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Chapter XXXI

Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior Mahmud Akhter Shareef Carleton University, Canada Vinod Kumar Carleton University, Canada Uma Kumar Carleton University, Canada Ahsan Akhter Hasin Bangladesh University of Engineering & Technology, Bangladesh

AbsTRAcT Research related to the impact of individual characteristics in their acceptance of online systems driven by information and communication technology (ICT) observed that dissimilarities among individuals influence their adoption and use of the systems. Thus, research streams investigating this issue generally follow the traditions of the theory of reasoned action (TRA) or the theory of planned behavior (TPB). Research reveals that individual characteristics, mediated by beliefs, affect attitudes, which affect intentions and behaviors. These two major behavioral theories related to technology acceptance and the intention to use technology might provide significant theoretical paradigms in understanding how online system adoption and diffusion, driven by information technology, can vary globally. In this study, the authors’ first objective is to understand TRA and TPB as they study ICT-based online adoption and diffusion globally. Then, based on that theoretical framework, their second objective focuses on developing a theory of ICT adoption and diffusion as an online behavior. Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior

InTRODucTIOn Evolution, which may denote a variety of concepts, is most generally defined as the accumulation of historically acquired information in an organized fashion (Bandura, 1986). Technological evolution seems to refer to natural forces not dissimilar to the forces of natural selection. The technological stage of evolution is characterized by the development and expansion of technology and information from generation to generation and by intensification of competition between human groups. On the other hand, technological development implies complete control over the process. This controlled process of technology development, diffusion, disruption, and adoption has cultural, behavioral, and social aspects (Kumar et al, 2008). The adoption and extensive use of ICT-based online systems in public and private organizations has expanded dramatically. The Internet has become, within a very short time, one of the basic media of modern society to accept ICT. Many countries now consider understanding online systems and mastering the basic skills and concepts of ICT as part of the paradigms of market development. It is the single most powerful tool for participating in global markets, promoting political accountability, improving the delivery of and cost cutting in basic services, developing efficiency in operations of public and private organizations, and enhancing local development opportunities. Researchers indicate that, from the last decade, about 50 percent of all new capital investment in organizations has been in information technology (IT)-based online systems (Westland and Clark 2000). This huge investment in online systems and ICT can only be realized if its full potential is achieved. For ICT to achieve its full potential, it must be accepted and used by employees of organizations internally and by citizens externally. Explaining user acceptance of new technology is often regarded as a research area of great potential in contemporary ICT literature (Hu et al. 1999). Organizational theorists, IT professionals,

psychologists, sociologists, economists, market researchers, policy makers, and academics are all keenly interested in analyzing different aspects of the IT-intensive online system adoption from their own fields. The globalization of the market economy is extremely helpful in understanding technology diffusion and adoption in developed countries as well as in some developing countries regarded as Asian giants—such as Singapore, Hong Kong, Taiwan, Malaysia, South Korea, China, Singapore, Thailand, and India. However, the diffusion of ICT and acceptance of online systems do not follow a single track for all countries. In each country, the different economic and government policies and differences in social, cultural, and behavioral aspects are very significant and prominent. This paper mainly concentrates on evaluating ICT-based online system adoption and diffusion criteria based on the previously mentioned perspectives. Researchers also argue that the cultural, social, and behavioral attitudes in adopting online systems are strongly affected by some external attributes arising from political, economic, and marketing issues (AL-Shehry et al., 2006; Damodran et al., 2005). However, before going into further analysis regarding those aspects, we should examine brief definition of IT. Information technology (IT), also known as information and communication(s) technology (ICT) is concerned with the use of modern computer-based technology in managing, organizing, diffusing, and processing information in different public and private sectors. The fundamental opportunity offered by an online system is for suppliers, developers, and sellers (i.e., providers of ICT) to gain direct access to different stakeholders without the development and maintenance costs associated with the physical distribution channels. In the electronic medium, competitors can emerge from anywhere in the world with significant differences in attitude, especially toward adopting new ICT. As a result, national and also global cultural attributes show significant disparities in the behavioral intention

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Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior

and attitudes of users of online systems. A society produces some values, ideas, intentions, and speculations about the human personality. These perceived psychological phenomena depend on rules, regulations, relationships, religious and political views, values, culture, tradition, etc. Depending on cultural and social factors, the behavioral intention to adopt online system operated through ICT can be affected substantially (Engel et al., 1993). Based on the literature reviews (Chase and Tansik, 1978; Donthu and Boonghee, 1998; Furrer et al., 2000; Kale and Sudharshan, 1987; Kettinger et al.; 1995; Kogut and Singh, 1988; Li, 1994; Liu et al., 2001), the importance of those social values for determining adoption factors of online system is evident. Social values generate attitudes and beliefs that lead to the stakeholders’ behavior of using certain objects, viz., IT (Shareef et al., 2008). Therefore, studies of behavioral intentions and culture have a significant place in the development of an adoption framework of ICT-based online system. Research related to the impact of individual characteristics observed that dissimilarities among individuals influence their adoption and use of online systems (Titah and Barki, 2005). A research stream (Carter and Bélanger, 2005; Gilbert et al., 2004; Phang et al., 2005; Titah and Barki, 2005) investigating the influence of individual characteristics on online system adoption that generally follows the tradition of the TRA and TPB (Fishbein and Ajzen, 1975) reveals that individual characteristics mediated by beliefs affect attitudes, which affect intentions and behaviors. These two major behavioral theories related to technology acceptance and the intention to use technology might provide significant theoretical paradigms of understanding how IT-intensive online system adoption and diffusion can vary globally. Technology Acceptance Model (TAM) by Davis et al., (1989) is also an information system theory that models how users come to accept and use a technology. However, TAM has used TRA to conceptualize its paradigms of modeling.

