Systematic Review of Fuzzy Scales for Multiple Criteria Decision-Making Issues during COVID-19 ^†

Abstract

The COVID-19 epidemic, which can be compared to the economic catastrophe of World War II, slowed down business activities and had a significant impact on all aspects of business operations. Fuzzy scales are popular MCDM (multi-criteria decision-making) methods in modeling COVID-19 problems owing to the multi-dimensionality and complexity of health and socio-economic systems. This study aims to examine 104 works that used MCDM approaches with fuzzy scales in various COVID-19 pandemic issues and were published in top peer-reviewed journals indexed in Web of Science and Scopus. This study presents a systematic review of (1) the prevalence of fuzzy scales in scientific research for multiple criteria decision-making during COVID-19; (2) bibliometric analysis was used to identify the most important articles, authors, journals, themes, and countries; and (3) the impact of fuzzy scales on spreading established fields of research in new directions was iew of Fuzzy Scales for Multiple Criteriaconsidered. Furthermore, it addresses pertinent filed criticism, validating certain claims and dispelling others. Finally, the present study result helps regulators, academic scholars, and policy-makers to understand the current perspective and trends on multiple criteria decision-making with fuzzy scales during COVID-19 and understand the relevant areas that require further investigation.

1. Introduction

One of the most significant pandemics in the last two generations has affected the world from December 2019 to the present day. Every day, countless individuals lose their lives, and thousands of people become infected with this new coronavirus, which is characterized by its highly contagious nature [1]. Humans are typically affected by respiratory infections, which range in severity from the common cold to serious conditions like Middle East respiratory syndrome (MERS) or severe acute respiratory syndrome (SARS) [2]. The actual pandemic (COVID-19), which was introduced by the recently identified coronavirus SARS-CoV-2, has a higher mortality and contagiousness ratio than its predecessors [3]. The rapid spread of SARS-CoV-2, which has resulted in 102 million cases and 2.2 million fatalities worldwide, was made possible by ignorance and the virus’ unknown nature.

Governments, nations, and societies have learned from each of these waves and improved their response mechanisms. However, given the virus’ unpredictable behavior, somatological diversity, and the recent emergence of new virus variants [2], we continue to face numerous new challenges to the global healthcare system’s viability. Numerous operational, logistical, organizational, and moral–ethical standards have been established in this area as a result of COVID-19 and among its waves for management, healthcare professionals, and associates. Similarly, it is more than likely that a fourth wave could occur, given the difficulties encountered in the distribution and application of the COVID-19 vaccine and the accumulated total of active cases. This is more likely to result in a saturation of the healthcare system. The management of specialized training for medical personnel must, therefore, be improved in light of current conditions, and buildings must be transformed into patient accommodations.

Decision-making models are currently used in patient emergencies to deal with this crisis by providing crucial data regarding the prediction of spreading, the evaluation of various factors, determining the weights of criteria, and restructuring decision-making [4]. In this regard, fuzzy-based decision models, based on the theory put forth in the early 1800s, have significant application in decision-making, as they are thought to be a more flexible and dynamic approach and, at the same time, a procedure that is more sensitive to real-life scenarios.

This broad shift in perspective has created the opportunity for future research questions, investigations of previously overlooked positive phenomena, and novel approaches to well-established areas of research. Accordingly, during recent decades, this movement has triggered a growth in research in various fields of study. As a result, this movement has made ripples with regard to the MCDM (multi-criteria decision-making) methods. Thus, we attempt to assess the situation and pose the following questions: what are the notable characteristics of the existing research inspired by this viewpoint?; how have researchers across the MCDM with fuzzy scales engaged and interpreted this viewpoint?; and what are amongst the most significant contributions that have originated?

2. Literature Review

Numerous fuzzy MCDM (FMCDM) methods have been proposed in the literature over the years, differing in terms of questions, theories, and results. Various techniques were not applied to other problems because they were developed for a specific problem. A variety of FMCDM techniques have recently been developed to select the best compromise options. The motivation for developing the FMCDM approaches came from a variety of real-world issues that call for the consideration of multiple criteria, as well as from the desire of practitioners to improve decision-making processes as a result of recent advancements in computer technology, scientific computing, and mathematical optimization [5]. All methods aim to improve decision-making by making it more informed and formalized. MCDM and FMCDM are classified into various fields and approaches in previous studies [6,7]. The MCDM approach can be divided into two groups [4,8]: traditional MCDM and FMCDM.

