Exploring Factors and Techniques for Effective Team Formation in Project Management: A Multi-Criteria Decision-Making Approach

Forming ideal teams is a promising approach for improving team performance and attaining project success. This study first explores the factors that affect team formation, then determines the main factors by using Artificial Intelligence techniques, and finally, allocates weights to the main factors to prioritize their impact on constructing optimal teams. Aiming to undertake a more effective approach to forming effective project teams, this study proposes a Text Mining Framework of three Stages: Data Preprocessing, Data Processing, and Data Post-processing. To determine the main factors that mostly influence the team formation process, this study focuses on the seven main factors of only two themes, the human-related and team-related factors, and ranks them according to their allocated weights obtained by the Best-Worst method, indicating their level of influence on forming project teams, as follows: Skills & Competencies, Expertise & Proficiency, Personality, Teamwork, Work Experience, Education & Knowledge, and Characteristics. This study contributes to the knowledge of solving the Team Formation Problem in the Project Management domain by proposing a Text Mining Framework, from factor extraction until factor weights allocation using the Best-Worst method.