Purpose - This paper sets out o determine influences on team performance processes and develop an overall team success model (TSM). Design/methodology/approach - A total of 55 individual students grouped in 18 teams, ranging in size from two to five, were measured at several stages in semester-long team projects. Forty-four separate questions were studied in each measurement stage. These 44 questions were reduced to five factors through exploratory factor analysis (EFA). Structural equation modeling (SEM) was then used to determine the significance and interrelationships of these factors, as well as the influence of gender and grade point average (GPA). Findings - This research develops and validates a series of factors that lead to IT team success. The factors include emotions, personal processes, and team processes. The overall R2 of the final model was high at 0.601. Significant relationships were found between many factors. GPA had a positive impact on team processes, while negative emotions showed a negative correlation with team processes. Team processes and trust had positive impacts on project success/grade. All were significant at p < 0.05. Passive positive emotions reflected a negative effect on project grade but only at p < 0.10. Research limitations/implications - The major limitations of the project are the relatively small sample size as well as the use of student team projects. The work can serve as a framework for larger and more varied projects. Practical implications - Virtually all significant information technology (IT) projects are developed by a group of individuals working together as a team. The development of a team success model which can improve project success can have tremendous value to industry. Implications may be extendable to other team projects. Originality/value - Past analysis of the factors that lead to information systems project success has been neither comprehensive nor conclusive. Further study is recommended with more significant and varied projects to further validate the strong preliminary research findings.
All Science Journal Classification (ASJC) codes
- Management Information Systems
- Organizational Behavior and Human Resource Management
- Management of Technology and Innovation