A Decision-Making Approach for Ranking Tertiary Institutions’ Service Quality Using Fuzzy MCDM and Extended HiEdQUAL Model

Abstract

The attainment of excellence in institutions is maintained through the institutions’ adherence to its core values and efficient service delivery. These factors are very important in facilitating global development of a country and determining the world ranking of an institution. To this effect, this study presents an effective approach for evaluating and ranking quality of services in a higher institution, taking four higher institutions in Nigeria as case studies. Service quality consists of different attributes and many of them are intangible and difficult to measure, which means that using the previously known measurement approach will be insufficient. Therefore, a fuzzy method was proposed to resolve the ambiguity of the concepts and intra-uncertainty, which are associated with human judgments in decision-making. This study adopted a contextualized service quality model for educational domain called HiEdQUAL with some extended criteria in order to evaluate the perception of service quality by respondents from the selected higher institutions: two private universities and two public universities from the south-west region of Nigeria. Four Multi-Criteria Decision-Making (MCDM) methods: TOPSIS, Yager’s min-max, Compensatory AND, and Ordered Weighted Averaging are applied to comparatively evaluate the quality of services in the four higher institutions. The MCDM methods are engaged independently to validate the reliability of the ranking results. The importance weight of each performance criterion is found with Fuzzy Analytical Hierarchy Process (FAHP) algorithm. This study has been able to practically establish Ext-HiEdQUAL as a new service quality model for higher education with six concepts and 33 criteria. The output of the Fuzzy MCDM ranking recommends institution B as the best institution to students based on the Ext-HiEdQUAL measures. Also, findings from the sensitivity analysis showed that Yager’s min-max outperform the other investigated methods in this study by being consistent and exceptionally tolerant in most instances when there is significant deviation in criteria weights.