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The superiority of BWM over other weighting methods for obtaining the weight values of the attributes is that it achieves high-confidence results with a reasonable number of pairwise comparisons. Although the best-worst method (BWM) is a well-known multi-criteria decision-making (MCDM) method that has been successfully utilized in almost all scientific areas to solve challenging real-life problems, no research has comprehensively examined the state-of-the-art in this regard. The present study depicts a detailed overview of publications concerned with BWM during the period 2015–2022. Based on the information obtained from the Scopus database, this work presents a big picture of current research on BWM. In other words, this paper analyzes the existing literature about BWM and identifies thematic contexts, application areas, emerging trends, and remaining research gaps to shed light on future research agendas aligning with those gaps. Further, the most recent BWM research is analyzed in the top ten scientific areas, from engineering to materials science. “Engineering”, “computer science”, and “business, management, and accounting” are the hottest fields of BWM research. China is the most active country regarding “engineering” and “computer science”, whereas India is the leader in “business, management, and accounting”. The study also reveals that there are still many research gaps in BWM research. The big picture taken in this study will not only showcase the current situation of BWM research but will also positively impact the direction and quality of new research. [ABSTRACT FROM AUTHOR]

Shelters are vital for affected people after a disaster because of the accommodation, safety, and security. In this paper, we analyze the shelter site selection criteria for disaster preparedness applying the best–worst method under interval type-2 fuzzy sets. The proposed approach utilizes the advantages of fewer pairwise comparisons with the best–worst method and better reflection of uncertainty with interval type-2 fuzzy sets. For this reason, the criteria are determined based on a literature review and the opinion of nine disaster experts. The experts have worked as disaster officers in a variety of locations, including Sivrice (Elazığ), Pazarcık, and Elbistan (Kahramanmaras) and Syrian refugee camps such as Nizip container city. In this step, 6 main criteria and 25 sub-criteria are evaluated using the proposed approach. According to the nine experts' opinions, the most important main criterion is determined as proximity. Distribution center capacity, adequate distribution logistics personnel, available electricity, distance to settlement, and landslides and flooding are also determined as the five most important sub-criteria. For disaster preparedness, responsible organizations and managers should consider these important criteria for temporary shelter site selection. [ABSTRACT FROM AUTHOR]

The weaponized unmanned aerial vehicle (UAV) swarms have posed a significant threat to maritime civilian and military installations. For effective defense deployment, threat assessment has become a critical part of maritime defense decision-making. However, due to the uncertainty of threat information and the ignorance of decision-makers' psychological behaviors, there are great challenges in obtaining a reliable and accurate threat assessment result to assist in maritime defense decision-making. To this end, this paper proposes an integrated threat assessment method for maritime defense against UAV swarms based on improved interval type-2 fuzzy best-worst method (IT2FBWM), prospect theory and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje, in Serbian). Firstly, the improved IT2FBWM is designed by introducing interval type-2 fuzzy set (IT2FS) and entropy-based information to obtain attribute weights with high reliability. Then, the hybrid fuzzy scheme covering IT2FS and interval number is constructed to express the uncertainty of different types of threat information. Next, VIKOR is extended to hybrid fuzzy environment and combined with prospect theory to consider the influence of psychological behaviors of decision-makers. Finally, the improved IT2FBWM and extended VIKOR are integrated to determine the threat ranking of targets and the priority defense targets. A case study of maritime threat assessment is provided to illustrate the performance of the proposed method. Moreover, sensitivity and comparative experiments were conducted, and the results indicate that the proposed method not only obtain the reliable threat assessment result but also outperforms the other methods in terms of attribute weight determination, decision preference consideration and decision mechanism. [ABSTRACT FROM AUTHOR]

