ETiPs: A Rule-based Team Performance Prediction Model Prototype

Abstract

Understanding human potentials in teams are crucial because having the right people in a team can impact team performance. However, to date, there is no consensus on the right composition of team members because team dynamism and its interrelated factors is complex to uncover. Therefore, this paper presents an implementation of a rule-based team performance prediction model prototype or known as eTiPs. This prototype was developed to predict team effectiveness based on four factors: prior academic achievement, personality types, personality diversity, and software development methodology. Three main components of the eTiPs consist of interface, rule-based inference engine, and database was developed to realise the prediction model. A tested and verified IF-THEN rules extracted from rough set technique were used as inference engine of the eTiPs prototype, thus increasing validity and reliability of eTiPs to determine team effectiveness. To assess the usefulness and ease of use of the eTiPs, a usability evaluation was carried out by 12 experts from academic and industrial domain. Results show that the eTiPs able to provide a useful tool for decision makers as early preventive mechanism to predict team effectiveness. Future works will incorporate the eTiPs with intelligent elements to improve decision making process. © 2011 Published by Elsevier Ltd.