Technological-Personal-Environmental (TPE) Framework: A Conceptual Model for Technology Acceptance at the Individual Level

INTRODUCTION In the literature, there are several theories and models proposed for technology acceptance. In general, there are two streams of those theories and models; one is with assumption of rational decision and utility maximization and another one is irrational decision due to social pressure and imitation behaviors. Some theories and models integrate elements from both streams. On the other hand, the theories and models can also be classified into the firm level and individual level, which were proposed to examine technology acceptance of organizations and of individuals, respectively. Technological-Organizational-Environmental (TOE) framework is a widely used model for examining technology acceptance at the firm level. This model is comprehensive, consisting factors related to three aspects--technological, organizational, and environmental. Although there are several technology acceptance models and theories for technology acceptance at the individual level, those models are not comprehensive as TOE. However, TOE in nature was designed for technology acceptance at the firm level. Therefore, this paper aims to propose an overarching model, which on one hand inherits the comprehensiveness of TOE and on the other hand is adapted for technology acceptance at the individual level. In the following sections, we first review the related theories and models of technology acceptance, followed by the newly proposed model with detailed discussions on the potential variables in the model. Then a discussion is presented. LITERATURE REVIEW Technology Acceptance Theories In the literature, there are several technology acceptance theories. The Theory of Reasoned Action (TRA), proposed by Fishbein and Ajzen (1975), posits that behavioral intentions are determined by an individual's attitude toward the behavior and subjective norms. TRA has two extensions--Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM). TPB, proposed by Ajzen (1991), posits that behavioral intentions are influenced by an individual's attitude toward the behavior, the subjective norms, and the individual's perception of behavioral control. TAM is an adaptation of TRA in the information systems (IS) field. The model posits that technology acceptance is influenced by perceived usefulness, perceived ease of use and subjective norm (Davis, 1989). In Roger's (1962) and Moore and Benbasat's (1991) Innovation Diffusion Theory (IDT), relative advantage, ease of use, and image are postulated to influence individual technology acceptance. Technology Readiness Index (TRI), proposed by Parasuraman (2000), posits that an individual's technology acceptance is "an interplay between drivers (optimism, innovativeness) and inhibitors (discomfort, insecurity) of technology readiness" (p.317). However, only personal factors, rather than any social factors, are considered in this model. All of these models can be categorized as rational choice models, which emphasize self-interest, conscious decision making, and economic optimization. They assume that technology acceptance processes are choice procedures which are systematically conducted and follow a rational path based upon perfect information (Abrahamson, 1991). However, House and Singh (1987) argued that "most assumptions of rational choice theory of decision making are frequently violated in practice" (p.702), and that "much of the empirical work on decision making suggests that decisions are made in much less rational ways than specified by rational choice theory" (p.707). Furthermore, in the real world it is impossible to obtain perfect information, thus bringing forth uncertainty and jeopardizing the anticipation of the decision consequences. Social Factors Although most of the models discussed heretofore consider various social factors, they are generally fragmented and there is a lack of specific focus on such issue (McCarthy et al. …

[1]  Younghwa Lee,et al.  The Technology Acceptance Model: Past, Present, and Future , 2003, Commun. Assoc. Inf. Syst..

[2]  T. C. Edwin Cheng,et al.  Adoption of internet banking: An empirical study in Hong Kong , 2006, Decis. Support Syst..

[3]  Younghwa Lee,et al.  An empirical investigation of anti-spyware software adoption: A multitheoretical perspective , 2008, Inf. Manag..

[4]  Pamela R. Haunschild,et al.  Modes of Interorganizational Imitation: The Effects of Outcome Salience and Uncertainty , 1997 .

[5]  Melinda Korzaan,et al.  The Influence of Personality Traits and Information Privacy Concerns on Behavioral Intentions , 2008, J. Comput. Inf. Syst..

[6]  Mark Casson,et al.  Information and Organization: A New Perspective on the Theory of the Firm , 1997 .

[7]  Vincent S. Lai,et al.  An Empirical Investigation of the Determinants of User Acceptance of Internet Banking , 2003, J. Organ. Comput. Electron. Commer..

