior”, the description of the behavior of the system as a whole is made explicit. For example in Figure 3-(a) different subsystems interact by exchanging command events: such an interaction models the global behavior of the system, namely the alternate timed behavior of two rotating engines. Timing specifications are modelled through timer state machines, such as t1 and t2 in the picture, which are initially set to a time-in (Tin) state and move autonomously to a time-out (Tout) a state once a fixed and definite time interval has expired. The same behavior can be modelled explicitly, as observed, by the state machine in the lower part of the Part-Whole state diagram of Figure 3-(b). It consists of two states, TLeft and TRight, each one describing a global state of the system through state propositions C1 and C2 associated, respectively, to states TLeft and TRight: C1 = t1.TIn ∧ el.Stop ∧ er.Run

(1)

C2 = t2.TIn ∧ er.Stop ∧ el.Run

(2)

Since the system is at any time either in state TLeft or TRight, but not in both, joint logical and timing properties of the components can be easily inferred, for example “the two engines are not active at the same time” and “each engine is active only when its associated timer is in state time in”. It is also possible to verify that state transitions linking the two states maintain the validity of the associated state propositions, as described in (Pazzi, 2012). The state machine within a PWS plays the double role of being both an interface to the complex system which has the current system as part and to implement a complex synchronized behavior in the component machines. The two roles played by the state behavior thus define the so called “Janus”, i.e. double face, aspect of the holonic paradigm.

3. THE STEAM BOILER SPECIFICATION PROBLEM The steam boiler specification problem has been used for years as a test for comparing specification formalisms. It deals with the most safety-critical part of a nuclear energy production plant, the steam boiler which produces steam subtracting heat from the nuclear reaction. The steam boiler must be continuously supplied with water through some pumps: the quantity of water present when the steam-boiler is working has to be neither too low nor too

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high; otherwise the steam-boiler or the turbine operated by the steam flow might be seriously affected. Although the problem seems relatively simple, safety constraints raise its complexity. A strong notion of modularized control is therefore needed. We show that the holonic framework, through the PWS approach, is well suited in structuring control specifications in such a way that safety policies may be enforced at different hierarchical levels, each corresponding to some physical or logical entity in the domain. 3.1 Overview

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The system must maintain the water level in the steam boiler within a given interval. Failing to do so may result in the overheating of the nuclear plant. The basic control task is therefore given by feeding water into the boiler in such a way to maintain the proper level. In order to do that, pumps have to be switched on and off. When a pump fails starting, an alternate, backup, pump is used. A pump fails when the water does not circulate within five seconds after the start of the engine. the water level is read through specific sensors. Since one or more may fail, redundant sensors are employed, and the correct value is given by comparing the different instruments read. Operating the steam boiler plant means therefore having to take into account not only control strategies, but also fault management policies. It is clear that a single, monolithic, control program has to face unusual complexity issues, given by the concurrent modelling of both aspects, including the different operational modes which may result from the different failures that may occur. Adopting the right level of modularization helps therefore in partitioning the different tasks, operating modes and failure management policies. Figure 4 shows the mutual relationships among the different levels of complexity at which the different devices may be grouped; each level correspond to a specific holonic module and may be used as part of the more complex module linked to it by the arrow, labelled by the fault management behavior provided by each level. For example, the topmost one (labelled by A) gathers basic components. Such components fail silently and are used both in assembling simple devices (C) and redundant voting sensors (B). Redundant voting sensors and pools of redundant devices (D) exhibit finally a fail operational behavior towards the main control module (E). 3.2 Fail-Silent Sub-devices This group gathers simple mechanical or hardware components, whose structure is not further specified and perform their function when they are turned on or off. Such components undergo random faults, which are faults which are not further analyzable and whose happening is predictable only in statistical terms. It includes synchronous subsystems assembled from hardware components, which can be seen as single units on their own. The elements of this group exhibit a behaviour that can be assumed to be fail silent, meaning that they either work or, in case of failure, stop responding for an unspecified period of time. Any other causal or malicious behaviour which can be subsumed under the general category of byzantine failures, may also be reduced to fail silent behaviours by well know techniques, such as the Voltan approach.

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Figure 4. Hierarchical arrangement and mutual dependence of control levels and corresponding failure modes.

