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The purpose of this paper is to develop a framework for the identification, categorization and prioritization of social sustainability barriers in health-care supply chains.

An exploratory survey tool is used to identify barriers that are relevant to a health-care supply chain. The identified barriers are grouped into five main categories and experts’ opinions were applied to validate the content. Finally, an analytical hierarchical process (AHP) is used to prioritize the main categories and sub-categories of the barriers.

The exploratory phase identified 34 barriers that are relevant to a health-care supply chain. These barriers were grouped into the following categories: poor infrastructure, organizational culture, poor coordination, stakeholder disparity, and uncertainty. Organizational culture and poor coordination were assigned the highest priority through the AHP. Overall, lack of management support, lack of commitment and lack of coordination were found to be the top relevant barriers to a health-care supply chain.

This study only explored and prioritized the barriers of social sustainability. Future research should explore the impact of the identified barriers on the overall performance of the hospital supply chain.

The findings of this study may be of value to the local health-care industry in achieving their objectives by overcoming social sustainability barriers, which would in turn facilitate the implementation of social sustainability programs that can positively contribute to the overall supply chain performance.

Social sustainability has grown in importance as a pressurizing issue to push supply chain managers to assess their social impacts on the communities. This is especially important in service supply chains such as health care, where human element is a part of every stage.

Despite practitioners’ and academics’ growing emphasis on the social dimension of sustainability, the categorization and prioritization of social sustainability practices across health-care supply chains and general service care supply chains have not been addressed. This study aims to cover this gap by contributing to both the academic literature and the practical health-care environment.

This study aims to identify barriers to social sustainability in the health-care industry in the United Arab Emirates. Furthermore, the impact of these dimensions on social sustainability is examined.

A comprehensive questionnaire has been developed based on semi-structured interviews with different departments of two tertiary hospitals in the first phase. In the second phase, data are collected from ten public and private hospitals situated in the United Arab Emirates. In the third phase, responses are examined using principal component analysis to identify the five major barriers for social sustainability. A measurement model (confirmatory analysis) is developed to examine the relationship among these dimensions. Finally, a structural model is developed to examine the significance of these dimensions to the notion of social sustainability in health care.

The statistical model shows a 61 per cent variance for social sustainability, which is caused by infrastructure, organizational culture, lack of coordination, stakeholder’s disparity and uncertainty, which are positively and highly correlated measurement barriers to social sustainability practices implementation.

Health-care professionals and stakeholders believe that the elimination of obstacles to social sustainability must be multi-dimensional and not limited to specific practices.

This study would enable health-care industry to examine the extent of obstruction for social sustainability. Hospital administrators and medical professionals could use this feedback to assess and benchmark their performance against that of other competitive hospitals.

The contribution of this paper is to advance the understanding of social sustainability in the health-care sector by viewing it from the perspective of the stakeholders and the social exchanges that occur among them.

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.

The purpose of this study is to develop a methodology for the identification, categorization and prioritization of operational government-supported healthcare supply chain barriers (GHSCBs).

This study develops a theoretical background for identifying and segregating relevant GHSCBs and proposes a 5W2H (a Toyota production system) with fuzzy DEcision MAking Trial and Evaluation Laboratory (DEMATEL) embedded approach to quantify the causal–effect relationships among the identified operational GHSCBs.

Seven GHSCBs (i.e. uncertainty of demand management, lack of continuous improvement and learning, lack of deadline management, lack of social audit, warehousing equipment unavailability, human resource shortage and inadequate top level monitoring) were identified as significant cause group where the government, top management and decision-makers of government-supported healthcare supply chain (GHSC) have to put efforts.

The results obtained are specific to the GHSC of Indian perspective, which could be extended to global context. However, the proposed approach can be a base and provide a platform to understand and analyze the interactions among GHSCBs.

The proposed methodology will show the appropriate areas for allocating efforts and resources to mitigate the impact of GHSCBs for successful implementation of healthcare supply chain.

According to best of the authors' knowledge, this is the first study of operational barrier for GHSC in India in specific. The use of 5W2H embedded fuzzy DEMATEL approach for the development and analysis of the theoretical framework of Indian GHSCBs is unique in barrier literature.

