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The purpose of this paper is to make out a complete solution to logistic outsourcing problem in a medium‐scale organization by using consistent fuzzy preference relation (CFPR) and vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) method.

The initial approach to this research was to develop a comprehensive framework for logistic outsourcing problem and selection of most appropriate third party logistic (3PL) provider.

It has been found that the organization should outsource logistic activities. The alternatives (3PL providers) have also been ranked and the fifth 3PL provider has been termed as best third party logistic provider.

The parameters selected for this study and developed framework are applicable only to a medium‐scale organization manufacturing automobile parts in northern India.

This is probably the first time that an attempt has been made to apply the two‐phase methodology approach, using CFPR and VIKOR, to analyze a multi‐criteria logistic outsourcing problem. A case is provided which demonstrates how to solve logistic outsourcing, a multi‐criteria decision‐making problem.

The advent of globalization not only made the manufacturing sector highly competitive but also facilitated best-quality products. The trend is further augmented by e-Commerce which increases the penetration to the targeted customer with the easy availability of customized product. In this backdrop, Indian manufacturing industries are striving hard to seek out best systems which will yield maximum profitability. Time is ripe to realize the true potential of agile manufacturing system (AMS). Infusion of AMS in manufacturing industry will bring forth the elusive mix of customer needs and products at lowest possible cost. But adoption and implementation of AMS is a challenging task in itself. There are certain facilitators and criteria which not only facilitate the system but also help in the effective and smooth implementation of this system. The purpose of this paper is to identify the criteria to weightage and ranking to AMS facilitators. This study was carried out by different approaches, namely, entropy approach, multi-objective optimization on the basis of ratio analysis (MOORA) method, Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) analysis and a cross-sectional survey of manufacturing firms in India.

The criteria and facilitators are identified followed by the application of entropy approach, MOORA method and VIKOR analysis to study and analyze the criteria weight and provide the ranking to AMS facilitators.

The result of the entropy approach concludes that beneficiary and non-beneficiary criteria carry 48.43 and 51.56 percent weight, respectively. MOORA method and VIKOR analysis conclude that organization structure and virtual enterprise facilitators are carrying the first and second rank, respectively.

This study is completed on the basis of responses from few experts from industry and academicians who may not reflect the attitude of entire industry community.

This research is expected to facilitate policy makers in government and industries to frame policies for optimum utilization of resources and infrastructure for better performance. This paper helps the researcher to do a case study on the implementation of AMS and then finally helps to society in getting the high-quality product in an easy way.

Integration of entropy approach, MOORA method and VIKOR analysis with identification of AMS criteria weightage and ranking to AMS facilitators has been recommended for an industry which is an innovative effort for the execution of AMS.

This paper aims to deal with the problems such as epistemic uncertainty, common cause failure (CCF) and dynamic fault behaviours that arise in complex systems and develop an effective fault diagnosis method to rapidly locate the fault when these systems fail.

First, a dynamic fault tree model is established to capture the dynamic failure behaviours and linguistic term sets are used to obtain the failure rate of components in complex systems to deal with the epistemic uncertainty. Second, a β factor model is used to construct a dynamic evidence network model to handle CCF and some parameters obtained by reliability analysis are used to build the fault diagnosis decision table. Finally, an improved Vlsekriterijumska Optimizacija I Kompromisno Resenje algorithm is developed to obtain the optimal diagnosis sequence, which can locate the fault quickly, reduce the maintenance cost and improve the diagnosis efficiency.

In this paper, a new optimal fault diagnosis strategy of complex systems considering CCF under epistemic uncertainty is presented based on reliability analysis. Dynamic evidence network is easy to carry out the quantitative analysis of dynamic fault tree. The proposed diagnosis algorithm can determine the optimal fault diagnosis sequence of complex systems and prove that CCF should not be ignored in fault diagnosis.

The proposed method combines the reliability theory with multiple attribute decision-making methods to improve the diagnosis efficiency.