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3.3 Fail-Explicit Devices By the term device we mean an object exposing an internal structure constituted by simpler parts which exhibit a fail silent behavior. By comparing the behavior of different components belonging to the previous level, it is possible to infer explicitly a fault of the assembly. In the steam boiler specification, pumps play a critical role. Each pump may be turned on or off. In moving from off to on the pump requires five seconds in order to balance the pressure of the steam boiler to which it injects fresh water: after this time the water should circulate from the pump to the steam boiler. According to such a real-life specification, a more general pattern of behavior may be inferred, constituted by a timer, by an actuator and by a sensor. In the pump, for example, the actuator is the engine of the pump and the sensor is the water-flow sensor. A pump capable of detecting its own failure is therefore, at the behavioral level, the assemblage of a timer, an engine and a flow sensor, as shown in the upper part of the PWS in Figure 5. States Off and On are specified, respectively, by the state propositions C1 = e.Off ∧ fs.NF and C2 = e.On ∧ fs.Flow, that is the behavior linking the two states is considered successful if engine e starts (i.e. it moves from the Off to the On state) and flow detector fs moves from the NF (no flow detected) to the Flow state. The overall state transition linking the two states employs a given amount of time in order to possibly achieve the final result; the system has therefore to wait for such a definite time interval. After such a time interval has expired without reaching

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condition C2 the pump reaches an explicit failure state. The PWS diagram in Figure 5 depicts a fragment of the whole joint behavior, namely the starting phase. Starting from state Off, transition t, once triggered by event pumpOn, moves the system to a special waiting state W after having sent a start event to engine e and having started the timer t. The timer is designed for resting in the time-in state for a fixed amount of time, namely the five seconds required by the specification. The system rests in the W state until exactly one the two conditions occur: either state proposition C2 becomes true or timer t moves to the timeout state Tout. In the former case the system starts successfully within the specified timing requirements and the system takes state transition t′ towards the success state On. In the latter case an explicit failure is detected and the system moves to the explicit failure state Fail through transition t′′,. Such a state may be reached, at any time, through transition t′′′, when the flow sensor denotes a lack of pressure moving to state NF. Figure 5. The assembly of two low-level fail-silent components and of a timer allows to detect a failure either in the starting or in the working phase of a pump, through an explicit Fail state.

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3.4 Redundant devices Pumps are used to inject water into the steam boiler. Due to their critical function, there are four pumps in parallel which may be turned on in order to always have at least one working, replacing a faulty device by a backup one and implementing one of the most effective techniques in fault management. Unfortunately, dealing with different devices makes the approach very difficult to be managed effectively. In other words, the use of redundancy often makes problem complexity worse, since redundancy management has to be interleaved with the overall process control. The proposed approach suggests instead dealing with redundant devices as components of a single system which guarantees the functionality of a single “virtual” pump. In other words, the implementation activates a single pump at the time, and in case of failure, switches to a backup one. At the logical level, a system of N redundant pumps may therefore be programmed and seen

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as a single pump. The interface of the PWS therefore hides the swap amongst defective and working units, thus cutting the complexity of the control algorithm which deals with the pumps. Similar techniques may be also effective for the water level sensors, where a voting algorithm may be used instead. In both cases, the system has to signal that it is working in a degraded mode that is in a mode where one or more failures happened and we have to take the entire system towards a fail safe state. Figure 6. Redundant fail explicit devices represented as a single device at the aggregate behavioural level.

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In figure 6, redundant fail explicit devices can be represented as a single device at the aggregate behavioral level (due to space reasons we depict the case of only two replicated pumps). The interface distinguishes amongst a regular and a degraded working state (respectively On and DOn). Figure 6 depicts the behavior of pump with a single backup pump: the same mechanisms may be extended to more replicated pumps. Observe that the interface taken from the behavior of the pump of Figure 5 is used twice in the upper, component part of the diagram. The system starts in the Off state, whose semantics is denoted by the state propositions which asserts that both pumps are off (p1.Off ∧ p2.off). When a pumpOn start event is received by the PWS, transition t2 is taken and waiting state W1 is reached, in which pump p1 completes its waiting phase. After that, p1 moves either to state On or to state Fail. In the former case, the pump units complete the startup phase moving to state On through transition t3. In the latter case, pump p1 fails starting, and the system moves to the waiting state W2, where alternate pump p2 is started. State W2 may be reached also from the working state state On after a failure in pump p1: in that case recovery pump p2 is also started by transition t5. Control moves out from state W2 when either pump p2 starts successfully or when it fails starting. In the former case the control moves to state DOn, meaning that the system is working in a degraded state since one pump has already failed and a

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second failure would not be be mended by a third pump (in this example). In case pump p2 fails, state Fail is reached through transition t7. Observe that state Fail may be also reached through transition t8 in case pump p2 fails while working. 4. CONCLUSIONS Since systems are formed by subsystems, that is by systems being part of more complex systems, it is customary to model, in the static case, such a containment relationship by a special modelling construct, called part-of relationship. Little or no attention has been paid, however, to the dynamical characterization of containment among systems. Understanding how the behavior of the parts influences the behavior of the whole, and vice versa, is in our opinion, of paramount importance, since most software systems are assembled from other software systems, each embodying its own behavior. More complex behavior host emergent properties, which do not pertain, however, to the component of the system exhibiting such a behavior. The paper shows that the holistic framework, as implemented by Part-Whole Statecharts, is a viable idea in order to encapsulate emergent properties of systems by a modular approach which allows to control complexity of artefacts, as well as to place increasingly complex behavior at different composition levels.

