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Due to the rapid surge in the number of COVID-19 cases in India, the health-care supply chain (HCSC) disruptions and uncertainties have increased manifold posing severe challenges to health-care facilities and significantly hampering the functioning of the health industry. This study aims to propose a hierarchical structural model of enablers of HCSC in the COVID-19 outbreak and identifies inter-relationships among them in the health-care market.

Enablers of emergency HCSC have been identified through extensive literature review and experts’ opinions. Subsequently, total interpretive structural modeling (TISM) and cross-impact matrix-multiplication (MICMAC) analysis have been implemented to determine the hierarchical inter-relationships among enablers and classify them according to their contribution to the overall system.

The research has identified and validated 15 enablers of the emergency supply chain in health-care businesses. The study resulted in a seven-level hierarchical structural model based on enabler’s driving and dependence powers. Further, the application of MICMAC analysis resulted in the classification of enablers into four groups, namely, autonomous, dependent, linkage and independent group.

This study would help health professionals, policymakers and academia to implement the theoretical model constructed to alleviate the effect of COVID-19 by improving the HCSC performances in pandemic situations. This study has social and economic implications in terms of cost-effective and efficient delivery of care services in health emergencies.

The proposed theoretical model constructed is a new effort addressing the issues of HCSC in the COVID-19 crisis. Procedural implementation of TISM and MICMAC analysis in this study would help researchers to grasp concepts in a very lucid manner. The present study is one of the very few studies analyzing enablers in pandemic situations by implementing the TISM approach.

The study aims to envisage upon conceptualizing and developing the scales of smart health-care supply chain (HCSC) performance in the era of the fourth industrial revolution.

This study has implemented structural equation modelling to analyse the survey data. To analyse the collected data from the field investigation involving a sample size of 323, the IBM SPSS AMOS 26 software package is considered to implement exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) in this study.

The measurement model of the study developed using EFA and CFA has resulted in validating 32 items out of the 42 items. Resultantly, the analysis using the above-mentioned tools and the parsimony of items to scale development makes it more susceptible to contributing significantly to the current HCSC literature.

The HC providers need to consider a holistic and systematic approach while taking into account the constructs of smart HCSC performance, specifically, the effect of HCSC responsiveness and industry 4.0 between the independent and dependent variables. The scales are validated from the perspectives of developing countries such as India, and hence, their generalizability with respect to first-world countries is practically limited.

The scales validated in this study would facilitate managers and key decision-makers to apply the various elements of HCSC practices, gauge the application of these scales and monitor the performance of health-care facilities.

Inventory management systems in health-care supply chains (HCSC) have been pushed to breaking point by the COVID-19 pandemic. Unanticipated demand shocks due to stockpiling of medical supplies caused stockouts, and the stockouts triggered systematic supply chain (SC) disruptions inconceivable for risk managers working individually with limited information about the pandemic. The purpose of this paper is to respond to calls from the United Nations (UN) and World Health Organization (WHO) for coordinated global action by proposing a research agenda based on a review of current knowledge and knowledge gaps on the role of collaboration in HCSCs in maintaining optimal stock levels and reinforcing resilience against stockout disruptions during pandemics.

A systematic review was conducted, and a total of 752 articles were analyzed.

Collaborative planning, forecasting and replenishment practices are under-researched in the HCSC literature. Similarly, a fragmented application of extant SC collaborative risk management capabilities undermines efforts to enhance resilience against systematic disruptions from medical stockouts. The paucity of HCSC articles in humanitarian logistics and SC journals indicates a need for more research interlinking two interdependent yet critical fields in responding to pandemics.

Although based on an exhaustive search of academic articles addressing HCSCs, there is a possibility of having overlooked other studies due to search variations in language controls, differences in publication cycle time and database search engines.

The paper relies on COVID-19's uniqueness to highlight the limitations in optimization and individualistic approaches to managing medical inventory and stockout risks in HCSCs. The paper proposes a shift from a fragmented to holistic application of relevant collaboration practices and capabilities to enhance the resilience of HCSCs against stockout ripple effects during future pandemics. The study propositions and suggestion for an SC learning curve provide an interdisciplinary research agenda to trigger early preparation of a coordinated HCSC and humanitarian logistics response to future pandemics.