The purpose of this study is the identification and analysis of key ethical issues of green procurement (GP) and the potential solutions to mitigate the issues in the Indian automobile sector.

Based on the literature review and expert elicitation, 23 ethical issues of GP in the Indian automobile industry and 11 solutions to mitigate these issues were identified. This paper explores the ethical issues based on an integrated method consisting of interpretative structural modelling fuzzy Matrice d'Impacts Croisés-Multiplication Appliquée á un Classement, analytical hierarchy process and the solutions to mitigate these issues using fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje.

The findings suggest that ethical issues such as favouritism towards suppliers and failure to fulfil business objectives by top management are identified as the most significant variables with the highest importance weights, while top management commitment for ethical behaviour is identified as the most potent solution for mitigating the issues.

This study is limited to the literature review and experts’ opinions.

The results may help practitioners and researchers to focus on major ethical issues of GP to strategize proactive solutions that may help to mitigate or eliminate the ethical issues.

This paper is an original contribution of the analysis of GP and provides an interesting insight into the Indian automotive industry.

This paper aims to propose a bed and breakfast (B&B) recommendation method that takes into account review timeliness and user preferences to help consumers choose the most satisfactory B&B.

This paper proposes a B&B ranking method based on improved intuitionistic fuzzy sets. First, text mining and cluster analysis are combined to identify the concerns of consumers and construct an attribute set. Second, an attribute-level-based text sentiment analysis is established. The authors propose an improved intuitionistic fuzzy set, which is more in line with the actual situation of sentiment analysis of online reviews. Next, subjective-objective combinatorial assignments are applied, considering the consumers’ preferences. Finally, the vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) algorithm, based on the improved score function, is advised to evaluate B&Bs.

A case study is presented to illustrate the use of the proposed method. Comparative analysis with other multi-attribute decision-making (MADM) methods proves the effectiveness and superiority of the VIKOR algorithm based on the improved intuitionistic fuzzy sets proposed in this paper.

Proposing a B&B recommendation method that takes into account review timeliness and user customization is the innovation of this paper. In this approach, the authors propose improved intuitionistic fuzzy sets. Compared with the traditional intuitionistic fuzzy set, the improved intuitionistic fuzzy set increases the abstention membership, which is more in line with the actual situation of attribute-level sentiment analysis of online reviews.

The purpose of this paper is to propose a multi-criteria decision-making model based on the case-based reasoning (CBR) method for interval-valued probabilistic linguistic term set (IVPLTS), which can cluster different categories of building suppliers for targeted management.

First, a new score function and distance measure for IVPLTS are proposed. Second, a green building supplier evaluation criterion system is constructed from five aspects: operation management, green management, cooperation potential, service level and product information. Finally, the IVPLTS-CBR model is used to evaluate the green building suppliers and groups them into three preset categories.

The feasibility and validity of the proposed method are verified by comparing with the advanced TOPSIS method and the IVPLTS-based VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. The compared results show that the proposed method is more consistent with the actual situation and has strong theoretical significance and practical value.

This paper presents a new method for clustering construction suppliers. Decision makers can use this method to classify construction suppliers into different categories, so that they can be targeted management. In this way, suppliers can be better guided and motivated to accelerate the green transformation and contribute their share to achieve the strategic goal of carbon neutral and carbon peak as soon as possible.

A new score function and distance measure for IVPLTS are proposed. Besides, a novel IVPLTS-CBR method is applied to rank and cluster building suppliers.

The purpose of this paper is to develop a stochastic multi-criteria decision-making approach to solute the warehouse location problem in the stochastic environment which contains uncertain condition.

In developed approach, the weight of criteria was calculated by using the stochastic analytic hierarchy process (SAHP) method. Alternative ranking was made and evaluated by fuzzy VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje).

This study dealt with warehouse location selection problem of a supermarket that has sellers in many regions in Turkey and selected proper warehouse.

