Group Decision and Negotiation

, Volume 21, Issue 5, pp 703–725 | Cite as

Team Spirit: The Influence of Psychological Collectivism on the Usage of E-Collaboration Tools



The use of information technologies in virtual teams has become common, but little is known about how psychological factors may affect future usage decisions in this context. Our study focuses on psychological collectivism, which is an individual-level form of collectivism (an individual trait capturing people’s “team spirit” or psychological attachments to groups) and investigates how this trait affects team members’ rational decision making processes. Partial Least Squares analysis applied to data collected from 120 team members suggest that psychological collectivism influences both team-referenced perceptions (confidence in one’s team’s capability) and system-referenced perceptions (the perceived usefulness of the e-collaboration tool), and these factors together affect future usage intentions.


Electronic collaboration Technology use Media richness Group potency Confidence in team capabilities Psychological collectivism 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Agarwal R, Prasad J (1999) Are individual differences germane to the acceptance of new information technologies?. Decis Sci 30(2): 361–391CrossRefGoogle Scholar
  2. Akgun AE, Keskin H, Byrne J, Imamoglu SZ (2007) Antecedents and consequences of team potency in software development projects. Inf Manag 44(7): 646–656CrossRefGoogle Scholar
  3. Bajwa DS, Lewis LF, Pervan G, Lai VS (2005) The adoption and use of collaboration information technologies: international comparisons. J Inf Technol 20(2): 130–140. doi: 10.1057/palgrave.jit.2000037 CrossRefGoogle Scholar
  4. Bandura A (1997) Self-efficacy: the exercise of control. W.H. Freeman, New YorkGoogle Scholar
  5. Brown HG, Poole MS, Rodgers TL (2004) Interpersonal traits, complementarity, and trust in virtual collaboration. J Manag Inf Syst 20(4): 115–137Google Scholar
  6. Brown SA, Dennis AR, Venkatesh V (2010) Predicting Collaboration Technology Use: Integrating Technology Adoption and Collaboration Research. J Manag Inf Syst 27(2): 9–53. doi: 10.2753/mis0742-1222270201 CrossRefGoogle Scholar
  7. Cable DM, Yu KYT (2006) Managing job seekers organizational image beliefs: The role of media richness and media credibility. J Appl Psychol 91(4): 828–840CrossRefGoogle Scholar
  8. Chidambaram L, Tung LL (2005) Is out of sight, out of mind? An empirical study of social loafing in technology-supported groups. Inf Syst Res 16(2): 149–168CrossRefGoogle Scholar
  9. Chin WW (1997) Overview of the PLS method. vol 2005. University of Houston, Houston, TX, USAGoogle Scholar
  10. Chin WW (1998) The Partial Least Squares approach for Structural Equation Modeling. In: Marcoulides A (eds) Modern methods for business research. Lawrence Erlbaum Associates, Mahwa, N.J., pp 295–336Google Scholar
  11. Chin WW, Gopal A (1995) Adoption intention in GSS: relative importance of beliefs. Data Base Adv Inf Syst 26(2–3): 42–64CrossRefGoogle Scholar
  12. Colquitt JA, Hollenbeck JR, Ilgen DR, LePine JA, Sheppard L (2002) Computer-assisted communication and team decision-making performance: the moderating effect of openness to experience. J Appl Psychol 87(2): 402–410CrossRefGoogle Scholar
  13. Cramton CD (2001) The mutual knowledge problem and its consequences for dispersed collaboration. Organ Sci 12(3): 346–371CrossRefGoogle Scholar
  14. Curseu PL (2006) Emergent states in virtual teams: a complex adaptive systems perspective. J Inf Technol 21(4): 249–261. doi: 10.1057/palgrave.jit.2000077 CrossRefGoogle Scholar
  15. Daft RL, Lengel RH (1986) Organizational information requirements, media richness and structural design. Manage Sci 32(5): 554–571CrossRefGoogle Scholar
  16. Daft RL, Lengel RH, Trevino LK (1987) Message equivocality, media selection, and manager performance: implications for information systems. MIS Quart 11(3): 355–366CrossRefGoogle Scholar
  17. Dasgupta S, Granger M, McGarry N (2002) User acceptance of e-collaboration technology: an extension of the technology acceptance model. Group Decis Negot 11(1): 87–100CrossRefGoogle Scholar
