Journal of Information Technology

, Volume 25, Issue 2, pp 152–169 | Cite as

Gender differences in intentional social action: we-intention to engage in social network-facilitated team collaboration

  • Aaron XL Shen
  • Matthew KO Lee
  • Christy MK Cheung
  • Huaping Chen
Research Article


The growth and popularity of Web 2.0 applications help people to build and maintain their social networks online and further encourage social network-facilitated team collaboration. In this study, we conceptualized the use of instant messaging in social network-facilitated team collaboration as an intentional social action and further investigated the effect of gender differences in the development of we-intention (i.e. collective intention) to engage in such collaboration. A research model was developed and empirically tested with 482 university students in Mainland China. The results demonstrated that the effects of attitude, positive anticipated emotions, and group norms on we-intention were more important for men, whereas the effects of social identity and negative anticipated emotions were more significant for women to collectively participate in social network-facilitated team collaboration. We believe the implications of this study would shed considerable light on both research and practice.


we-intention gender instant messaging social networking anticipated emotions social influence 



The work described in this paper was partially supported by a grant from the Research Grant Council of the Hong Kong Special Administrative Region, China (Project No. CityU 145907). The authors acknowledge with gratitude the generous support of the Hong Kong Baptist University for the project (FRG/08-09/II-58) without which the timely production of the current report/publication would not have been feasible.