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Rogers (1995) Diffusion of Innovation Theory is also a powerful theory in predicting technology diffusion and adoption. However, in this study since our prime focus is to investigate human behavior, attitude, and belief in accepting ICT, we have focused primarily on TRA and TPB. Here, our first objective is to understand TRA and TPB as we study ICT-based online adoption and diffusion globally. Then, based on that theoretical framework, our second objective focuses on developing a theoretical framework of ICT adoption and diffusion as an online behavior. In the next section, we will investigate basic concepts of TRA and TPB with a background synopsis and briefly illustrate their utility in identifying ICT-based online acceptance behavior. The next section develops conceptual paradigms of ICT-based online system acceptance. The conclusion explains the usage of TRA and TPB in relation to online system acceptance behavior grounded on the proposed theoretical framework. Finally, future research direction is suggested.

TheOReTIcAl fRAmewORk Of TRA AnD Tpb Behavioral attitude is dependent on some external and internal factors including experience, personality, and social values (Engel et al., 1993). Behavioral intention has significant implications in assessing adoption determinants. Service literature has incorporated behavioral intention in their models for a long time to identify dimensions that create the intention to accept certain systems (Azjen and Fishbein, 1980; Bellizzi and Hite, 1992; Cox and Rich, 1964; Davis et al., 1989). Nevertheless, IT service designers have not given enough priority to social characteristics of different stakeholders, like behavior, personality, attitude, belief, values etc., as an antecedent of the adoption framework (Damodaran et al., 2005). Several authors intended to use the frameworks of TRA and TPB to postulate the fundamental

Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior

paradigms of different acceptance characteristics of information technology (Davis, 1989; Treiblmaier et al., 2004; Warkentin et al., 2002). In 1980, Ajzen and Fishbein formulated the TRA. This resulted from attitude research using the Expectancy Value Models (Fishbein, 1968). They formulated the TRA after trying to estimate the discrepancy between attitude and behavior. The fundamentals of the TRA come from the field of social psychology. Social psychologists attempt, among other things, to explain how and why attitude affects behavior. That is, how and why people’s beliefs change the way they act. The study of the ways attitude influences behavior began in 1872 with Charles Darwin. Darwin defined attitude as the external expression of an emotion. In the 1930s psychologists defined attitude as an emotion or thought with a behavioral component. This behavior could be non-verbal such as body language, signals, signs, or vocally expressed. Psychologists argued about what should make up the term attitude. Social psychologists suggest that attitude includes behavior and cognition, and that attitude and behavior are positively correlated. TRA has three general constructs: (1) behavioral intention, (2) attitude, and (3) subjective norm. Ajzen and Fishbein (1980) proposed that a person’s behavior is determined by the person’s intention to perform the behavior and that this intention is, in turn, a function of the person’s attitude toward the behavior. One of the potential reflectors of possible behavioral outcome is intention. Intention is the cognitive representation of a person’s readiness to perform an intended behavior, and it is considered to be the immediate indicator of behavior. Behavioral intention measures the relative strength of a person’s likelihood to perform an anticipated behavior. It comprises motivational or attitudinal factors that capture how persons are engaging to perform the intended behavior (Ajzen 1991). So, TRA conjectures that behavioral intention is the most influential predictor of behavior. In a meta analysis of 87 studies, an average correlation of

.53 was observed between intentions and behavior (Sheppard et al. 1988). For different contexts, the magnitude of beliefs, which in turn affect attitude, differs. So, these constructs will be evaluated by a person’s valuation of the weight of these consequences. One might have the belief that adopting modern ICT is good for one’s professional career. It enhances efficiency and also effectiveness. However, it is time consuming to learn and resources are also not always available. Each of these beliefs can be weighted based on one’s perception of the merits of those beliefs. Subjective norm is regarded as a combination of perceived expectations from relevant individuals or groups along with the intention to comply with these expectations. It is considered as the person’s belief that individuals or groups associated with that person expect that the person should or should not perform the behavior and the person’s expectation to comply with the specific references (Fishbein and Ajzen, 1975). Associates of one individual might have engaged in ICT-based projects. They have enough skill and are advancing their professional career by adopting ICT. These associates have explicit and implied influence on that individual’s intention to learn ICT. However, at the same time that individual’s brother might have had adverse consequences in trying to adopt ICT in professional life. That brother may have devoted much time, money, and efforts to learn IT and, ultimately, could not pay back these investments. So, he might discourage that person from learning ICT. This circumstance might have a negative impression on that individual’s decision making about learning ICT. The beliefs of these people, weighted by the importance of the individual attitude to each circumstance/opinion, might influence the person’s behavioral intention to use ICT, which in turn will affect that person’s behavior to learn or not learn ICT in a professional career. So, a person’s intention toward a specific behavior is affected by the person’s attitude toward that behavioral

