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This research aims to explore the various green supply chain management (GSCM) performance measures and develop the efficient performance measurement framework for evaluation of influence of GSCM adoption on organizational performance.

This research proposes a hybrid framework of Pythagorean fuzzy analytic hierarchy process and Pythagorean fuzzy weighted aggregated sum product assessment technique. The usefulness of proposed framework is validated using empirical case example of Indian manufacturing organization.

The finding reveals that the overall performance of case organization is 67.03% based on define set of performance measures. Further, the proposed framework has been validated with other three Indian automobile manufacturing organizations. The results obtained were confirmed with selected empirical case company. The proposed hybrid framework provides the effective path to measure and benchmark the impact of each performance measures on system performance.

This research is limited to automobile sector of India; hence the results obtained in this study may not be comprehensibly used to other sectors due to different product and process fields.

This research aids the industrial practitioners to effectively implement the green supply chain management (GSCM) and helps them to boost the overall performance of business organizations in three dimensions of sustainability.

The Sustainable Lean Six Sigma (SLSS) adoption approach, advancements in Internet technologies and the use of Industry4.0 technologies has resulted in faster customer need fulfilment. The Industry4.0 technologies have resulted in a new paradigm where strategic and operational decisions are in favour of profitability and long-term viability. The purpose of this study is to identify Industry4.0-SLSS practices and sustainable supply chain performance metrics, as well as to develop a framework for decision-makers and managers to make supply chains more sustainable.

The 33 Industry4.0-SLSS practices and 24 performance metrics associated with the sustainable supply chain are shortlisted based on extensive literature review and expert opinion. The Pythagorean Fuzzy Analytical Hierarchy Process (PF-AHP) approach is used to evaluate the weights of Industry4.0-SLSS practices after collecting expert panel opinions. The Weighted Aggregated Sum Product Assessment (WASPAS) methodology used these weights to rank performance metrics.

According to the results of PF-AHP, “Product development competencies (PDC)” are first in the class of major criteria, followed by “Advanced technological competencies (ATC)” second, “Organisational management competencies (OMC)” third, “Personnel and sustainable competencies (PSC)” fourth and “Soft Computing competencies (SCC)” fifth. The performance metric “Frequency of NPD” was ranked first by the WASPAS method.

The proposed paradigm helps practitioners to comprehend Industry4.0 technology and SLSS practices well. The identified practices have the potential to boost the sustainability and supply chain's performance. Organizational effectiveness will benefit from practices that promote a sustainable supply chain and the use of developing technology. Managers can evaluate performance using performance metrics that have been prioritized.

The present study is one of the unique attempts to establish a framework for enhancing the performance of the sustainable supply chain. The idea of establishing Industry4.0-SLSS practices and performance measures is the authors' original contribution.

This research aims to identify and prioritize the circular economy (CE) benefits (CEBs) due to the adoption of CE enablers (CEEs) in the Indian manufacturing organization context.

This research proposes a hybrid framework of Pythagorean fuzzy analytic hierarchy process (PF-AHP) and Pythagorean fuzzy TODIM (an acronym in Portuguese for Interactive Multicriteria Decision-Making) techniques. It identifies the CEEs and CEBs based on literature review and validated through industrial experts. Further, this research conducts an empirical case study to demonstrate the applicability of the proposed framework.

The result shows that CE enabler SE1 (clear vision, support and commitment from top management for CE adoption) is the most critical enabler for CE implementation. The CE benefit CEB1 (improves the value chain of products and mitigating environmental damage during product life cycle phase) is the most significant benefit derived from the adoption of CEEs. The proposed framework will provide a more accurate, structural and systematic approach to the business organizations for achieving the CEBs in a stepwise manner through the effective adoption of CEEs.

The findings of this research are nation-specific and based on a case study of single manufacturing industry. Thus, the result obtained can vary from case to case and nation to nation.

A deep understanding of each CEEs and CEBs would help build confidence among decision-makers and industrial practitioners to eliminate the risks associated with CE implementation.

The COVID-19 pandemic has showcased the lack of resilience found in the global value chains (GVCs) of multinational enterprises (MNEs). Existing evidence shows that MNEs have only recently and slowly started recovering and attempting to rebuild the resilience of their GVCs. This paper analyzes the challenges/inhibitors faced by MNEs in building their resilience through their GVCs.

A four-stage hybrid model was used to identify the interrelationship among the identified inhibitors and to distinguish the most critical ones by ranking them. In the first stage, we employed a modified total interpretive structural modeling (m-TISM) approach to determine the inter-relationship among the inhibitors. Additionally, we identified the inhibitors' driving power and dependency by performing a matrix multiplication applied to classification (MICMAC) analysis. In the second stage, we employed the Pythagorean fuzzy analytic hierarchy process (PF-AHP) method to determine the weight of the criteria. The next stage followed, in which we used the Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method to rank the inhibitors. Finally, we performed a sensitivity analysis to determine the robustness of the framework we had built based on the criteria and inhibitors.

