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The COVID-19 pandemic has had a significant and worldwide influence on healthcare delivery, and it has significantly increased the pace at which digital technology is being used. Blockchain, one of these developing digital technologies, is distinguished by a number of properties. This study focuses on a blockchain-enabled healthcare supply chain. The purpose of this work is to investigate how blockchain technology (BCT) benefits the performance of healthcare supply chain management (HSCM).

The present study is based on the empirical research. Blockchain Technology (BCT), Healthcare Sustainable Supply Chain Practices (HSSCP), Healthcare Supply Chain Performance (HSCP) and Stakeholders’ Involvement (SI) practices are identified from the literature review and hypotheses are framed to check their interrelationship. For testing of hypothesis, a questionnaire was developed. Data collection was done by healthcare professionals via Google docs. The IBM SPSS version 22.0 was used to analyze the data and IBM SPSS AMOS 22.0 software was used for the development of structural modal. The data was collected through the Google form from the stakeholders of healthcare sector and analyzed through Structural Equation Modelling.

This research is focused on adoption of BCT enabled Healthcare Sustainable Supply Chain to improve HSCP. From the result, it had been found that BCT is positively effecting the stakeholder's involvement (SI) and HSSCP practices. Cumulatively, they positively impact the performance of HSCP. From this study, it is found that adoption of BCT enabled Healthcare Sustainable Supply Chain succours to combat COVID-19 situation.

This study attempts to show the potential benefits of the adoption of BCT enabled HSSCP to improve HSCP.

Idea of circular economy defies the classical “make-use-dispose” approach of linear economic model. In the context of health-care industry, it relies heavily on the supply chain practices implemented by industry stakeholders. The purpose of this study is to explore such relationships, study their structure and put it across for attaining sustainability at large.

This study is an empirical research conducted on 145 health-care firms. The collected data is analysed to develop structural and measurement model. The five constructed hypotheses are examined and tested through structural equation modelling.

The study illustrates the latent relationships that exist among the stakeholders involvement, sustainable supply chain practices, sustainable performance and circular economy for health-care industry. It is found that the adoption of sustainable supply chain practices improves health-care performance, which, in turn, have positive influence on circular economy.

The structural and measurement model is developed in the context of circular health-care economy. It can be validated or improvised by conducting similar research in other industry using different methods. This research work fulfils the long existing gap in research by offering a linkage between various constructs to achieve health-care circular economy. Based on the research results, future researchers can build theories of circular economy and sustainability for health-care industry.

The study attempts to study the supply chain ways to achieve circular economy for Indian health-care sector. It considered latent relationships among the set of constructs, which are needed for theory building at later stage.

The already-strained vaccine supply chain (VSC) of the expanded program for immunization (EPI) require a more robust and structured distribution network for pandemic/outbreak vaccination due to huge volume demand and time constraint. In this paper, a lean-agile-green (LAG) practices approach is proposed to improve the operational, economic and environmental efficiency of the VSC.

A fuzzy decision framework of importance performance analysis (IPA)–analytical hierarchy process (AHP)–technique for order for preference by similarity in ideal solution (TOPSIS) has been presented in this paper to prioritize the LAG practices on the basis of the influence on performance indicators. Sensitivity analysis is carried out to check the robustness of the presented model.

The derived result indicates that sustainable packaging, coordination among supply chain stakeholders and cold chain technology improvement are among the top practices affecting most of the performance parameters of VSC. The sensitivity analysis reveals that the priority of practices is highly dependent on the weightage of performance indicators.

This study's finding will help policymakers reframe strategies for sustainable VSC (SVSC) by including new management practices that can handle regular immunization programs as well as emergency mass vaccination.

To the best of the authors' knowledge, this is the first study that proposes the LAG framework for SVSC. The IPA–Fuzzy AHP (FAHP)–Fuzyy TOPSIS (FTOPSIS) is also a novel combination in decision-making.

Today, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully for retaining operational excellence. Accordingly, varieties of paramount practices, i.e. Lean, Agile, Resilient and Green practices, are integrated in present study with the objective to develop a Decision Support Framework (DSF) to select robust supplier under the extent of Lean-Agile-Resilient-Green (LARG) practices for a manufacturing firm. The framework is developed and validated in the Indian automotive sector, where the primary data is collected based on perceptions of the respondents working in an automotive company.

LARG metrics can ponder ecological balance, customer satisfaction, associations, effectiveness and sustainability and thus, the study consolidated LARG practices in one umbrella to develop a DSF. The analytical approach under DSF is developed by the integration AHP, DEMATEL, ANP, Extended MOORA and SAW techniques in present study to evaluate a robust supplier under the aegis of LARG practices in SC. DSF is developed by scrutinizing and categorizing LARG characteristics, where the selected LARG characteristics are handled by fuzzy sets theory to deal with the impreciseness and uncertainty in decision making.

The study has identified 63 measures (15 for Lean, 15 for Agile, 14 for resilient and 19 for Green) to support the robust supplier selection process for manufacturing firms. The findings of study explicate “Internal communication agility”, “Interchangeability to personnel resources”, “Manufacturing flexibility”, “degree of online solution”, “Quickness to resource up-gradation”, “Manageability to demand and supply change”, “Overstocking inventory practices” as significant metrics in ranking order. Additionally, “Transparency to share information”, “Internal communication agility”, “Manufacturing Flexibility”, “Green product (outgoing)” are found as influential metrics under LARG practices respectively.

A technical DSF to utilize by the managers is developed, which is connected with knowledge-based theory and a case of an automobile manufacturing firm is presented to illustrate its implementation. The companies can utilize presented DSF to impose service excellence, societal performance, agility and green surroundings in SC for achieving sustainable outcomes to be welcomed by the legislations, society and rivals. The framework represents an important decision support tool to enable managers to overcome imprecise SC information sources.

