stdClass Object ( [id] => 8534 [paper_index] => EW201611-01-001309 [title] => FACTORS AFFECTING UNIVERSITY STUDENTS’ INTENTION TO USE FACEBOOK: A CASE STUDY OF ZARQA UNIVERSITY [description] =>
  1. Aijan, H., & Hartshorne, R. “Investigating faculty decisions to adopt Web 2.0 technologies: theory and empirical tests”, The Internet and Higher Education, 2008, 11(2), 71-80.
  2. Ajzen, I. (1991). The theory of planned behavior. . Organizational behavior and human decision processes, 50, 179-211.
  3. AL-Majali, & N.M, Nik Kmariah, “Applications of Planned Behavior Theory (TPB) on Internet Banking Services Adoption (IBSA) in Jordan: Structural Equation Modeling (SEM) Approach. The 2010 International Conference on Innovation and Management, Penan g, Malaysia, July 7- 10, 2010.
  4. Al Muala, A.M., Nik Mat, N. K., Isa, F. M., Isa, F. M. (2011) Actual Visit Behavior through Antecedents of Tourists Satisfaction among International Tourists. ASEAN MARKETING JOURNAL June 2011 - Vol.III – No1.
  5. Al Muala, A.M., AL Majali, M. M., AL Ziadat, M. (2012).  The usage of internet banking services among Jordanian consumers. Journal of Internet Banking and Commerce, April 2012, Vol. 17, No.1
  6. AL Ziadat, M, AL Majali, M, Al Muala, A.M, Khawaldeh. K (2013). Factors Affecting University Student's Attitudes toward E- Commerce: Case of Mu'tah University. International Journal of Marketing Studies, www.ccsenet.org/ijms. Vol. 5, No. 5, October 2013
  7. Baron, R., & Kenny, D. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.
  8. Brown, S. A., Massey, A. P., Montoya-Weiss, M. M. & Burkman, J. R. (2002). Do I really have to? User acceptance of mandated technology. European Journal of Information Systems, 11, 283-295
  9. Cheung, R., & Vogel, D. “Can Facebook Enhance the Communications between Teachers and Students”, The International Journal of Learning, 2011, 17(11), 386-397.
  10. Constantinides, E. (2004). “Influencing the online consumer’s behavior: the Web experience”. Internet Research. Vol. 14, No. 2, pp. 111-126.
  11. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.
  12. Daud,D,.  Piew,T,. Keoy, K,. Hassan, P (2011).Perceived Technology, Online Trust for the Online Purchase Intention in Malaysia International Journal of Business and Management Vol. 6, No. 6; June 2011 Perceived Risk,
  13. Delafrooz N, Paim LH, Haron SA, Sidin SM, Khatibi A (2009). Factors affecting students’ attitude toward online shopping. Afr. J. Bus. Manag., 3(5):200-9.
  14. Fishbein, M., & Ajzen, I. (1975). Beliefs, Attitude, and intention behavior. London: Addison-Wesley Publishing Company.
  15. Fishbein, M., & Ajzen, I. (1980). Understanding attitudes and predicting family behavior: Prentice-Hall Englewood Cliffs, NJ.
  16. Hair Jr, J. Black, WC/Babin, BJ/Anderson, RE & Tatham, RL (2006): Multivariate Data Analysis. Auflage, Upper Saddle River.
  17. Ito M. et al.., 2010, Hanging Out, Messing Around, and Geeking Out: Kids Living and Learning with New Media, The MIT Press, Cambridge, MA
  18. Gutman J (1982). "A means-end chain model based on consumer categorization Processes". J. Marketing 46: 60-72.
  19. Lenhart, A., Purcell, K., Smith, A., & Zickuhr, K. Social Media and Mobile Internet Use Among Teens and Young Adults, 2010. Retrieved Feb. 21, 2012., from Pew Internet & American Life Project http://pewinternet.org/Reports/2010/Social-Media-and-Young-Adults.aspx
  20. Li,N and Zhang, P (2002). Consumer online Shopping Attitudes and Behavior: An Assessment of research. Eighth Americas Conference on Information System.
  21. Odeh, A. Y. (2007). Factors Affecting Academic Achievement for Students in "Basics of Scientific Research and Informatics" Course. Zarqa Journal for Research and Studies, Vol. 8, No. 2, 2007
  22. Malhotra, Y., & Galletta, D. F. (1999). Extending the technology acceptance model to account for family influence: Theoretical bases and empirical validation. Proceedings of the 32nd Hawaii International Conference on System Sciences, 1999.
  23. Mason, R. Learning technologies for adult continuing education””, Studies in Continuing Education, 2006, 28(2), 121-133.
  24. Mersha, Y, Bishaw, A and Tegegne, F (2013). Factors Affecting Female Students’ Academic Achievement at Bahir Dar University. CICE Hiroshima University, Journal of International Cooperation in Education, Vol.15 No.3 (2013) pp.135 -148.
  25. Michieal KSd (1998). E-shock the electronic shopping revolution: Strategies for retailers and manufactures. London, Mac Millan Business.
  26. Park, S. Y. (2009). An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use e-Learning. Educational Technology & Society, 12 (3), 150–162.
  27. Pedersen PE, Ling R (2003). Modifying adoption research for mobile internet service adoption: cross-disciplinary interactions. In Proceedings of the 36th Hawaii International conference on System Science (HICSS-36), Big Island, HI, Los Alamitos, CA: IEEE Computer Society Press. pp. 6-9.
  28. Ractham, P., Kaewkitipong, L., & Firpo, D. “The Use of Facebook in an Introductory MIS Course: Social Constructivist Learning Environment”. Decision Sciences Journal of Innovative Education, 2012, 10(2), 165-188.
  29. Radner, R. and Rothschild, M. "On the Allocation of Effort," Journal of Economic Theory (1975), pp. 358-376.
  30. Selwyn, N. Screw Blackboard. Do it on Facebook! An investigation of students' educational use of Facebook. Paper presented at the Poke 1.0 - Facebook social research symposium, University of London. http://www.scribd.com/doc/513958/Facebook-seminar-paper-Selwyn, 2007.
  31. Shwu-Ing W (2003). "The relationship between consumer characteristics and attitude toward online shopping". Manag. Intelligence Planning 21(1):37-44.
  32. Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: a test of competing models. Information Systems Research, 6(2), 144-176.
  33. Thompson RL, Higgins CA, Howell JM (1991). Personal Computing: Toward a Conceptual Model of Utilization. MIS Q., 15(1): 125-143.
  34. Szymanski, D.M., and Hise, R.T. (2000). “E-satisfaction: an initial examination”, Journal of Retailing, 76(3), pp. 309-322.
  35. Vandenbosch B, Huff SL (1997). Searching and scanning: how executives obtain information from executive information systems. MIS Q., 21 (March): 81–108.
  36. Venkatesh V, Morris MG, Davis GB, Davis FD (2003). User acceptance of information technology: toward a unified view. MIS Q., 27(3): 425-478.
  37. Venkatesh V, Davis, FD (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Manage. Sci., 45(2): 186-204.
  38. Wolfinbarger M, Gilly MC (2001). Shopping online for freedom, control, and fun. Calif. Manage. Rev., 43(2):34-55.