  1. Adam, A. (2002). Exploring the Gender Question in Critical Information Systems, Journal of Information Technology 17: 59–67.CrossRefGoogle Scholar
  2. Ahuja, M.K. and Thatcher, J.B. (2005). Moving Beyond Intentions and Toward the Theory of Trying: Effects of work environment and gender on post-adoption information technology use, MIS Quarterly 29 (3): 427–459.Google Scholar
  3. Ajzen, I. and Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior, Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  4. Arena, M. and Benjamin, S. (2009). Leading in a Hyper-Connected Society, Pegasus Communication 19 (9): 10–11.Google Scholar
  5. Armitage, C.J. and Conner, M. (2001). Efficacy of the Theory of Planned Behavior: A meta-analytic review, British Journal of Social Psychology 40: 471–499.CrossRefGoogle Scholar
  6. Bagozzi, R.P. (2007). The Legacy of the Technology Acceptance Model and a Proposal for a Paradigm Shift, Journal of the Association for Information Systems 8 (4): 244–254.Google Scholar
  7. Bagozzi, R.P. and Dholakia, U.M. (2002). Intentional Social Action in Virtual Communities, Journal of Interactive Marketing 16 (2): 2–21.CrossRefGoogle Scholar
  8. Bagozzi, R.P. and Lee, K.H. (2002). Multiple Routes for Social Influence: The role of compliance, internalization, and social identity, Social Psychology Quarterly 65 (3): 226–247.CrossRefGoogle Scholar
  9. Bagozzi, R.P. and Dholakia, U.M. (2006a). Open Source Software User Communities: A study of participation in Linux user groups, Management Science 52 (7): 1099–1115.CrossRefGoogle Scholar
  10. Bagozzi, R.P. and Dholakia, U.M. (2006b). Antecedents and Purchase Consequences of Customer Participation in Small Group Brand Communities, International Journal of Research in Marketing 23 (1): 45–61.CrossRefGoogle Scholar
  11. Bagozzi, R.P., Baumgartner, H. and Pieters, R. (1998). Goal-Directed Emotions, Cognition and Emotion 12 (1): 1–26.CrossRefGoogle Scholar
  12. Boyer, K.K., Olson, J.R., Calantone, R.J. and Jackson, E.C. (2002). Print vs Electronic Surveys: A comparison of two data collection methodologies, Journal of Operations Management 20: 357–373.CrossRefGoogle Scholar
  13. Bratman, M.E. (1997). I Intend that We J, in G.H. Hintikka and R.T. Dordrecht (eds.) Contemporary Action Theory, Dordrecht: Kluwer Academic Publishers, pp. 49–63.Google Scholar
  14. Cheung, C.M.K., Lee, M.K.O. and Chiu, P. (2010). Online Social Networks: Why do we use facebook? Computers in Human Behavior, (in press).Google Scholar
  15. Cheung, C.M.K., Shen, A.X.L., Lee, M.K.O. and Wang, W.P. (2007). Let's Work Together! – We-intention to use instant messaging for e-collaboration, in H. Osterle, J. Schelp and R. Winter (eds.) Proceedings of the 15th European Conference on Information Systems (St. Gallen, Switzerland, June 2007); University of St. Gallen.Google Scholar
  16. Chin, W. (1998). The Partial Least Squares Approach to Structural Equation Modeling, in G.A. Marcoulides (ed.) Modern Methods for Business Research, New Jersey: Lawrence Erlbaum Associates.Google Scholar
  17. Cobbs, C. and Sentinel, O. (2005). Women narrow online gender divide, [WWW document] (accessed 30th October 2009).
  18. Conner, M. and Armitage, C.J. (1998). Extending the Theory of Planned Behavior: A review and avenues for future research, Journal of Applied Social Psychology 28: 1429–1464.CrossRefGoogle Scholar
  19. Crites, S.L., Fabrigar, L.R. and Petty, R.E. (1994). Measuring the Affective and Cognitive Properties of Attitudes: Conceptual and methodological issues, Personality and Social Psychology Bulletin 20: 619–634.CrossRefGoogle Scholar
  20. Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. (1989). User Acceptance of Computer Technology: A comparison of two theoretical models, Management Science 35 (8): 982–1003.CrossRefGoogle Scholar
  21. Dholakia, U.M., Bagozzi, R.P. and Pearo, L.K. (2004). A Social Influence Model of Consumer Participation in Network- and Small-group-based Virtual Communities, International Journal of Research in Marketing 21: 241–263.CrossRefGoogle Scholar
  22. Djamasbi, S. and Loiacono, E.T. (2008). Do Men and Women Use Feedback Provided by their Decision Support Systems (DSS) Differently? Decision Support Systems 44: 854–869.CrossRefGoogle Scholar
  23. Dube, L. and Morgan, M.S. (1996). Trend Effects and Gender Differences in Retrospective Judgments of Consumption Emotions, Journal of Consumer Research 23: 156–162.CrossRefGoogle Scholar
  24. Durndell, A. and Haag, Z. (2002). Computer Self-efficacy, Computer Anxiety, Attitudes toward the Internet and Reported Experience with the Internet, by Gender, in an East European Sample, Computers in Human Behavior 18: 521–535.CrossRefGoogle Scholar
  25. Ellemers, N., Kortekaas, P. and Ouwerkerk, J.W. (1999). Self-Categorisation, Commitment to the Group and Group Self-Esteem as Related but Distinct Aspects of Social Identity, European Journal of Social Psychology 29 (2/3): 371–389.CrossRefGoogle Scholar
  26. Fallows, D. (2005). How women and men use the internet, [WWW document]∼/media//Files/Reports/2005/PIP_Women_and_Men_online.pdf.pdf (accessed 30th October 2009).