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Becker, S., Hasselbring, W., Boskovic, M., Dhama, A., Giesecke, S., Happe, J., Koziolek, H., Lipskoch, H., Meyer, R., Muhle, M., Paul, A., Ploski, J., Rohr, M., Swaminathan, M., Warns, T., Winteler D. (2006). Trustworthy software systems: a discussion of basic concepts and terminology. SIGSOFT Software Engineering Notes, 31(6), 1-18. Carter, W. C., Avizienis, A, Laprie, J. C. (eds.). (1987). The Evolution of fault-tolerant computing. Wien, New York: Springer-Verlag. Dominici, G., Palumbo, F. (2012). Decoding the Japanese Lean Production System according to a Viable Systems Perspective. Systemic Practice and Action Research, online first: doi: 10.1007/s11213-012-9242-z. Dominici, G. (2012). The holonic approach for flexible production: a theoretical framework. Elixir Journal, 42, 6106-6110. Dominici, G. Cuccia, L., Argoneto P., Renna, P. (2010). The Holonic Production System: a Multi Agent Approach. iBusiness, 2(3): 201-209. doi: 10.4236/ib.2010.23025. Hammer, W. (1980). Product Safety Management and Engineering. Prentice-Hall. Koestler, A. (1976). The ghost in the machine. London: Hutchinson. Kopetz, H. (2011). Real-time systems. New York: Springer. Leveson, N. G. (2011). Engineering a Safer World: Systems Thinking Applied to Safety. Cambridge, Ma: MIT Press. Norman. D. A. (1993). Things that Make us Smart. Addison-Wesley.

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Pazzi, L. (1997). Extending Statecharts for representing Parts and Wholes. Proceedings of the EuroMicro-97 Conference, Budapest, Hungary. Pazzi, L. (1999). Implicit versus explicit characterization of complex entities and events. Data & Knowledge Engineering ,31, 115-134. Pazzi, L. (2000). Part-Whole Statecharts for the Explicit Representation of Compound Behaviors. Proceedings of the UML 2000 Conference, York (UK): Springer. 1939, 541-555. Pazzi, L., Pradelli, M. (2008). A State-Based Systemic View of Behavior for Safe Medical Computer Applications. CBMS '08. 21st IEEE International Symposium on Computer-Based Medical Systems, 2008, 108 -113. Pazzi, L., Pradelli, M. (2010). Using Part-Whole Statecharts for the safe modeling of clinical guidelines. Proceedings of the 2010 IEEE Workshop on Health Care Management (WHCM), 1-6. doi: 10.1109/WHCM.2010.5441269. Pazzi, L. (2012). Modularity and part-whole compositionality for computing the state semantics of statecharts. Proceedings - International Conference on Application of Concurrency to System Design, ACSD2012, 193-203. Perrow, C. (1999). Normal accidents : living with high-risk technologies. Princeton, N.J.: Princeton University Press. Smith, G. F. (1989). Representational effects on the solving of an unstructured decision problem. IEEE Transactions on Systems, Man, and Cybernetics, SMC-19, 1083-1090. 262

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This work is a revised and extended version of the paper presented at The 2 nd WCSA Conference, Complexity Systemic Science and Global Energy Agenda, Palermo, Italy, September 26 and 27, 2011.

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Expansion Economiesi Fernando Buendía Economic and Administrative Sciences School, Universidad Panamericana-Campus Guadalajara, Zapopan, Jalisco, Mexico, e-mail: [email protected] Received September 21, 2012 / revised November 15 / accepted November 16 / published online November 17, 2012. DOI: 10.7350/BSR.A18.2012 – URL: http://dx.medra.org/10.7350/BSR.A18.2012

ABSTRACT

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According to the new international trade theory, trade need not be the result of international differences in technology and factor endowments. Instead, trade is the result of the exploitation of scale economies. Under increasing returns, trade is similar to the growth of the labor force and regional agglomerations. Nevertheless, these findings cannot be generalized to all kinds of firms and industries. It is true that in certain cases centripetal forces caused by scale and agglomeration economies can compel firms to cluster in a given geographical area and become localized. In other cases, however, because of centrifugal increasing returns stemming from expansion economies, firms have incentives to become global. This paper develops a simple model of expansion economies and shows that they are a special case of increasing returns that cause the growth of the firm by its dispersion, thus they are completely different from scale economies. In order to exploit economies of expansion, manufacturing firms tend to expand their economic activities to different locations, regions and countries. The level to which firms spread out in different region depends on the local demand. When such local demand is completely satisfied by the firm, it may decide to star business activities in another region, and so on. Keywords: Expansion economies, increasing returns, scale economies, growth of the firm, system dynamics.