Green lean six sigma (GLSS) is a sustainable development approach that leads to improved patient care with improved safety and quality of service to patients. This study aims to identify, study, model and analyze GLSS success factors for the Indian health-care facility.

Interpretive structural modeling (ISM) and Impact Matrix Cross-Reference Multiplication Applied to a Classification analyses have been used to understand the hierarchical structure among the GLSS success factors. This enabled the development of dependency relationships between success factors, in particular, which factors support the development of other factors.

Specifically, this study found that the success factors “commitment of management” and “financial availability” are the most critical to GLSS implementation success, as they support the development of all other success factors. Meanwhile “embedding sustainable measures at each stage of the service”; “the capability and effectiveness of real-time data collection”; and “feedback and corrective actions” most directly support the GLSS implementation in the health-care facility and serve as the final indicators of implementation progress.

The major implication of this research work lies in suggesting a direction for practitioners to execute the GLSS approach through a systematic understanding of classification and structural relationships among different enablers. This study also facilitates health-care managers to explore different GL wastes in hospitals and challenges to sustainability pursuits in health-care that assist in an organization’s efforts toward sustainable development.

This research work is the first of its kind that deals with the identification and analysis of the prominent factors that foster the inclusive implementation of GLSS within the health-care facility.

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 purpose of this study is to provide insights into how accounting and accountability systems can contribute to transforming metrics used thus far in research performance evaluation. New metrics are needed to increase research impact on the challenges addressed by science. In particular, we document and reflect on accounting transformations towards responsible research and innovation (RRI).

The study draws on the European H2020 MULTI-ACT research project that focuses on the development of a collective research impact framework in the area of health research. We document, analyse and report our engagement in this project, which also included research funders, patient organizations, health researchers, accounting practitioners and health care providers. Drawing on RRI, Mode 2 knowledge production and accounting performativity, we inquire into the potential of accounting technologies to foster knowledge production and increase research impact.

The study shows how the engagement of accounting with other disciplines enables the development of new and relevant forms of research impact assessment. We document how accounting can be mobilised for the development of new forms of research impact assessment (i.e. indicators that evaluate key accountability dimensions to promote RRI) and how it helps to overcome the difficulties that can emerge during this process. We also show how the design of multiple accountabilities’ indicators, although chronically partial, produced a generative interrogation and discussion about how to translate RRI to research assessment in a workable setting, and the pivotal role of certain circumstances (e.g. the presence of authoritative actors) that appear during the knowledge production process for creating these generative opportunities.

This study illustrates the key role of accounts in the generation of knowledge. It also shows the value of considering the stakes of all affected actors in devising fruitful accounting approaches. This collective perspective is timely in the accounting discipline and could foster the connection between academics and practice which is so far under-reported. This perspective should be useful for policymakers such as the European Union and managers in the design of new policies, initiatives and practices.

Discussing and devising appropriate research assessment frameworks is strategic for the maximization of the social impact of research results. Accounting has a key role to play in optimizing a sustainable return on investment in research.

How to assess research impact in a more balanced way is in an early stage of development. The study provides empirical and practical material to advance further work and develop its potential to broaden the conceptualization of accountability.

A literature review revealed that government of various developing economies have put an effort on health-care supply chain through the executing critical factors (CFs) directly. Although they have attained some significant benefits in this tactic, but it was not up to satisfactory level. One of the reasons can be attributed to the fact that government/policy makers are not quantifying the impact of CFs on health-care supply chain. This paper aims to propose a methodology to quantify and estimate the impact of CFs on government-supported health-care supply chain (GHSC).

The Graph Theoretic Approach is proposed for estimating the impact and utility of CFs on an Indian GHSC. This study is also extended to scenario analysis for comparing results with different performance situation.

The results obtained from this study show that performance of Indian GHSC is satisfactory, but performance gaps exist which need to be reduced. In this research work, 12 CFs are identified under two significant categories (SCs), i.e. enablers and barriers and the intensity of enablers and barriers have been calculated to show the impact or influence of CFs on GHSC. The value of intensity shows that the role or impact of enabler category (i.e. performance measurement, employee recognition and reward, technology adoption, training cell, inbuilt analytical tool for IT system) is higher on Indian GHSC in comparison to barriers category to enhance the performance of GHSC.