The study presented a proficient platform to review the most significant LARG alternative in the SC. The study suggested a cluster of LARG metrics to support operational improvement in manufacturing firms for shifting gear toward sustainable SC practices. The present study embraces its existence in enrolling a high extent of collaboration amongst clients, project teams and LARG practices to virtually eradicate the likelihood of absolute project failure.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.

The purpose of this paper is twofold: firstly, to provide a measurement instrument for supply chain 4.0 ambidexterity by applying the theoretical perspective of ambidexterity to advance Industry 4.0; secondly, to empirically analyse how supply chain 4.0 ambidexterity and lean supply chain management contribute to enhancing the focal firm’s operational performance.

Empirical results are obtained through analysis of survey data from a sample of 209 Spanish focal firms in industrial sectors in an intermediate position in the supply chain. Structural equation modelling was performed to test the three proposed hypotheses.

Drawing on resource orchestration theory and the relational resource-based view, this study empirically demonstrates the full mediating role of lean supply chain management in the relationship between supply chain 4.0 ambidexterity and the focal firm’s operational performance.

Although recent research has highlighted the pertinence of applying inter-organisational ambidexterity to foster Industry 4.0 (Hofmann et al., 2019), to the best of the authors’ knowledge, this is one of the first studies to apply this theoretical framework to explain the transition to supply chain 4.0. In addition, to date, to the best of the authors’ knowledge, no study exists that has developed a measurement scale and used this concept in an empirical analysis to advance theory development.

This study aims to propose an integrated framework for analyzing the effect of lean and agile innovation on the lean and agile supply chains.

The literature was reviewed and the dimensions of lean and agile supply chain/innovation were extracted. The statistical population included the managers and experts of pharmaceutical companies in Isfahan province. Eight pharmaceutical companies were selected. A researcher-made questionnaire was used to investigate the research variables. The face and content validity of the questionnaire and the data reliability were confirmed. After data collection, the studied companies were positioned in a two-by-two matrix and the associated data of two cells of the matrix, i.e. high lean supply chain/innovation and high agile supply chain/innovation were used for further statistical effect analysis using Smart-PLS.

The research results indicated that with the improvement of lean innovation in pharmaceutical companies, the lean supply chain improved by 97.9%; and with the improvement of agile innovation, the agile supply chain improved by 97.1%.

Considering lean innovation, pharmaceutical companies should deal with the process of conceptualizing innovation, and regarding agility strategy, their focus should be more on generating ideas to improve their agile supply chain. This study was performed during the COVID-19 pandemic and offers appropriate innovation strategies to improve the supply chain of pharmaceutical companies.

The literature review implies that no research has been conducted on the selected and classified variables of this study. Also, using the positioning matrix before statistical analysis distinguishes this paper from similar studies.

This paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.

The new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.

The proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.

This paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.

The advancements in internet technologies and the use of sophisticated digital devices in supply chain operations incessantly generate enormous amounts of data, which is termed as big data (BD). The BD technologies have brought about a paradigm shift in the supply chain decision-making towards profitability and sustainability. The aim of this work is to address the issue of implementation of the big data analytics (BDA) in sustainable supply chain management (SSCM) by identifying the relevant factors and developing a structural model for this purpose.

Through a comprehensive literature review and experts’ opinion, the crucial factors are found using the PESTEL framework, which covers political, economic, social, technological, environmental and legal factors. The structural model is developed based on the results of the total interpretive structural modelling (TISM) procedure and MICMAC analysis.

The policy support regarding IT, culture of data-based decision-making, inappropriate selection of BDA technologies and the laws related to data security and privacy are found to affect most of the other factors. Also, the company’s vision towards environmental performance and willingness for material and energy optimization are found to be crucial for the environmental and social sustainability of the supply chain.

The study is focused on the manufacturing supply chain in emerging economies. It may be extended to other industry sectors and geographical areas. Also, additional factors may be included to make the model more robust.

The proposed model imparts an understanding of the relative importance and interrelationship of factors. This may be useful to managers to assess their strengths and weaknesses and ascertain their priorities in the context of their organization for developing a suitable investment plan.

The study establishes the importance of BDA for conservation and management of energy and material. This is crucial to develop strategies for enhancing eco-efficiency of the supply chain, which in turn enhances the economic returns for the society.

This study addresses the implementation of BDA in SSCM in the context of emerging economies. It uses the PESTEL framework for identifying the factors, which is a comprehensive framework for strategic planning and decision-making. This study makes use of the TISM methodology for model development and deliberates on the social and environmental implications too, apart from theoretical and managerial implications.

Food sustainability is a world-acknowledged issue that requires urgent integrated solutions at multi-levels. This study aims to explore how food firms can improve their sustainability performance through digital traceability practices, considering the mediating effect of sustainability-oriented innovation (SOI) and the moderating effect of supply chain learning (SCL) for the food supply chain therein.

Hierarchical regression with a moderated mediation model is used to test the proposed hypotheses with a sample of 359 food firms from four provinces in China.

Digital traceability has a significant positive impact on the three pillars of sustainability performances among food firms. SOI (product innovation, process innovation and organisational innovation) mediates the relationship between digital traceability and sustainability performance. SCL plays moderating roles in the linkage between digital traceability and both product and process innovation, respectively.

This paper contributes as one of the first studies to develop digital traceability practices and their sustainability-related improvements for Chinese food firms; it extends studies on supply chain traceability to a typical emerging market. This finding can support food sustainability practice in terms of where and how to invest in sustainability innovation and how to improve economic, environmental and social performance.