Assessing quality management practices: Comparative analysis of public and private universities using fuzzy inference system

Abstract

Aim: This study aims to examine how public and private universities implement quality management practices and identify areas requiring improvement. Methodology: A purposive sample of 14 universities, representing both public and private sectors, was selected. Data were gathered from 28 department heads using questionnaires. The responses were analyzed through ttests, means, and standard deviations. To capture subjective perceptions more effectively, the Fuzzy Inference System (FIS) was applied to model satisfaction levels across key quality management factors. Findings: Results indicate that moderate satisfaction occurred in the case where leadership and process approaches were used less frequently, whereas the other case showed higher satisfaction because the evidencebased decision-making approach was more dominant. These findings highlight the gap in improvement processes and leadership, while highlighting the values of data-driven practices. Practical Implications: The study provides recommendations for strengthening quality management in universities, including enhancing leadership capacity, adopting systematic improvement processes, and encouraging evidence-based decision-making. It also suggests that pursuing international accreditation through the Higher Education Commission could help universities align with global standards and enhance their institutional reputation.