A Conceptual Framework for Team Selection using Semantic Case-based Reasoning
DescriptionOrganizations have come to realize the importance of teamwork because there are many tasks that require the efforts and inputs of multiple individuals to collectively accomplish things that might take longer or are simply impossible to be carried out by a single person.
From previous works, a number of authors have tried to tackle the issue of team selection in different settings using a number of approaches but it was observed that these models did not consider a combination of more selection criteria (such as capability, history, personality and context), which can ensure the formation of high performing teams, which serves as the motivation for this study. Therefore, there is a need to model a selection process that considers a combination of more criteria (knowledge dimensions) to ensure not just an efficient selection process but also the formation of a high performing team.
Naturally, most of the decisions made by the personnel in charge of setting up a team in an enterprise may be judged from past knowledge or experiences gained overtime in selecting individuals, like the capability, previous teams that a person has served in before, quality of performance. This method is associated with case-based reasoning (CBR) approach, a technique considered to be the most appropriate for developing systems that are experience-based.
Thus, this work proposes a semantic case-based reasoning approach to team selection in an enterprise that will embrace more knowledge dimensions such as capability, history, personality and context, when compared to previous automated approaches to team selection.