The obtained numerical results are completely in specific to the Indian perspective only; hence, they cannot be generalized for other countries. Simultaneously, this study is related to government supported health-care system; hence, the selection of expert panel was crucial due to the unavailability of doctors and other stakeholders of government system.

The proposed approach is aimed at providing a procedure for evaluating the impact of CFs on HSC in general and GHSC in specific. This study is an attempt to assist government and top management of GHSC to assess the impact of CFs on GHSC and accordingly define its course of actions.

Although various issues related to the CFs have been broadly identified and analyzed, no dedicated study has been reported in the field for quantification of impacts of CFs. Furthermore, this proposed model has an ability to recognize the specific contribution of each CF and overall contribution.

Regardless of the diverse research on big data analytics (BDA) across different supply chains, little attention has been paid to exploit this information across service supply chains. The healthcare supply chains, where supply chain operations consume the second highest expenditures, have not completely attained the potential gains from data analytics. So, this paper explores the challenges of BDA at various levels of healthcare supply chains.

Drawing on the resource-based view (RBV), this research explores the various challenges of big data at organizational and operational level of different nodes in healthcare supply chains. To demonstrate the links among supply chain nodes, the authors have used a supplier-input-process-output-customer (SIPOC) chart to list healthcare suppliers, inputs (such as employees) supplied and used by the main healthcare processes, outputs (products and services) of these processes, and customers (patients and community).

Using thematic analysis, the authors were able to identify numerous challenges and commonalities among these challenges for the case of healthcare supply chains across United Arab Emirates (UAE). An applicable exploration on organizational (Socio-technical) and operational challenges to BDA can enable healthcare managers to acclimate efficient and effective strategies.

The identified common socio-technical and operational challenges could be verified, and their impacts on the sustainable performance of various supply chains should be explored using formal research methods.

This research advances the body of literature on BDA in healthcare supply chains in that (1) it presents a structured approach for exploring the challenges from various stakeholders of healthcare chain; (2) it presents the most common challenges of big data across the chain and finally (3) it uses the context of UAE where government is focusing on medical tourism in the coming years.

Originality of this work stems from the fact that most of the previous academic research in this area has focused on technology perspectives, a clear understanding of the managerial and strategic implications and challenges of big data is still missing in the literature.

The purpose of this paper is to investigate why multi-tier apparel suppliers integrate social sustainability practices into their supply chains and what barriers these suppliers encounter while embedding social sustainability practices.

This study employs a qualitative research design, drawing on data from semi-structured interviews with 46 owners and managers from 33 multi-tier apparel suppliers in Bangladesh, an important outsourcing hub for the global apparel industry. To corroborate research findings, the views of owners and managers were triangulated by further interviewing 11 key representatives of institutional actors such as third-party auditors, a donor agency, industry associations, regulatory agencies and a non-governmental organisation (NGO).

The authors' findings suggest a range of divergent institutional drivers and barriers – coercive, mimetic and normative – that determine the implementation of multi-tier suppliers' social sustainability practices. The key reported drivers were buyers' requirements, external stakeholders' expectations, top management commitment and competition. Conversely, cost and resource concerns and gaps in the regulatory framework were identified as key social sustainability implementation barriers. In particular, owners and managers of second-tier and third-tier supplier firms experienced more internal barriers such as cost and resource concerns than external barriers such as gaps in values, learning and commitment (i.e. compromise for mutual benefit and non-disclosure of non-compliance) that impeded effective social sustainability implementation.

Social sustainability in supply chain management has received significant attention from academics, business practitioners, governments, NGOs and supranational organisations. However, limited attention has been paid to investigating the drivers and barriers for social sustainability implementation from a developing country's multi-tier supplier perspective. The authors' research has addressed this knowledge gap.

The evidence from the authors' study provides robust support for key assumptions of institutional theory and has useful implications for both managers and policy-makers.

The authors' study contributes to the embryonic research stream of socially sustainable multi-tier supply chain management by connecting it to the application of institutional theory in a challenging institutional context.