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.
- Arbuckle, J. (1999). AMOS 4.0 Documentation Package, Chicago: Small Waters.Google Scholar
- 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 ScholarCross Ref
- Bentler, P.M (1990). "Comparative Fit Indices in Structural Models," Psychological Bulletin, Vol.107, pp. 238--246.Google ScholarCross Ref
- 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 ScholarCross Ref
- 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 ScholarDigital Library
- Bollen, K.A. (1986). "Sample Size and Bentler and Bonnet's Nonnormed Fit Index," Psychometrika, Vol.51, 375--377.Google ScholarCross Ref
- Bollen, K.A. (1989). Structural Equations Modeling with Latent Variables, New York: Wiley.Google Scholar
- 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 ScholarCross Ref
- 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 Scholar
- 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 Scholar
- 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 Scholar
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 Scholar
- Chidambaram, L. (1996). "Relational Development in Computer-Supported Groups," MIS Quarterly, Vol.20, No.2, pp. 143--165. Google ScholarDigital Library
- 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 ScholarCross Ref
- Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.), Hillsdale, NJ: Lawrence Earlbaum Associates.Google Scholar
- Cook, T.D. and Campbell, D.T. (1979). Quasi-Experimentation: Design and Analysis Issues, Boston, MA: Houghton Mifflin Company.Google Scholar
- 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 Scholar
- 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 ScholarCross Ref
- Griffin, E. (1997). A First Look at Communication Theory (3rd ed.), New York: McGraw-Hill.Google Scholar
- 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 ScholarDigital Library
- Hartley, P. (1997). Group Communication, London, U.K.: Routledge.Google Scholar
- Hoffer, J.A., Prescott, M.B., and McFadden, F.R. (2002). Modern Database Management (6th ed.), Upper Saddle River, NJ: Prentice-Hall. Google ScholarDigital Library
- 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 Scholar
- Hogg, M., and Tinsdale, T.S. (2001). Handbook of Social Psychology: Group Processes, Malden, MA: Blackwell.Google Scholar
- 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 Scholar
- 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 Scholar
- 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 Scholar
- Johansen, R. (1988). Groupware: Computer Support for Business Teams, New York: Free Press. Google ScholarDigital Library
- Joreskog, K.G. and Sorbom, D. (1988). LISREL 7: A Guide to the Program and Applications, Chicago: SPSS Inc.Google Scholar
- Kline, R.B. (1998). Principles and Practice of Structural Equation Modeling, New York: Guilford Press.Google Scholar
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- 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 ScholarCross Ref
- Meredith, W. (1993) "Measurement Invariance, Factor Analysis and Factorial Invariance, Psychometrika, Vol.58, No.4, pp. 525--543.Google ScholarCross Ref
- 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 ScholarCross Ref
- Saris, W.E., and Stronkhorst, L.H. (1984). Causal Modeling in Nonexperimental Research: An Introduction to the LISREL Approach, Amsterdam: Sociometric Research Foundation.Google Scholar
- Seashore, S. (1954). Group Cohesiveness in the Industrial Work Group, Ann Arbor: University of Michigan Press.Google Scholar
- Stine, R. (1989). "An Introduction to Bootstrap Methods: Examples and Ideas". Sociological Methods and Research, Vol.8, pp. 243--291.Google ScholarCross Ref
- 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 ScholarCross Ref
- Tucker, L.R. and Lewis, C. (1973). "A Reliability Coefficient for Maximum Likelihood Factor Analysis," Psychometrika, Vol.38, pp. 1--10.Google ScholarCross Ref
- 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 ScholarCross Ref
- 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 Scholar
Index Terms
- Cohesion in virtual teams: validating the perceived cohesion scale in a distributed setting
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