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Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior

outcome and the attitude a person perceives other people would have towards the performance of that behavior. A person’s attitude, combined with subjective norms, forms the person’s behavioral intention. From the review of TRA, we get the essence that behavioral intention, a function of both attitudes toward a behavior and subjective norms toward that behavior can predict actual behavior. A person’s attitudes about learning ICT in professional life combined with the subjective norms about learning ICT in professional life, each with their own weight, will determine intention of learning ICT in professional life (or not), which will then lead to the actual behavior. Fishbein and Ajzen asserted that attitudes and norms are not weighted equally in predicting a specific behavior. Most important is context-based measurement, i.e., issue or subject related measurement. “Indeed, depending on the individual and the situation, these factors might be very different effects on behavioral intention; thus a weight is associated with each of these factors in the predictive formula of the theory. For example, you might be the kind of person who cares little for what others think. If this is the case, the subjective norms would carry little weight in predicting your behavior” (Miller, 2005, pp. 127). TRA has been tested in numerous studies across many areas—including dieting (Sejwacz et al., 1980), using condoms (Greene, Hale, and Rubin, 1997), consuming genetically engineered foods (Sparks et al., 1995), and limiting sun exposure (Hoffman et al., 1999). ICT literature incorporated this theory to define attitudes, behavioral intention, and cultural differences on the way to adopting online systems (George, 2000; Collier and Bienstock, 2006). This theory can be extended to conceptualize the human behavioral pattern in the decision-making strategy and, ultimately, to design the application of ICT, whether it is Ecommerce (EC) and E-government (EG), looking at global behavioral attitudes. The validity of the TRA is extensive within some conditions; however, under circumstances

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where internal and external factors might control or affect the motivation of the outcome of behavior, TRA is a relatively poor or partial predictor of those types of behaviors. For actual behavioral outcome, it appears not to be completely voluntary and under control; this resulted in the addition of certain external or internal factors, termed as perceived behavioral control. With this addition, the theory was called the TPB. TPB is a theory that predicts intended and rational behavior, because behavior can be deliberative, organized, and planned. Thus, TPB, which is an extension of TRA, was developed to incorporate behavioral control factors in predicting behavior. This theory extends the incomplete concept of TRA in predicting an actual behavior under the influence of certain stimuli that intended behaviors are also controlled by some uncertainty. Therefore, performing a behavior depends not only on intention but also on some external or internal factors that may interfere with the motivational behavior. Behavioral control is conceptualized as one’s perception of the context of performing a behavior. This construct reflects a person’s perception of the presence or absence of external favoring or nonfavoring resources and opportunities to perform a behavior of interest (Barnett and Presley, 2004). It is a product of belief of availability of external pursuing factors multiplied by a perception of importance of those factors to the achievement of behavioral outcome. Based on the context of behavioral outcome, this behavioral control needs a significant insight from the researchers to identify the related factors. For example, external or internal factors, which can control the outcome of a behavior, can influence an actual behavior (Netemeyer et al., 1990). In this theory, the main dependent construct is behavioral intention/conduct and the main independent construct(s)/factor(s) are attitudes toward that behavior, subjective norms, and perceived behavioral control. The theory explains that individual behavior is driven by behavioral intentions where behavioral intentions are

Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior

a function of an individual’s attitude toward the behavior, the subjective norms surrounding the performance of the behavior, and the individual’s perception of the ease with which the behavior can be performed (behavioral control). Although Ajzen (1991) has suggested that the link between behavior and behavioral control outlined in the model should be between behavior and actual behavioral control, rather than perceived behavioral control, the difficulty of assessing actual control has led to the use of perceived control as a dummy variable. This theory has a significant implication in identifying differences in the users’ perception of the intention to adopt an ICT-based online system. These are characterized by cultural differences, security perceptions from the local external environment, and a disposition of trust as a behavioral control (Robey and Sahay, 1996; Warkentin et al.2002). TPB provides useful information for the development of communication strategies and consumer behavior. This theory is also used in evaluation studies like ICT adoption and diffusion, predicting online behavior toward, for example, EC and EG. In the IS literature, this theory has been used in identifying users’ behaviors and attitudes in issues relating to Internet use, online purchase, household computer use, and online privacy, security, and trust. It is also frequently used in predicting user acceptance of word processing technology, user intentions to use microcomputers and IS, and organizational judgments in evaluating employees motivation towards job schedule (Ajzen, 1991; Albarracin et al., 2001; Barnett and Presley, 2004; Bernadette, 1996; Brown and Venkatesh, 2005; Kraut et al., 1998; Mathieson, K., 1991; Newburger, 1999; Pavlou and Fygenson, 2006; Vijayan et al., 2005). This model can also be used in other fields like, for predicting citizens’ voting behavior, disease prevention behavior, biological behavior etc. (Jaccard and Davidson, 1972).

