Open Access
Issue
MATEC Web of Conferences
Volume 56, 2016
2016 8th International Conference on Computer and Automation Engineering (ICCAE 2016)
Article Number 01012
Number of page(s) 6
Section Computer and Information technologies
DOI https://doi.org/10.1051/matecconf/20165601012
Published online 26 April 2016
  1. F. D. Davis, A technology acceptance model for empirically testing new end-user information systems: Theory and results. Massachusetts Institute of Technology, Sloan School of Management, (1986).
  2. M. Fishbein, I. Ajzen, Belief, attitude, intention and behaviour: An introduction to theory and research, Boston, Massachusetts: Addison-Wesley (1975).
  3. F. D. Davis, Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart., 13(3), 319–340 (1989). [CrossRef]
  4. I. Ajzen, The theory of planned behavior. Organ. Behav. Hum. Decis. Process., 50(2), 179–211 (1991). [CrossRef]
  5. F. D. Davis, R. P. Bagozzi, P. R. Warshaw, User acceptance of computer technology: A comparison of two theoretical models. Manag. Sci.’ 982–1003 (1989). [CrossRef]
  6. V. Venkatesh, F. D. Davis, A theoretical extension of the technology acceptance model: Four longitudinal field studies. Manag.Sci., 46(2), 186–204 (2000). [CrossRef]
  7. J. Schepers, M. Wetzels, A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Info. & Manag., 44(1), 90–103 (2007). [CrossRef]
  8. V. Venkatesh, H. Bala, Technology acceptance model 3 and a research agenda on interventions. Decis. Sci., 39(2), 273–315 (2008). [CrossRef]
  9. W. R. King, J. He, A meta-analysis of the technology acceptance model. Info. & Manag., 43(6), 740–755 (2006). [CrossRef]
  10. V. Venkatesh, M. G. Morris, Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quart., 24(1), 115–139 (2000). [CrossRef]
  11. V. Venkatesh, Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion in the technology acceptance model. Info. Syst. Res., 11(4), 342–365 (2000). [CrossRef]
  12. V. Venkatesh, M. G. Morris, G.B. Davis, F. D. Davis, User acceptance of information technology: Toward a unified view. MIS Quart., 27(3), 425–478 (2003). [CrossRef]
  13. T. J. Larsen, A. M. Sorebo, O. Sorebo, The role of task-technology fit as users motivation to continue information system use. Comput. Hum. Behav. 25(3), 778–784(2009). [CrossRef]
  14. J. M. O. Egea, M. V. R. Gonzales, Explaining physicians’ acceptance of EHCR systems: An extension of TAM with trust and risk factors. Comput. Hum. Behav., 27(1),319–332 (2011). [CrossRef]
  15. T. S. Behrend, E. N. Wiebe, J. E. London, E. C. Johnson, Cloud computing adoption and usage in community colleges. Behav. & Info. Tech., 30(2), 231–240 (2011). [CrossRef]

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