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    A Model for Assessing the Performance of Virtual Teams

    153590_29806_2010_Pub_59899_GDN2010_Netherlands.pdf (148.5Kb)
    Access Status
    Open access
    Authors
    Jarman, Rodney
    Pervan, Graham
    Bajwa, D.
    Date
    2010
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Jarman, Rodney and Pervan, Graham and Bajwa, Deepinder. 2010. A Model for Assessing the Performance of Virtual Teams, in de Vreede, G-J. (ed), The 11th Group Decision and Negotiation Conference on System Sciences 2010, Jun 21 2010, pp. 124-127. Delft, The Netherlands: The Centre for Collaboration Science, University of Nebraska.
    Source Title
    Proceedings of the 11th group decision and negotiation conference 2010
    Source Conference
    The 11th group decision and negotiation conference on system sciences - 2010
    ISBN
    9789056382360
    School
    School of Information Systems
    URI
    http://hdl.handle.net/20.500.11937/44968
    Collection
    • Curtin Research Publications
    Abstract

    Virtual teams have been subject to discussion for over a decade ranging from Lipnack and Stamps (1997) through to Wakefield et al. (2008). Generally speaking, virtual teams have members in geographically dispersed locations who have a common purpose and interact through various communication technologies. This paper introduces a model that is an initial attempt to unify different models through the inclusion of all potential factors that can impact virtual team performance. The model, called Virtual Team Assessment (VTA), seeks to explain virtual team performance in terms of 19 outcomes, 60 factors and 23 processes. The outcomes are spread over four domains to provide a broad view of team performance. The factors and processes are an attempt to describe every potential impact on team performance. The VTA model is based in an extensive literature review and has been used to capture data and explain results in three case studies. It was developed because there was no existing model that would provide a frame of reference sufficient to contain all the data collected. While the model itself is not a predictive theory, it has proved useful in classifying research findings and for understanding team performance in the field.

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