100 years after the Spanish flu, the COVID-19 crisis showed that large-scale epidemics and pandemics do not belong to the past. On the report of the World Health Organization, COVID-19 is the most significant public health problem of the twenty-first century. Like previous epidemics, the current crisis is accompanied by uncertainty, mistrust, doubt and fear, and this has led to an infodemic connection to the epidemic. So not only are we fighting an epidemic, but also, we are brawling an infodemic. To reduce the social and economic consequences and harmful effects of infodemic health, and to overcome it, we need to implement strategies against infodemic. Evaluating strategies based on multiple characteristics can be considered multi-criteria decision-making (MCDM) problem. According to the literature, there is no study that aims on proposing an integrated approach to evaluate infodemic management strategies under uncertain environment. Therefore, in this paper, an integrated framework based on the extended version of best–worst method (BWM) and Combined Compromise Solution (CoCoSo) methods under a spherical fuzzy set (SFS) is developed for the first time to address the COVID-19 infodemic management strategies selection. Initially, the criteria are weighted using the developed SFS BWM which reduces uncertainty in pairwise comparisons. In the next step, the 15 selected strategies are analyzed and ranked using SFS CoCoSo. The outputs of this paper illustrate that online tools for fact checking COVID-19 information and engage and empower communities are placed in the first and second priorities, respectively. The comparison of ranking results SFS-CoCoSo with other MCDM methods demonstrates the performance of the proposed approach and its ranking stability. [ABSTRACT FROM AUTHOR]

As a powerful tool for improving customer satisfaction, quality function deployment (QFD) can convert customer requirements (CRs) into engineering characteristics (ECs) during product development and design. Aiming to address the deficiencies of traditional QFD in expert evaluation, CRs' weight determination and ECs' importance ranking, this paper proposes an enhanced QFD model that integrates hesitant fuzzy binary semantic variables, the Best–Worst Method (BWM), and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The objective is to determine the prioritization of product engineering characteristics. Indeed, hesitant fuzzy linguistic term sets (HFLTS) have found extensive application in decision-making problems. Compared to other fuzzy language methods, HFLTS offers greater convenience and flexibility in addressing decision-makers' hesitations and uncertainties. Initially, the combination of hesitant fuzzy linguistic term sets with interval binary tuple language variables is employed to articulate the uncertainty in the assessment information provided by QFD team members. Subsequently, the improved BWM and TOPSIS methods based on HFLTS are used to improve the accuracy of the importance ranking of engineering characteristics by determining the weights of CRs and prioritizing ECs in two stages. Finally, the feasibility and effectiveness of the proposed method are validated through an illustrative example. [ABSTRACT FROM AUTHOR]

With the use of cutting-edge technologies like artificial intelligence (AI), robotics, and the Internet of Things (IoT), Industry 5.0 represents a breakthrough move towards a sustainable and human-centered industrial future. Industry 5.0 endeavors to transform industries such as consumer electronics by emphasizing sustainability and collaboration, in contrast to its predecessors, who only concentrated on automation and efficiency. Along with improved manufacturing efficiency and product innovation, this change in the consumer electronics sector also redefines the human-machine interaction. This paper proposes a novel hybrid integrating model that combines the Entropy Weight Method (EWM), Best-Worst Method (BWM), and an acronym in Portuguese for Interactive Multicriteria Decision Making (TODIM) using single-valued neutrosophic trapezoidal numbers to evaluate Industry 5.0 enablers. The EWM provides objective weight for criteria, while the BWM captures the subjective preferences of decision-makers. The TODIM method ranks alternatives based on these weighted criteria using single-valued neutrosophic trapezoidal numbers, which effectively handle uncertainties and imprecise information inherent in decision-making processes. The proposed hybrid model effectively evaluates the Industry 5.0 consumer electronics sector using an empirical study emphasizing personalization, sustainability, resilience, and smart manufacturing criteria. The model enhances decision-making by balancing objective metrics with subjective preferences, thus guiding stakeholders toward informed and sustainable technological investments. The hybrid EWM-BWMTODIM method with single-valued neutrosophic trapezoidal numbers demonstrated robustness in accommodating subjective and objective criteria weights. Sensitivity analysis revealed variations in aggregation methods and values significantly influenced final rankings, emphasizing the method's adaptability and responsiveness to decision-maker preferences and environmental changes. [ABSTRACT FROM AUTHOR]

