Academic researchers’ behavioural intention to use academic social networking sites: A case of Malaysian research universities

Information Development

Volumn 35, Issue 2, 2019, Pages 245-261

  Salahshour Rad, Maryam ^a   Nilashi, Mehrbakhsh ^a   Mohamed Dahlan, Halina ^a   Ibrahim, Othman ^a  

^a UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

Author keywords

academics; Malaysia; researchers; social networking sites; universities; UTAUT

Indexed keywords

EID: 85060020024     PISSN: 02666669     EISSN: 17416469     Source Type: Journal    
DOI: 10.1177/0266666917741923     Document Type: Article

References (74)

1. Ajzen I, (1991) The theory of planned behaviour. Organizational Behaviour and Human Decision Processes 50(2): 179–211.
2. Al-Aufi AS, Fulton C, (2014) Use of social networking tools for informal scholarly communication in humanities and social sciences disciplines. Procedia-Social and Behavioural Sciences 147, 436–445.
3. Al-Badi AH, Al Hinai YS, Sharma SK, Williams S, (2013) Usage of social networking tools in research and collaboration. Journal of Emerging Trends in Economics and Management Sciences 4(6): 515–523.
4. Allen T, Henn G, (2007) The Organization and Architecture Of Innovation. Routledge.
5. Almousa O, (2011) Users’ classification and usage-pattern identification in academic social networks. In Applied Electrical Engineering and Computing Technologies (AEECT), 6-8 December. Jordan: IEEE, 1–6.
6. Arthur JK, Adu-Manu KS, Yeboah C, (2013) A conceptual framework for the adoption of social network technologies (SNTs) in teaching–case of Ghana. IJCSI International Journal of Computer Science 10(5).
7. Bankole FO, Bankole OO, Brown I, (2011) Mobile banking adoption in Nigeria. The Electronic Journal of Information Systems in Developing Countries 47.
8. Barker V, (2009) Older adolescents’ motivations for social network site use: The influence of gender, group identity, and collective self-esteem. Cyber Psychology & Behaviour 12(2): 209–213.
9. Boontarig W, Chutimasakul W, Papasratorn B, (2013) A conceptual model of intention to use health information associated with online social network. Computing, Communications and IT Applications Conference (ComComAp), 1-4 April, Hong Kong, China: IEEE, 25–29.
10. Boyd D, (2008) Facebook’s privacy trainwreck. Exposure, invasion, and social convergence. Convergence: The International Journal of Research into New Media Technologies 14(1): 13–20.
11. Brown SA, Dennis AR, Venkatesh V, (2010) Predicting collaboration technology use: Integrating technology adoption and collaboration research. Journal of Management Information Systems 27(2): 9–54.
12. Bullinger A, Renken U, Moslein K, (2011) Understanding online collaboration technology adoption by researchers-a model and empirical study. Thirty Second International Conference on Information Systems. 4-7 December. Shanghai, China: ICIS, 1–11.
13. Cao X, Cai Z, Zhang X, (2014) Understanding user’s sustained participation in social research network sites. Proceeding of the 19th Pacific Asia Conference on Information Systems (PACIS). 24-28 June, Chengdu, China, 37.
14. Carlos Martins Rodrigues Pinho J, Soares AM, (2011) Examining the technology acceptance model in the adoption of social networks. Journal of Research in Interactive Marketing 5(2/3): 116–129.
15. Chen R, (2013) Member use of social networking sites—an empirical examination. Decision Support Systems 54(3): 1219–1227.
16. Cheung CM, Chan GW, Limayem M, (2005) A critical review of online consumer behaviour: Empirical research. Journal of Electronic Commerce in Organizations 3(4): 1–19.
17. Chin WW, (1998) The partial least squares approach to structural equation modeling. Modern Methods for Business Research 295(2): 295–336.
18. 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.
19. Compeau DR, Higgins CA, (1995) Computer self-efficacy: Development of a measure and initial test. MIS Quarterly 189–211.
20. Davis FD, (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 319–340.
21. Dermentzi E, Papagiannidis S, Toro CO, Yannopoulou N, (2016) Academic engagement: Differences between intention to adopt Social Networking Sites and other online technologies. Computers in Human Behavior 61, 321–332.
22. Ellison NB, Boyd D, (2013) Sociality through Social Network Sites (pp. 151–172). Oxford: Oxford University Press.
23. Elsayed AM, (2016) The use of academic social networks among Arab researchers: A survey. Social Science Computer Review 34(3): 378–391.
