Examining the antecedents of social networking sites use among CEGEP students

Education and Information Technologies

Volumn 22, Issue 5, 2017, Pages 2103-2123

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

^a MCGILL UNIVERSITY   (Canada)

Author keywords

CEGEP students; Facebook; Need for self expression; TAM

Indexed keywords

EID: 84988611079     PISSN: 13602357     EISSN: 15737608     Source Type: Journal    
DOI: 10.1007/s10639-016-9535-4     Document Type: Article

References (69)

1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
2. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs: Prentice-Hall, NJ.
3. Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215.
4. Boyd, D., & Ellison, N. (2008). Social Network Sites: Definition, History, and Scholarship. Journal of Computer-Mediated Communication, 13(1), 210-230. doi:10.1111/j.1083-6101.2007.00393.x.
5. Burton-Jones, A., & Hubona, G. S. (2006). The mediation of external variables in the technology acceptance model. Information Management, 43(6), 706-717. doi:10.1016/j.im.2006.03.007.
6. Chang, W., & Lee, C. (2013). Trust as a learning facilitator that affects students’ learning performance in the Facebook community: An investigation in a business planning writing course. Computers & Education, 62, 320-327. doi:10.1016/j.compedu.2012.11.007.
7. Chau, P. Y. K. (1996). An empirical investigation on factors affecting the acceptance of CASE by systems developers. Information Management, 30, 269-280.
8. 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.
9. Choi, G., & Chung, H. (2013). Applying the Technology Acceptance Model to Social Networking Sites (SNS): Impact of Subjective Norm and Social Capital on the Acceptance of SNS. International Journal of Human Computer Interaction, 29(10), 619-628. doi:10.1080/10447318.2012.756333.
10. Churchill, G. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64-73.
11. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
12. Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
13. Dahlstrom, E., de Boor, T., Grunwald, P., & Vockley, M. (2011). ECAR National Study of Students and Information Technology in Higher Education. EDUCUASE Center for Applied Research. Retrieved from http://www.educause.edu.
14. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
15. Davis, F. D., Bagozzi, R., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982-1003.
16. 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.
17. Dishaw, M., & Strong, D. (1999). Extending the technology acceptance model with task-technology fit constructs. Information Management, 36(1), 9-21. doi:10.1016/s0378-7206(98)00101-3.
18. Duggan, M. (2015). The Demographics of Social Media Users. Pew Research Center: Internet, Science & Tech Retrieved 28 January 2016, from http://www.pewinternet.org/2015/08/19/the-demographics-of-social-media-users/.
19. English, R., & Duncan-Howell, J. (2008). Facebook goes to college: Using social networking tools to support students undertaking teaching practicum. Journal of Online Learning and Teaching, 4(4), 596-601.
20. Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.
21. Fornell, C., & Larcker, D. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39-50.
22. Garson, J. (2016). "Modal Logic", The Stanford Encyclopedia of Philosophy, Edward N. Zalta (ed.), Spring 2016 Edition, URL = http://plato.stanford.edu/archives/spr2016/entries/logic-modal/, accessed: July 2016.
23. Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(7), 2-77.
24. Greenhow, C., & Askari, E. (2015). Learning and teaching with social network sites: A decade of research in K-12 related education. Education and Information Technologies. doi:10.1007/s10639-015-9446-9.
25. Hair, J., Ringle, C., & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. The Journal of Marketing Theory and Practice, 19(2), 139-152. doi:10.2753/mtp1069-6679190202.
26. Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R. R. Sinkovics & P. N. Ghauri (Eds.), Advances in International Marketing (pp. 277-320). Bingley: Emerald.
27. Hew, K. (2011). Students’ and teachers’ use of Facebook. Computers in Human Behavior, 27(2), 662-676. doi:10.1016/j.chb.2010.11.020.
28. 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.
29. Kabilan, M. K., Ahmad, N., & Abidin, M. J. Z. (2010). Facebook: An online environment for learning of English in institutions of higher education? The Internet and Higher Education, 13(4), 179-187.
30. Kalpidou, M., Costin, D., & Morris, J. (2011). The Relationship Between Facebook and the Well-Being of Undergraduate College Students. Cyberpsychology, Behavior, And Social Networking, 14(4), 183-189. doi:10.1089/cyber.2010.0061.
31. Karahanna, E., & Straub, D. W. (1999). The psychological origins of perceived usefulness and ease-of-use. Information Management, 35(3), 237-250.
32. Karahanna, E., Xin Xu, S., & Zhang, N. (2015). Psychological Ownership Motivation and Use of Social Media. Journal of Marketing Theory and Practice, 23(2), 186-207. doi:10.1080/10696679.2015.1002336.
33. Karvounidis, T., Chimos, K., Bersimis, S., & Douligeris, C. (2014). Evaluating Web 2.0 technologies in higher education using students’ perceptions and performance. Journal of Computer Assisted Learning, 30(6), 577-596. doi:10.1111/jcal.12069.
34. King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information Management, 43, 740-755.