This study combined SAHP and fuzzy VIKOR methods as a solution approach for warehouse location selection problems.

Driven by motivation of quality enhancement and brand reputation promotion, automotive industries try to improve product quality and customer satisfaction by performing quality pilot programs continuously. The purpose of this paper is to develop a dynamic model to select the improvement quality pilot program from competitive candidates based on dynamic customers’ feedback.

An extended dynamic multi-criteria decision-making method is developed by embedding dynamic triangular fuzzy weighting average operators into fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, and the novel evaluation indicator “ζ” is introduced to reflect prioritization performance.

The two evaluation indicators (Q and “ζ” ) assist quality managers to identify the best program with respect to multiple conflicting criteria and the best choice based on these two indexes shows high conformity. Besides, ranking sequences obtained by “ζ” can avoid the dilemma that there are several candidates with top priority calculated by comprehensive group utility value Q.

The dynamic MCDM method has been applied into the quality improvement procedure in Chinese domestic auto factories and contributes to highly efficient promotion.

Few dynamic models on pilot program selection for quality improvement based on dynamic customers’ feedback, this study deals with the dynamic promotion by an extended fuzzy VIKOR method and presents a case application.

In the context of India, this article proposes an integrated multicriteria decision-making (MCDM) regression-based methodology to evaluate input-level performance of the schools and investigate the impact of this performance along with contextual factors, i.e. medium of instruction and location of the school, on the school's output level performance, i.e. student pass rate.

First, Shannon entropy-based approach is applied for the weight assignment to different parameters. Then, integrated VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) technique for order preference by similarity to an ideal solution (TOPSIS)-based methodology is devised to measure the input-level performance of a school. Finally, multiple linear regression (MLR) analysis is incorporated to study the effect of input-level performance and above-mentioned contextual factors on the school's output-level performance.

Proposed methodology is applied to assess the input-level performance of 82,930 primary and secondary schools of West Bengal, India. All the factors have a significant impact on boys' pass rate, whereas only input-level performance and location of the school have a significant influence on the girls' pass rate.

The entropy-based approach highlights the importance of scientific weight assignment. Integrated MCDM demonstrates the significance of aggregation due to the variation in scores related to input-level performance across the methods. Regression analysis facilitates the exploration of determinants influencing the output-level performance of the schools.

This work depicts a holistic picture of the performance measurement system of the schools. It encompasses scientific weight assignment to the evaluation criteria, integrated input-level performance assessment of the schools and investigation into the effect of this performance, as well as other contextual factors on the output level performance.

The purpose of this study is to provide a decision support tool to deal with the problem of seting priorites among patients competing for limited health care resources. Limited resources and unlimited demands prevent health-care services to be provided to all those in need. This became publicity evident with the current Covid-19 pandemic. Although controversial, health care rationing has always existed and is now inevitable. Setting priorities becomes then inevitable. How to define those priorities is a complex and yet irresolvable issue mainly because it involves several and conflicting criteria, translated into efficiency and equity considerations. This is why multi-criteria decision analysis (MCDA) was introduced to health care as an appropriate decision-support framework for solving complex problems.

This paper proposes the application of two combined approaches – analytic hierarchy process (AHP)-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and AHP-VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), as decision support tools to rank patients with competing needs in a more effective and equitable way. A rationing scenario involving four patients, differentiated by personal characteristics and health conditions, is used to illustrate, test and compare the applicability of both approaches. After extraction of the relative weights of the prioritization criteria involved in the hypothetical scenario from paired wise comparison methods, TOPSIS and VIKOR priority setting methods were designed.

Results suggest that patients ranking from both combination approaches are similar and in accordance with the order made directly by health-care professionals. Therefore, the relative weights computed by AHP in combination with TOPSIS and/or VIKOR methods could be used with suitable applicability by health-care decision-makers.

This study is the first attempt to apply a combination of MCDA methods to patients’ prioritization context and the first to cross previous studies to deepen and consolidate the research.