  18. Davis F (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart 13(3): 319–340CrossRefGoogle Scholar
  19. Davis FD, Bagozzi RP, Warshaw PR (1989) User acceptance of computer technology: A comparison of two theoretical models. Manag Sci 35(8): 982–1003CrossRefGoogle Scholar
  20. Desanctis G, Poole MS (1994) Capturing the complexity in advanced technology use: adaptive structuration theory. Organ Sci 5(2): 121–147CrossRefGoogle Scholar
  21. de Jong A, de Ruyter K, Wetzels M (2005) Antecedents and consequences of group potency: A study of self-managing service teams. Manag Sci 51(11): 1610–1625CrossRefGoogle Scholar
  22. Dennis AR, Fuller RM, Valacich JS (2008) Media, tasks, and communication processes: A theory of media synchronicity. Mis Quart 32(3): 575–600Google Scholar
  23. Dennis AR, Kinney ST (1998) Testing media richness theory in the new media: the effects of cues, feedback, and task equivocality. Inf Syst Res 9(3): 256–274CrossRefGoogle Scholar
  24. Ford DP, Connelly CE, Meister DB (2003) Information systems research and Hofstede’s culture’s consequences: an uneasy and incomplete partnership. IEEE Trans Eng Manag 50(1): 8–25CrossRefGoogle Scholar
  25. Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Market Res 18(1): 39–50CrossRefGoogle Scholar
  26. Friedman RA, Currall SC (2003) Conflict escalation: dispute exacerbating elements of e-mail communication. Human Relat 56(11): 1325–1347CrossRefGoogle Scholar
  27. Fuller MA, Hardin AM, Davison RM (2006) Efficacy in technology-mediated distributed teams. J Manag Inf Syst 23(3): 209–235CrossRefGoogle Scholar
  28. Gefen D, Rose GM, Warkentin M, Pavlou PA (2005) Cultural diversity and trust in IT adoption: a comparison of potential e-voters in the USA and South Africa. J Glob Inf Manag 13(1): 54–78CrossRefGoogle Scholar
  29. Gefen D, Straub D (2005) A practical guide to factorial validity using PLS-graph: tutorial and annotated example. Commun Assoc Inf Syst 16: 91–109Google Scholar
  30. Gefen D, Straub D, Boudreau MC (2000a) Structural equation modeling and regression: guidelines for research practice. Commun Assoc Inf Syst 4(7): 1–77Google Scholar
  31. Gefen D, Straub DW, Boudreau MC (2000b) Structural equation modeling and regression: guidelines for research practice. Commun Assoc Inf Syst 4(7): 1–77Google Scholar
  32. Greenberg J (1987) The college sophomore as guinea pig: setting the record straight. Acad Manag Rev 12(1): 157–159Google Scholar
  33. Gully SM, Incalcaterra KA, Joshi A, Beaubien JM (2002) A meta-analysis of team-efficacy, potency, and performance: Interdependence and level of analysis as moderators of observed relationships. J Appl Psychol 87(5): 819–832CrossRefGoogle Scholar
  34. Guzzo RA, Yost PR, Campbell RJ, Shea GP (1993) Potency in groups: articulating a construct. Br J Soc Psychol 32(1): 87–106CrossRefGoogle Scholar
  35. Harman HH (1967) Modern factor analysis, 2 edn. University of Chicago Press, ChicagoGoogle Scholar
  36. Hedlund J, Ilgen DR, Hollenbeck JR (1998) Decision accuracy in computer-mediated versus face-to-face decision-making teams. Organ Behav Human Decis Process 76(1): 30–47CrossRefGoogle Scholar
  37. Hinds PJ, Mortensen M (2005) Understanding conflict in geographically distributed teams: The moderating effects of shared identity, shared context, and spontaneous communication. Organ Sci 16(3): 290–307. doi: 10.1287/orsc.1050.0122 CrossRefGoogle Scholar
  38. Hofstede G (1980) Culture’s consequences: international differences in work-related values. Sage Publications, Beverly HillsGoogle Scholar
  39. Igbaria M, Iivari J, Maragahh H (1995) Why do individuals use computer technology? A Finnish case-study. Inf Manag 29(5): 227–238CrossRefGoogle Scholar
  40. Jackson CL, Colquitt JA, Wesson MJ, Zapata-Phelan CP (2006) Psychological collectivism: a measurement validation and linkage to group member performance. J Appl Psychol 91(4): 884–899CrossRefGoogle Scholar
  41. Jarvenpaa SL, Leidner DE (1999) Communication and trust in global virtual teams. Organ Sci 10(6): 791–815CrossRefGoogle Scholar
  42. Johns G (2006) The essential impact of context on organizational behavior. Acad Manag Rev 31(2): 386–408CrossRefGoogle Scholar