Seeking the greatest possible return on long-term investments, investors naturally seek equities of the best-performing companies that fit their investment timeframe. Long-term investment success rests on selecting the best companies, which requires a challenging analysis reviewing voluminous and often-conflicting data about companies and understanding broader economic forecasts. This paper undertook a case study deployment of MCDM methodologies to examine the suitability and effectiveness of Multi-Criteria Decision-Making (MCDM) methods in assessing and ranking the best stocks for portfolio inclusion. A combination of MCDM techniques comprised a methodology to evaluate and rank Saudi Arabian banking stocks based on their performance in the Saudi stock market. Specifically, the paper combined the Best–Worst Method (BWM) and Ranking Alternatives by Perimeter Similarity (RAPS) for the analysis. BWM calculated each criterion's relative impact (weight) in selecting a stock. RAPS then used the weighting to rank the results of the investigation. The study's findings yielded encouraging results regarding using an integrated MCDM technique to derive optimal banking sector securities in the expansive Saudi stock market. The novel application of the robust RAPS technique combined with BWM encourages continued and increased use of MCDM techniques in financial matters and broader application in evaluating equities. [ABSTRACT FROM AUTHOR]

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In order to address the issues of emergency decision-making and optimization (EDMO) of fire accidents in colleges, this paper proposes the EDMO way to take into account the synergies among divergent divisions replacements and the psychology of decision makers (DMs) on the basis of the best-worst method (BWM) and VIKOR within an interval 2-tuple linguistic (ITL) surroundings and cumulative prospect theory (CPT). First, DMs use the ITL to evaluate the degree of synergy among replacements from divergent divisions, the language information can be processed accurately and the information loss can be avoided. Then, the multi-alternative amalgamations consisted of divergent divisions replacements are built. On the grounds of the DMs' value assignment, the collaborative decision matrix of multi-alternative amalgamations can be gained. And the optimal weight of the evaluation standards can be computed based on the ITL-BWM method. The CPT is extended into VIKOR to think about the effect of the DMs' psychological behavior on the decision result. Furthermore, the positive and negative utility matrices can be computed through the value function of CPT. On the grounds of the positive and negative utility matrices, the distance from the utility value of multi-alternative amalgamations to the desired right solution of positive and negative utility can be obtained, and the cumulative foreground value function is used to replace the distance among each replacement to the positive and negative right desired solutions, it can avoid ignoring the effect of the correlations among different attributes on the outcome. Furthermore, the model is applied to the example and an analysis of the sensitivity of the factors of the decision-making mechanism coefficient and the weights of synergistic indicators is carried out to prove the validity and stability of the model. [ABSTRACT FROM AUTHOR]

Neutrosophic cubic set (NCS) can process complex information by combining interval neutrosophic set and single-valued neutrosophic set. It can simultaneously describe the uncertain and certain part of information. Prospect theory (PT) is based on bounded rationality and can reflect decision maker's different risk attitudes to gains and losses. Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) method can measure and rank the alternatives according to compromise solution. Considering the bounded rationality of decision makers and compromise solution of alternatives, this paper combines the PT with MARCOS method to neutrosophic cubic environment to solve multi-attribute decision-making problem. First, the theoretical basis of NCS is introduced. Second, the PT and MARCOS method are combined. To reflect subjective views of decision makers and the objectivity of decision-making information, this paper uses geometric average method to combine subjective weights (calculated by the best-worst method) and objective weights (calculated ed by the entropy method). Then, the PT-MARCOS method is applied to a decision-making problem. Further, a sensitivity analysis is conducted to study the influence of different attenuation factor values and different expectation coefficient on the ranking; and through comparative analysis to illustrate the superiority of the PT-MARCOS method. Finally is the conclusion. [ABSTRACT FROM AUTHOR]

