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Cohesion in virtual teams: validating the perceived cohesion scale in a distributed setting

Published:19 September 2006Publication History
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Abstract

With the advent of new technology-enabled organizational forms, firms are increasingly relying on virtual teams to accomplish organizational objectives. For those studying these environments, sound measurement of work team phenomena, such as group cohesion, is the key to understanding the impact of these new technologies on team processes and performance. Bollen and Hoyle (1990) created a six-item Perceived Cohesion Scale (PCS) to measure cohesion in groups and employed a study of large groups to assess the psychometric qualities of their scale. Chin et al. (1999) validated the PCS measure using a study of small groups that were collocated. The present effort extends the Chin et al. (1999) adaptation of Bollen and Hoyle's PCS scale to virtual teams and attempts to validate it in this setting. Our findings indicate support for the validity, reliability and factorial stability of the measure in this virtual team context.

References

  1. Arbuckle, J. (1999). AMOS 4.0 Documentation Package, Chicago: Small Waters.Google ScholarGoogle Scholar
  2. Bagozzi, R.P. and Yi, Y. (1988). "On the Evaluation of Structural Equation Models," Journal of the Academy of Marketing Science, Vol.16, pp. 74--94.Google ScholarGoogle ScholarCross RefCross Ref
  3. Bentler, P.M (1990). "Comparative Fit Indices in Structural Models," Psychological Bulletin, Vol.107, pp. 238--246.Google ScholarGoogle ScholarCross RefCross Ref
  4. Bentler, P.M., and Bonnet, D.G. (1980). "Significance Tests and Goodness of Fit in the Analysis of Covariance Structures", Psychological Bulletin, Vol.88, pp. 588-606.Google ScholarGoogle ScholarCross RefCross Ref
  5. Boudreau, M.C., Gefen, D., and Straub, D.W. (2001). "Validation in Information Systems Research: A State-of-the-Art Assessment," MIS Quarterly, Vol.25, No.1, pp. 1--16. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Bollen, K.A. (1986). "Sample Size and Bentler and Bonnet's Nonnormed Fit Index," Psychometrika, Vol.51, 375--377.Google ScholarGoogle ScholarCross RefCross Ref
  7. Bollen, K.A. (1989). Structural Equations Modeling with Latent Variables, New York: Wiley.Google ScholarGoogle Scholar
  8. Bollen, K. A. and Hoyle, R. H. (1990). "Perceived Cohesion: a Conceptual and Empirical Examination," Social Forces, Vol.69, No.2, pp. 479--504.Google ScholarGoogle ScholarCross RefCross Ref
  9. Bollen, K. A., and Stine, R. A. (1993). "Bootstrapping Goodness-of-Fit Measures in Structural Equation Models," in Bollen, K. A., and Long, J. S. (Eds.) Testing Structural Equation Models, Newbury Park, CA: Sage, pp. 111--135.Google ScholarGoogle Scholar
  10. Bormann, E. (1983). "Symbolic Convergence: Organizational Communication and Culture," in Putnam, L.L., and Pacanowsky, M.E. (Eds.), Communication and Organizations: An Interpretive Approach, Beverly Hills, CA: Sage, pp. 99--122.Google ScholarGoogle Scholar
  11. Bormann, E. (1996). "Symbolic Convergence Theory and Communication in Group Decision Making," in Hirokawa, R., and Poole, M. (Eds.), Communication and Group Decision Making (2nd ed.), Thousand Oaks, CA: Sage, pp. 81--113.Google ScholarGoogle Scholar