  27. Fishbein, M. and Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An introduction to theory and research, Reading, Ma: Addison-Wesley.Google Scholar
  28. Fornell, C. and Larcker, D.F. (1981). Evaluating Structural Equation Models with Unobservable Variable and Measurement Error, Journal of Marketing Research 18 (1): 39–50.CrossRefGoogle Scholar
  29. French, D.P., Sutton, S., Hennings, S.J., Mitchell, J., Wareham, N.J., Griffin, S., Hardeman, W. and Kinmonth, A.L. (2005). The Importance of Affective Beliefs and Attitudes in the Theory of Planned Behavior: Predicting intention to increase physical activity, Journal of Applied Social Psychology 35 (9): 1824–1848.CrossRefGoogle Scholar
  30. Fujita, F., Diener, E. and Sandvik, E. (1991). Gender Differences in Negative Affect and Well-being: The case for emotional intensity, Personality Processes and Individual Differences 61: 427–434.Google Scholar
  31. Gefen, D. and Straub, D.W. (1997). Gender Differences in the Perception and Use of E-mail: An extension to the theory acceptance model, MIS Quarterly 21 (4): 389–400.CrossRefGoogle Scholar
  32. Gilbert, M. (1989). On Social Facts, London: Routledge.Google Scholar
  33. Hair, J.F., Tatham, R.L., Anderson, R.E. and Black, W. (1998). Multivariate Data Analysis, Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  34. Ilie, V., Van Slyke, C., Green, G. and Lou, H. (2005). Gender Differences in Perceptions and Use of Communication Technologies: A diffusion of innovation approach, Information Resources Management Journal 18 (3): 13–31.CrossRefGoogle Scholar
  35. Isaacs, E., Walendowski, A., Whittaker, S., Schiano, D.J. and Kamm, C. (2002). The Character, Functions, and Styles of Instant Messaging in the Workplace, in E.F. Churchill, J. McCarthy, C. Neuwirth and T. Rodden (eds.) Proceedings of the 2002 ACM Conference on Computer Supported Cooperative Work (New Orleans, Louisiana, USA, 16–20 November 2002); New Orleans, Louisiana, USA: ACM Press.Google Scholar
  36. Joreskog, K.G. and Wold, H. (1982). The ML and PLS Techniques for Modeling with Latent Variables: Historical and comparative aspects, in K.G. Joreskog and H. Wold (eds.) Systems Under Indirect Observation: Causality, structure, prediction (Vol. I), Amsterdam: North-Holland, pp. 263–270.Google Scholar
  37. Karahanna, E., Straub, D.W. and Chervany, N.L. (1999). Information Technology Adoption across Time: A cross-sectional comparison of pre-adoption and post-adoption beliefs, MIS Quarterly 23 (2): 183–213.CrossRefGoogle Scholar
  38. Keil, M., Tan, B.C.Y., Wei, K.K. and Saarinen, T. (2000). A Cross-Cultural Study on Escalation of Commitment Behavior in Software Project, MIS Quarterly 24 (2): 299–325.CrossRefGoogle Scholar
  39. Kelman, H.C. (1958). Compliance, Identification, and Internalization: Three processes of attitude change, Journal of Conflict Resolution 2 (1): 51–60.CrossRefGoogle Scholar
  40. Komiak, X. and Benbasat, I. (2006). The Effects of Personalization and Familiarity on Trust and Adoption of Recommendation Agents, MIS Quarterly 30 (4): 941.Google Scholar
  41. Kwong, T.C.H. and Lee, M.K.O. (2004). Understanding the Behavioral Intention to Digital Piracy in Virtual Communities – A propose model, in e-Technology, e-Commerce and e-Service, in K.-J. Lin and J. Ho (eds.) IEEE International Conference, (Taipei, Taiwan, 29–31 March 2004); Taipei: ACM Press, pp. 223–226.Google Scholar
  42. Lee, M.K.O. and Turban, E. (2001). A Trust Model for Consumer Internet Shopping, International Journal of Electronic Commerce 6 (1): 75–91.Google Scholar
  43. Lenhart, A. and Madden, M. (2007). Social networking websites and teens: An overview, [WWW document]∼/media//Files/Reports/2007/PIP_SNS_Data_Memo_Jan_2007.pdf.pdf (accessed 30th October 2009).
  44. Lenhart, A., Madden, M., Macgill, A.R. and Smith, A. (2007). Teens and social media, [WWW document]∼/media//Files/Reports/2007/PIP_Teens_Social_Media_Final.pdf.pdf (accessed 30th October 2009).
  45. Liu, Y. (2002). What Does Research Say About the Nature of Computer-Mediated Communication: Task-oriented, social-emotion-oriented, or both? Electronic Journal of Sociology 6 (1), [www document] (accessed 29th March 2010).
  46. Manstead, A.S.R. and Parker, D. (1995). Evaluating and Extending the Theory of Planned Behavior, European Review of Social Psychology 6: 69–95.CrossRefGoogle Scholar
  47. Minton, H.L. and Schneider, F.W. (1980). Differential Psychology, Prospect Heights, IL: Waveland Press.Google Scholar
  48. Morris, M.G., Venkatesh, V. and Ackerman, P.L. (2005). Gender and Age Differences in Employee Decisions about New Technology: An extension to the theory of planned behavior, IEEE Transactions on Engineering Management 52 (1): 69–84.CrossRefGoogle Scholar
  49. Newsted, P.R., Huff, S.L. and Munro, M.C. (1998). Survey Instruments in Information Systems, MIS Quarterly 22 (4): 553–554.CrossRefGoogle Scholar
  50. Ong, C. and Lai, J. (2006). Gender Differences in Perceptions and Relationships among Dominants of e-Learning Acceptance, Computers in Human Behavior 22: 816–829.CrossRefGoogle Scholar
  51. Osterman Research (2006). Instant messaging tough enough for business: No server required, [WWW document] (accessed 30th October 2009).