Multicriteria decision-making (MCDM) techniques have successfully been used to address a wide range of real-world decision-making issues. The best–worst method (BWM) is one of the several deterministic MCDM approaches. A recently proposed method called the multichoice best–worst method (MCBWM) takes into account several linguistic terms for pairwise comparisons of relative preferences among the criteria. It has been shown that the MCBWM approach has advantages over BWM: it reduces the calculation and determines optimal weight values by providing the choices for the optimal solution. This paper proposes a unique method for group decision-making based on MCBWM. We extended the MCBWM to solve group decision-making problems. A novel solution approach was developed and validated for multiple problems. Two examples and one case study were solved using the proposed approach to demonstrate the validity and application of the proposed method. The results were further compared with existing models to validate the proposed approach. We found that the obtained ranking order for all problems is the same and that the proposed model has a higher consistency ratio than the existing approaches. This method can be extended to other mathematical programming models for collective decision making in uncertain situations. [ABSTRACT FROM AUTHOR]

One of the most important issues in multi-criteria decision making is the number of requited judgments decision-maker/analyst has to perform. This paper presents a comparison of the results obtained by standard analytic hierarchy process (AHP), limited AHP, and best-worst method (BWM) if the number of criteria is 6, 7, and 8. The examples show that BWM's results are comparable with the results if standard AHP is used, while the limited version of AHP is generally inferior to the other two methods. [ABSTRACT FROM AUTHOR]

Quality Function Deployment (QFD) is commonly used to translate customer requirements into design specifications in the product conceptual design phase. House of Quality (HOQ) is an essential part of QFD to map different requirements of product solutions using a design relationship matrix. In traditional approaches, the way of deciding weights in the relationship matrix can lead to a distortion in ranking of technical measures. Although some methods like Analytic Hierarchy Process have been proposed to improve this problem, they require additional data collection and process. This paper introduces two effective approaches based on Best–Worst Method and Full Consistency Method (FUCOM) to decide weights of technical measures in the relationship matrix of HOQ. The novel integrated approach of FUCOM-QFD is developed for rapid weight allocation in the relationship matrix. The proposed BWM-QFD and FUCOM-QFD approaches use consistency ratio and total deviation measures in reliable decision-making. They not only reduce data collection, but also improve inconsistency problems. The vector-based pairwise comparison and consistency measure are two important features of the proposed approaches. A case study demonstrates improvement in the efficiency and accuracy of weighing solutions for technical measures compared to the existing methods. [ABSTRACT FROM AUTHOR]

Metaverse has made sense for organizations regarding new opportunities it is likely to offer, and studies on Metaverse-related subjects in different areas have increased incredibly. Advertising is an area where Metaverse-related studies are few. For the first time, this paper prioritizes Metaverse ad appeals and performs the Parsimonious Best-worst method (BWM-P) for this purpose. BWMP, an improved version of the BWM method, allows consistent results to be achieved quickly by reducing the number of pairwise comparisons. Regarding the findings, Metaverse experience is the paramount Metaverse ad appeal, followed by product familiarity and NFT of advertisement, respectively. Further, standardization and Metaverse bonuses are the other significant Metaverse ad appeals. The present research contributes to existing knowledge by analyzing ad appeals to ensure the effectiveness of advertising strategies in the Metaverse world. [ABSTRACT FROM AUTHOR]

Concerning the overwhelming advantages of solar energy, controlling and exploiting solar energy by using solar panels is one of the main fields of research in the domain of renewable energy. The choice of solar panel technology is highly significant to exploit as much energy as possible. In this paper, the main goal is to select the best technology for solar panels by investigating nine technologies from the first, second, and third generations of solar panels. Moreover, five sustainable criteria of electrical, mechanical, economic, technical, and climate, and 20 subcriteria are given for making decision analysis. Then, the best–worst method is employed according to the experts' opinions for weighting the criteria and for comparing the ranking of the solar energy technologies a framework based on the MULTIMOOSRAL multiple criteria decision‐making method is proposed. Finally, sensitivity analysis will be conducted on the ranking of the technologies. By exploiting the proposed methodology, CIS/CIGS and Perovskite Solar cell are ranked 1 and 2 as the best solar panel technologies for the selected locations. [ABSTRACT FROM AUTHOR]

