FUZZY DEM-SAW: A NOVEL HYBRIDIZED MODEL OF FUZZY DEMATEL-SAW IN LECTURERS� PERFORMANCE EVALUATION BASED ON TEACHING, RESEARCH, SERVICE AND COMMERCIALIZATION (TRSC) CRITERIA FOR PROMOTION

Abstract

This study introduces an innovative hybridized model, Fuzzy DEM-SAW, designed to enhance the precision and efficacy of lecturers' performance evaluations for the purpose of promotion. This novel approach integrates two distinct methodologies, Fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) and SAW (Simple Additive Weighting), presenting a comprehensive framework for the evaluation of lecturers based on the critical criteria of Teaching, Research, Service, and Commercialization (TRSC). The study�s purpose is to rank lecturers for promotion. The Fuzzy DEMATEL technique is employed to derive weights, serving as a fundamental basis for subsequent ranking through the Fuzzy SAW process. The proposed model is applied to a case study, revealing significant findings pertaining to lecturers' performance evaluation. The outcomes disclose that Benone secured the foremost position with an Si value of 0.7, followed by Begu-Ellah at 0.583, and Bemane at 0.488. These results provide valuable insights for decision-makers involved in the promotion evaluation process. This research not only contributes to the advancement of hybridized fuzzy models but also holds practical implications for optimizing the assessment of lecturers in academic institutions, thereby contributing to the broader discourse on performance evaluation methodologies in academia. � Little Lion Scientific.