Evaluating Service Quality in Infant and Childcare Institutions: A Decision-Making Framework Using Interval Type-2 Fuzzy MCDM

Wen Zheng

doi:10.31081/dmame8220251602

Authors

Wen Zheng Associate Professor, Department of Labor Economics, Shandong Labor Vocatonal and Technical College, Jinan, Shandong, China, 250354.

DOI:

https://doi.org/10.31081/dmame8220251602

Keywords:

Interval Type-2 Fuzzy Sets, Multi-Criteria Decision-Making, Service Quality Evaluation, Public Childcare Institutions, Expert Judgment Aggregation

Abstract

The study presents a comprehensive framework for evaluating service quality in public childcare institutions by employing an integrated Interval Type-2 Fuzzy Multi-Criteria Decision-Making (IT2F-MCDM) approach. This framework is designed to systematically address uncertainty inherent in human judgement by converting expert linguistic evaluations into Interval Type-2 Fuzzy Numbers (IT2FNs). Decision alternatives, represented by childcare institutions, and evaluation criteria, including safety, staff qualifications, emotional support, and infrastructural conditions, are identified through a combination of expert consultation and an extensive review of existing literature. Expert opinions are aggregated using the Fuzzy Weighted Averaging (FWA) operator, following the normalisation of criterion weights, which are likewise expressed in IT2FN form. The assessment process produces an overall fuzzy performance value for each childcare institution, derived from expert evaluations across the specified criteria. These fuzzy performance values are subsequently defuzzified into crisp scores using the centre-of-gravity technique, enabling more transparent interpretation and practical applicability of the results. Based on the resulting crisp values, childcare institutions are ranked according to their relative levels of service quality. To examine the robustness and stability of the proposed framework, a sensitivity analysis is performed by systematically varying the weights assigned to the evaluation criteria. This analysis provides insight into how changes in criterion importance influence institutional rankings. Furthermore, the reliability of the IT2F-MCDM results is verified through comparative analysis with established decision-making techniques, including Fuzzy TOPSIS and Fuzzy VIKOR. The consistency observed across these methods confirms the validity of the proposed approach. Overall, the framework functions as a dependable decision-support tool capable of assisting childcare administrators and policymakers in making evidence-based decisions aimed at enhancing service quality.

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