This paper reports a coherent method for ranking fruit juice products in the Iranian food industry by the best–worst method by examining the factors affecting product quality. To achieve the aim, a combination of laboratory methods and mathematical calculations was used. The statistical population in this study included samples of products of several food companies (SH, S, P) in Iran. Some factors affecting the quality of fruit juice products including alcohol, sugar, degrees Brix, and pH were considered and several samples of apple and grape juice from different brands were prepared and analyzed. In the first stage, to determine the value of the parameters of each sample was determined by the standard analysis methods. Then, the best–worst method was applied to measure the selection criteria of juice producers, and then the function of linear values of the piece was used to rank the Juice products of the studied companies (SH, S, P). The results showed the following order for the studied brands: P-Apple > S-Grape > SH-Apple > SH-Grape > S-Apple. This study showed that the multi-criteria decision theory is a promising method to rank food products of different companies. [ABSTRACT FROM AUTHOR]

In this paper a multi-criteria decision-making (MCDM) method is developed to rank a set of insurance companies. The proposed method is based on combining two MCDM methods: Extended Best–Worst (EBW) and Multiple Reference Point (MRP) methods. We formulate the problem of finding a priority vector from a set of interval pairwise comparisons applying an EBW method which allows the decision maker (DM) to use interval values in order to describe the relative importance of one criterion over another. The EBW method, using fuzzy set theory, can successfully handle the vagueness and ambiguity present in the judgments. Lastly, the MRP method is employed to obtain an overall score for each company using the weights established at the first stage. A case study is presented to rank Spanish non-life insurance companies based on the constructed model. Since the evaluation of insurance companies involves a great number of indicators, it is a complex MCDM issue. The results show the effectiveness of the proposed method and offer an insightful reference for an evaluation of the insurance industry. [ABSTRACT FROM AUTHOR]

With the rapid development of unmanned aerial vehicles (UAVs) and their applications in problems such as power line inspection, selecting the appropriate UAV supplier according to several sustainable attributes has attracted many interests. In this regard, an integrated multiattribute group decision-making (MAGDM) method based on the best-worst method (BWM) and MULTIMOORA method with two-dimension linguistic intuitionistic fuzzy variables (2DLIFVs) is proposed in this paper for the selection of UAV suppliers. First, the 2DLIFV is utilized to represent the uncertain, fuzzy, and linguistic evaluations of the experts on the evaluation attributes. Second, the two-dimension linguistic intuitionistic fuzzy BWM (2DLIF-BWM) is introduced to compute the weights of the attributes. Then, a novel expert weight calculation method that combines the uncertainty degree and consensus degree of the experts is introduced. Next, the 2DLIF-MULTIMOORA method is proposed, where the aggregation operators and distance measures of the 2DLIFVs are used to determine the ranking results of different alternatives. Finally, a real case of selecting a sustainable UAV supplier for power line inspection is presented to illustrate the process of the proposed method. The experimental results are further analyzed through sensitivity and comparative analyses to show the feasibility and effectiveness of the proposed method. From the results, it can be found that the proposed method can more flexibly represent the uncertain assessments while providing reasonable and reliable results. [ABSTRACT FROM AUTHOR]

