Understanding Knowledge Management System antecedents of performance impact: Extending the Task-technology Fit Model with intention to share knowledge construct

Little investigations have been made to examine the effect of employees׳ intention to share knowledge on Knowledge Management Systems’ (KMS) use, lack of contribution from users has been listed as a failure factor for KMS. Researchers generally assess KMS by frequency of use, disregarding system impact on employees׳ performance, despite its impact on the system׳s long-term success. This paper contributes to KMS research by extending Task Technology Fit (TTF), a model which is widely employed to study KMS, with the intention to share knowledge construct, in investigating the determinants of KMS performance impact. The paper starts with exploratory study, where interviews were conducted with a sample of KM users to explore possible constructs. In light of the interview results, a research hypothetical model was built integrating system and task characteristics constructs of TTF model. To validate the model, a survey was then conducted with 95 administration and technical staff of different managerial levels, for two different Knowledge Management Systems in two organizations. Intention to share knowledge, task characteristics, perceived Task Technology Fit, KMS characteristics, and utilization were found to have substantial influences on KMS performance impact. Among the key factors, intention to share knowledge was found to be especially important as it positively and significantly affects perceived Task Technology Fit, utilization, and KMS performance impact. The suggested integrated model helps for better understanding of KMS from the perspective of users’ motivation, system design, and tasks. This paper contributes-with academic and practical implications for KMS researchers, developers, and managers.