A Best-Worst Multi-Criteria Decision-Making Method By Belief Functions And Its Applications In Maternity Clinic Service Evaluation.

Abstract

Evaluating the quality of healthcare services in maternity clinics is a complex task that involves multiple criteria, making it a typical multi-criteria decision-making (MCDM) problem. This thesis introduces a Best-Worst MCDM method based on belief functions and demonstrates its applications in the evaluation of maternity clinic services. The proposed method, called the Evidential Best-Worst Method (EBWM), extends the traditional Best-Worst Method (BWM) by incorporating the theory of belief functions to handle uncertainty and imprecision more effectively. Unlike the traditional BWM, the EBWM allows decision makers to express their preferences using linguistic terms and confidence levels, which are then modeled using belief structures. The methodology involves determining the linguistic terms and confidence levels, identifying the key evaluation criteria for maternity clinic services, and determining the importance weights of the criteria using the EBWM. The proposed approach is applied to a case study evaluating the service quality of a maternity clinic. The results demonstrate the effectiveness of the EBWM in capturing the decision makers' preferences and providing a more robust and reliable assessment of the maternity clinic's service quality compared to traditional MCDM methods. The development and application of the EBWM contributes to the field of MCDM by providing a novel approach that can handle the inherent uncertainties and vagueness in the evaluation of complex healthcare services. The findings of this thesis have practical implications for maternity clinic management, helping them to identify areas for improvement and enhance the overall quality of service provided to expectant mothers