1. INTRODUCTION Within this literature there are two frequently cited theories about the origin of agglomeration economies: Porter’s (1990) highly influential interpretation of regional blocks as industrial clusters and Krugman’s (1979, 1991a, 1991b, 1996a, 1996b) economics of geography. These authors argue that, although transportation and information costs have fallen, many industries remain highly concentrated in few countries and, more specifically, in few narrow localities within these countries. In recent years, economists have paid considerable attention to agglomeration economies, for they are the key factor to explain the process of accumulation of industrial activity in certain areas, the economic growth of the countries where those areas are located, the concentration of international trade between few countries, and the evolution of cities.

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Even though geographic economics has gained an important place in economic analysis, its findings cannot be generalized to all kinds of firms and industries. It is evident that in certain cases centripetal forces caused by scale economies and agglomeration economies can force firms to concentrate in a given geographical area and become localized. In other cases, however, because of centrifugal increasing returns, firms have incentives to become global. Furthermore, that firms expand their economic activities to different geographical areas is one of their most remarkable features1. For instance, traditional firms, such as Ford, General Motors, and CocaCola, and more recently created enterprises, such as Wal-Mart and Starbucks, tend to multiply their operations in a large number of locations. The expansion of the firm thus plays an important role in its growth and has to be considered a fundamental element of economic modeling, especially in the fields of industrial economics, international trade theory, urban economics, and industrial clusters. This paper outlines a simple model of the growth of the firm, which is caused by the scattering of its economic activities in different locations. This approach differs from other treatments —which assume that scale economies are the sole source of increasing returns to the growth of the firm— in that increasing returns are produced by expansion economies, which are internal to firms and, therefore, provide an endogenous explanation of its size. This paper has three additional sections. Section two discusses the theoretical background of the theory of the growth of the firm. In the third section, the theory of expansion economies is outlined. In section four, the case of Starbuck Coffee Company is used to provide empirical evidence about how expansion economies work.

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2. THE THEORETICAL FOUNDATIONS OF THE EXPANSION OF THE FIRM Before the mid-1970s, countries were assumed to trade with each other in terms of technology, as assumed by David Ricardo in the early 19th century, or in terms of factor endowments, according to the Heckscher-Ohlin theory developed in the 1920s. These theories provided good explanations of the trade patterns in the first half of the 20th century (cf. Krugman, 1996b). But as many researchers observed, comparative advantage seemed less relevant in the modern world, where most international trade takes place between countries with similar technologies and similar factor proportions; and quite similar goods are often both exported and imported by the same country. This implied that, at least among the richer countries, intra-industry trade (whereby, a country both exports and imports the same product) dominated relative to interindustry trade (whereby two countries export one product and imports another one). Many trade theorists observed that these patterns of intra-industry trade were driven by economies of scale. If the average cost of producing a given good declines with total production, then it could be optimal to split up production so that countries specialize in different brands of cars, for instance. Such specialization would make sense even without differences in factor proportions and technology. In the field of economic geography, the agglomeration of economic activities in given locations and how cities organized themselves spatially were also explained using the notion of scale economies. But, as it was the case in the field of trade theory, these insights were not supported by well-articulated models. Specifically, these approaches, because of increasing returns, could not deal with imperfect market structures and multiple equilibria. 1

While the globalization of the firm suggests that the location and ownership of production is becoming geographically more dispersed, centripetal economic forces makes for more pronounced geographical concentration of such activities once the firm situates itself within a particular region or country.

