Examining the antecedents of Facebook acceptance via structural equation modeling: A case of CEGEP students

Knowledge Management and E-Learning

Volumn 9, Issue 1, 2017, Pages 69-89

  Doleck, Tenzin ^a   Bazelais, Paul ^a   Lemay, David John ^a  

^a MCGILL UNIVERSITY   (Canada)

Author keywords

Antecedents of technology use; CEGEP; College students; Facebook; Social media; Technology acceptance

Indexed keywords

EID: 85016119911     PISSN: 20737904     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (58)

1. Agarwal, R., Sambamurthy, V., & Stair, R. (2000). Research report: The evolving relationship between general and specific computer self-efficacy-An empirical assessment. Information Systems Research, 11(4), 418-430. http://dx.doi.org/10.1287/isre.11.4.418.11876
2. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
3. Bandura, A. (1995). Exercise of personal and collective efficacy in changing societies. In A. Bandura (Ed.), Self-efficacy in changing societies (pp. 1-45). New York: Cambridge University Press.
4. Burton-Jones, A., & Hubona, G. S. (2006). The mediation of external variables in the technology acceptance model. Information & Management, 43(6), 706-717. http://doi.org/10.1016/j.im.2006.03.007
5. Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Modern Methods for Business Research (pp. 295-336). Mahwah, NJ: Erlbaum.
6. Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211. http://dx.doi.org/10.2307/249688
7. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
8. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. http://dx.doi.org/10.1287/mnsc.35.8.982
9. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132. http://dx.doi.org/10.1111/j.1559-1816.1992.tb00945.x
10. Doleck, T., Bazelais. P., & Lemay, D. J. (2016). Examining the antecedents of social networking sites use among CEGEP students. Education and Information Technologies. doi: 10.1007/s10639-016-9535-4
11. Finstad, K. (2010). Response interpolation and scale sensitivity: Evidence against 5-point scales. Journal of Usability Studies, 5(3), 104-110.
12. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
13. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
14. Gefen, D. (2002). Customer loyalty in e-commerce. Journal of Association for Information Systems, 3, 27-51.
15. Gefen, D. (2003). TAM of just plain habit: A look at experienced online shoppers. Journal of Organizational and End User Computing, 15(3), 1-13.
16. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Inexperience and experience with online stores: The importance of tam and trust. IEEE Transactions On Engineering Management, 50(3), 307-321. http://dx.doi.org/10.1109/tem.2003.817277
17. Gefen, D., Straub, D. W., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information System, 4: 7.
18. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152. http://dx.doi.org/10.2753/mtp1069-6679190202
19. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135.
20. Holmström, S. (2007). Niklas Luhmann: Contingency, risk, trust and reflection. Public Relations Review, 33(3), 255-262. http://doi.org/10.1016/j.pubrev.2007.05.003
21. Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195-204.
22. Jamieson, S. (2004). Likert scales: How to (ab)use them. Medical Education, 38(12), 1217-1218. http://dx.doi.org/10.1111/j.1365-2929.2004.02012.x
23. Jarvenpaa, S. L., Tractinsky, N., & Vitale, M. (2000). Consumer trust in an internet store. Information Technology and Management, 1, 45-71.
24. King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & Management, 43(6), 740-755. http://doi.org/10.1016/j.im.2006.05.003
25. Lai, H. M., & Chen, C. P. (2011). Factors influencing secondary school teachers' adoption of teaching blogs. Computers & Education, 56(4), 948-960.
26. Lampe, C., Wohn, D. Y., Vitak, J., Ellison, N. B., & Wash, R. (2011). Student use of Facebook for organizing collaborative classroom activities. International Journal of Computer-Supported Collaborative Learning, 6(3), 329-347. http://dx.doi.org/10.1007/s11412-011-9115-y
27. Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191-204. http://dx.doi.org/10.1016/s0378-7206(01)00143-4
28. Libaque-Saenz, C. F., Wong, S. F., Chang, Y., Ha, Y. W., & Park, M.-C. (2014). Understanding antecedents to perceived information risks: An empirical study of the Korean telecommunications market. Information Development, 32(1), 91-106. http://doi.org/10.1177/0266666913516884
