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Predicting Consumer Behavior: An Extension of Technology Acceptance Model

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  • Mohammad Hasan Galib
  • Khalid Ait Hammou
  • Jennifer Steiger

Abstract

The purpose of this study is to examine the predictive power of the technology acceptance model (TAM) on customer’s intention to participate in the social customer relationship management (sCRM) program. Three additional constructs, perceived risk, user satisfaction, and perceived enjoyment were added to the original TAM. The collected data (n=264) were subject to statistical analysis of structural equation modeling, exploratory and confirmatory factor analysis. The study reveals that TAM by itself is not a robust model to predict customer’s intention to participate in the sCRM program. Among the original constructs of TAM, attitude is the only determinant of intention. The impact of perceived usefulness and perceived ease of use was not significant on intention. Among the extended variables, perceived risk is the only variable that significantly influenced intention; perceived enjoyment and user satisfaction did not have any impact on intention. By applying the TAM to the sCRM, this study extends the overall body of the theoretical knowledge surrounding technology acceptance.

Suggested Citation

  • Mohammad Hasan Galib & Khalid Ait Hammou & Jennifer Steiger, 2018. "Predicting Consumer Behavior: An Extension of Technology Acceptance Model," International Journal of Marketing Studies, Canadian Center of Science and Education, vol. 10(3), pages 1-73, August.
    • Handle: RePEc:ibn:ijmsjn:v:10:y:2018:i:3:p:73
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    1. Harrigan, Paul & Soutar, Geoff & Choudhury, Musfiq Mannan & Lowe, Michelle, 2015. "Modelling CRM in a social media age," Australasian marketing journal, Elsevier, vol. 23(1), pages 27-37.
    2. Gruen, Thomas W. & Osmonbekov, Talai & Czaplewski, Andrew J., 2006. "eWOM: The impact of customer-to-customer online know-how exchange on customer value and loyalty," Journal of Business Research, Elsevier, vol. 59(4), pages 449-456, April.
    3. 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.
    4. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    5. 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.
    6. Ha, Sejin & Stoel, Leslie, 2009. "Consumer e-shopping acceptance: Antecedents in a technology acceptance model," Journal of Business Research, Elsevier, vol. 62(5), pages 565-571, May.
    7. Gatignon, Hubert & Robertson, Thomas S, 1985. "A Propositional Inventory for New Diffusion Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 11(4), pages 849-867, March.
    8. 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.
    9. 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.
    10. Bernadette Szajna, 1996. "Empirical Evaluation of the Revised Technology Acceptance Model," Management Science, INFORMS, vol. 42(1), pages 85-92, January.
    11. Forsythe, Sandra M. & Shi, Bo, 2003. "Consumer patronage and risk perceptions in Internet shopping," Journal of Business Research, Elsevier, vol. 56(11), pages 867-875, November.
    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.
    13. Bruner, Gordon II & Kumar, Anand, 2005. "Explaining consumer acceptance of handheld Internet devices," Journal of Business Research, Elsevier, vol. 58(5), pages 553-558, May.
    14. Paul A. Pavlou & David Gefen, 2004. "Building Effective Online Marketplaces with Institution-Based Trust," Information Systems Research, INFORMS, vol. 15(1), pages 37-59, March.
    15. Hong-Mei Chen & Stephen L. Vargo, 2014. "Rethinking Social CRM Design: A Service-Dominant Logic Perspective," Progress in IS, in: Francisco J. Martínez-López (ed.), Handbook of Strategic e-Business Management, edition 127, pages 767-784, Springer.
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    2. Dovilė Barysė, 2022. "People’s Attitudes towards Technologies in Courts," Laws, MDPI, vol. 11(5), pages 1-28, September.

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