Iterative multi-attribute reverse auctions in practice create certain difficulties for both the buyer and participating bidders. While the buyer faces the problem of creating the right attribute weights, the bidders have difficulty in adjusting the attribute values in each round. In this paper, we present an iterative multi-attribute reverse auction mechanism based on integrated data envelopment analysis (DEA) and best–worst method (BWM) with an objective of reducing the intervention of the buyer in the determination of the winner and also easing up the preference elicitation process. Unlike the typical scoring auctions, the proposed mechanism does not require the buyer to estimate the characteristics of the participating sellers in order to determine the optimal scoring function. As there will be no other intervention from the buyer during the winner determination process, the proposed method makes the procurement process impartial and corruption-free. Besides solving the buyer's problem, the proposed mechanism is also associated with an optimal bid determination method (OBDM) to assist the sellers in formulating improvised bids in iterative rounds of the auction. Simulation experiments show that the proposed OBDM benefits both the buyer and sellers. For the buyer, it provides higher expected utility and attribute values as per his preferences; for the seller, it gives a better expected profit and a higher probability of winning. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak has currently led to serious social and economic consequences. In poor and developing countries, there are more challenges and barriers to tackling the pandemic. The study's aim is to propose a hybrid approach to multiple-criteria decision-making (MCDM) models for determining the most efficient intervention strategies. The methodology is a combination between the Best-Worst Model (BWM) and Group Best-Worst Model (GBWM) to estimate the efficiency score of intervention. Based on the background of knowledge, five groups of stakeholders including Academicians, Entrepreneurs, Commons Residents, Social Workers, Health Workers are considered decision-makers (DMs). A set of nine potential strategies was evaluated and prioritized by all DMs. The findings have shown that different groups of stakeholders prioritized differently the importance of criteria due to their interests. In the context of Vietnam, however, the Availability of Health Systems is prioritized as the most important intervention. The results and proposed model of this paper contributed to MCDM literature as well as a good reference to apply practically in many different countries. [ABSTRACT FROM AUTHOR]

In the real world, there are complex decision‐making problems in which a variety of intertwined factors and hierarchical structures exist, and it is difficult or impossible to solve these problems using classical methods. The prioritization of circular economy (CE) adoption barriers is one such complex problem that cannot be solved using current classical methods. Hence, in this paper, for the first time, a new method, namely, FBWDS, is developed. FBWDS derives from the combination of fuzzy best–worst method (BWM), fuzzy decision‐making trial and evaluation laboratory (DEMATEL), and Supermatrix structure. This proposed method establishes weights of the intertwined factors in hierarchical networks under uncertainty; these weighted factors and their interdependencies are calculated using the fuzzy BWM and fuzzy DEMATEL techniques, respectively. In addition, the Supermatrix structure is applied to integrate the results of these two techniques. The proposed approach efficiency is evaluated in the field of the CE adoption barriers using data from a cable and wire industry in Iran. The results showed that "high setup costs," "financial limitations," and "absence of public awareness about CE" rank as the most challenging barriers, and "lack of standards for designing recycled products" and "absence of standard system to evaluate performance" are the least important barriers to CE adoption in the cable and wire industry. [ABSTRACT FROM AUTHOR]

As a response to the urgent call for recovery actions against the COVID-19 crisis, this research aims to identify action priority areas post COVID-19 toward achieving the targets of the sustainable development goals (SDGs) within the 2030 Agenda for Sustainable Development launched by the United Nations (UN). This paper applies a mixed-method approach to map the post-COVID-19 SDGs targets on a fuzzy action priority surface at the country level in Iran, as a developing country, by taking the following four main steps: (1) using a modified Delphi method to make a list of the SDGs targets influenced by COVID-19; (2) using the best–worst method, as a multi-criteria decision-making tool, to weight the COVID-19 effects on the SDGs targets achievement; also (3) to weight the impact of the SDGs targets on the sustainable development implementation; and finally (4) designing a fuzzy inference system to calculate the action priority scores of the SDGs targets. As a result, reduction of poor people proportion by half (SDG 1.2), development-oriented policies for supporting creativity and job creation (SDG 8.3), end the pandemics and other epidemics (SDG 3.3), reduction of deaths and economic loss caused by disasters (SDG 11.5), and financial support for small-scale enterprises (SDG 9.3) were identified as the highest priorities for action, respectively, in the recovery agenda for sustainable development post COVID-19. The provided fuzzy action priority surface supports the UN's SDGs achievement and implementing the 2030 Agenda for Sustainable Development in Iran. It also serves as a guideline to help the government, stakeholders, and policy-makers better analyze the long-term effects of the pandemic on the SDGs and their associated targets and mitigate its adverse economic, social, and environmental consequences. [ABSTRACT FROM AUTHOR]