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The paper aims to clarify the relationship of various enablers of supply chain (SC) management like lean enablers, agile enablers and leagile enablers. It proposes modeling the enablers to find the most appropriate strategy or methodology for determining the lean enabled SC agility.

The paper proposed the fuzzy SWARA-WASPAS methodology for determining the role of lean in enabling the SC agility. Also in continuation the AHP methodology is applied to find the priority weightage and ranking of leagile enablers, and a comparative analysis is done to select the best approach among the above two methodologies so that it would be beneficial for all the stakeholders.

The paper provides the investigation and identification of 28 lean enablers, 11 agile factors which are highly responsible to affect any SC specially focusing of automobile sector. Apart from above 9 leagile enablers were also identified in the paper. Finally, the comparative analysis has been done in the results obtained by two methodologies – AHP & fuzzy SWARA-WASPAS – to determine the lean enabled SC agility, and also to which strategy should be adopted by the organizations as per the customized requirement of their SC.

The research limitation is that in future, there may be more number of lean, agile and leagile enablers which may be explored by different researchers in their findings, which may vary the output result accordingly. Though the research implications focus on having an advantage and impact on all aspects whether it is social, economic or commercial, there is a possibility of exploration of new and better decision-making tools and approaches in future. Also, the researchers are encouraged to test the proposed propositions further by taking case study of any automobile manufacturing organizations for the validation of the results.

The paper includes implications for the development of a powerful interrelationships between lean enablers, agile enablers and leagile enablers, which will help organization and the managers to take decisions regarding selection of best strategy appropriate to them to enhance their SC. This will also help new researchers of the field to take help of the research findings for exploring new and better optimization tools and techniques in future.

The findings of the research work will definitely help society, as the successful implementation of the lean, agile or leagile strategies in their SC system will leads to an increase in their efficiency and productivity, which will ultimately results in huge advantage to all the stakeholders directly or indirectly connected with the organization. The productivity dynamics cycle will also improve which will lead to more benefits to all in the market and achieving higher living index with better living standards.

This paper fulfills an identified need to study the various enablers of lean, agile and leagile SC, as well as their interrelationships. Also there is a need to understand the importance and effect of lean in enabling the SC agility.

Sustainability, as we all know has become such a crucial global matter that even the United Nations has not failed to take cognizance of it and has addressed the same through the formation of ‘Sustainable Development Goals’. As per an article on Global Reporting Initiative's Medium platform, it has been estimated that ‘the supply chain activities of a firm account for around 90% of its sustainability impressions’ (according to Sustainalytics' future-proofing supply chains study). Taking this view forward, sustainable supply chain management (SSCM) is one such area which has acquired substantial significance in the recent times. Studies in the area of SSCM has found an increasing attention especially in the past two decades. This paper strives to review the recent literature in SSCM to identify the recent trends in this area of research. The paper attempts to identify the contemporary and upcoming research topics and also the research gaps in the field of SSCM which could act as a potential source of further research for the academia.

The purpose of this study is to establish a synthetic group decision framework based on the Pythagorean fuzzy (PF) set to select the optimal medicine cold chain logistics provider (MCCLP). Fierce market competition makes enterprises must constantly improve every link in the process of enterprise sustainable development. The evaluation of MCCLP in pharmaceutical enterprises is an important link to enhance the comprehensive competitiveness. Because of the fuzziness of expert cognition and the complexity of the decision procedure, PF set can effectively handle the uncertainty and ambiguity in the process of multi-criteria group decision decision-making (MCGDM).

This paper develops an integrated group decision framework through combining the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique and combined compromise solution (CoCoSo) approach to select a satisfactory MCCLP within PF circumstances. First, the PF set is used to process the ambiguity and uncertainty of the cognition ability of experts. Second, a novel PF knowledge measure is propounded to measure the vagueness of the PF set. Third, a comprehensive criterion weight determination technique is developed through aggregating subjective weights attained utilizing the PF DEMATEL approach and objective weight deduced by knowledge measure method. Furthermore, an integrated MCGDM approach based on synthetic weight and CoCoSo method is constructed.

The outcomes of sensibility analysis and comparison investigation show that the suggested decision framework can help decision experts to choose a satisfactory MCCLP scientifically and reasonably. Accordingly, the propounded comprehensive decision framework can be recommended to enterprises and organizations to assess the MCCLP for their improvement of core competitiveness.

MCCLP selection is not only momentous for pharmaceutical enterprises to improve transportation quality and ensure medicine safety but also provides a strong guarantee for enterprises to improve their core competitiveness. Nevertheless, enterprises face certain challenges due to the uncertainty of the assessment environment as well as human cognition in the process of choosing a satisfactory MCCLP. PF set possesses a formidable capability to address the uncertainty and imprecision information in the process of MCGDM. Therefore, pharmaceutical enterprises can implement the proposed method to evaluate the suppliers to further improve the comprehensive profit of enterprises.

