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Models Of Technology Adoption: An Integrative Approach

Author

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  • Andrei OGREZEANU

    (University Politehnica of Bucharest)

Abstract

The interdisciplinary study of information technology adoption has developed rapidly over the last 30 years. Various theoretical models have been developed and applied such as: the Technology Acceptance Model (TAM), Innovation Diffusion Theory (IDT), Theory of Planned Behavior (TPB), etc. The result of these many years of research is thousands of contributions to the field, which, however, remain highly fragmented. This paper develops a theoretical model of technology adoption by integrating major theories in the field: primarily IDT, TAM, and TPB. To do so while avoiding mess, an approach that goes back to basics in independent variable type’s development is proposed; emphasizing: 1) the logic of classification, and 2) psychological mechanisms behind variable types. Once developed these types are then populated with variables originating in empirical research. Conclusions are developed on which types are underpopulated and present potential for future research. I end with a set of methodological recommendations for future application of the model.

Suggested Citation

  • Andrei OGREZEANU, 2015. "Models Of Technology Adoption: An Integrative Approach," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 5, pages 55-67, June.
    • Handle: RePEc:cmj:networ:y:2015:i:5:p:55-67
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    References listed on IDEAS

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    1. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    2. Sree Nilakanta & Richard W. Scamell, 1990. "The Effect of Information Sources and Communication Channels on the diffusion of Innovation in a Data Base Development Environment," Management Science, INFORMS, vol. 36(1), pages 24-40, January.
    3. Robinson, Leroy Jr. & Marshall, Greg W. & Stamps, Miriam B., 2005. "Sales force use of technology: antecedents to technology acceptance," Journal of Business Research, Elsevier, vol. 58(12), pages 1623-1631, December.
    4. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    5. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    6. Marios Koufaris, 2002. "Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior," Information Systems Research, INFORMS, vol. 13(2), pages 205-223, June.
    7. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    8. Teo, Thompson S. H. & Lim, Vivien K. G. & Lai, Raye Y. C., 1999. "Intrinsic and extrinsic motivation in Internet usage," Omega, Elsevier, vol. 27(1), pages 25-37, February.
    9. Igbaria, M. & Iivari, J., 1995. "The effects of self-efficacy on computer usage," Omega, Elsevier, vol. 23(6), pages 587-605, December.
    10. Kieran Mathieson, 1991. "Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior," Information Systems Research, INFORMS, vol. 2(3), pages 173-191, September.
    11. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    12. Shirley Taylor & Peter A. Todd, 1995. "Understanding Information Technology Usage: A Test of Competing Models," Information Systems Research, INFORMS, vol. 6(2), pages 144-176, June.
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    Cited by:

    1. Cobelli, Nicola & Cassia, Fabio & Burro, Roberto, 2021. "Factors affecting the choices of adoption/non-adoption of future technologies during coronavirus pandemic," Technological Forecasting and Social Change, Elsevier, vol. 169(C).

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    More about this item

    Keywords

    Technology adoption; Innovation diffusion; Technology management; Innovation management; Information technology;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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