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The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

In the supply chain disruption risk, the issue of supplier evaluation and selection is solved by an extended VIKOR method based on regret theory.

Considering the influence of irrational emotions of decision makers, an evaluation model is designed by the regret theory and VIKOR method, which makes the decision-making process closer to reality.

The paper has some innovations in the evaluation index system and evaluation model construction. The method has good stability under the risk of supply chain interruption.

The mixed evaluation information is used to describe the attributes, and the evaluation index system is constructed by the combined method of the social network analysis method and the literature research method to ensure the accuracy and accuracy of the extracted attributes. The issue of supplier evaluation and selection is solved by an extended VIKOR method based on regret theory.

Sustainable supplier selection is of vital importance in sustainability decision of supply chain under carbon neutrality. Multi-criteria decision-making approaches are widely used in sustainable supplier selection and generally classified the involved criteria into three sustainable development (SD) dimensions: Environmental, Social and Economic. During the assignment of appropriate weighted scores to the criteria, most of the methods considered mutually exclusive criteria. However, some criteria cover multidimensions since ambiguity vagueness makes them difficult to classify into one dimension exclusively. The purpose of this paper is to find proper approaches addressed to multidimensional overlapping criteria in the evaluation of suppliers’ sustainability performance.

This study proposes three approaches to resolve the multidimensional overlapping criteria issue by data envelopment analysis (DEA) methods. The first approach uses all dimensional criteria and “dimensional overlapping criteria” in a single DEA model. The second approach consists of two-stage DEA. The first stage is to find SD dimensional performances, which are used in the second stage. The third approach uses an aggregate weight-constrained DEA model with additional constraints. Such approaches are applied to an empirical case study with six dimensions.

Results indicate that the third approach is better than the first two approaches in balancing the development among all dimensions instead of focusing on the superiority dimension to obtain high performance.

Discussing overlapping criteria in the context of sustainable supplier evaluation and other multi-criteria evaluation have a noticeable impact on evaluation systems, but appropriate approaches for this issue are currently under-researched.

This paper aims to classify journal papers in the context of hybrid quality function deployment QFD and multi-criteria decision-making (MCDM) methods published during 2004–2021.

A conceptual classification scheme is presented to analyze the hybrid QFD-MCDM methods. Then some recommendations are given to introduce directions for future research.

The results show that among all related areas, the manufacturing application has the most frequency of published papers regarding hybrid QFD-MCDM methods. Moreover, using uncertainty to establish a hybrid QFD-MCDM the relevant papers have been considered during the time interval 2004–2021.

There are various shortcomings in conventional QFD which limit its efficiency and potential applications. Since 2004, when MCDM methods were frequently adopted in the quality management context, increasing attention has been drawn from both practical and academic perspectives. Recently, the integration of MCDM techniques into the QFD model has played an important role in designing new products and services, supplier selection, green manufacturing systems and sustainability topics. Hence, this survey reviewed hybrid QFD-MCDM methods during 2004–2021.

The purpose of this article is to develop a new model called strategy segmentation methodology (SSM) by combining the Kraljic portfolio matrix (KPM) and the supplier relationship model (SRM) so that the buyer company can effectively conduct its relations with its suppliers.

The importance weights of the criteria defining the dimensions of each model are calculated with the single-valued neutrosophic analytical hierarchy process (SVN-AHP) method. Subsequently, the derived importance weights are employed in the single-valued neutrosophic technique for order preference by similarity to ideal solution (SVN-TOPSIS) method to obtain the scores of the suppliers and their supplied items. In order to illustrate the feasibility of the proposed methodology, a case study in the machinery industry is performed with the related comparative analysis.

The implementation of SSM enables to formulate various strategies to manage suppliers taking into account the items they procure, their capabilities and performance and the supplier–buyer relationship strength. Based on the proposed strategies, it is concluded that the firm in the case study should terminate its relationship with six of its suppliers.