[8]  M. Fleischer,et al.  processes of technological innovation , 1990 .

[9]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[10]  Patrick Y. K. Chau,et al.  A perception-based model for EDI adoption in small businesses using a technology-organization-environment framework , 2001, Inf. Manag..

[11]  W. Scott,et al.  Institutions and Organizations. , 1995 .

[12]  Jitendra V. Singh,et al.  Organizational Behavior: Some New Directions for I/O Psychology , 1987 .

[13]  A. Bandura Self-efficacy: toward a unifying theory of behavioral change. , 1977, Psychology Review.

[14]  Lori Rosenkopf,et al.  INSTITUTIONAL AND COMPETITIVE BANDWAGONS: USING MATHEMATICAL MODELING AS A TOOL TO EXPLORE INNOVATION DIFFUSION , 1993 .

[15]  Mark Srite,et al.  The Role of Espoused National Cultural Values in Technology Acceptance , 2006, MIS Q..

[16]  António Soares Aguiar,et al.  Why Do Firms Adopt E-Procurement Systems? Using Logistic Regression to Empirically Test a Conceptual Model , 2008, IEEE Transactions on Engineering Management.

[17]  J. J. Po-An Hsieh,et al.  ScholarWorks @ Georgia State University , 2016 .

[18]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[19]  Diane B. Walz,et al.  Identifying Exceptional Application Software Developers: A Comparison of Students and Professionals , 2003, Commun. Assoc. Inf. Syst..

[20]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[21]  Fred D. Davis,et al.  Extension of the Technology Acceptance Model: Four Longitudinal Field : . , 2000 .

[22]  I. Ajzen The theory of planned behavior , 1991 .

[23]  Pamela S. Tolbert,et al.  Institutional Sources of Change in the Formal Structure of Organizations: The Diffusion of Civil Service Reform, 1880-1935 , 1983 .

[24]  J. March,et al.  Organizational Learning , 2008 .

[25]  Eleanor T. Loiacono,et al.  A Cross-Cultural Comparison of U.S. and Chinese Website Customers , 2005, Journal of International Technology and Information Management.

[26]  James C. McElroy,et al.  Dispositional Factors in Internet Use: Personality Versus Cognitive Style , 2007, MIS Q..

[27]  Paul A. Fadil,et al.  The Moderating Effects of Technology on Career Success: Can Social Networks Shatter the Glass Ceiling? , 2009, Journal of International Technology and Information Management.

[28]  Eric Abrahamson Managerial Fads and Fashions: The Diffusion and Rejection of Innovations , 1991 .

[29]  Richard V. McCarthy,et al.  Building Relationships That Last: Integrating Public Relations Into Web Design , 2004, Journal of International Technology and Information Management.

[30]  Mark Harcourt,et al.  Discriminatory practices in hiring: institutional and rational economic perspectives , 2005 .

[31]  W. Powell,et al.  The iron cage revisited institutional isomorphism and collective rationality in organizational fields , 1983 .

[32]  Qing Hu,et al.  Assimilation of Enterprise Systems: The Effect of Institutional Pressures and the Mediating Role of Top Management , 2007, MIS Q..

[33]  Yajiong Xue,et al.  Avoidance of Information Technology Threats: A Theoretical Perspective , 2009, MIS Q..

[34]  Margaret Tan,et al.  Factors Influencing the Adoption of Internet Banking , 2000, J. Assoc. Inf. Syst..

[35]  Kar Yan Tam,et al.  Factors Affecting the Adoption of Open Systems: An Exploratory Study , 1997, MIS Q..

[36]  A. Parasuraman,et al.  Technology Readiness Index (Tri) , 2000 .

[37]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[38]  Mark S. Granovetter The Strength of Weak Ties , 1973, American Journal of Sociology.

[39]  F. Lai,et al.  Crossing the Chasm - Understanding China's Rural Digital Divide , 2010 .

[40]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[41]  Ali F. Emdad,et al.  Factors and Impacts of Low Utilization of Internet: The Case of Arab Countries , 2009, Journal of International Technology and Information Management.

[42]  Wei-Na Shi,et al.  The adoption of internet banking: An institutional theory perspective , 2008 .