 

[author] => Dr. Ayed Al Muala [googlescholar] => https://scholar.google.co.in/citations?view_op=view_citation&hl=en&imq=EPRA+International+Journal+of+Economic+and+Business+Review&citation_for_view=KeqZGcIAAAAJ:Tiz5es2fbqcC&gmla=AJsN-F7IAhL3Uv6vA1v_DDofGKjHtPCsCXnpyOYpDt39APx196qDFuXWVB51gtYu6AmMHul2-fSWrBufYfFfrfhteGcbrr8vxFVWXfo1FCTs-sRD0n3SZW4 [doi] => [year] => 2016 [month] => November [volume] => 4 [issue] => 11 [file] => eprapub/EW201611-01-001309.pdf [abstract] =>

The present study attempts to determine the success factors in improving students' intention to use Facebook in Jordanian universities in general and in particular in Zarqa University with the help of technology acceptance model (TAM). The research model comprises of four independent variables namely perceived usefulness, perceived ease of use, family influence, perceived trust and one dependent variable namely students' intention to use Facebook. In the process of conducting the main study, 600 questionnaires were distributed to among Zarqa University students. Out of this number, 70 were undelivered, and 36 questionnaires were incomplete (missing responses). The researcher obtained the achieved response rate a total of 494 responses were usable for subsequent analysis, giving a response rate of 82 %. The questionnaire is divided into four parts: part (1) demographic variables (12 items); part (2) perceived ease of use and perceived usefulness by (10 items) adopted from Davis, (1989); family influence by (5items) adopted from Ajzen and Fishbein (1975); perceived trust by (6 items)adopted from Daud (2011), and part (3) attitude by (5 items) adopted from Shih & Fang (2004), Finally, part (4), student’s intention by (5 items) adopted from Al Muala(2011). Furthermore, this study used Structural Equation Modeling (SEM) by using Amos program instead of multiple regression because SEM can give more superior empirical results (Hair et al., 2006). The findings of the study show a significant and positive link between variables (perceived ease of use, perceived trust, and family influence) and attitude. Additionally, there a significant and positive link between variables (perceived usefulness and attitude) and intention to use Facebook. And one insignificant impact between perceived usefulness and attitude to use Facebook . For mediating effect of perceived usefulness was not mediates.

KEY WORDS: Facebook, Intention, TAM, Jordan.

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