24. Ernst CPH, Pfeiffer J, Rothlauf F, (2013) The influence of perceived belonging on social network site adoption. Proceedings of the Nineteenth Americas Conference on Information Systems, 15-17 August. Chicago, Illinois: AMCIS, 1–10.
25. Gefen D, Karahanna E, Straub DW, (2003) Trust and TAM in online shopping: An integrated model. MIS Quarterly 27(1): 51–90.
26. Gruzd A, Staves K, Wilk A, (2012) Connected scholars: Examining the role of social media in research practices of faculty using the UTAUT model. Computers in Human Behaviour 28(6): 2340–2350.
27. Hair JF, Black WC, Babin BJ, Anderson RE, (2010) Multivariate Data Analysis: A Global Perspective (7th). New Jersey: Pearson Education Inc.
28. Henseler J, Ringle CM, Sinkovics RR, (2009) The use of partial least squares path modeling in international marketing. Advances in International Marketing (AIM): 20, 277–320.
29. Hoffman DL, Novak TP, Peralta M, (1999) Building consumer trust online. Communications of the ACM 42(4): 80–85.
30. Jeng W, He D, Jiang J, (2015) User participation in an academic social networking service: A survey of open group users on Mendeley. Journal of the Association for Information Science and Technology 66(5): 890–904.
31. Jiang X, (2011) Privacy concern toward using social networking services: A conceptual model. 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), (pp. 3180–3183) IEEE.
32. Jordan K, (2014) Academics and their online networks: Exploring the role of academic social networking sites. First Monday 19(11).
33. Kaba B, Toure B, (2014) Understanding information and communication technology behavioural intention to use: Applying the UTAUT model to social networking site adoption by young people in a least developed country. Journal of the Association for Information Science and Technology 65(8): 1662–1674.
34. Keil M, Tan BC, Wei KK, Saarinen T, Tuunainen V, Wassenaar A, (2000) A cross-cultural study on escalation of commitment behaviour in software projects. MIS Quarterly 299–325.
35. Khechine H, Lakhal S, Pascot D, Bytha A, (2014) UTAUT model for blended learning: The role of gender and age in the intention to use webinars. Interdisciplinary Journal of E-Learning and Learning Objects 10, 33–52.
36. Kim DJ, Steinfield C, Lai YJ, (2008) Revisiting the role of web assurance seals in business-to-consumer electronic commerce. Decision Support Systems 44(4): 1000–1015.
37. Kwon SJ, Park E, Kim KJ, (2014) What drives successful social networking services? A comparative analysis of user acceptance of Facebook and Twitter. The Social Science Journal 51(4): 534–544.
38. Lakhal S, Khechine H, Pascot D, (2013) Student behavioural intentions to use desktop video conferencing in a distance course: Integration of autonomy to the UTAUT model. Journal of Computing in Higher Education 25(2): 93–121.
39. Lallmahomed MZ, Rahim NZA, Ibrahim R, Rahman AA, (2013) Predicting different conceptualizations of system use: Acceptance in hedonic volitional context (Facebook). Computers in Human Behaviour 29(6): 2776–2787.
40. Leng GS, Lada S, Muhammad MZ, Ibrahim AAHA, Amboala T, (2011) An exploration of social networking sites (SNS) adoption in Malaysia using technology acceptance model (TAM), theory of planned behaviour (TPB) and intrinsic motivation. Journal of Internet Banking and Commerce 16(2): 1–27.
41. Lin HF, (2006) Understanding behavioural intention to participate in virtual communities. Cyber Psychology & Behaviour 9(5): 540–547.
42. Lorenzo-Romero C, Del Chiappa G, (2014) Adoption of social networking sites by Italian. Information Systems and E-Business Management 12(2): 165–187.
43. Lorenzo-Romero C, Constantinides E, Alarcon-del-Amo MDC, (2011) Consumer adoption of social networking sites: implications for theory and practice. Journal of Research in Interactive Marketing 5(2/3): 170–188.
44. Madhusudhan M, (2012) Use of social networking sites by research scholars of the University of Delhi: A study. The International Information & Library Review 44(2): 100–113.
45. Marchewka JT, Liu C, Kostiwa K, (2007) An application of the UTAUT model for understanding student perceptions using course management software. Communications of the IIMA 7(2): 93.
46. McKnight DH, Choudhury V, Kacmar C, (2002) Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research 13(3): 334–359.
47. Miller JB, (2012) Toward a New Psychology of Women (2nd ed.) Boston: Beacon Press.
48. Moore GC, Benbasat I, (1991) Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research 2(3): 192–222.
