Team attributes and performance of operational service teams: An empirical taxonomy development

Lee, Peter K.C.; To, W.M.; Yu, Billy T.W.

Abstract

Teams have been regarded as an integral element of a number of operations management (OM) strategies and many of their related concepts such as group dynamics and people issues are considered important for knowledge of behavioral operations. In practice, the management of operational service teams is challenging for OM managers because of its potential problems such as unstructured tasks and negative member behavior. In this study, operational service teams’ attribute patterns and their associated performance levels were examined using a configuration approach. Based on the data collected from 201 operational service teams in Hong Kong and Macao (China), an empirical taxonomy was developed, comprising team attributes including team use, organizational support, clear goals, collaborative climate, coercive influence and adaptation difficulty. The taxonomy indicated that there were three attribute patterns among the sample teams. The analyzed results indicated that the sample teams of different attribute patterns achieved markedly different levels of team performance. The study contributes to the literature by providing empirical evidence that team attributes and their combined patterns are determinants of operational service teams’ performance. It also contributes to practitioners by reporting the current status of operational service team management and offering guidelines on enhancement of team performance.

Citation

Lee, P. K., To, W., & Yu, B. T. (2013). Team attributes and performance of operational service teams: An empirical taxonomy development. International Journal of Production Economics, 142(1), 51-60. https://doi.org/10.1016/j.ijpe.2012.05.005

• Journal Article Type: Article
• Acceptance Date: May 2, 2012
• Online Publication Date: May 23, 2012
• Publication Date: 2013-03
• Deposit Date: Jun 1, 2023
• Journal: International Journal of Production Economics
• Print ISSN: 0925-5273
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 142
• Issue: 1
• Pages: 51-60
• DOI: https://doi.org/10.1016/j.ijpe.2012.05.005
• Keywords: Industrial and Manufacturing Engineering; Management Science and Operations Research; Economics and Econometrics; General Business, Management and Accounting