With the rising needs of health-care (HC) services during the health outbreaks, it is essential to upgrade the existing HC delivery infrastructure. The study aims to prioritize and highlight the interrelationships among the key factors of the smart health-care supply chain (HCSC) by implementing the concept of Industry 4.0.

The key factors of implementing Industry 4.0 in HCSC have been identified through extensive literature review and stakeholders' opinions. To achieve the abovementioned objectives, the present study proposed hybrid multi-criteria decision-making (MCDM) tools, namely, the fuzzy-analytic hierarchy process (AHP) and fuzzy- decision-making trial and evaluation laboratory (DEMATEL). The Fuzzy-AHP prioritized the factors of implementing Industry 4.0 in HCSC, while the cause–effect relationships among the factors have been explored using fuzzy-DEMATEL.

The results of the study indicated that HC logistics management (HCLM) is the most prioritized factor of implementing Industry 4.0 in HCSC, followed by the integrated HCSC, then sustainable HCSC practices, HCSC innovation and technological aspects, HCSC institutional perspectives, HCSC competitiveness, social aspects and economic factors of HCSC. The cause–effect analysis has highlighted integrated HCSC, HCLM, HCSC competitiveness and social aspects as the cause group factors and they are the critical success parameters for implementing Industry 4.0 in the HCSC.

The results of the study can be useful for policymakers, humanitarian organizations, health administrators and other decision makers considering the smartening of HCSC to enhance the operational performance of health facilities.

This is one of the few studies to have been conducted so far in which the subfactors of HCSC implementing Industry 4.0 have been identified and analyzed using the fuzzy-AHP and fuzzy-DEMATEL hybrid approach.

The authors have previously validated a design of the health-care supply chain which treats patients as inventory without loss of respect for the patients. This work continues examination of patients as inventory while addressing the dual objectives of reducing redundancy in services and creating greater efficiency in the health-care supply chain. Historical data is used to forecast health care needs in light of the increasingly specialized health-care professionals, which have resulted in much more flexible and expensive supply chains. The lack of common data storage, or electronic medical records (EMRs), has created a need for redundancy (or rework) in medical testing. The use of EMR will also enhance our ability to forecast needs in the future. We perform simulations using SigmaFlow software to address our goals relative to the resource constraints, monetary constraints, and the overall culture of the medical supply chain. The simulation outcomes lead us to recommendations for data warehousing as well as providing mechanisms, like inventory postponement strategies, to establish structures for more efficiency, and reduced flexibility in the supply chains.

Healthcare supply chains (HCSCs) face severe challenges when compared to regular chains. Besides avoiding bankruptcy, they must accomplish their goal which is to save lives. Since 2019 the COVID-19 pandemic evidenced that a HCSC disruption generates disruptions to other SCs. Therefore, the objective of this paper is threefold: conduct a systematic literature review to build a HCSC operational excellence (HSCOE) definition; build a conceptual framework by mapping the antecedents of HSCOE and formulate hypotheses; test the hypotheses using a fuzzy-Set Qualitative Comparative Analysis (fsQCA) combined with partial least squares structural equation modeling (PLS-SEM) techniques to obtain empirical validation.

Given this context, this paper conducted a systematic literature review to build a HSCOE conceptual framework and used a fsQCA combined with PLS-SEM techniques to obtain empirical validation.

The paper revealed a relationship between important variables to achieve HSCOE, such as Supply chain 4.0, SC risk management, SC integration, SC resilience (antecedents) and HSCOE (consequent).

The literature contributions of this paper are as follows: validating a new scale for each of the constructs; finding evidence of the causal relationships between the latent variables; measuring how the constructs influence the HSCOE; in addition, the results address important literature gaps identified by researchers and serve as a guide to organizations that need to implement these practices. Furthermore, this study recommends that HCSC managers consider the implementation of robust initiatives concerning the latent variables presented in this work.

This study develops and tests a model exploring the relationship between supply chain (SC) counterfeit risk management and performance in the healthcare supply chain (HCSC).

In the proposed theoretical model, HCSC counterfeit risk management is characterized by HCSC counterfeit risk orientation (HCRO), HCSC counterfeit risk mitigation (HCRM) and HCSC risk management integration (HRMI), while performance is represented by healthcare logistics performance (HLP) and healthcare organization overall performance (HOP). Partial least squares structural equation modeling (PLS-SEM) and survey data from 55 HCSC managers are used to test the research hypotheses.