cOncepTuAl pARADIgms Of IcT ADOpTIOn This section of research is organized to identify and figure out theoretical perspectives of adoption framework of ICT-based online systems as behavioral outcome grounded on TRA and TPB. Therefore, in this study our dependent variable is actual behavior towards adoption of ICT-based online systems. This research, first attempts to investigate the prime aspects of online system adoption by individuals. Then, after analyzing those prime aspects of ICT adoption driven by ICT, successively, this research attempts to recognize and postulate the plausible explanatory variables for adoption. While investigating and revealing the prime perspectives of independent variables of online system adoption, this research explores the literature that addresses ICT-based online system adoption, implementation, characteristics, and related issues and the fundamental essences of TRA and TPB as derived in the previous section. Then, by comparing, adjusting, and integrating views collected from those studies, this research illustrates the design perspectives of ICT-based online system adoption for investigating explanatory variables. Ventura (1995), in his early work on adoption of ICT-based online systems, argued that the integrative view of the ICT adoption paradigm should investigate technical, organizational, and institutional factors simultaneously to reveal a comprehensive concept. Drawing a reference from a study by Chwelos et al. (2001) on electronic data interchange (EDI) adoption, Tung and Rieck (2005) postulated that an online system adoption framework can be investigated from three interrelated perspectives: the technological, organizational, and inter-organizational aspects. The technological aspect deals with perceived characteristics of ICT; the organizational aspect reveals organizational characteristics of ICT users in multi-levels, whereas the inter-organizational perspective encompasses factors relating to the

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Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior

actions of other organizations and collaboration between the public and private sectors. Al-adawi et al. (2005) and Chwelos et al. (2001) conceptualized an online adoption model from the perspectives of technology and trust. Heeks and Bailur (2007) looked at both technological and social aspects to formulate the impacts of ICT-intensive systems, like EC and EG. In the light of the Socio-technical theory, Damodran et al. (2005) also formulated online system adoption concepts based on social, organizational, and technical perspectives. Anthopoulos et al. (2007), while developing the design of EG, emphasized that ICT strategic plans are political. The online paradigm emphasized internal networking, external collaboration, and globalization through adoption of technology, by putting services and information that public organizations offer online for stakeholders so that these services and information can be easily reached (Dunleavy, 2002; Moon, 2002). However, different researchers (AL-Shehry et al., 2006) emphasized that online system adoption is more than a technological matter, as it is influenced by many factors, such as organizational, behavioral, economic, social, and cultural issues. These are important forces, and they relate to the pattern and functions of public and private organizations, as well as government itself and good governance (Carter and Belanger, 2004; Holtham, 1992; Moon and Norris, 2005). Chen and Thurmaier’s (2005) model includes technological, cultural, economic, behavioral, and organizational perspectives to design an adoption framework of ICT-based systems. Steyaert (2004) adopted a marketing perspective to formulate technology performance. He proposed an EC-based performance model to evaluate EG performance in terms of citizen satisfaction. Parent et al. (2005) and Warkentin et al. (2002) investigated the effect of trust on adoption of ICT projects. They suggested that trust in online systems, an antecedent of adoption, has political, organizational, and behavioral perspectives. Gilbert et al. (2004) proposed integration of the

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service quality, technology, and behavioral aspects of the technology adoption framework. Consistent with practices in the IS research literature, Wang (2002), in studying the adoption of electronic tax filing, argued that individual differences refer to user factors that include traits such as personality and demographic variables. Also important are situational and contextual variables that account for differences attributable to circumstances, such as experience, prior knowledge, learning, and training, as aspects to be investigated in an adoption framework. Titah and Barki (2005) extensively reviewed adoption literature of EG and they suggested that technological, organizational, social, cultural, behavioral, and economic aspects should be considered in a comprehensive framework of ICT system adoption. Other researchers also postulated that the use of online systems is overwhelmingly influenced by several behavioral, cultural, marketing, economic, social, and organizational aspects (Barnett and Presley, 2004; Brown and Venkatesh, 2005; Karahanna et al., 1999; Pavlou and Fygenson, 2006; Straub et al., 1995; Venkatesh and Davis, 2000; Vijayan et al., 2005). Therefore, from our literature review, we perceive that technological, behavioral, social, cultural, organizational, economic, political, and marketing aspects might provide important insights while investigating explanatory variables for ICT-based online system adoption, especially for investigating perceived behavioral control. Now to delineate the theoretical paradigms and examine theoretical discourses that we observed from TRA and TPB, this research, at the outset of this present section, looks at Contingency Theory. The perspective originated with the work of Woodward (1965), who argued that technologies directly determine differences in such organizational attributes as organizational control, multilevel interactions, system of work, centralization of authority, and the formalization of rules and procedures. Environmental change and uncertainty, technology, different stakehold-

Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior

ers, culture, behavioral differences, and different organizational attributes are all identified as environmental factors impacting the effectiveness of different organizational forms. If we translate the core doctrine of Sociotechnical Theory (Trist and Bamforth, 1951) and Complementary Theory (Massini and Pettigrew, 2003), which explains the social aspects of people and society and technical aspects of information, communication, and technology, we get deep insights into integrating the social, organizational, and technological aspects of the ICT adoption framework. These theories refer to the interrelatedness of social, cultural, organizational, marketing, political, economic, and technical aspects. The discursive discourses of these theories explain the systems consisting of social and organizational elements as well as technical elements, and emphasizes that successful systems require the integrative interaction of technical, organizational, and social aspects of the system (Damodaran et al., 2005). This doctrine of integrating all the aspects related to online system characteristics is also supportive of ideas from the Complementary theory, which several researchers of online system investigated. This theory suggests that in developing and conceptualizing the framework of ICT implementation, variables influencing the complete process at different phases should be considered as part of an integrated system of factors that are mutually reinforced (Massini and Pettigrew, 2003; Whittington and Pettigrew, 2003). Drawing inferences from all the previously mentioned paradigms, culture plays a significant role in conceptualizing adoption of an online system by developing perceived behavioral control, one of the important antecedents of behavioral intention. A fundamental paradigm of TRA from an online ICT perspective is its assertion that any other factors that influence behavior do so only indirectly by influencing attitude and subjective norms in presence of certain external and internal factors as behavioral control. Such variables would

include, among others things, the system design characteristics, communication styles, behavioral characteristics and perception of trust and security, social and cultural values (including cognitive styles and other personality variables), and work related properties (Vijayan et al., 2005). So TRA is quite appropriate in the context of predicting the behavior of using online systems. Further, TPB gives a new outlook on external facilities, which have a direct effect on intention for a behavior and behavioral outcome. Mathieson (1991) used the TPB as well as the Technology Acceptance Model (TAM) to predict user’s intentions. As a general model, it is designed to explain most human behaviors (Ajzen, 1991). Hence, it is reasonable to conjecture that a TPB-based model could effectively explain ICT-based online adoption behavior (Pavlou and Fygenson, 2006; Sheppard et al., 1988;). TPB includes three distinct categories of external beliefs related to attitudinal, normative, and control aspects― the antecedents of behavioral intention. These beliefs are context and situation specific and cannot be generalized a priori. Hence, for each new behavior, one must explore several explicit beliefs that have specific context (Ajzen and Fishbein 1980). According to information management principles for online adoption, a prime factor for adoption is creating awareness among the prospective users. This means informing the end users about the implementation of innovation, important factors and issues, basic paradigms of the new system, comprehensive information about advantages and disadvantages, and the overall security of the system. Awareness is a relative concept. The public may be partially aware or completely aware of the strategic functionality of ICT. Awareness provides the retrospective material from which prospective users develop cues, concepts, or subjective ideas about their experience. As we learned from TRA and TPB, beliefs about a system turn to the attitude of using the system. However, awareness of the system is important at the beginning to develop beliefs.

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Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior

Before developing an attitude to adopt an online system, prospective users need to be aware of its complete characteristics, including functional behavior, strategic benefits of the system, the safety and legal environment, etc. So we categorize this predicted variable for adoption as antecedents of beliefs to use, since awareness is the primary stimulus of creating attitudinal, normative, and behavioral control beliefs. This research defines Perceived Awareness (PA) as having and acquiring knowledge as much as a user perceived to be sufficient to learn the characteristics of online system and interact through perception or by means of information about ICT. TAM is a widely referenced theoretical model for predicting the intention to use and the acceptance of IS by individuals. It proposes that perceived ease of use (PEOU) and perceived usefulness (PU) determine the attitude toward adoption of ICT. The attitude, in turn, leads to the intention to use ICT and the eventual acceptance (Bhattacherjee, 2001; Davis et al., 1989; Lucas and Spitler, 1999; Moon, 2002; Venkatesh, 2000). Several researchers strongly predicted that these two constructs develop attitudinal belief and perceived behavioral control (PBC) in adopting ICT-based systems (Chau and Hu, 2001; Davis, 1989; Pavlou and Fygenson, 2006; Vijayan et al., 2005). We can borrow the same definitional concepts for these two constructs of beliefs from TAM. PU has marketing, economic, and organizational aspects. PEOU is assumed to influence PU, because the easier a system is to use, the more useful it can be. A system will not be accepted if users do not perceive the system both useful and easy to use (Davis, 1989). Several scholarly articles (Brown and Venkatesh, 2005; Collier and Bienstock, 2006; Loiacono et al., 2002; Udo, 2001; Wolfinbarger and Gilly, 2003; Yoo and Donthu, 2001) reveal that, for online interaction, communication quality, technical and design quality, and informational quality help to measure the constructs PU and PEOU for online adoption by citizens and business organizations.

