The Integration of DEMATEL and SAW Methods for Developing a Research Performance Assessment Model for Lecturers

Abstract

This work aims to integrate two decision analytic methodologies, DEMATEL and SAW, to develop a comprehensive and effective model for assessing research performance among instructors. These strategies aim to rectify the deficiencies of traditional evaluation models, which often neglect the complexity of interconnections among performance metrics. This study utilizes research performance data from lecturers, encompassing publication count, journal quality, impact, funding, and cooperation. SAW is employed to calculate aggregate scores utilizing weights obtained from the DEMATEL analysis, whereas DEMATEL is utilized to delineate and assess the interrelationships among the evaluation criteria. The results indicate that the quantity of publications significantly influences research quality, succeeded by research impact and journal quality. Alternative A, with a maximum score of 0.996, demonstrated that the professor excelled in nearly all categories. A clear and objective evaluation methodology was developed by integrating DEMATEL with SAW. The development of more flexible criterion weights to accommodate shifts in academic practices and research priorities is a significant implication for future investigations. To evaluate this model's appropriateness and effectiveness in various academic contexts, it must be further assessed across multiple topic areas and types of educational institutions. This study facilitates the implementation of big data technology in academic performance evaluation, enhancing the accuracy and relevance of assessment methods.