Does size matter? An investigation into the role of virtual team size in IT service provisioning
Industrial Management & Data Systems
Article publication date: 17 October 2016
The purpose of this paper is to investigate the potential influence of virtual team size on team performance by examining group processes in the context of information technology (IT) service provisioning. This paper proposes a theoretical model of the relationships and presents an empirical study to verify the model.
Utilizing a survey questionnaire as the data collection instrument, this study focuses on IT service provisioning professionals who are actively engaged in virtual work contexts to test the relationships proposed by the theoretical model. A consistent version of the partial least square structural equation modeling (PLS-SEM) approach is used to assess the proposed hypotheses.
Although the statistical analyses did not provide support for the hypothesized effects of team size on virtual team performance, the results provide novel insights that may help teams overcome the functioning challenges that they face, as reported in the previous literature on virtual team size. In addition, the results highlight the importance of specific group processes for obtaining superior team performance.
Currently, virtual teams are a reality in several organizations, especially in the IT service provisioning industry. However, despite its importance, the literature suggests that virtual team size has not yet been fully explored as a possible means of enhancing group collaboration in such contexts. This paper attempts to provide an empirical contribution to this field using the latest developments in PLS-SEM.
The authors would like to thank Guest Editor Professor Jorg Henseler and two anonymous reviewers for their valuable comments and recommendations that helped enhance the quality of this paper.
Watanuki, H.M. and Moraes, R.d.O. (2016), "Does size matter? An investigation into the role of virtual team size in IT service provisioning", Industrial Management & Data Systems, Vol. 116 No. 9, pp. 1967-1986. https://doi.org/10.1108/IMDS-07-2015-0300
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