Richness Versus Parsimony Antecedents of Technology Adoption Model for E-Learning Websites

  • Hsiu-Li Liao
  • Hsi-Peng Lu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5145)


E-learning can be viewed as an innovation in information technology (IT) and learning. The Technology Acceptance Model (TAM) has previously received significant attention in the IS research field. The Perceived Characteristics of Innovating (PCI) antecedents of technology adoption decisions have not been widely researched empirically. This study explores students’ perceptions of utilizing the e-learning website in their decision processes. This work also identifies which model supports a more explanation of variance in the e-learning context. Both TAM and PCI antecedents are investigated in the same context of an e-learning website. Experimental results demonstrate that the PCI constructs explain slightly more variance in users’ intentions of continued use than TAM antecedents. The PCI adoption model provides increasingly rich information concerning the continued use of e-learning website.


Technology Acceptance Model (TAM) Perceived Characteristics of Innovating (PCI) beliefs E-learning Intentions 


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  1. 1.
    Bahreininejad, A.: E-learning and associated issues in Iran. International Journal of Distance Education Technologies 4(4), 1–4 (2006)Google Scholar
  2. 2.
    Agarwal, R., Harahanna, E.: Time flies when you’re having fun: cognitive absorption and beliefs about information technology usage. MIS Quarterly 24(4), 665–694 (2000)CrossRefGoogle Scholar
  3. 3.
    Agarwal, R., Prasad, J.: The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences 28(3), 557–582 (1997)CrossRefGoogle Scholar
  4. 4.
    Brown, A.: Learning from a distance. Journal of Property Management 71(4), 42–45 (2006)Google Scholar
  5. 5.
    Al-Gahtani, S.S., King, M.: Attitudes satisfaction and usage: factors contributing to each in the acceptance of information technology. Behaviour & Information Technology 18(4), 277–297 (1999)CrossRefGoogle Scholar
  6. 6.
    Wixom, B.H., Todd, P.A.: A Theoretical Integration of User Satisfaction and Technology Acceptance. Information Systems Research 16(1), 85–102 (2005)CrossRefGoogle Scholar
  7. 7.
    Barclay, D.W., Higgins, C.A., Thompson, R.: The Partial Least Squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Tech. Stud. 2(2), 285–309 (1995)Google Scholar
  8. 8.
    Chin, P.R.: Newsted: Structural equation modeling analysis with small samples using partial least squares. Statistical Strategies for Small Sample Research (1998)Google Scholar
  9. 9.
    Plouffe, C.R., Hulland, J.S., Vandenbosch, M.: Research report: richness versus parsimony in modeling technology adoption decisions–understanding merchant adoption of a smart card-based payment system. Information systems research 12(2), 208–222 (2001)CrossRefGoogle Scholar
  10. 10.
    Cooper, W.H., Richardson, A.J.: Unfair comparisons. J. Appl. Psych. 71(2), 179–184 (1986)CrossRefGoogle Scholar
  11. 11.
    Douglas, D.E., Van Der Vyver, G.: Effectiveness of e-learning course materials for learning database management systems: an experimental investigation. Journal of Computer Information Systems 44(4), 41–48 (2004)Google Scholar
  12. 12.
    Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13(3), 319–340 (1989)CrossRefGoogle Scholar
  13. 13.
    Davis, F.D.: User Acceptance of Information Technology System Characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies 38(3), 475–487 (1993)CrossRefGoogle Scholar
  14. 14.
    Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: User Acceptance of Computer Technology: A Comparison of Two Theoretical Model. Management Science 35(8), 982–1003 (1989)Google Scholar
  15. 15.
    Fornell, C., Larcker, D.F.: Evaluating structural equation models with unobservable variables and measurement error. Journal Marketing Research 18, 39–50 (1981)CrossRefGoogle Scholar
  16. 16.