Although KPM has become the basis of purchasing strategies for various businesses, it neglects the characteristics of suppliers and the buyer–supplier relationship. In this study, KPM is integrated with the SRM approach presented by Olsen and Ellram (1997) to overcome these disadvantages of KPM. The novel integration of the two approaches enables the realization of a robust and reliable supplier classification model.

This study aims to focus on sustainable supplier selection in a construction company considering a new multi-criteria decision-making (MCDM) method based on dominance-based rough set analysis. The inclusion of sustainability concept in industrial supply chains has started gaining momentum due to increased environmental protection awareness and social obligations. The selection of sustainable suppliers marks the first step toward accomplishing this objective. The problem of selecting the right suppliers fulfilling the sustainable requirements is a major MCDM problem since various conflicting factors are underplay in the selection process. The decision-makers are often confronted with inconsistent situations forcing them to make imprecise and vague decisions.

This paper presents a new method based on dominance-based rough sets for the selection of right suppliers based on sustainable performance criteria relying on the triple bottom line approach. The method applied has its distinct advantages by providing more transparency in dealing with the preference information provided by the decision-makers and is thus found to be more intuitive and appealing as a performance measurement tool.

The technique is easy to apply using “jrank” software package and devises results in the form of decision rules and ranking that further assist the decision-makers in making an informed decision that increases credibility in the decision-making process.

The novelty of this study of its kind is that uses the dominance-based rough set approach for a sustainable supplier selection process.

The present study aims to provide a practical and robust assessment technique for assessing countries' investability in global supply chains to practitioners. Thus, the proposed approach can help decision-makers evaluate and select appropriate countries in the expansion process of the global supply chains and reduce risks concerning country (market) selection.

The present study proposes a novel decision-making approach, namely the REF-Sort technique. The proposed approach has many valuable contributions to the literature. First, it has an efficient basic algorithm and can be applied to solve highly complicated decision-making problems without requiring advanced mathematical knowledge. Besides, some characteristics differentiate REF-Sort apart from other techniques. REF-Sort employs the value or value range that reflects the most typical characteristic of the relevant class in assignment processes. The reference values in REF-Sort and center profiles are similar in this regard. On the other hand, class references can be defined as ranges in REF-Sort. Secondary values, called successors, can also be employed to assign a value to the appropriate class. REF-Sort can also determine the reference and successor values/ranges independently of the decision matrix. In addition, the proposed model is a maximally stable and consistent decision-making tool, as it is resistant to the rank reversal problem.

The current papers' findings indicate that countries have different features concerning investment. Hence, the current paper pointed out that only 22% of the 95 countries are investable, whereas 19% are risky. Thus, decision-makers should make detailed evaluations using robust, powerful, and practical decision-making tools to make more reasonable and logical decisions concerning country selection.

The current paper proposes a novel decision-making approach to evaluate. According to the authors' information, the proposed model has been applied to evaluate investable countries for the global supply chains for the first time.

Untimely delivery of goods and services, especially in a post-COVID landscape, is a critical harbinger of end-to-end fulfillment. Existing literature in supplier delivery modeling is focused on penalizing suppliers for late deliveries built into a contractual transaction, which eventually erodes trust. As such, a holistic modeling technique focused on long-term relationship building is missing. This study aims to design a supplier evaluation model that analytically equates supplier delivery performance to cost realization while replicating a core attribute of successful supply chains – alignment, leading to long-term supplier relationships.

The supplier evaluation model designed in this paper uses delivery deviation as a unit of measure as opposed to delivery duration to enhance consistency with enterprise resource planning protocols. A one-sided modified Taguchi-type quality loss function (QLF) models delivery lateness to construct a multinomial probability penalty cost function for untimely delivery. Prescriptive analytics using simulation and optimization of the proposed mathematical model supports buyer–supplier alignment.