35. Kock, N. (2015a). WarpPLS. Retrieved from http://www.warppls.com
36. Kock, N. (2015b). WarpPLS 5.0 user manual. ScripWarp Systems. Retrieved from http://cits.tamiu.edu/WarpPLS/UserManual_v_5_0.pdf
37. Lederer, A. L., Maupin, D. J., Sena, M. P., & Zhuang, Y. (2000). The technology acceptance model and the World Wide Web. Decision Support Systems, 29(3), 269-282.
38. Lee, Y., Kozar, K., & Larsen, K. (2003). The technology acceptance model: Past, present, and, future. Communications of the Association for Information Systems, 12(50), 752-780.
39. 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), 1-14.
40. Lin, K., & Lu, H. (2011). Why people use social networking sites: An empirical study integrating network externalities and motivation theory. Computers in Human Behavior, 27(3), 1152-1161. doi:10.1016/j.chb.2010.12.009.
41. Manca, S. & Ranieri, M. (2015). Implications of social network sites for teaching and learning. Where we are and where we want to go. Education and Information Technologies. Advance online publication. doi:10.1007/s10639-015-9429-x
42. McFarland, D. J., & Hamilton, D. (2006). Adding contextual specificity to the technology acceptance model. Computers in Human Behavior, 22(3), 427-447. doi:10.1016/j.chb.2004.09.009.
43. 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.
44. Newsroom (2016). Company Info | Facebook Newsroom. Retrieved 20 June 2016, from http://newsroom.fb.com/company-info/
45. Pempek, T., Yermolayeva, Y., & Calvert, S. (2009). College students’ social networking experiences on Facebook. Journal of Applied Developmental Psychology, 30(3), 227-238. doi:10.1016/j.appdev.2008.12.010.
46. Pew Research Center (2015). U.S. Smartphone Use in 2015. Retrieved 18 February 2016, from http://www.pewinternet.org/files/2015/03/PI_Smartphones_0401151.pdf
47. Porter, C., & Donthu, N. (2006). Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics. Journal of Business Research, 59(9), 999-1007. doi:10.1016/j.jbusres.2006.06.003.
48. Rodríguez-Hoyos, C., Haya, I., & Fernández-Díaz, E. (2015). Research on SNS and education: the state of the art and its challenges. Australasian Journal of Educational Technology, 31(1), 100-111.
49. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: The Free Press.
50. 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. doi:10.1016/j.im.2006.10.007.
51. Schroeder, J., & Greenbowe, T. (2009). The chemistry of Facebook: Using social networking to create an online community for the organic chemistry laboratory. Innovate: Journal of Online Education, 5(4).
52. Selwyn, N. (2009). Faceworking: exploring students’ education-related use of Facebook. Learning, Media And. Technology, 34(2), 157-174. doi:10.1080/17439880902923622.
53. Sun, H., & Zhang, P. (2006). The role of moderating factors in user technology acceptance. International Journal of Human Computer Studies, 64(2), 53-78. doi:10.1016/j.ijhcs.2005.04.013.
54. Swanson, E. B. (1988). Information system implementation: Bridging the gap between design and utilization. Homewood, IL: Irwin.
55. Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42(1), 85-92.
56. Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
57. Teo, T. (2009). Modelling technology acceptance in education: A study of pre-service teachers. Computers & Education, 52(2), 302-312. doi:10.1016/j.compedu.2008.08.006.
58. Teo, T. (2014). Modelling Facebook usage among university students in Thailand: the role of emotional attachment in an extended technology acceptance model. Interactive Learning Environments, 1-13. doi:10.1080/10494820.2014.917110.
59. Teo, T., Lee, C. B., & Chai, C. S. (2008). Understanding pre-service teachers’ computer attitudes: Applying and extending the Technology Acceptance Model. Journal of Computer Assisted Learning, 24(2), 128-143.
60. Tess, P. (2013). The role of social media in higher education classes (real and virtual) - a literature review. Computers in Human Behavior, 29(5), A60-A68. doi:10.1016/j.chb.2012.12.032.
61. Thompson, R., Higgins, C., & Howell, J. (1991). Personal Computing: Toward a Conceptual Model of Utilization. MIS Quarterly, 15(1), 125. doi:10.2307/249443.
62. Turkle, S. (2011). Alone together: why We expect more from technology and less from each other. New York: Basic Books.
63. Social Media Update (2014). Social Media Update. Retrieved 9 April 2016, from http://www.pewinternet.org/files/2015/01/PI_SocialMediaUpdate20144.pdf
64. Valenzuela, S., Park, N., & Kee, K. (2009). Is There Social Capital in a Social Network Site?: Facebook Use and College Students’ Life Satisfaction, Trust, and Participation. Journal of Computer-Mediated Communication, 14(4), 875-901. doi:10.1111/j.1083-6101.2009.01474.x.
65. Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27, 451-481.
66. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186-204.
67. 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.
68. Wang, R., Scown, P., Urquhart, C., & Hardman, J. (2012). Tapping the educational potential of Facebook: Guidelines for use in higher education. Education and Information Technologies, 19(1), 21-39. doi:10.1007/s10639-012-9206-z.
69. Wold, H. (1982). Soft modeling: the basic design and some extensions. In K. Joreskog & H. Wold (Eds.), Systems under indirect observation (pp. 1-54). Amsterdam: Netherlands.