The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
The Impact of Knowledge Coordination on Virtual Team Performance over Time1
Abstract
As the role of virtual teams in organizations becomes increasingly important, it is crucial that companies identify and leverage team members’ knowledge. Yet, little is known of how virtual team members come to recognize one another’s knowledge, trust one another’s expertise, and coordinate their knowledge effectively. In this study, we develop a model of how three behavioral dimensions associated with transactive memory systems (TMS) in virtual teams—expertise location, task–knowledge coordination, and cognition-based trust—and their impacts on team performance change over time. Drawing on the data from a study that involves 38 virtual teams of MBA students performing a complex web-based business simulation game over an 8-week period, we found that in the early stage of the project, the frequency and volume of task-oriented communications among team members played an important role in forming expertise location and cognition-based trust. Once TMS were established, however, task-oriented communication became less important. Instead, toward the end of the project, task–knowledge coordination emerges as a key construct that influences team performance, mediating the impact of all other constructs. Our study demonstrates that TMS can be formed even in virtual team environments where interactions take place solely through electronic media, although they take a relatively long time to develop. Furthermore, our findings show that, once developed, TMS become essential to performing tasks effectively in virtual teams.
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Citations
Cites
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Baron, R. M., & Kenny, D. A. (1986) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.51.6.1173 · Cited by 91,532
The Measurement of Observer Agreement for Categorical Data
Landis, J. R., & Koch, G. G. (1977) · Biometrics · doi:10.2307/2529310 · Cited by 81,148
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
A Paradigm for Developing Better Measures of Marketing Constructs
Churchill, G. A. (1979) · Journal of Marketing Research · doi:10.1177/002224377901600110 · Cited by 16,549
Organizational Learning: A Theory of Action Perspective
Argyris, C., & Schön, D. A. (1997) · Reis · doi:10.2307/40183951 · Cited by 11,113 · cited 2×
“(1994) allow each member to express how he/she understands the overall problem and think systematically (Argyris and Schön 1978).”
BackgroundAn integrative model of organizational trust
Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995) · The Academy of Management Review · doi:10.2307/258792 · Cited by 10,736
The Content Analysis Guidebook
Neuendorf, K. A. (2017) · doi:10.4135/9781071802878 · Cited by 9,286 · cited 1×
“According to Neuendorf (2002), the unit of analysis for content coding can either be determined in advance (an etic approach) or generated during the analysis (an emic approach).”
MethodAffect and Cognition Based Trust as Foundations for Interpersonal Cooperation in Organizations
McAllister, D. J. (1995) · Academy of Management Journal · doi:10.2307/256727 · Cited by 7,346
Regression Diagnostics: Identifying Influential Data and Sources of Collinearity
Belsley, D. A., Kuh, E., & Welsch, R. E. (1980) · Wiley Series in Probability and Statistics · doi:10.1002/0471725153 · Cited by 7,297
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003) · Information Systems Research · doi:10.1287/isre.14.2.189.16018 · Cited by 6,479
Estimating within-group interrater reliability with and without response bias
James, L. R., Demaree, R. G., & Wolf, G. (1984) · Journal of Applied Psychology · doi:10.1037/0021-9010.69.1.85 · Cited by 4,774
Lewis, J. D., & Weigert, A. (1985) · Social Forces · doi:10.2307/2578601 · Cited by 4,163
Relation of sample size to the stability of component patterns.
Guadagnoli, E., & Velicer, W. F. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.2.265 · Cited by 2,880
Transactive Memory: A Contemporary Analysis of the Group Mind
Wegner, D. M. (1987) · Theories of Group Behavior · doi:10.1007/978-1-4612-4634-3_9 · Cited by 2,700
The Mutual Knowledge Problem and Its Consequences for Dispersed Collaboration
Cramton, C. D. (2001) · Organization Science · doi:10.1287/orsc.12.3.346.10098 · Cited by 1,916
Demographic Diversity, Conflict, and Work Group Outcomes: An Intervening Process Theory
Pelled, L. H. (1996) · Organization Science · doi:10.1287/orsc.7.6.615 · Cited by 1,489
Out of Sight, Out of Sync: Understanding Conflict in Distributed Teams
Hinds, P. J., & Bailey, D. E. (2003) · Organization Science · doi:10.1287/orsc.14.6.615.24872 · Cited by 974
Toward Contextualized Theories of Trust: The Role of Trust in Global Virtual Teams
Jarvenpaa, S. L., Shaw, T. R., & Staples, D. S. (2004) · Information Systems Research · doi:10.1287/isre.1040.0028 · Cited by 773
Communication, Learning, and Retrieval in Transactive Memory Systems
Hollingshead, A. B. (1998) · Journal of Experimental Social Psychology · doi:10.1006/jesp.1998.1358 · Cited by 471
Socially Shared Cognition at Work: Transactive Memory and Group Performance
Moreland, R. L., Argote, L., & Krishnan, R. (1996) · What's Social about Social Cognition? Research on Socially Shared Cognition in Small Groups · doi:10.4135/9781483327648.n3 · Cited by 456 · cited 1×
“Subsequent studies by Moreland and his colleagues further confirmed that the presence of TMS improved team performance (Moreland et al. 1996; Moreland and Myaskovsky 2000).”
Cited by
Media, Tasks, and Communication Processes: A Theory of Media Synchronicity1
Dennis, A. R., Fuller, R. M., & Valacich, J. S. (2008) · MIS Quarterly · doi:10.2307/25148857 · Cited by 1,511
Virtual Teams Research: 10 Years, 10 Themes, and 10 Opportunities
Gilson, L. L., Maynard, M. T., Jones Young, N. C., Vartiainen, M., & Hakonen, M. (2015) · Journal of Management · doi:10.1177/0149206314559946 · Cited by 825
Leading virtual teams: Hierarchical leadership, structural supports, and shared team leadership.
Hoch, J. E., & Kozlowski, S. W. J. (2014) · Journal of Applied Psychology · doi:10.1037/a0030264 · Cited by 657
Trust and team performance: A meta-analysis of main effects, moderators, and covariates.
De Jong, B. A., Dirks, K. T., & Gillespie, N. (2016) · Journal of Applied Psychology · doi:10.1037/apl0000110 · Cited by 616
Virtual Work: Bridging Research Clusters
Raghuram, S., Hill, N. S., Gibbs, J. L., & Maruping, L. M. (2019) · Academy of Management Annals · doi:10.5465/annals.2017.0020 · Cited by 426
Metadata
- Authors
- Kanawattanachai, P., & Yoo, Y.
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 2007-12-01
- Volume
- 31
- Issue
- 4
- Pages
- 783-808
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W2129539485
- Cited by
- 614
- References
- 22
- FWCI
- 36.56
- Type
- journal article
- Language
- en
- Open access
- closed
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