Since the MCDM problems are diverse, many different techniques have been suggested as solutions. Complete aggregation methods were the first ones including SAW (Simple Additive Weighting) with two stages in weighting [9], TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) [10], WASPAS (Weighted Aggregated Sum Product Assessment) [11], VIKOR (VlseKriterijumska Optimizacija Kompromisno Resenje) [12], MAUA (Multi-Attribute Utility Analysis) [13], MOORA (Multi-Objective Optimization based on Ratio Analysis) [14], COPRAS (Complex Proportional Assessment) [15], ARAS-F (Fuzzy Additive Ratio Assessment Method), ARAS-G (Additive Ratio Assessment Method with Gray values), MULTIMOORA (Multiobjective Optimization Ratio Analysis Plus Full Multiplication Form) [16], COPRAS-G (Complex Proportional Assessment of alternatives to Grey Relations), and ARAS (Additive Ratio Assessment) [1]. Case studies of incomplete aggregation techniques, including NAIADE (Novel Approach to Imprecise Assessment and Decision Environments) [3], PROMETHEE (Preference Ranking Organisation Method for Enrichment Evaluations) [17], and ELECTRE (Elimination and Choice Translating Reality Method), involve comparing alternatives in a pair-wise manner [18]. Additionally, pair-wise comparisons have been used in the ANP (Analytical Network Process) and AHP (Analytic Hierarchy Process) [4]. Fuzzy multi-attribute decision-making (FMADM) and fuzzy multi-objective decision-making (FMODM) are the two subcategories of FMCDM [6]. Reference [2] investigated the development of MADM between 1900 and 2021.

The FMADM approach has a finite and implicit goal, whereas the FMODM approach has an infinite and explicit goal. The decision-objective-makers in FMADM are unified under the decision-utility-maker, which is a super function that depends on the selection criteria. Assigned fuzzy weights in FMODM reflect the relative importance of the decision-maker’s goals, such as optimal resource utilization, quality improvement, and remaining explicit. The ability of FMCDM models to take into account various selection criteria is their most significant advantage. Fuzzy sets were used in the MCDM field [19]. The intersection of all the fuzzy goals is what Ref. [3] refers to as the fuzzy set of a decision. Reference [20] compiled a list of MADM problem applications for the fuzzy set theory.

The MCDM problems are greatly impacted by aggregation techniques, and grouping operators have been widely used in MCDM. Reference [19] created many functions for evaluating each alternative’s suitability in light of a given set of MCDM criteria in a fuzzy environment. Comparatively speaking, however, very few studies have concentrated on the MCDM issues in a hesitant fuzzy environment. Additionally, hesitation and uncertainty are typically viewed as unavoidable issues when making decisions. Numerous tools have been developed in the literature to more accurately express the evaluation data of decision makers, including fuzzy sets, fuzzy multi-sets, intuitionistic fuzzy sets, linguistic fuzzy sets, interval-valued fuzzy sets, and type-2 fuzzy sets.

3. Methodology

To address the MCDM issues and avoid the inherent narrative reviews, we conducted a systematic review of the literature on the topic of fuzzy scales [1]. A systematic literature review is a type of secondary study defined by Ref. [13] as a method of locating, assessing, and analyzing the evidence that is currently available and relevant to a specific research issue or field of study. This type of analysis points us in the direction of a transparent and repeatable process of selecting, analyzing, and reporting previously conducted research into a specific subject [20]. A literature review, in terms of research methodology, combines qualitative and quantitative analysis to investigate a specific issue of subjective interest [21]. Furthermore, few studies have created frameworks for conducting a systematic review. The first stage of the review is a systematic literature review, as recommended by Ref. [4]. Then, data collection and screening procedures were devised under the guidelines adapted from Ref. [9]. Furthermore, bibliometric analysis follows from Ref. [22]. This systematic review was conducted for two primary reasons. Firstly, researchers reviewing healthcare studies [15], supply chain management [18], and sustainability in emerging situations have frequently used this method in the context of MCDM with fuzzy scales during COVID-19 and the effectiveness of fuzzy scales’ perspectives and research trend studies [11]. The second concern is the different approaches for conducting a systematic literature review that considers how fuzzy theory affects MCDM problems [7]. The four main stages of the systematic review process are shown and described as follows:

(1)

Systematic review of the literature (Section II);

(2)

Data collection: Scopus and Web of Science (WoS) were utilized to collect the necessary data (Section A);

(3)

Data screening: using a quantitative approach, formal aspects of the collected data were evaluated and examined (Section A);

(4)

Applied techniques: bibliometric analysis and a review of the academic studies of MCDM issues were conducted during COVID-19 (Section IV).

Data Collection

The most complete scientific databases, namely Web of Science and Scopus, were used to gather the data (WoS), enabling the execution of trustworthy bibliometric studies [14]. The broad keywords MCDM issues, the COVID-19 pandemic, the fuzzy scales, and various country or sector names were used in both databases as research criteria to photograph fuzzy scales for MCDM issues affecting the scientific community. While authors, titles, and keywords were the research criteria in WoS, they were authors, abstracts, and keywords in Scopus. The first step in the review procedure was defining the unit of analysis. The sole research article was taken into account for this review as a whole. As a result, the article was the sole source of results in both databases. Finally, we chose only English-language articles. As it is the language that is most frequently used in both databases and widely regarded as the international academic language, English was chosen as the study’s main language [8]. There were no time restrictions. In August 2022, the queries on the various databases were performed. In comparison to WoS, which produced 43 recognized results, using Scopus, we produced a total of 61 results. Duplicates from both databases were subsequently deleted. As a result, in total, 104 papers were reviewed and listed in Figure 1.