  43. Joshi KD, Sarker S (2007) Knowledge transfer within information systems development teams: Examining the role of knowledge source attributes. Decis Support Syst 43(2): 322–335. doi: 10.1016/j.dss.2006.10.003 CrossRefGoogle Scholar
  44. Kilgour DM, Eden C (2010) Handbook of group decision and negotiation, vol 4. Advances in group decision and negotiation. Springer, New YorkCrossRefGoogle Scholar
  45. Kim SS (2009) The integrative framework of technology use: an extension and test. MIS Quart 33(3): 513–537Google Scholar
  46. Kim SS, Son JY (2009) Out of dedication or constraint? A dual model of post-adoption phenomena and its empirical test in the context of online services. MIS Quart 33(1): 49–70Google Scholar
  47. King WR, He J (2006) A meta-analysis of the technology acceptance model. Inf Manag 43(6): 740–755CrossRefGoogle Scholar
  48. Kock N (2005) Media richness or media naturalness? The evolution of our biological communication apparatus and its influence on our behavior toward e-communication tools. IEEE Trans Profess Commun 48(2): 117–130. doi: 10.1109/tpc.2005.849649 CrossRefGoogle Scholar
  49. Lee C, Tinsley CH, Bobko P (2002) An investigation of the antecedents and consequences of group-level confidence. J Appl Social Psychol 32(8): 1628–1652CrossRefGoogle Scholar
  50. Leidner DE, Kayworth T (2006) Review: a review of culture in information systems research: Toward a theory of information technology culture conflict. Mis Quart 30(2): 357–399Google Scholar
  51. Lester SW, Meglino BM, Korsgaard MA (2002) The antecedents and consequences of group potency: a longitudinal investigation of newly formed work groups. Acad Manag J 45(2): 352–368CrossRefGoogle Scholar
  52. Lim KH, Benbasat I (2000) The effect of multimedia on perceived equivocality and perceived usefulness of information systems. Mis Quart 24(3): 449–471CrossRefGoogle Scholar
  53. Limayem M, Hirt SG, Cheung CMK (2007) How habit limits the predictive power of intention: the case of information systems continuance. MIS Quart 31(4): 705–737Google Scholar
  54. Lohmoller J-B (1989) Latent variable path modeling with partial least squares. Physica-Verlag, HeidelbergGoogle Scholar
  55. Majchrzak A, Rice RE, Malhotra A, King N, Ba SL (2000) Technology adaptation: the case of a computer-supported inter-organizational virtual team. Mis Quart 24(4): 569–600CrossRefGoogle Scholar
  56. Markus ML (1994) Electronic mail as the medium of managerial choice. Organ Sci 5(4): 502–527CrossRefGoogle Scholar
  57. May A, Carter C (2001) A case study of virtual team working in the European automotive industry. Int J Ind Ergonomics 27(3): 171–186CrossRefGoogle Scholar
  58. Maznevski ML, Chudoba KM (2000) Bridging space over time: global virtual team dynamics and effectiveness. Organ Sci 11(5): 473–492CrossRefGoogle Scholar
  59. McGrath JE (1991) Time, interaction, and performance (TIP): a theory of groups. Small Group Res 22(2): 147–174CrossRefGoogle Scholar
  60. Ngwenyama OK, Lee AS (1997) Communication richness in electronic mail: critical social theory and the contextuality of meaning. MIS Quart 21(2): 145–167CrossRefGoogle Scholar
  61. Ostroff C, Harrison DA (1999) Meta-analysis, level of analysis, and best estimates of population correlations: Cautions for interpreting meta-analytic results in organizational behavior. J Appl Psychol 84(2): 260–270CrossRefGoogle Scholar
  62. Oyserman D, Coon HM, Kemmelmeier M (2002) Rethinking individualism and collectivism: evaluation of theoretical assumptions and meta-analyses. Psychol Bull 128(1): 3–72CrossRefGoogle Scholar
  63. Pauleen DJ, Yoong P (2001) Relationship building and the use of ICT in boundary-crossing virtual teams: a facilitator’s perspective. J Inf Technol 16(4): 205–220. doi: 10.1080/02683960110100391 CrossRefGoogle Scholar
  64. Petter S, Straub D, Rai A (2007) Specifying formative constructs in information systems research. Mis Quart 31(4): 623–656Google Scholar
  65. Rice RE, Shook DE (1990) Relationships of job categories and organizational levels of use of communication channels, including electronic mail—a meta analysis and extension. J Manag Stud 27(2): 195–229CrossRefGoogle Scholar