29. Lok, C. K. (2015). Adoption of smart card-based e-payment system for retailing in Hong Kong using an extended technology acceptance model. In M. Quaddus & A. G. Woodside (Eds.), E-services Adoption: Processes by Firms in Developing Nations Advances in Business Marketing and Purchasing (pp. 255-466). Emerald Group.
30. Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709-734. http://dx.doi.org/10.5465/amr.1995.9508080335
31. MacCallum, F. (2011). Understanding peer influence in children and adolescents. Child and Adolescent Mental Health, 16(3), 174-175. http://dx.doi.org/10.1111/j.1475-3588.2011.00617-10.x
32. McCoy, S., Everard, A., & Jones, B. M. (2005). An examination of the technology acceptance model in Uruguay and the US: A focus on culture. Journal of Global Information Technology Management, 8(2), 27-45.
33. McFarland, D. J., & Hamilton, D. (2006). Adding contextual specificity to the technology acceptance model. Computers in Human Behavior, 22(3), 427-447. http://doi.org/10.1016/j.chb.2004.09.009
34. Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222. http://dx.doi.org/10.1287/isre.2.3.192
35. Neufeld, G., & Maté, G. (2006). Hold on to your kids: Why parents need to matter more than peers. New York: Ballantine Books.
36. Newsroom. (2016). Company Info | Facebook Newsroom. Retrieved from http://newsroom.fb.com/company-info/
37. Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101-134.
38. Ringle, C. M., Wende, S., & Becker, J. M. (2015). SmartPLS 3. Bönningstedt: SmartPLS.
39. Rogers, E. M. (2003). Diffusion of innovations (5th edition). New York: The Free Press.
40. Ryan, A. M. (2000). Peer groups as a context for the socialization of adolescents' motivation, engagement, and achievement in school. Educational Psychologist, 35(2), 101-111. http://dx.doi.org/10.1207/s15326985ep3502-4
41. Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44(1), 90-103. http://doi.org/10.1016/j.im.2006.10.007
42. Straub, D., Keil, M., & Brenner, W. (1997). Testing the technology acceptance model across cultures: A three country study. Information & Management, 33(1), 1-11.
43. Sun, H., & Zhang, P. (2006). The role of moderating factors in user technology acceptance. International Journal of Human Computer Studies, 64(2), 53-78. http://doi.org/10.1016/j.ijhcs.2005.04.013
44. Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
45. Teo, T. (2009). Modelling technology acceptance in education: A study of pre-service teachers. Computers & Education, 52(2), 302-312. http://dx.doi.org/10.1016/j.compedu.2008.08.006
46. Teo, T., & Fan, X. (2013). Coefficient alpha and beyond: Issues and alternatives for educational research. Asia-Pacific Education Researcher, 22(2), 209-213. http://dx.doi.org/10.1007/s40299-013-0075-z
47. Teo, T. S. H., Lim, V. K. G., & Lai, R. Y. C. (1999). Intrinsic and extrinsic motivation in Internet usage. Omega, 27(1), 25-37. http://dx.doi.org/10.1016/s0305-0483(98)00028-0
48. Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 125-143. http://dx.doi.org/10.2307/249443
49. Triandis, H. C. (1971). Attitude and attitude change. John Wiley & Sons, New York.
50. Turkle, S. (2011). Alone together: Why we expect more from technology and less from each other. New York: Basic Books.
51. Vanderstraeten, R. (2002). Parsons, Luhmann and the theorem of double contingency. Journal of Classical Sociology, 2(1), 77-92. http://doi.org/10.1177/1468795X02002001684
52. Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365. http://dx.doi.org/10.1287/isre.11.4.342.11872
53. Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481.
54. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
55. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
56. Wold, H. (1982). Soft modeling: The basic design and some extensions. In K. G. Jöreskog & H. Wold (Eds.), Systems Under Indirect Observation, Part II. Amsterdam: North Holland Press.
57. Yi, M. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information & Management, 43(3), 350-363. http://dx.doi.org/10.1016/j.im.2005.08.006
58. Yousafzai, S. Y., Foxall, G. R., & Pallister, J. G. (2010). Explaining internet banking behavior: Theory of reasoned action, theory of planned behavior, or technology acceptance model? Journal of Applied Social Psychology, 40(5), 1172-1202. http://dx.doi.org/10.1111/j.1559-1816.2010.00615.x