Computational approach for roles selection via integrated multi-criteria decision making

Abstract

Some characteristics and actions are necessary for qualification as an Academic Leader or Academic Manager. Yet, there is a lack of study on how to cultivate and prevent the loss of these qualities and characteristics among distinguished academics. Due to the lack of this training, vacant Academic Administrator positions will remain unfilled. Thus, throughout the Talent Development Intervention programme, an efficient approach for assessing the knowledge, abilities, and experience of potential academics is required. This paper compares and integrates the combination results of six (6) Multi-criteria Decision-Making methods using Simple Additive Weightage (SAW), Weight Product Method (WPM), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), ELECTRE (Elimination and Choice Expressing Reality), and CFPR (Consistent Fuzzy Preference Relations) based on the proposed model of Multi-Criteria Tacit Knowledge Acquisition. Based on the proposed model, one set of empirical research employs four (4) principal criteria and seven (7) sub-criteria to choose the best applicant for academic administrator positions. The research reveals that, with the exception of the SAW method, other processes provide identical results