Internet of things (IoT) is the technology enabler in smart city adoption and creates circular economy (CE). The purpose of this chapter is to find out the relationship nexus between IoT, smart city and CE and its practical constraints in execution. This chapter elaborately maps the empirical evidence available in the literature survey of smart city development, information and communication technology (ICT) and CE. The contributions from outstanding scholars and current topics are analyzed using high citations index. The authors referred the topics with scholarly publishers and validated the data. Following that, significant technology subjects such as big data and analytics, as well as intelligent information systems, are individually examined. The findings are the challenges in implementing IoT and its interoperability capacity due to interlinking of different devices and systems. Another key challenger as well as drivers are data volume and quality, privacy, complexity and governance. The research can help policymakers, IT infrastructure provider, bureaucrats and all other concerned stakeholders to get sensitized on the implementation of IoT at smart city infrastructure. It also describes about the importance of collaboration and embracing open innovation (OI) while implementing IoT. This study is innovative in its approach and referred literature in the field of IoT, smart city, and CE by high citation index (HCI). It also researched about the various constraints in building CE through technology deployment and discusses about multilayer and multifunctional collaboration.

The purpose of this paper is to explore a new grey relational analysis model to measure the coupling relationship between the indicators for the water environment status assessment. Meanwhile, the model deals with the problem that the changing of indicator order may result in the changing of the degree of grey relation.

The binary index submatrix of the sample matrix is given first. Then the product of the matrix and its own transpose is used to measure the characteristics of the index and the coupling relationship between the indicators. Thirdly, the grey relational coefficient is defined based on the matrix norm, and a grey coupling relational analysis model is proposed.

The paper provides a novel grey relational analysis model based on the norm of matrix. The properties, normalization, symmetry, relational order invariance to the multiplicative, are studied. The paper also shows that the model performs very well on the water environment status assessment in the eight cities along the Yangtze River.

The model in this paper has supplemented and improved the grey relational analysis theory for panel data.

As environmental protection and sustainable development become more widely recognized, greater emphasis has been placed on the significance of green supplier selection (GSS), which can support businesses both upstream and downstream in enhancing their environmental performance while preserving their strategic competitiveness. Therefore, this paper aims to propose a new framework to study GSS.

Firstly, this paper establishes a GSS evaluation criteria system including product competitiveness, green performance, quality of service and enterprise social responsibility. Secondly, based on the spherical fuzzy sets (SFSs), the Average Induction Ordered Weighted Averaging Operator-Criteria Importance Through Inter Criteria Correlation (AIOWA-CRITIC) method is used to determine the subjective and objective weights and the combination of weights are determined by game theory. In addition, the GSS framework is constructed by the Cumulative Prospect Theory-Technique for Order Preference by Similarity to Ideal Solution (CPT-TOPSIS) method. Finally, the validity and robustness of the framework is verified through sensitivity comparative and ablation analysis.

The results show that Y3 is the most promising green supplier in China. This study provides a feasible guidance for GSS, which is important for the greening process of the whole supply chain.

Under spherical fuzzy sets, AIOWA and CRITIC are used to determine weights of indicators. CPT and TOPSIS are combined to construct a decision model, considering the ambiguity and uncertainty of information and the risk attitudes of decision-makers.

Cybersecurity has received growing attention from academic researchers and industry practitioners as a strategy to accelerate performance gains and social sustainability. Meanwhile, firms are usually prone to cyber-risks that emanate from their supply chain partners especially third-party logistics providers (3PLs). Thus, it is crucial to implement cyber-risks management in 3PLs to achieve social sustainability in supply chains. However, these 3PLs are faced with critical difficulties which tend to hamper the consistent growth of cybersecurity. This paper aims to analyze these critical difficulties.

Data were sourced from 40 managers in Nigerian 3PLs with the aid of questionnaires. A novel quantitative methodology based on the synergetic combination of interval-valued neutrosophic analytic hierarchy process (IVN-AHP) and multi-objective optimization on the basis of a ratio analysis plus the full multiplicative form (MULTIMOORA) is applied. Sensitivity analysis and comparative analysis with other decision models were conducted.

Barriers were identified from published literature, finalized using experts’ inputs and classified under organizational, institutional and human (cultural values) dimensions. The results highlight the most critical dimension as human followed by organizational and institutional. Also, the results pinpointed indigenous beliefs (e.g. cyber-crime spiritualism), poor humane orientation, unavailable specific tools for managing cyber-risks and skilled workforce shortage as the most critical barriers that show the highest potential to elicit other barriers.