We find business sustainability to have the highest importance and managerial governance as the most critical inhibitor hindering the path to resilience. Based on these insights, we derive four research propositions aimed at strengthening the resilience of such GVCs, followed by their implications for theory and practice.

Our findings contribute to the extant literature by uncovering key inhibitors that act as barriers to MNEs. We link out our findings with a number of propositions that we derive, which may be considered for implementation by MNEs and could help them endow their GVCs with resilience.

This study aims to investigate and classify the hospital logistics key performance indicators (KPIs) using the context of public hospitals in remote areas.

The public hospitals in northern Thailand were selected for the case study. The questionnaire was developed and used to collect data from hospital logistics experts. Then, the analytic hierarchy process (AHP) method was used to evaluate the hospital logistics KPIs in each dimension.

This research found that the procurement management dimension is ranked highest. Information and technology management is the last rank in the hospital logistics KPIs used for public hospitals in remote areas.

The public hospitals located in northern Thailand were selected for the case study. Fuzzy multi-criteria decision-making methods can be used to reduce the vagueness of the values.

The results from this study can be a guideline for hospitals to improve the efficiency of their logistics operations.

The decision-makers in the hospital can use these results to improve the hospital’s logistics performance in the future, which could help increase the service level and the safety of the patients.

The hospital logistics KPIs were revised, and the crucial KPIs were prioritized for improving the hospital logistics using the AHP method.

The sustainable and circular growth of agro-produce is crucial in today's era. The current paper focuses on identifying the drivers which promote sustainability as well as circularity in the agro-produce supply chain and favor its implementation in agro-produce supply chain.

Drivers are identified by carrying out a brief literature review and then short-listed based on the expert's opinion. The crucial drivers identified are then categorized into four groups, i.e. farms, social, government and organization. A DEMATEL-DANP approach is used to analyze the relation among subfactors and factors by deriving network relations map. Further, the weights of each subfactor are measured followed by calculating the ranks of the drivers in significance with successful implementation of sustainable circular economy.

This study has applied DEMATEL-DANP approach to analyze the relationship among four factors and twelve sub factors and their contribution towards adopting the culture of sustainable circular economy in agro-produce supply chain. The results show that “Integration of farmers” and “Updated infrastructure and tools of the farm to promote diverse farming” are primary drivers for implementing SCE in APSC.

The research explored the domains of sustainability and circularity separately. Drivers that could accelerate the implementation of circularity in agro-produce in a sustainable manner were identified. This will help in designing sustainable circular model for working of the agro-produce supply chain.

Selecting the optimal supplier is a challenging managerial decision that involves several dimensions that vary over time. Despite the considerable attention devoted to this issue, knowledge is required to be updated and analyzed in this field. This paper reveals new opportunities to advance supplier selection (SS) research from a multidimensional perspective. Moreover, this study aims to formalise SS knowledge to enable the appropriate selection of sustainable, resilient and circular criteria.

This study is developed in two stages: first, a systematic literature review is conducted to select relevant papers. Descriptive and thematic analyses are employed to analyze criteria, solving approaches and case studies. Second, a criterion knowledge-based framework is developed and validated by experts to be implemented as ontology using Protégé software.

Evaluating the viability of suppliers need further studies to integrate other criteria and to align SS objectives with research advancement. Artificial intelligence tools are needed to revolutionize and optimize the traditional techniques used to solve this problem. Literature lucks frameworks for specific sectors. The proposed ontology provides a consistent criteria knowledge base.

For academics, the results of this study highlight opportunities to improve the viable SS process. From a managerial perspective, the proposed ontology can assist managers in selecting the appropriate criteria. Future works can enrich the proposed ontology and integrate this knowledge base into an information system.

This study contributes to promoting knowledge about viable SS. Capitalizing the knowledge base of criteria in a computer-interpretable manner supports the digitalization of this critical decision.

This research identifies the enablers for implementing circular supply chains (CSCEs) and analyzes interrelationships between them to quantify their driving and dependence power to understand the critical CSCEs.

Initially, 10 CSCEs are identified for the Indian apparel industries through an extant literature review and validated using the Delphi method by seeking experts' opinions. The identified CSCEs are subjected to a novel neutrosophic interpretive structural modeling (N-ISM) method to capture the interrelationships between CSCEs and compute the driving and dependence power of CSCEs.

The findings of the present research work revealed that “supportive legislative framework, awareness of circular economy's potential for revenue gain and availability of trained research and development (R&D) team” are the critical CSCEs that need to be considered while implementing a circular supply chain in apparel industries.

This study offers insightful implications to guide practitioners in implementing the circular economy in apparel supply chains.

This research work is one of the earlier studies to analyze the enablers for implementing circular supply chains. This study has explored CSCEs in the context of apparel industries. From a methodological perspective, the novel N-ISM method is worth highlighting as the originality of the work.