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Agency theory also asserted those behavioral aspects (Eisenhardt, 1989). Several online researchers accepted two constructs― compatibility and image― from diffusion of innovation theory (DOI) as the creator of normative beliefs. When a person observes that close, important individuals have adopted and are using an online system frequently; this may create motivational beliefs in that person to also use, or not use, this online system. Compatibility is also responsible for imparting attitudinal beliefs for a person’s behavior to comply with a virtual system. Compatibility has cultural, behavioral, and social aspects. It is dependent on individual characteristics, such as avoiding personal interaction and social influence. Several researchers indicated that specific characteristics of online systems that allow users to avoid personal interaction might create the perception of compatibility among users to adopt an online system (Gilbert et al., 2004). Shedding light on TRA and TPB, the compatibility of an online system with adopters’ beliefs, values, and attitudes reflects the behavioral aspect. From the socio-technical and complementary theories, beliefs and attitudes of adopters of a new technology system also have social and cultural aspects. Several researchers use this construct as the significant predictor of online adoption (Brown and Venkatesh, 2005; Carter and Bélanger, 2004; Chen and Thurmaier, 2005; Pavlou and Fygenson, 2006; Shareef et al., 2007). Image, as proposed by Moore and Benbasat (1991), influences the acceptance and use of an innovation according to the DOI theory. Image refers to the perceptions that prospective users have of innovation as a status and prestige symbol. Interaction with online systems reflects a perception of superior status, which creates normative beliefs. So, several researchers included this construct in their proposed model of online adoption (Gefen et al., 2002; Gilbert et al, 2004; Pavlou and Fygenson, 2006; Phang et al, 2005; Tung and Rieck, 2005; Vijayan et al., 2005). Since adoption of online systems might reflect the adopter’s familiarity

Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior

with modern technology, higher level of education, competence in using the computer and Internet, and perception of modernism, these phenomena impart some degree of social values and prestige to adopters. Therefore, this research argues that image has social, behavioral, and also cultural aspects. Superior perception of using online has cultural ingredients. It also depends on personal behavioral ideology. Both compatibility and image constructs can be conceptualized from original DOI theory. Socio-technical theory has great implications in evaluating the success of IT. According to this theory, it is essential for the technical system to be properly synthesized with the social-cultural aspect and the organizational environment in which the technical system must operate (Damodaran et al., 2005; Finkelstein and Dowell, 1996; NAO, 1999). Based on this theory, looking at the online behavior of consumers for adopting an ICT-based online system reveals that in the virtual environment ICT adoption is significantly affected by trust disposition attitude as well as beliefs which have technological, behavioral, social, cultural, and organizational perspectives. Many consumers do not trust online systems due to their technology beliefs and behavioral characteristics. A disposition and attitude of trust towards online systems can be fundamentally described by normative beliefs and motivation to comply with the specific characteristics of the online environment. It is also dependent on institutional based beliefs (private organizations for EC and public organizations for EG). TRA suggests that trusting attitudes or beliefs significantly affect behavior. This trust disposition attitude is in turn characterized by cultural effects. Hofstede (1994) defined culture as “the collective programming of the mind”. Hofstede’s (1994) findings strongly suggest that cultural differences and social values differentiate customers in terms of their disposition and attitude of trust that, in turn, influence the perception and expectation of adopting online systems. However, adoption of an online system by

influential members of a person’s nearby associates also affects that person’s motivational belief towards online acceptance (Brown and Venkatesh, 2005). So, disposition and beliefs of trust can affect attitude and subjective norm constructs. We define this belief, i.e., trust disposition attitude, here as the general belief of an individual toward human beings, society, organizations, i.e., toward any object. This belief is also characterized by normative values of society and culture. The control beliefs incorporated into different online system adoption models account for factors that may inhibit or encourage performance and behavior, such as lack/availability of resources, influence of external surrounding systems, knowledge, or social opportunity or barriers for engaging in that behavior (Ajzen 1985, 1991; Ajzen and Madden 1986; Taylor and Todd, 1995). In this connection, researchers have investigated a wide range of issues― including the attitude of a government, technology absorption capability, appropriateness of technology, and management of ICT. Other topics of investigation have been development and maintenance of technology, cooperation and conflict between government and citizens, and the social and economic benefits of online systems by adopting new IT (Brudney and Sally, 1995; Bugler and Stuart, 1993; Cusumano and Elenkov, 1994; Norris and Moon, 2005). Many researchers have asserted that adoption of the new technology is closely related to knowledge and experience of that system and also availability of resources (Al-adawi et al., 2005; AL-Shehry et al., 2006; Carter and Bélanger, 2004; Chen and Thurmaier, 2005; Parent et al., 2005; Tung and Rieck, 2005; Warkentin et al., 2002). Users can secure and achieve traditional service without prior knowledge of modern ICT or availability of resources― including computers, Internet connection, call-center, and access. However, the adoption of online systems implies acceptance, use, and adoption of the Internet, virtual environment, software, and computers. From TPB, DOI, and Transaction Cost Analysis