4. Result and Discussions

This section explains the prevalence and bibliometric analysis results.

4.1. Prevalence

Table 1. Articles published statistical results.

Region	Country	Number of Articles
Asia	China, India	67
Africa	Southern Africa, Cabo Verde	24
Europe	United Kingdom	8
North/South America	USA	6
Australia/Oceania	Australia, Samoa	19

shows the proof that specific nations and areas frequently serve as hubs within continents. There is evidence that certain countries and regions tend to be at the center of this growth, even though the current systematic review confirms the use of fuzzy scales for MCDM issues during the COVID-19 pandemic. For instance, 54% of the publications using samples from (k = 67 articles) for the MCDM with fuzzy scale were in Asia. Only 5% of the articles were published in Europe, 8% were published in Australia/Oceania, and 33% were published in Africa. Antarctica and North/South America displayed comparable trends. The majority of articles in Asia were from China and India. In Southern Africa, Cabo Verde produced 50% of the articles, with the remainder distributed throughout Europe. However, there has been an increase in interest in several new countries and regions with regard to using fuzzy scales to address MCDM issues. In the dataset, participant samples only ever represented 84 of the world’s countries once, and of these 14, 6 were only ever used in multinational studies’ empirical research.

4.2. Bibliometric Analysis

Figure 2 shows that numerous research methodologies have been used to conduct studies in the field of MCDM. The 124 publications were manually grouped into 4 different study types to analyze the various research approaches that have been used in this field: quantitative, qualitative, mixed, and other. Quantitative studies emphasize the gathering of quantifiable data and the application of mathematical, statistical, or computational techniques. In the context of this article, qualitative studies are a type of research that focuses on gathering information through conversation and open-ended questions. Studies that combine quantitative and qualitative methods are called mixed studies. The other category includes case studies and other types of reports.

Figure 2 exhibits the percentage of various study types that were used in the fuzzy scale to address the study of MCDM issues. Only 25% of the 124 articles consisted of mixed-approach studies. Instead, 56% were qualitative and 18% were quantitative. Only a few articles used a combination of methods to develop their approaches. According to current qualitative and quantitative theories, the question “what” has been answered fairly effectively, but “how” is still a mystery. It is also clear that there are not many review articles available that offer current information on MCDM issues.

5. Conclusions and Future Directions

This study conducted a systematic literature review to understand the importance and characteristics of fuzzy scales among MCDM studies during the COVID-19 pandemic. We determined the current trends through prevalence and Bibliometric analysis. However, the current trends confirmed that fuzzy scales are key to investigating MCDM issues. The conducted studies originated from Asian countries. In general, Asian countries and businesses were affected by the COVID-19 pandemic [5]. This is the positive outcome of this study’s results. This study is contributing to the theory by identifying the current trends in and usefulness of the fuzzy scales while addressing the MCDM issues among businesses and societies.

However, there are limitations to this study. Multi-criteria methodologies are still developing and exponentially spreading in the international scientific community, despite being a relatively new research method, to simplify complex decision-making situations. They have been successfully used as ideal decision-maker methodologies to handle complex situations, as demonstrated in prior studies [6]. Commercial and energy fields have emerged in engineering, in addition to gaining importance in other industries. The applications of FMCDA and FMCDM that have been reviewed confirm their enormous value in situations like the COVID-19 pandemic. The future of FMCDA must be made clear, and the sooner we succeed in the vast array of fuzzy sets [23], obtaining an improvement in the social health of the population, the earlier we can realize the significance of fMCDA decision sciences within the various scientific fields. This is a crucial fact to consider, especially for emergency first aid teams, who also need to concentrate on other pertinent issues [11].

In addition, future works need to consider fuzzy multi-criteria decision analysis techniques that are used to investigate various factors, including isolation planning, the location of quarantine centers, safe nursing homes, safe homes, safe masks, an epidemic-controlling model, and an intensive care unit beds augmentation model for COVID-19 hospitals, and ensure that a large number of patients receive the care they need. Better staffing for COVID-19 management can be ensured through studies involving various lockdown models or policing the individuals who have produced COVID-19 antibodies. Understanding the degree of community spread will be made easier with thorough research and data analytics. Additionally, new SARS-CoV-2 virus variants are discovered every week. Therefore, the decision criteria must either ensure that the current testing, treatment, and vaccines are still effective or consider alternative approaches to combating the virus’ effects. The application of the fuzzy-based MCDM method can also be modified based on each patient’s unique circumstances.