The supplier evaluation model designed herein not only optimizes likelihood parameters for early and late deliveries for competing suppliers to enhance total landed cost comparisons for on-shore, near-shore and off-shore suppliers but also allows for the creation of an efficient frontier toward supply base optimization.

At a time of systemic disruptions such as the COVID pandemic, global supply chains are at risk of business continuity. Supplier evaluation models need to focus on long-term relationship modeling as opposed to short-term contractual penalty-based modeling to enhance business continuity. The model offered in this paper is grounded in alignment – a cornerstone of successful supply chain integration, and offers an interesting departure from traditional modeling techniques in this genre.

The results from this analytical approach offer flexibility to a supply manager toward building redundancies in the supply chain using an efficient frontier within the supply landscape, which also helps to manage disruption and maintain end-to-end fulfillment.

The model offered in this paper is grounded in alignment – a cornerstone of successful supply chain integration, and offers an interesting departure from traditional modeling techniques in this genre. The authors offer a rational solution by creating an evaluation model that uses penalty cost modeling as an internal quality measure to rate suppliers and uses the outcome as a yardstick for negotiations instead of imposing penalties within contracts.

As the COVID-19 epidemic ravages the world in the fourth industrial revolution era, the manufacturing sector faces its worst situation in a century. Lean philosophy, renowned as a “warrior philosophy,” can be an able rescuer to these industries. This study aims to identify the hurdles to lean strategy implementation and conduct an analysis to provide cognizance to policymakers, practitioners and decision-makers.

This study aims to identify the obstacles that obstruct lean implementation into seven primary barriers/components, with the fuzzy DEMATEL approach being used to evaluate the critical factors as well as the cause and effect factors among them. Expert opinions are sought to obtain the relevant data for evaluation purposes.

The results reveal that a firm should focus on firm cultural conflict scenario, resources–responses incapability, improve on suppliers’ attitude and execute a proper planning and logistics equation to alleviate the hindrances of implementing lean. As these causal factors influence the effect factors, namely, top management vision, management–employee relationship and human resource building, focusing on them automatically improves the effect factors; thus, the surge to overcome resistance to lean implementation is alleviated.

This research aids in identifying and analyzing lean implementation issues in the manufacturing and industrial sectors. The observations, results and insights drawn can act as a guiding force to rupture the resistance envelope covering the domain of lean implementation and possibly reinstating industries to survive and excel in the business post-COVID era.

This research introduces barriers to lean implementation in a unique way, as it articulates all sections of an industry and group the barriers based on the classification. It further prioritizes the barriers for their importance in the Indian industrial scenario. This would help the industry professionals and managers access the barriers and generate insight on how and where to start implementing lean.

This study aims to develop a comprehensive green supplier governance (GSG) concept and explore whether specific GSG approaches (green supplier assessment, green supplier assistance and green strategic partnership with suppliers (GSPS)) bring environmental and economic performance. Moreover, this study aims to reveal a synergistic effect of three GSG approaches on performance improvement.

Using data collected from 200 Chinese manufacturing firms, regression analysis was employed to reveal the relationship between specific GSG approaches and firm performance. Further, cluster analysis was used to identify groupings of firms regarding implementation levels of three GSG approaches and compare the performance of the firm groups.

Green supplier assessment (GSA) can bring environmental performance, but GSA is not associated with economic performance. Green supplier assistance is positively associated with economic performance, while green supplier assistance cannot improve environmental performance. Only GSPS leads to improvement for both environmental and economic performance. Furthermore, firms with high implementation levels of GSA and GSPS (whether with high or low implementation levels of GSAS) can achieve the best environmental and financial performance.

This study provides implications for firms to more strategically and comprehensively implement GSG approaches, which can be more effective in bringing environmental and economic performance.

The authors' study extends the GSG concept with two approaches by subdividing the collaborative approach into green supplier assistance and GSPS based on the collaboration levels. This study also sheds light on how to improve firm performance by different GSG approaches and reveals a synergistic effect of three GSG approaches on performance.