    Lin, H.-F., Lee, G.-G.: Effects of socio-technical factors on organizational intention to encourage knowledge sharing. Management Decision 44(1), 74–88 (2006)CrossRefGoogle Scholar
  17. 17.
    Huang, E.: The acceptance of women centric websites. Journal of Computer Information Systems 45(4), 75–83 (2005)Google Scholar
  18. 18.
    Hulland, J.: Use of Partial Least Squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal 20(2), 195–204Google Scholar
  19. 19.
    Jieun, Y., Ha, I., Choi, M., Rho, J.: Extending the TAM for a t-commerce. Information and Management 42(7), 965 (2005)CrossRefGoogle Scholar
  20. 20.
    Koufaris, M.: Applying the technology acceptance model and flow theory to online consumer behaviour. Information Systems Research 13(2), 205–223 (2002)CrossRefGoogle Scholar
  21. 21.
    Lee, M.K.O., Cheung, C.M.K., Chen, Z.: Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation. Information and Management 42(8), 1095 (2005)CrossRefGoogle Scholar
  22. 22.
    Lu, J., Yu, C.S., Liu, C.: Facilitating conditions, wireless trust and adoption intention. Journal of Computer Information Systems 46(1), 17–24 (2005)MathSciNetGoogle Scholar
  23. 23.
    Moore, G.C., Benbasat, I.: Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems 2(3), 192–222 (1991)CrossRefGoogle Scholar
  24. 24.
    Nunnally, J.C.: Psychometric Theory. McGraw-Hill, New York (1978)Google Scholar
  25. 25.
    Palvia, S.C.: Effectiveness of Asynchronous and Synchronous Modes for Learning Computer Software for Endusers: an Experimental Investigation. Journal of Computer Information Systems 41(2) (2000)Google Scholar
  26. 26.
    Fretty, P.: Go the distance. PM Network 20(9), 16–21 (2006)Google Scholar
  27. 27.
    Rogers, E.M.: Diffusion of innovation. The Free Press, New York (1983)Google Scholar
  28. 28.
    Rogers, E.M.: Diffusion on Innovations. The Free Press, New York (1995)Google Scholar
  29. 29.
    Seyal, A.H., Rahim, M., Rahman, M.N.: Determinants of academic use of the Internet: A structural equation model. Behaviour & Information Technology 21(1), 71–86 (2002)CrossRefGoogle Scholar
  30. 30.
    Mackay, S., Stockport, G.J.: Blended learning, classroom and e-learning. The Business Review 5(1), 82–88 (2006)Google Scholar
  31. 31.
    Tornatzky, L., Fleischer, M.: The Processes of Technological Innovation. Lexington Books, New York (1990)Google Scholar
  32. 32.
    Tornatzky, L.J., Klein, K.J.: Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management 29(1), 28–45 (1982)Google Scholar
  33. 33.
    Van Slyke, C., Belanger, F., Comunale: Factors influencing the adoption of web-based shopping the impact of trust. Database for Advances in Information Systems 35(2), 32–46 (2004)Google Scholar
  34. 34.
    Van Slyke, C., Lou, H., Day, J.: The impact of perceived innovation characteristics on intention to use groupware. Information Resources Management Journal 15(1), 5–12 (2002)Google Scholar
  35. 35.
    Venkatesh, V., Davis, F.D.: A model of the antecedents of perceived ease of use: development and test. Decision Sciences 27, 451–481 (1996)CrossRefGoogle Scholar
  36. 36.
    Venkatesh, V., Speier, C., Morris, M.G.: User acceptance enablers in individual decision making about technology toward an integrated model. Decision Sciences 33(2), 297–316 (2002)CrossRefGoogle Scholar
  37. 37.
    Ilie, V., Van Slyke, C., Green, G., Lou, H.: Gender differences in perceptions and use of communication technologies: a diffusion of innovation approach. Information Resources Management Journal 18(3), 13–31 (2005)Google Scholar
  38. 38.
    Yi, Y., Wu, Z., Tung, L.L.: How individual differences influence technology usage behaviour? Toward an integrated framework. Journal of Computer Information Systems 46(2), 52–63 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Hsiu-Li Liao
    • 1
  • Hsi-Peng Lu
    • 1
  1. 1.Department of Information SystemsNational Taiwan University of Science and TechnologyTaipeiTaiwan, R.O.C.

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