By illustrating the most significant barriers, this study will assist policy makers and industry practitioners in developing strategies in a coordinated and sequential manner to overcome these barriers and thus, achieve socially sustainable supply chains.

This research pioneers the use of IVN-AHP-MULTIMOORA to analyze cyber-risks management barriers in 3PLs for supply chain social sustainability in a developing nation.

This study examines the mediating and moderating effects of business regulatory compliance (BRC) on the association between sustainable supply chain management practices (SSCMP) and operational performance (PERFOP), and how corporate sustainability culture (CSC) serves as a boundary condition to BRC.

This research draws data from 245 firms operating in multiple industries in Ghana. Ordinary Least Square (OLS) was employed to test the direct effects, while Hayes Process Macros was employed to test the indirect and conditional effects among the study variables using a structural equation modelling approach.

The results showed that SSCMP has a direct positive effect on PERFOP. The study further revealed that BRC mediates the relationship between SSCMP and PERFOP. This study found that BRC negatively moderates the association between SSCMP and PERFOP, suggesting that high levels of BRC generate unintended adverse effect on the SSCMP- PERFOP link. However, the results revealed that CSC serves as a boundary condition to BRC.

To the best of our knowledge, this is the first study that emphasizes how the resource-based view and regulatory focus theory interact to explain how different degrees of CSC and BRC impact SSCMP performance outcomes. This study advances research in the sustainability literature, in response to calls for further research in this domain. This study draws decision-makers attention on the need to make sustainability practices an integral part of corporate culture in order to set a business tone that stimulates easy compliance to sustainability requirements.

The study seeks to shed light on the estimates of the carbon shadow price in the literature relying on frontier techniques. The shadow price of undesirable outputs, such as greenhouse gas emissions, assists policymakers in determining the most cost-effective methods for reducing emissions.

The study relies on the PSALSAR and PRISMA approaches for a systematic literature review. The Web of Science and Scopus databases were used for the references.

Both parametric and nonparametric methods have been employed in the literature to estimate the shadow prices of undesirable outputs. Also, results were discussed according to the methodological and application aspects, and broad conclusions on obtained results were provided, bridging climate change mitigation policies and the shadow price of undesirable outputs.

The present study applies an integrated method, PSALSAR, to conduct a systematic review of 53 studies published between 2014 and 2023 in which efficiency models were applied to estimate the shadow price of undesirable outputs, especially CO₂. After presenting the most applicable parametric and nonparametric estimation models, a systematic summary of included articles was provided, highlighting the key features of publications.

Food supply chain resilience is a critical aspect in ensuring the continuous and reliable flow of food, particularly in the face of disruptions. This study aims to address specific gaps in the existing literature by conducting a bibliometric analysis. The primary objective is to identify key areas of concern and lacunae related to disruptions and resilience within the food supply chain. The study also strives to contribute to the field by developing a comprehensive framework that evaluates the factors influencing resilience. Furthermore, the research intends to propose effective strategies for mitigating and recovering from disruptions, emphasizing the urgency of these measures in light of identified gaps in the current body of literature.

To achieve these objectives, the authors extracted the most relevant papers from Scopus and Web of Science (WoS) databases. The analysis parameters included a comprehensive review of current food supply chain practices and an exploration of trending research topics, such as sustainability, adaptability, circular economy and agility. Notably, the study recognized the pervasive impact of COVID-19 on food supply chain disruptions, with a high occurrence in the literature. Using advanced analytics tools like VOSviewer and Biblioshiny, the research delved into the role of modern technologies, including Industry 4.0, the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML) and blockchain in addressing disruptions and enhancing resilience.

The research reveals a significant impact of the COVID-19 pandemic on food supply chain disruptions, underscoring the critical need for strategies to bolster resilience. Notably, the study identifies the pivotal role of modern technologies (Industry 4.0, IoT, AI, ML and blockchain) in mitigating disruptions and enhancing resilience in the food supply chain. The bibliometric analysis conducted through VOSviewer and Biblioshiny provides valuable insights into research trends and focal areas within the literature.

The observed importance of Industry 4.0, IoT, AI, ML and blockchain implies a practical need for integrating these technologies into food supply chain operations. Moreover, the paper discusses strategies for reducing the impact caused by disruptions, providing practical guidance for resilience planning in food supply chains. Researchers can leverage the findings to direct future efforts toward areas with identified gaps and opportunities, fostering advancements in the field and offering practical insights for real-world applications.

By amalgamating insights from bibliometric analysis and the developed framework, this study contributes to a holistic understanding of the challenges and opportunities in fortifying the resilience of the food supply chain. The identified factors and strategies offer valuable insights for researchers and practitioners seeking to address disruptions in food supply chains. The study’s unique contribution lies in bridging theoretical perspectives with practical applications, enhancing the relevance of business-to-business/industrial supply chain theories.