# Developing a Decision-Making Framework to Improve Healthcare Service Quality during a Pandemic
## 2 Literature Review
### Decision-Making Methods Used  
There are numerous decision-making tools that can be implemented to improve service quality in a healthcare setting. For example, [PERSON] and [PERSON] [7] integrated quality function deployment (QFD), service quality measurement (SERVQUAL), and failure modes and effects analysis (FMEA) approaches for service quality improvement in a public hospital in Turkey. [PERSON] et al. [8] combined the analytic hierarchy process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and fuzzy theory to form a framework for evaluating and comparing quality of service in different hospitals. [PERSON] et al. [10] constructed a general hybrid framework for adopting Radio Frequency Identification (RFID) equipment into the healthcare sector. Their framework integrated the decision-making trial and valuation laboratory (DEMATEL), DEMATEL-based analytic network process (DANP), and multi-criteria optimization and compromise solution (VIKOR) methods. Researchers continue to explore new MCDM methods. For example, [PERSON] [11] proposed a new intuitionistic distance-based approach COMET (characteristic objects method). [PERSON] and [PERSON] [12] used MABAC (Multi-Attributive Border Approximation Area Comparison) method for the selection of transport and handling resources in logistics centers. [PERSON] [13] proposed the best-worst method (BWM) method. Recently, [PERSON] et al. [14] developed the Stable Preference Ordering Towards Ideal Solution method (SPOTIS) method, which is a rank reversal free method. However, [PERSON] et al. [15] demonstrated that the determination of the weights of the attribute plays a vital role in these MCDM methods. While a myriad other methods has been developed, the remainder of this section will focus on the BWM, MAMCA, and MOLP methods, as these methods comprise the decision-making framework proposed in this paper. The BWM method is a structural procedure for solving multi-criteria decision-making problems with selected criteria and alternatives. The BWM method has two unique advantages over other MCDM methods: (1) it is simple procedure that requires less information, and (2) it is more reliable, as it provides more consistent results [13]. In the BWM method, stakeholders rank criteria from best to worst, and weights are then assigned to these criteria based on the rankings. This feature is especially helpful when multiple stakeholders are involved in the decision-making process, as it allows decision makers to identify criteria that are perceived as important to multiple stakeholder groups. Recently, researchers in other fields have become interested in BWM. For example, to evaluate overall manufacturing performance, [PERSON] et al. [16] developed a performance evaluation framework. [PERSON] et al. [17] combined BWM with rough strength-relation for predicting transportation disruption factors in order to allow managers to focus on the particular issue instead trying to address all of the related factors. In another study, [PERSON] et al. [18] used BWM to determine that \"lack of technological infrastructure\" was the biggest challenges to implementing Industry 4.0 in the leather industry. Despite these successful applications, BWM has some limitations, such as: (1) it is incapable of considering the ordinal consistency, and (2) there is not consistency of the threshold limit in determining the reliability of the results [19]. Traditional MCDM methods are limited by the fact that they require all stakeholders to consider the same set of criteria. Thus, they are unable to accommodate multiple stakeholders with their own set of criteria or decision trees. To address this issue, and to allow the inclusion of multiple stakeholders, we utilize a new interactive tool called MAMCA to evaluate alternatives to the selected criteria. MAMCA is a multi-actor decision-making tool that can predict the best solution for each involved stakeholder group based on their respective sets of criteria [20].