An Integrated Fuzzy Delphi and Best Worst Method (BWM) for performance measurement in higher education

Abstract

This paper proposes a novel multiple-criteria decision-making (MCDM) framework for performance measurement in higher education institutions (HEIs) using semi-structured interviews, expert panels, and questionnaires. The proposed method comprises the fuzzy Delphi method (FDM) and Best-Worst Method (BWM). Fuzzy set theory is used to address the vagueness and uncertainty of experts’ judgments, and the group decision-making process is handled by the Delphi method. The FDM filters out the criteria extracted from the literature, and BWM finds the relative weight of the criteria and indicators. A real-world case from a public university is employed to illustrate the applicability and effectiveness of the proposed framework using a seven-category framework. Findings show that “education” and “human capital” are the most important criteria. Further, “the number of patents and inventions,” “ratio of faculty/students,” and “students’ satisfaction with teaching quality” are the most critical performance indicators.