HCRO has a significant positive effect on HCRM, while HCRM has a positive impact on HRMI. With respect to HLP, HCRM has a nonsignificant effect, while HRMI has a significant impact, thus confirming the important mediating role of HRMI. Finally, HLP has a significant positive effect on the overall performance of healthcare organizations.

All study participants were from the United States, limiting the generalizability of the study findings to different countries or regions. The sample size employed in the study did not allow the authors to distinguish among the different types of healthcare organizations.

This study delineates between a healthcare organization's philosophy toward counterfeiting risks vs actions taken to eliminate or reduce the impact of counterfeiting on the HCSC. By offering firm-level guidance for managers, this study informs healthcare organizations about addressing the challenge of counterfeiting in the HCSC.

The study aims to identify and analyse the drivers of resilient healthcare supply chain (HCSC) preparedness in emergency health outbreaks to prevent disruption in healthcare services delivery in the context of India.

The present study has opted for the grey clustering method to identify and analyse the drivers of resilient HCSC preparedness during health outbreaks into high, moderate and low important grey classes based on Grey-Delphi, analytic hierarchy process (AHP) and Shannon's information entropy (IE) theory.

The drivers of the resilient HCSC are scrutinised using the Grey-Delphi technique. By implementing AHP and Shannon's IE theory and depending upon structure, process and outcome measures of HCSC, eleven drivers of a resilient HCSC preparedness are clustered as highly important, three drivers into moderately important, and two drivers into a low important group.

The analysis and insights developed in the present study would help to plan and execute a viable, resilient emergency HCSC preparedness during the emergence of any health outbreak along with the stakeholders' coordination. The results of the study offer information, rationality, constructiveness, and universality that enable the wider application of AHP-IE/Grey clustering analysis to HCSC resilience in the wake of pandemics.

This paper aims to explore the drivers of sustainable healthcare supply chain (SHCSC) performance measurement through extensive literature review and experts' opinions. The drivers are then scrutinized and their priority vector is calculated to provide quality and cost-effective healthcare supply chain (HCSC) services.

The drivers of the SHCSC performance measurement are validated using the grey-Delphi technique. After validating the drivers, they are prioritized using the grey-analytic hierarchy process (G-AHP), a multi-criteria decision-making tool.

The findings of the study highlight the prioritized drivers based on the preferences given by the experts. The findings of the study highlight the most prioritized drivers of healthcare (HC) by-product management system, coordinating and facilitating green suppliers in the HCSC and green packaging of pharmaceutical as well as other essential items.

The HCSC managers should coordinate with all the stakeholders across the supply chain and involve them in the decision-making process to make products and services greener and become complicit in complying with the sustainable policy guidelines. The study highlights the strategic policy and managerial implications for implementing sustainability in the HCSC.

The validation and prioritization of the drivers of SHCSC in developing nations' contexts is the key contribution of the study. Grey-AHP enables a practical approach towards enhancing the sustainability of the HCSC and opening the doors for generalizing the study for future research works.

This paper aimed to identify the impact that Industry 4.0 can have on the service sector and how its combination can generate benefits for Sustainability 4.0 in the context of the Triple Bottom Line.

A Systematic Literature Review (RSL) was developed using the following combinations of keywords on the Web of Science and Scopus databases: Industry 4.0 And Sustainability, Industry 4.0 And Service, and Industry 4.0 And Sustainable Development, in which 24 papers were selected.

As a result, the authors found 100 benefits for sustainable development, which were further categorized into 54 advantages for the economic area, 25 for the social segment and 21 for environmental aspects. In this way, the results can help private companies understand the use of these technologies aimed at sustainable growth, plus bolstering the government to conduct public policies to encourage these practices in technology organizations.

As a practical implication, this study offers insight into the evolution of sustainable development. It enables the emergence of works that wish to explore the service sector, providing relevant information for decision-making and influencing managers and policymakers on the importance of applying Industry 4.0 toward the sustainability of the service sector and its applications.

The originality of this study lies in expanding the understanding generated by 4.0 technologies, by diverting attention from the manufacturing and agricultural sectors, which have abundant literature on the subject. With this, this work demonstrated that modern technologies have greater possibilities of an action directed at the service sector, in addition to being able to contribute to Sustainability 4.0 from the perspective of the sustainability tripod.