  12. Bormann, E., Cragan, J., and Shields, D. (1994). "In Defense of Symbolic Convergence Theory: A Look at the Theory and Its Criticism after Two Decades," Communication Theory, Vol.4, pp. 259--294.Google ScholarGoogle ScholarCross RefCross Ref
  13. Bormann, E., Knutson, R., and Musolf, K. (1997). "Why Do People Share Fantasies? An Empirical Investigation of a Basic Tenet of the Symbolic Convergence Communication Theory," Com-munication Studies, Vol.48, pp. 254--276.Google ScholarGoogle ScholarCross RefCross Ref
  14. Browne, M.W. and Cudeck, R.A. (1993). "Alternative Ways of Assessing Model Fit," in Bollen, K.A., and Long, J.S. (Eds.), Testing Structural Equation Models, Newbury Park, CA: Sage, pp. 136--162.Google ScholarGoogle Scholar
  15. Chidambaram, L. (1996). "Relational Development in Computer-Supported Groups," MIS Quarterly, Vol.20, No.2, pp. 143--165. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Chin, W.W., Salisbury, W.D., Pearson, A.W., and Stollak, M.J. (1999). "Perceived Cohesion in Small Groups: Adapting and Testing the Perceived Cohesion Scale in a Small Group Setting," Small Group Research, Vol.30, No.6, pp. 751--766.Google ScholarGoogle ScholarCross RefCross Ref
  17. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.), Hillsdale, NJ: Lawrence Earlbaum Associates.Google ScholarGoogle Scholar
  18. Cook, T.D. and Campbell, D.T. (1979). Quasi-Experimentation: Design and Analysis Issues, Boston, MA: Houghton Mifflin Company.Google ScholarGoogle Scholar
  19. DeSanctis, G. (1988). "Small Group Research in Information Systems: Theory and Method," Paper presented at the Harvard Colloquium on Experimental Research in Information Systems, University of British Columbia, August 19-20.Google ScholarGoogle Scholar
  20. Guzzo, R.A. and Dickson, M.W. (1996). "Teams in Organizations: Recent Research on Performance and Effectiveness," Annual Review of Psychology, Vol.47, pp. 307--338.Google ScholarGoogle ScholarCross RefCross Ref
  21. Griffin, E. (1997). A First Look at Communication Theory (3rd ed.), New York: McGraw-Hill.Google ScholarGoogle Scholar
  22. Hair, J.F., Jr., Anderson, R.E., Tatham, R.L., and Black, W.C. (1998). Multivariate Data Analysis with Readings (5th ed.), Englewood Cliffs, NJ: Prentice-Hall. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Hartley, P. (1997). Group Communication, London, U.K.: Routledge.Google ScholarGoogle Scholar
  24. Hoffer, J.A., Prescott, M.B., and McFadden, F.R. (2002). Modern Database Management (6th ed.), Upper Saddle River, NJ: Prentice-Hall. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Hogg, M.A. (1987). "Social Identity and Group Cohesiveness," in Turner, J.C., Hogg, M.A., Oakes, P.J., Reicher, S.D., and Wetherell, M.S. (Eds.), Rediscovering the Social Group: A Self-Categorization Theory, Oxford: Basil-Blackwell, pp. 89--116.Google ScholarGoogle Scholar
  26. Hogg, M., and Tinsdale, T.S. (2001). Handbook of Social Psychology: Group Processes, Malden, MA: Blackwell.Google ScholarGoogle Scholar
  27. Hollingshead, A.B., and McGrath, J.E. (1995). "Computer-assisted Groups: A Critical Review of Empirical Research," in Guzzo, R.A., and Salas, E. (Eds.), Team Effectiveness and Decision Making in Organizations, San Francisco, CA: Jossey-Bass, pp. 46--78.Google ScholarGoogle Scholar
  28. Hu, L.T., and Bentler, P.M. (1995). "Evaluating Model Fit," in Hoyle, R.H. (Ed.), Structural Equation Modeling: Concepts, Issues, and Applications, Thousand Oaks, CA: Sage, pp. 76--99.Google ScholarGoogle Scholar