  52. Putrevu, S. (2001). Exploring the Origins and Information Processing Differences between Men and Women: Implications for advertisers, Academy of Marketing Science Review 10, [www document] (accessed 29th March 2010).
  53. Radicati Group Inc (2006). Instant Messaging Market: 2006–2010, Palo Alto, CA: The Radicati Group, Inc.Google Scholar
  54. Richard, R., de Vries, N.K. and van der Pligt, J. (1998). Anticipated Regret and Precautionary Sexual Behavior, Journal of Applied Social Psychology 28: 1411–1428.CrossRefGoogle Scholar
  55. Roberts, T. (1991). Gender and the Influence of Evaluations in Self Assessment in Achievement Settings, Psychological Bulletin 109: 297–308.CrossRefGoogle Scholar
  56. Searle, J.R. (1990). Collective Intentions and Actions, in P. Cohen, J. Morgan and M. Pollack (eds.) Intentions in Communication, Cambridge: MIT Press, pp. 401–415.Google Scholar
  57. Shen, A.X.L., Cheung, C.M.K., Lee, M.K.O. and Chen, H. (2010). How Social Influence Affects We-Intention to Use Instant Messaging: The moderating effect of usage experience, Information Systems Frontier, (in press).Google Scholar
  58. Stockard, J., Van-de-Kragt, A.J. and Dodge, P.J. (1988). Gender Roles and Behavior in Social Dilemmas: Are there sex differences in cooperation and in its justification? Social Psychology Quarterly 51: 154–163.CrossRefGoogle Scholar
  59. Teo, T.S.H. (2001). Demographic and Motivation Variables Associated with Internet Usage Behavior, Internet Research 11 (2): 125–137.CrossRefGoogle Scholar
  60. Thomsen, D.K., Mehlsen, M.Y., Viidik, A., Sommerlund, B. and Zachariae, R. (2005). Age and Gender Differences in Negative Affect – Is there a role for emotion regulation? Personality and Individual Differences 38: 1935–1946.CrossRefGoogle Scholar
  61. Tuomela, R. (1995). The Importance of Us: A philosophical study of basic social notions, Stanford: Stanford University Press.Google Scholar
  62. Tuomela, R. (2005). We-intention Revisited, Philosophical Studies 125 (3): 327–369.CrossRefGoogle Scholar
  63. Tuomela, R. (2006). Joint Intention, We-Mode and I-Mode, Midwest Studies in Philosophy 30 (1): 35–58.CrossRefGoogle Scholar
  64. Turner, J.C. (1987). Rediscovering the Social Group: A self-categorization theory, Oxford: B. Blackwell.Google Scholar
  65. van der Pligt, J., Zeelenberg, M., van Dijk, W.W., de Vries, N.K. and Richard, R. (1998). Affect, Attitudes, and Decisions: Let's be more specific, European Review of Social Psychology 8: 33–66.CrossRefGoogle Scholar
  66. Van Slyke, C., Comunale, C.L. and Belanger, F. (2002). Gender Differences in Perceptions of Web-based Shopping, Communication of the ACM 45 (7): 82–86.CrossRefGoogle Scholar
  67. Venkatesh, V. and Davis, F.D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four longitudinal field studies, Management Science 46 (2): 186–204.CrossRefGoogle Scholar
  68. Venkatesh, V. and Morris, M.G. (2000). Why Don’t Men Ever Stop to Ask for Directions? Gender, social influence, and their role in technology acceptance and usage behavior, MIS Quarterly 24 (1): 115–139.CrossRefGoogle Scholar
  69. Venkatesh, V., Morris, M.G. and Ackerman, P.L. (2000). A Longitudinal Field Investigation of Gender Difference in Individual Technology Adoption Decision-Making Processes, Organizational Behavior and Human Decision Processes 83 (1): 33–60.CrossRefGoogle Scholar
  70. Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003). User Acceptance of Information Technology: Toward a unified view, MIS Quarterly 27 (3): 425–478.Google Scholar
  71. Venkatesh, V., Morris, M.G., Sykes, T.A. and Ackerman, P.L. (2004). Individual Reactions to New Technologies in the Workplace: The role of gender as a psychological construct, Journal of Applied Social Psychology 34 (3): 445–467.CrossRefGoogle Scholar
  72. Wallace, D.W., Giese, J.L. and Johnson, J.L. (2004). Customer Retailer Loyalty in the Context of Multiple Channel Strategies, Journal of Retailing 80 (4): 249–263.CrossRefGoogle Scholar
  73. Wilson, M. (2004). A Conceptual Framework for Studying Gender in Information Systems Research, Journal of Information Technology 19: 81–92.CrossRefGoogle Scholar
  74. Wold, H. (1989). Introduction to the Second Generation of Multivariate Analysis, in H. Wold (ed.) Theoretical Empiricism, New York: Paragon House.Google Scholar
  75. Zhang, K.Z.K., Lee, M.K.O., Cheung, C.M.K. and Chen, H. (2009). Understanding the Role of Gender in Bloggers’ Switching Behavior, Decision Support Systems 47 (4): 540–546.CrossRefGoogle Scholar

Copyright information

© Association for Information Technology Trust 2010

Authors and Affiliations

  • Aaron XL Shen
    • 1
  • Matthew KO Lee
    • 2
  • Christy MK Cheung
    • 3
  • Huaping Chen
    • 4
  1. 1.Department of Information SystemsUSTC-CityU Joint Research CenterChina
  2. 2.Department of Information SystemsCity University of Hong KongKowloonHong Kong
  3. 3.Department of Finance and Decision SciencesHong Kong Baptist UniversityKowloonHong Kong
  4. 4.Department of Information SystemsUniversity of Science and Technology of ChinaHefeiP.R. China

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