  66. Richardson RM, Smith SW (2007) The influence of high/low-context culture and power distance on choice of communication media: Students’ media choice to communicate with Professors in Japan and America. Int J Intercult Relat 31(4): 479–501CrossRefGoogle Scholar
  67. Sarker S (2006) Technology adoption by groups: a test of twin predictions based on social structure and technological characteristics. In: IGADIT Workshop, international conference on information systems (ICIS), Milwaukee, WI, Dec 2006Google Scholar
  68. Sarker S, Valacich JS, Sarker S (2005) Technology adoption by groups: a valence perspective. J Assoc Inf Syst 6(2): 37–71Google Scholar
  69. Selwyn N (2003) ‘Doing IT for the kids’: re-examining children, computers and the ‘information society’. Media Cult Soc 25(3): 351–378Google Scholar
  70. Shivers-Blackwell SL (2004) Reactions to outdoor teambuilding initiatives in MBA education. J Manag Dev 23(5): 614–630CrossRefGoogle Scholar
  71. Sun H, Zhang P (2006) The role of moderating factors in user technology acceptance. Int J Human Comput Stud 64(2): 53–78CrossRefGoogle Scholar
  72. Te’eni D (2001) Review: a cognitive-affective model of organizational communication for designing IT. Mis Quart 25(2): 251–312CrossRefGoogle Scholar
  73. Triandis HC (1995) Individualism and collectivism. Westview Press, BoulderGoogle Scholar
  74. Turel O (2010) Interdependence issues in analyzing negotiation data. Group Dec Negot 19(2): 111–125CrossRefGoogle Scholar
  75. Turel O, Yuan Y (2007) User acceptance of web-based negotiation support systems: the role of perceived intention of the negotiating partner to negotiate online. Group Decis Negot 16(5): 451–468CrossRefGoogle Scholar
  76. Turel O, Zhang Y (2010) Does virtual team composition matter? Trait and problem-solving configuration effects on team performance. Behav Inf Technol 29(4): 363–375. doi: 10.1080/01449291003752922 CrossRefGoogle Scholar
  77. Turel O, Zhang Y (2011) Should I e-collaborate with this group? A multilevel model of usage intentions. Inf Manag 48(1): 62–68CrossRefGoogle Scholar
  78. Turel O, Serenko A, Bontis N (2007) User acceptance of wireless short messaging services: deconstructing perceived value. Inf Manag 44(1): 63–73CrossRefGoogle Scholar
  79. Turel O, Serenko A, Bontis N (2010) User acceptance of hedonic digital artifacts: a theory of consumption values perspective. Inf Manag 47(1): 53–59CrossRefGoogle Scholar
  80. Valentine G, Holloway SL (2002) Cyberkids? Exploring children’s identities and social networks in on-line and off-line worlds. Ann Assoc Am Geograph 92(2): 302–319CrossRefGoogle Scholar
  81. Venkatesh V, Davis F (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci 46(2): 186–204CrossRefGoogle Scholar
  82. Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Quart 27(3): 425–478Google Scholar
  83. Webster J, Staples S (2006) Comparing virtual teams to traditional teams: An identification of new research opportunities. In: Martocchio JJ (eds) Research in personal and human resources management, vol 25. Elsevier, Boston, pp 181–214Google Scholar
  84. Weisband SP (1992) Group discussion and 1st advocacy effects in computer-mediated and face-to-face decision-making groups. Organ Behav Human Decis Process 53(3): 352–380CrossRefGoogle Scholar
  85. Whiteoak JW (2007) The relationship among group process perceptions, goal commitment and turnover intention in small committee groups. J Bus Psychol 22(1): 11–20CrossRefGoogle Scholar
  86. Wixom BH, Todd PA (2005) A theoretical integration of user satisfaction and technology acceptance. Inf Syst Res 16(1): 85–102CrossRefGoogle Scholar
  87. Yi MY, Fiedler KD, Park JS (2006) Understanding the role of individual innovativeness in the acceptance of IT-based innovations: comparative analyses of models and measures. Decis Sci 37(3): 393–426CrossRefGoogle Scholar
  88. Zhang DS, Lowry PB, Zhou LN, Fu XL (2007) The impact of individualism—collectivism, social presence, and group diversity on group decision making under majority influence. J Manag Inf Syst 23(4): 53–80CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Mihalyo College of Business & EconomicsCalifornia State UniversityFullertonUSA
  2. 2.McMaster UniversityHamiltonCanada

Personalised recommendations