  29. Information Technology Services, University of Texas (2003). AMOS FAQ #3: Multiple Group Analysis. Online: http://www.utexas.edu /cc /faqs/stat/amos/amos3.html (accessed January 2004)Google ScholarGoogle Scholar
  30. Johansen, R. (1988). Groupware: Computer Support for Business Teams, New York: Free Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Joreskog, K.G. and Sorbom, D. (1988). LISREL 7: A Guide to the Program and Applications, Chicago: SPSS Inc.Google ScholarGoogle Scholar
  32. Kline, R.B. (1998). Principles and Practice of Structural Equation Modeling, New York: Guilford Press.Google ScholarGoogle Scholar
  33. Langfred, C. (1998). "Is Group Cohesiveness a Double-Edged Sword? An Investigation of the Effects of Cohesiveness on Performance," Small Group Research, Vol.29, No.1, pp. 124--143.Google ScholarGoogle ScholarCross RefCross Ref
  34. Lott, A.J. and Lott, B.E. (1965). "Group Cohesiveness as Intrapersonal Attraction: A review of relationships with antecedent and consequent variables," Psychological Bulletin, Vol.64, pp. 259--309.Google ScholarGoogle ScholarCross RefCross Ref
  35. MacCallum, R.C. and Tucker, L.R. (1991). "Representing sources of error in common factor analysis: Implications for theory and practice," Psychological Bulletin, Vol.109, pp. 501--511.Google ScholarGoogle ScholarCross RefCross Ref
  36. McDonald, R.P. and Marsh, H.W. (1990). "Choosing a Multivariate Model: Noncentrality and Goodness of Fit," Psychological Bulletin, Vol.107, No.2, pp. 247--255.Google ScholarGoogle ScholarCross RefCross Ref
  37. Meredith, W. (1993) "Measurement Invariance, Factor Analysis and Factorial Invariance, Psychometrika, Vol.58, No.4, pp. 525--543.Google ScholarGoogle ScholarCross RefCross Ref
  38. Rosenfeld, L.B. and Gilbert, J.R. (1989). "The Measurement of Cohesion and its Relationship to Dimensions of Self-disclosure in Classroom Settings," Small Group Behavior, Vol.20, No.3, pp. 291--301.Google ScholarGoogle ScholarCross RefCross Ref
  39. Saris, W.E., and Stronkhorst, L.H. (1984). Causal Modeling in Nonexperimental Research: An Introduction to the LISREL Approach, Amsterdam: Sociometric Research Foundation.Google ScholarGoogle Scholar
  40. Seashore, S. (1954). Group Cohesiveness in the Industrial Work Group, Ann Arbor: University of Michigan Press.Google ScholarGoogle Scholar
  41. Stine, R. (1989). "An Introduction to Bootstrap Methods: Examples and Ideas". Sociological Methods and Research, Vol.8, pp. 243--291.Google ScholarGoogle ScholarCross RefCross Ref
  42. Stokes, J.P. (1983). "Components of Group Cohesion: Intermember Attraction, Instrumental Value, and Risk taking," Small Group Behavior, Vol.14, No.2, pp. 163--173.Google ScholarGoogle ScholarCross RefCross Ref
  43. Tucker, L.R. and Lewis, C. (1973). "A Reliability Coefficient for Maximum Likelihood Factor Analysis," Psychometrika, Vol.38, pp. 1--10.Google ScholarGoogle ScholarCross RefCross Ref
  44. Turner, M.E., Pratkanis, A.R., Probasco, P., and Leve, C. (1992). "Threat, Cohesion, and Group Effectiveness: Testing a Social Identity Maintenance Perspective on Groupthink," Journal of Personality and Social Psychology, Vol.63, No.5, pp. 781--796.Google ScholarGoogle ScholarCross RefCross Ref
  45. Wheaton, B., Muthen, B., Alwin, D., and Summers, G. (1977). "Assessing Reliability and Stability in Panel Models," in Heise, D. (Ed.), Sociological Methodology, San Francisco: Jossey-Bass, pp. 84--136.Google ScholarGoogle Scholar

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