With the increasing use of knowledge management technologies for collaborative work, organizations must recognize how to evaluate individual performance. User evaluations of information systems are frequently used as measures of MIS success, since it is extremely difficult to get objective measures of system performance. When the technology meets the user¡¦s needs and provides features that support the fit of the requirements of the task, positive performance impacts will result. This dissertation takes the special characteristics of the knowledge management system (KMS) and task into a research model and extends the theory of task technology fit with concepts from Fit-Appropriation Model. This dissertation goes on to empirically test the research model by investigating the task and related KMS characteristics. Furthermore, it seeks to understand the task technology fit, which links with KMS use and individual performance. Four hypotheses are developed. Structural equation modeling (SEM) techniques and moderated regressions will be used to provide statistical support indicating that there is a positive relationship between task-technology fit, the use of knowledge management systems and individual performance. The data was collected from 203 KMS users. This dissertation concludes with a discussion of the implications that the results have for future research, and managerial practices are described.