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By the late 1980s, Krugman (1979, 1980) integrated economies of scale into general equilibrium models of location and international trade, which are now commonly known as the new economic geography. In his seminal paper, Krugman (1979) argues that economies of scale are internal to the firm; so it can reduce its own average costs by extending the variety of products and expanding production. Under such conditions, markets cannot be perfectly competitive. Thus, for his treatment of Chamberlinian monopolistic competition, Krugman borrows with small modifications from Dixit and Stiglitz (1977). With this formulation Krugman articulated a simple model no more elaborated than the two-good Ricardian model, eliminated the multipleequilibrium problem, which is common when scale economies are external to firms, and provided an explanation of trade in a large number of differentiated products which fitted in well with the empirical literature on intra-industry trade. In the final section’ of his paper, Krugman (1979) laid the foundation of the “new economic geography” work he would develop later. Specifically, using the simple model developed in the first sections of this paper, he argues that in the absence of trade, consumer welfare will be highest in the region with the largest labor force. This is so because the real wage w/ p depends positively on the number of products n, which is greater in the region with the largest labor force. There will thus be a tendency for labor to migrate to the region that has the largest labor force, and therefore the greatest variety of products, at the beginning. Which region ends up with the greatest population, depends on the initial conditions which, when subject to increasing returns, define the final outcome. This mechanism gives rise to a cumulative process, resulting in concentration of production and urbanization. Thus the model contains a theory of urban growth, for people migrate to the cities offering a greater variety of consumption goods. The integration of scale economies into international trade is a major achievement, but the key questions concerning how urban agglomerations arise and how cities organize themselves are also closely related to the migration flows of firms across the geographic landscape. In point of fact, the dispersion of the firm plays a decisive role for the location of economic activity, which implies that the gains for international trade can be obtained without actual trade if firms of one region reproduce their activities in other regions. Although the model of dispersal economies developed by Polenke (2004) has shed light on the benefits of dividing up a firm to reduce pollution, it seems accurate to say that expansion economies still have a very limited place in standard economic analysis. Particularly, in the new international trade models, as it was said before, it has been suggested that economic activity (because of firm-specific economies of scale, product differentiation and imperfect competition) is concentrated geographically in few regions (leaving other regions relatively undeveloped), and with this, it has explicitly assumed that firms tend to be little globalized or expanded. This lack of interest in the globalization of the firm by trade scholars becomes rather surprising because the geographic expansion of firms —as opposed to its concentration in a large-scale production unit in specific geographical area— is perhaps one of the most common strategies firms have adopted to grow. Furthermore, the study of the globalization of the firm has been the focus of an extensive literature. One of the most well-known analyses in international business is Dunning (1993, 2000)’s OLI (Ownership, location and internationalization) paradigm, which, based on abundant empirical evidence, seeks to explain the causes of the existence of foreign direct investment (FDI) and multinational enterprises (MNEs). However, for many decades, as Dunning (1998) argued, international business scholars have overlooked the extent to which MNEs promote, or gravitate to, spatial clusters within a country or region. Therefore, the integration of the new models of international trade into the theory of

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MNEs would be fundamental in the development of international business theory2. On the other hand, the incorporation of the role of MNEs in the international allocation of production, the proponents of the new theory of international trade would be able to offer a more realistic explanation of the trends of trade. But it is necessary to provide an explanation of the diffusion of the firm before exploring the cross-fertilization of international business theory and international trade theory. The relevance of the growth of the firm through the expansion of its economic activities to other locations becomes also evident when it is compared with the traditional theories of the firm. Coase’s (1988) transaction costs approach and Williamson’s (1975) contracts perspective are of obvious importance to understand why firms exist and how they can reduce transactions costs. But they say little about how the firm grows. With his seminal article The Economies of Scale, Stigler (1958) laid the foundations of the theory of the growth of the firm. His argument is that the more rapid the rate to which a firm loses its share of the industry’s output (or capacity), the higher is its private cost of production relative to the cost of production of firms of the most efficient size. However, this is more a theory of the optimum size of plant (or manufacturing capacity of the firm) than a theory of the firm of optimum size. This distinction is important, for many economists have thought of scale economies as those economies stemming not only from plants of optimum size, but also from firms’ vertical integration. However, the economies that a vertically integrated firm obtains are radically different from Stigler’s original interpretation of scale economies. The earliest discussion of the properly combination of all the productive services that are part of the normal structure of the firm of best possible size has to be attributed to Chandler (1966, 1977, and 1990). The main intellectual contribution of Chandler’s historic perspective of large business was to recognize that, in order to achieve this goal, firms had to do a lot more than simply build large plants. They had to be able to maintain a high rate of throughput through their factories —that is, to keep their plants operating consistently at high levels of capacity utilization. In order to maintain a high rate of throughput, firms had to insure that shortfalls in supply did not disrupt their production processes and that output did not pile up in their warehouses unsold. The solution, as Chandler saw it, was for firms to bring these activities under their direct control by integrating backward into raw-material production and forward into distribution, and by building a managerial hierarchy capable of coordinating smoothly the flow of inputs and outputs from raw material to final sale. Therefore, through his historical theory of large business, Chandler has provided empirical evidence of the existence of what theoretically can be called economies of integration. Large firms could exploit not only economies of scale and economies of integration, but also economies of scope. According to Chandler, large firms can reap economies of scope by investing large quantities of financial resources in research and development, which allows them diversify their operations into other industries and introduce new products in markets other than the original ones. Big corporations, besides, compete strategically by moving into growing markets more rapidly and effectively than do their competitors. Such rivalry for market share and profits makes more effective the enterprise’s functional and strategic capabilities, which, in turn, provide the internal dynamic for its continuing growth. It also stimulates its owners and managers to expand its economic activities into distant markets in its own country and then to become multinational by moving abroad. 2

For a literature review on the present status of the relationship between ownership and location strategies to economic geography and theories of globalization, see Buckley and Ghauri (2004).