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Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior

(TCA), a user will not arrive at an intention to use an online system, which requires computer knowledge to get a competitive advantage, unless the user has competence from experience in the use of modern ICT. From technological, behavioral, economic, and organizational perspectives, it is anticipated that failing to get practical experience of technology will not create a user’s behavioral intention to adopt the system. Also, in the absence of computer knowledge, a user can not perceive the economic advantages of online, which is largely due to extensive use of the computer and the Internet. So the availability of resources and knowledge of resources are important criteria for prospective users of the online system. In general, prior research has suggested a positive relationship among availability of resources; knowledge of and prior experience with ICT, Internet, and computers; and an attitude to use the system (Levin and Gordon, 1989; Wang, 2002). Technology availability and computer selfefficacy have been examined in the IS literature (Compeau and Higgins, 1995; Wang, 2002). Continuing research efforts on availability of resources and knowledge, published in recent IS studies (Agarwal et al., 2000), confirmed the critical role that resource availability and experience play in understanding individual responses to online system adoption. Wang (2002) investigated the relation of technology availability and computer self-efficacy with behavioral intention to adopt online tax filling system and observed a positive relation. The proposed relationship between computer availability and knowledge and attitudinal intention to use an online system is based on the theoretical framework proposed by Davis (1989) and Davis et al. (1989). Based on the social cognitive theory (Bandura, 1986), technology availability and technology self-efficacy affect an individual’s perception of ability to use a computer, which, in turn, has an impact on creating a positive attitude toward using a technology intensive system. Bandura (1986) defined computer self-efficacy in general as: “People’s judgments of

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their capabilities to organize and execute courses of action required to attain designated types of performances. It is concerned not with the skills one has but with judgments of what one can do with whatever skills one possesses.” A society produces some values, ideas, intentions, and speculations on human personality. These values depends on several factors such as, rules, regulations, relationships, culture, tradition, etc. Online adoption can be affected extensively by different influences from the social environment (Engel et al., 1993). Based on the literature reviews (Chase and Tansik, 1978; Donthu and Boonghee, 1998; Furrer et al., 2000; Kale and Sudharshan, 1987; Kogut and Singh, 1988; Kettinger et al., 1995; Li, 1994; Liu et al., 2001), it is evident that those social values, which generate a pre-trust disposition or security concerns on the adopters’ part, are very important for determining PBC. Perceived local environmental security is strongly based on experience from the surroundings, society, culture, local values, and state-wide rules and regulations, and it is affected by both extrinsic and intrinsic motivations (Davis et al., 1992). Customers’ perception of high uncertainty from the status of the society/country environment would dissuade them from choosing an uncertain situation and insist that they avoid uncertainty through risk aversion behavior (Nakata and Sivakumar, 1996). Therefore, customers perceiving high uncertainty from the surrounding environment have higher trust expectation compared with customers having low uncertainty perceptions (Donthu and Boonghee, 1998). Actually, the importance of a social, institutional, judicial, and state structure, that regulates law and orders, increases in the absence of personal relationships between service providers and customers (Shapiro, 1987). Such local structural assurances provide the perceived environmental security that ultimately contributes toward perceived trustworthiness in global operations like an online system. Depending on the above arguments, this research assumes that the perceived local environmental

Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior

security perception of users can create PBC beliefs. Therefore, this paper defines the variable perceived local environmental security as, the degree to which a person perceives overall security assurance from the local environment (where he/she belongs) towards human beings, society, organizations, i.e., toward interrelations. This general security concern of individuals is based on cognitive experiences about security gathered from the country, government, society, local market, shopping, organizations, and interpersonal interaction. Now, the light shed by our previous analyses on technology, psychology, sociology, organizational behavior, and marketing theories and literature review, we propose the theoretical frame of TRA and TPB for online adoption behavior that is shown in Figure 1. The prime characteristic of this model is that we have introduced perceived awareness as the antecedent of technology beliefs, i.e., perceived awareness of technology causes beliefs on technology acceptance. In addition we have identified theoretically different attributes of technology usage beliefs which in turn affect

attitude, subjective norm, and behavioral control of online technology acceptance. These three factors affect behavioral intention to accept ICT-based online system which leads to actual behavior regarding acceptance of online system.

cOnclusIOn The proposed theoretical framework of ICTbased online adoption, grounded in TRA and TPB under the virtual environment context, has significant implications for technology adoption behavior for global users. We have also investigated TAM, TCA, DOI, Socio-technical Theory and Complementary Theory to reveal different attributes of technology beliefs and to develop the final theoretical framework for predicting behavior related to adoption of ICT-based online system based on TPB and TRA. Several researchers have attempted to describe and develop this behavior. Nevertheless, prospective users’ behavior in global context has been largely ignored. However, global users differ significantly, particularly in attitudes