49. Nandez G, Borrego A, (2013) Use of social networks for academic purposes: A case study. The Electronic Library 31(6): 781–791.
50. Nysveen H, Pedersen PE, (2014) Consumer adoption of RFID-enabled services. Applying an extended UTAUT model. Information Systems Frontiers 1–22.
51. Oh JS, Jeng W, (2011) Groups in academic social networking services: An Exploration of their potential as a platform for multi-disciplinary collaboration. Third International Conference on Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third International Conference on Social Computing (SocialCom) 9-11 October. Boston, United States: IEEE, 545–548.
52. Papadopoulou P, (2007) Applying virtual reality for trust-building e-commerce environments. Virtual Reality 11(2-3): 107–127.
53. Pardamean B, Susanto M, (2012) Assessing user acceptance toward blog technology using the UTAUT model. International Journal of Mathematics and Computers in Simulation 1(6): 203–212.
54. Park J, Yang S, Lehto X, (2007) Adoption of mobile technologies for Chinese consumers. Journal of Electronic Commerce Research 8(3): 196–206.
55. Pelling EL, White KM, (2009) The theory of planned behaviour applied to young people’s use of social networking web sites. Cyber Psychology & Behaviour 12(6): 755–759.
56. Pillai A, Mukherjee J, (2011) User acceptance of hedonic versus utilitarian social networking web sites. Journal of Indian Business Research 3(3): 180–191.
57. Pousttchi K, (2003) Conditions for acceptance and usage of mobile payment procedures. Proceedings of the International Conference on Mobile Business, Vienna, Austria, pp. 201–210.
58. Qin L, Kim Y, Hsu J, Tan X, (2011) The effects of social influence on user acceptance of online social networks. International Journal of Human-Computer Interaction 27(9): 885–899.
59. Rahman ALA, Jamaludin A, Mahmud Z, (2011) Intention to use digital library based on modified UTAUT model: Perspectives of Malaysian postgraduate students. World Academy of Science, Engineering and Technology 75, 116–122.
60. Riffai MMMA, Grant K, Edgar D, (2012) Big TAM in Oman: Exploring the promise of on-line banking, its adoption by customers and the challenges of banking in Oman. International Journal of Information Management 32(3): 239–250.
61. Schondienst V, Krasnova H, Gunther O, Riehle D, (2011) Micro-blogging adoption in the enterprise: An empirical analysis. Proceedings of the 10th International Conference on Wirtschaftsinformatik. Zurich, Switzerland, 16-18 Feb. 22.
62. Sekaran U, (2006) Research Methods for Business: A skill building approach. (4th ed.) New York, NY, John Wiley & Sons.
63. Shin DH, (2010) The effects of trust, security and privacy in social networking: A security-based approach to understand the pattern of adoption. Interacting with Computers 22(5): 428–438.
64. Straub DW, (1989) Validating instruments in MIS research. MIS Quarterly 147–169.
65. Tan X, Qin L, Kim Y, Hsu J, (2012) Impact of privacy concern in social networking web sites. Internet Research 22(2): 211–233.
66. Thelwall M, Kousha K, (2014) Academia. edu: social network or academic network?. Journal of the Association for Information Science and Technology 65(4): 721–731.
67. Van der Heijden H., (2004). User acceptance of hedonic information systems. MIS Quarterly, 695–704.
68. Venkatesh V, Bala H, (2008) Technology acceptance model 3 and a research agenda on interventions. Decision Science 39(2): 273–315.
69. Venkatesh V, Brown SA, Maruping LM, Bala H, (2008) Predicting different conceptualizations of system use: The competing roles of behavioural intention, facilitating conditions, and behavioural expectation. MIS Quarterly 483–502.
70. Venkatesh V, Morris MG, Davis GB, Davis FD, (2003) User acceptance of information technology: Toward a unified view. MIS Quarterly 425–478.
71. Wang YS, Wu MC, Wang HY, (2009) Investigating the determinants and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology 40(1): 92–118.
72. Wei HL, Lin KY, Lu HP, Chuang IH, (2015) Understanding the intentions of users to ‘stick’to social networking sites: A case study in Taiwan. Behaviour & Information Technology 34(2): 151–162.
73. Wu L, Li JY, Fu CY, (2011) The adoption of mobile healthcare by hospital’s professionals: An integrative perspective. Decision Support Systems 51(3): 587–596.
74. Zhou T, (2013) The effect of flow experience on user adoption of mobile TV. Behaviour & Information Technology 32(3): 263–272.