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Chandler claimed that firms that reaped scale economies, integration economies and scope economies improved upon the workings of the market, captured the resulting efficiency gains, obtained enormous competitive advantages, and over time brought under their managerial authority larger and larger portions of the economy. The only firms that could compete with them head to head, he argued, were those that completely duplicated their vertically integrated structures and managerial hierarchies. Because relatively few firms could raise the enormous amounts of capital required, these kinds of industries quickly took on oligopolistic structures. When The Visible Hand was first published in 1977, Chandler’s synthesis represented an extraordinary achievement. It provided a respectable alternative to the robber-baron view of big business that still figures prominently in the industrial economics literature. It also offered business historians for the first time a framework that made sense of the many (often antiquarian) histories of individual firms and industries that to that point largely constituted the field. Most significantly, it focused its attention on the central economic problem of understanding the changes that had occurred over time in the way the provisioning of goods and services was organized and drew out the implications of these changes for the structure of the American economy and for the place of the United States in the world. To summarize: with his ideas, Chandler went beyond Ronald Coase’s (1988) transaction costs approach, Oliver Williamson’s (1975) contracts perspective of the firm, and Stigler’s (1958) original formulation about scale economies, for he found out some of the most important causes of the growth of the firm. Chandler’s historical account is a very important empirical reference to outline a conceptual framework of how the firm can grow through the expansion of its economic activities to different geographical regions. 267 3. THE EXPANSION OF THE FIRM: A CONCEPTUAL FRAMEWORK The theory of expansion economies is about the relationship between the breeding of the optimal combination of all productive services of the vertically integrated firm in many different locations and its output, revenues and profits. Expansion economies, a source of increasing returns, are a control mechanism that explains endogenously the growth of those firms which have the capacity to expand. This is not a simple linear and exogenous growth. In fact, the growth of the firm produced by expansion economies is a powerful engine that gives rise to large firms competing in very concentrated industries and operates through the reproduction of the characteristics of the firm over long periods of time: The more machines, plants, and distribution facilities the firm has, the more goods and services it can produce. The more output it produces, the more it is profitable, which allows further investments in its expansion. This self-reinforcing mechanism, consequently, provides an endogenous explanation of the growth of the firm, which allows treating it as a complex system. To model the firm as a complex system, we assume a vertically integrated firm which carries out three main economic activities: production of inputs and manufacturing and distribution of final products. The firm’s total profits, π, can be defined by: N

N

i =1

i =1

π = ∑ p i qi − ci qi = ∑ qi ( pi − ci )

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(1)

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where pi is price, qi is quantity and ci is cost of the individual manufactured goods i . An important assumption in equation (1) is that pi − ci = α —where α is a constant—, which implies that the firm’s production functions is subject to constant returns, so the production of good i involves a fixed cost and a constant marginal costs. It is also assumed that prices cannot be reduced. Increasing returns is introduced by assuming that the behavior of qi depends of the following variables: I i , Pi and Di . I i is the minimum investment or scale required to produce the inputs of the firm. It is assumed that scale economies are reached if I i < a , which implies that the scale of the firm’s plant has to reach a minimum size a where it is profitable and possible to manufacture the individual good i. Pi is the minimum investment and scale to process the inputs and produce the final good. Here again it is necessary assume that Pi ≥ b , where b is the minimal size to make production of the goods of the firm possible and profitable. Di is the firm’s distribution network, which depend on t, the transportation capacity of the firm necessary to bring its products to the final consumer, retailers or wholesaler; w, the minimum storing capacity needed to distribute final goods, and n, the number of outlets, stores or particular distributors. Then the firm’s distribution capacity is defined by: Di = f (t , w, n, m ) ≥ d

268

(2)

It is assumed that each one of the n outlets has a minimum capacity or scale to function appropriately. This implies that, if the firm distributes its products through its own outlet chain, each outlet has to have the proper facilities, such as warehouse, counters, shelves, and etcetera. In the model it is assumed that the firm owns t, w, n and m, otherwise these variables are equal to zero. The effectiveness of advertising expenditure can be described by Ai = f [Di (t , w, n, m)]

(3)

That is to say, the effectiveness of advertising depends on t, w, n and m, because while these variables increases, Ai increases as well. This is so because the increasing availability of the firm’s products due to expanding distribution channels and the use of a larger number of marketing institutions, each dollar expended in advertising becomes more effective.