Figure 1. ICT-based online acceptance framework Beliefs Trust Disposition Perceived Usefulness

Perceived Awareness

Attitude toward ICT-based online system acceptance

Perceived Ease of Use Compatibility Image

Subjective Norm toward ICT-based online system acceptance

Behavioral Intention toward ICT-based online system acceptance

Actual Behavior toward ICT-based online system acceptance

Availability of Resources Computer Self-efficacy Perceived Local Environmental Security

PBC toward ICTbased online system acceptance

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and behavioral control beliefs. These differences arise from differences in technological diffusion, government policies, perceived environmental security concerns, organizational aspects, economic phenomena, and social and cultural values. Individuals’ perception of and expectation from an ICT-based online system significantly depend on cultural diversity (Tsikriktsis, 2002; Shareef et al., 2008). Culture contains standards, ideology, values, and expectations that develop personal attitudes and characteristics (Lemme, 1999). Expectations and perceptions are not homogeneous across customers of all countries. For the last couple of decades, several models have been developed to provide an approach for the comparative analysis of different cultures (Hofstede, 1980). Although each of the articles developed cultural models that employed somewhat different terminologies and conceptual paradigms, the core concept generated offer sufficient convergence to provide support for their universality. Over the past decades, the validity of these findings has been confirmed in studies exploring consumer attitude, consumer acceptance, consumer trust disposition, and consumer decision making. A fundamental problem encountered in any attempt to study and analyze culture is based on the fact that concept of culture is very complex and always has relative sense. It is only useful in explaining differences. The proposed theoretical framework, integrating different technology adoption and diffusion and social and cultural theories, successfully incorporated social and cultural beliefs for global intentions of online users. Therefore, this theoretical framework can be used to predict online adoption behavior of global consumers. To validate our judgment, we have focused on cultural differences of global consumers and incorporated some exploratory attributes like Perceived Local Environmental Security, Trust Disposition Attitude, and Availability of Resources to include characteristics of beliefs towards technology adoption of all consumers—either from developed or developing countries.

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PU, PEOU, compatibility, trust disposition, and computer self-efficacy are widely used in predicting ICT-based online acceptance behavior. However, from the theoretical aspects, this research paper finds philosophical underpinnings that the availability of resources and perceived environmental security are two strong beliefs for perceived behavioral control in the global context. It also conjectured that image might be a strong predictor for creating normative beliefs. However, the prime implication of this research is to develop its paradigm for extension of TRA and TPB that beliefs have also an antecedent for the majority of the global population who are unfamiliar with and unaware of ICT-based online systems. Without awareness of the characteristics, components, perceived functional benefits, and a usage of ICT-based online system, behavioral intention and actual use of online systems cannot be developed. Therefore, the fundamental paradigm of this theoretical framework for predicting ICT-based online acceptance behavior of global prospective users is based on the argument that perceived awareness is the primary predictor of developing beliefs to use online systems; perceived awareness should be used as the antecedent of attitudinal, normative, and perceived behavioral control beliefs in the ICT-based online acceptance framework based on TRA and TPB.

fuTuRe ReseARch DIRecTIOn This is a theoretical framework for predicting ICT-based online acceptance behavior for global consumers developed as an extended form of TRA and TPB. However, this extended theoretical framework is a general form. For different countries, perceived awareness might have different conjoint relationships with this model. Also, other attributes of attitudinal, normative, and behavioral control, especially those which are incorporated to capitalize on the global users phenomena― viz., perceived environmental security, image, and

Theory of Planned Behavior and Reasoned Action in Predicting Technology Adoption Behavior

availability of resources have different inherent properties based on country contexts. So future research to operationalize those constructs can be conducted in different countries that differ significantly in social, cultural, economic, political, and technological aspects. Future research can also be carried on to contrast online system diffusion in private and public sector and the ICT-based online system acceptance grounded on the proposed framework in different countries. These types of studies can give proper insights into how those global attributes and beliefs can affect online diffusion and acceptance.

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key TeRms AnD DefInITIOns Adoption of Online System: The term can be viewed as the acceptance and use of, and satisfaction with ICT-based online system. Attitude: Attitude can be defined as human beings’ personal evaluation or approach towards any course of action. It is derived from personal characteristics. Beliefs: It is psychological and behavioral perception about any action to be happened or not happened. Information Technology (IT): IT can be defined as the use of modern computer-based technology in managing and processing information in different public and private sectors. Perceived Awareness (PA): This term can be conceptualized as having and acquiring knowledge as much as a user perceived to be sufficient to learn the characteristics of online system and interact through perception or by means of information about ICT. Perceived Local Environmental Security: The term can be viewed as the degree to which a person perceives general security from the local environment (where he/she belongs) towards human beings, society, organizations, i.e., toward any object. This general security concern of individuals is based on cognitive experiences about security gathered from the country, government, society, local market, shopping, organizations, and inter-personal interaction. Trust: It is the general belief of an individual toward human beings, society, organizations, i.e., toward any object. This belief is also characterized by normative values of society and culture.

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