∂Ai ≥0 ∂Di (t , w, n, m )

(4)

Increasing returns also come from the fact that there is a mutual causality between Ai and Di (t , w, n, m) : in as much as Ai becomes higher the demand for the firm’s products grows, so it needs to enlarge its distribution capacities. The firm’s quantity of goods produced and distributed can be defined by: qi = f ( I i , Pi , Di , Ai )

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(5)

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Given equation (5), it is clear that the only way the firm can increase its revenue is by augmenting qi , the quantity of goods produced and distributed. But given that qi depends on I i , Pi , Di y Ai , the only way to increase qi is by investing part of the firm’s profits in augmenting I i , Pi , Di and Ai simultaneously and proportionally, according to the conditions established above. Proportional increases imply that a new plant to manufacture inputs ( I i +1 ), the firm has to open k new plants to manufacture final goods ( Pi ). If the firm decides to open a new plant to manufacture final goods, it is necessary that it sets up r new outlets or stores. Obviously k and r are whole positive numbers. For instance, if a brewer decides to open a new brewing and bottling plant, it has also to set up around 600 distribution outlets. The implications of I i , Pi , Di and Ai on the costs, revenues and profits of the firm can be seen in Figure 1. Figure 1. Expansion Economies and Profitability

269

At this point it is important to ask ourselves how much the firm will grow. Given that the growth of the firm is determined by the local, national and international demand the firm will face. But these demands have limits. For instance, in a given location the firm may open three outlets. If an additional outlet makes decrease the sales of the other three outlets, the optimal number of outlets for the firms to exploit expansion economies is three. Therefore, if we divide d l by x , the sale capacity of each outlet, and y, the production capacity of each plant of the firm, we obtain the optimal number of outlets at local level and the optimal number of plant the firm need at local level, respectively. As d l , d n and d i represents the levels of demand at local, national and international, they also provide the optimal number of plants and outlets at national and international level, given that we know the x and y. Therefore the firm’s level of manufacturing capacity expansion and level of distribution capacity are given by:

d d dl = El , n = E n and i = Ei xl xn xi

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(6)

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and dl d d = El , n = E n and i = Ei yl yn yi

(7)

respectively. An extension of Krugman’s model (1979 ) is that, when the movement of labor between countries or regions is allowed, world trade and factor mobility are substitutes for one another. In the framework outlined in the previous section something similar happens, but here the gains for trade occur not for factor mobility but for firms’ mobility. Therefore, in this model trade and the growth of the firm through its expansion are essentially equivalent, for the firm has an incentive to move to regions where it can find a demand. Besides, with perfect mobility of firms there are increasing returns, for firms continue growing, but there is no concentration of economic in a specific region because these firms spread out. In sum, in the presence of increasing returns in the form of scale economies, factor mobility appears to produce a process of agglomeration. Firm mobility, on the other hand, can substitute for international trade, but here increasing returns make the firm grow, but instead of agglomeration economies expansion economies produce a kind of geographical dispersion.

4. EXPANSION ECONOMIES, THE GROWTH OF THE FIRM, AND SYSTEM DYNAMICS 270

As mentioned before, expansion economies are a source of increasing returns and as such it is possible to explain the growth of the firm without assuming that they are going to produce agglomeration economies. However, in order to provide an endogenous explanation of how the firm grows through its expansion, it may be interesting to take a further step and describe the firms as complex systems. In the literature there is no conclusive definition of complex systems, but some authors (cf. Krugman, 1996a and Johnson, 2007) characterize complex systems by three main features: they are a collection of interacting parts or agents, these agents are affected by positive and negative feedbacks (memory) and they produce self-organization. Many of the interconnections of complex systems are actual physical flows, such as the level of water in a reservoir. Other interconnections, however, are flow of information. These interconnections or patterns of behavior operates through stocks and negative (stabilizing) and positive (reinforcing) feedbacks loops. These circular chains of cause-and-effect can be modeled using the tools of system dynamics (cf. Meadows, 2008 and Sterman, 2000), which consists of diagrams that represent relationships that are difficult to verbally describe. People have developed a language to describe cause-and-effect chains, while the diagrams used by system dynamics describe actual systems where there are circular chains of cause-and-effect. The systems dynamics literature has identified four types of system structures which generate the different patterns of behavior: exponential growth, goal-seeking, s-shape, and oscillation. As Figure 2 shows, in the system structure of the simple case of a firm exploiting expansion economies by opening in stores in a specific location (no production is assumed), there may be two feedback loops, one positive and one negative, that involve the variable “sales”. The positive loop is mutual causality between sales and actual stores. The negative loop involves sales and potential stores.

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Figure 1. System Structure of the Growth of a Firm subject to Expansion Economies

INITIAL TOTAL RELEVANT POPULATION Potential Stores

sales

SALES PER CONTACT

271

Actual Stores

BASE CONTACT RATE

At first, as Figure 3 shows, the positive loop dominates, but later the negative loop comes to dominate. When positive and negative loops are combined, a variety of patterns structures arise. The system structure that fits rather well the situation of a firm subject to expansion economies is that where a positive loop leads to early exponential growth, but then, after a delay, a negative feedback loop comes to dominate. This combination results in an s-shape pattern because the positive feedback loop leads to initial exponential growth, and then when the negative feedback loop take over it leads to the so-called goal seeking behavior. Figure 3 shows the results of a simulation run using the system structure of Figure 2, and illustrates a combination of positive and negative loops in the context of a firm exploiting expansion economies in a local market with a capacity to take up 500 stores. Figure 2. Number of Potential Stores in a Region

5. STARBUCKS COFFEE COMPANY: A CASE OF EXPANSION ECONOMIES In his book Onward: How Starbucks Fought for its Life without losing Soul, Howard Schultz (2011) describes how he started his global company. One day in Milan he entered in a small coffee bar where everybody seemed to know each other. He discovered how drinking coffee can connect people and create a community among them, and from that moment on he was

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determined to create a world-class network of stores where coffee and the romance of Italian espresso bars meet. In the fall of 2010, Starbucks, after forty years of history, had more than $10 billion in annual revenue and served around 60 million consumers a week in 16,000 stores in 54 countries. Starbucks’ impressive growth illustrates very well how economies of expansion work. This company sells brewed coffee through its network of stores (it produces no input or final goods as a car company, for instance), but the economic activities this firm performs can be helpful to provide empirical evidence about the theory of expansion economies. Table 1 presents the number of stores Starbucks Coffee has opened from 1987 to 2004. Table 1. Number of Outlets of Starbucks Co. from 1987 to 2004

272

Year 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

New Outlets per Year 17 16 21 30 32 49 107 153 252 338 397 474 612 1003 1208 1177 1339 1160

Total 17 33 54 84 116 165 272 425 677 1015 1412 1886 2498 3501 4709 5886 7225 8337

Even though the sale of each store has decreased in the last year (see Figure 3), the total sales of the company, as Table 2 shows, has increasing steadily since the foundation of the company. In fact, the decline of each store’s sales is a strategy the company implemented to produce a kind of “crowding effect” to prevent the entry of its rival in the urban zones where Starbucks’ stores are located. Although it is beneficial for Starbucks from a strategic point of view, the concentration of the company’s stores in an urban area reveals also the negative effects of scale economies. Therefore, the company has incentives to extend their economic activities in other places at local, national and international level. Data to show empirically that the growth of Starbucks comes from expansion economies and not from scale economies, and that these notions are completely different and have different sources, is given in Table 2. In this table there is a clear relationship between income and number of stores. This apparent mutual causality between revenues and number of stores is an empirical proof of the fact expansion economies is the increasing return mechanism that explains endogenously the growth of the firm.

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Figure 4. Decrease of Sales per Store 25 20 15 10 5 0 1992

1994

1996

1998

2000

2002

2004

Table 2. Relationship between Number of Outlets and Income Year

273

1995 1996 1997 1998 1999 2000 2001 2002 2003

Total Income (thousands dollars) $465,213 $697,872 $975,872 $1,308,702 $1,686,828 $2,177,614 $2,648,980 $3,288,908 $4,075,522

Income (% of change)

Number of outlets

50 39 34 29 29 21 24 24

677 1,015 1,412 1,886 2,498 3,501 4,709 5,886 7,225

Number of outlets (% of change) 50 39 34 32 40 34 25 23

6. CONCLUSIONS This paper develops a simple model of expansion economies as a source of increasing returns and an alternative mechanism to explain the growth of the firm and the de-concentration of economic activity. It shows that the growth of the firm need not be the result of the exploitation of scale economies, which in turn cause the agglomeration of economic activity in a geographical area and the accumulation of trade between few countries. This analysis, while very simple, may be useful to explain the globalization of the firm and revise international trade theories and those theories related to industrial clusters and urban economics.

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A previous version of this paper was presented and published in the proceeding of the proceedings of the 24th International Conference of the System Dynamic Society, July 23-27, 2006, Nijmegen, Netherlands.

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