Flexible Decision Approach for Analysing Performance of Sustainable Supply Chains Under Risks/Uncertainty

A comprehensive research on analyzing risk factors in emergency supply chains

Purpose

Unforeseen events can disrupt the operational process and negatively impact emergency resources optimization and its supply chain. A limited number of studies have addressed risk management issues in the context of emergency supply chains, and this existing research lacks inbuilt and practical techniques that can significantly affect the reliability of risk management outcomes. Therefore, this paper aims to identify and practically analyze the specific risk factors that can most likely disrupt the normal functioning of the emergency supply chain in disaster relief operations.

Design/methodology/approach

This paper has used a three-step process to investigate and evaluate risk factors associated with the emergency supply chain. First, the study conducts a comprehensive literature review to identify the risk factors. Second, the research develops a questionnaire survey to validate and classify the identified risk factors. At the end of this step, the study develops a hierarchical structure. Finally, the research investigates the weighted priority of the validated risk factors using the fuzzy-analytical hierarchy process (FAHP) methodology. Experts were required to provide subjective judgments.

Findings

This paper identified and validated 28 specific risk factors prevalent in emergency supply chains. Based on their contextual meanings, the research classified these risk factors into two main categories: internal and external risk factors; four subcategories: demand, supply, infrastructural and environmental risk factors; and 11 risk types: forecast, inventory, procurement, supplier, quality, transportation, warehousing, systems, disruption, social and political risk factors. The most significant risk factors include war and terrorism, the absence of legislative rules that can influence and support disaster relief operations, the impact of cascading disasters, limited quality of relief supplies and sanctions and constraints that can hinder stakeholder collaboration. Therefore, emergency supply chain managers should adopt appropriate strategies to mitigate these risk factors.

Research limitations/implications

This study will contribute to the general knowledge of risk management in emergency supply chains. The identified risk factors and structural hierarchy taxonomic diagram will provide a comprehensive risk database for emergency supply chains.

Practical implications

The research findings will provide comprehensive and systemic support for respective practitioners and policymakers to obtain a firm understanding of the different risk categories and specific risk factors that can impede the effective functioning of the emergency supply chain during immediate disaster relief operations. Therefore, this will inform the need for the improvement of practices in critical aspects of the emergency supply chain through the selection of logistics and supply chain strategies that can ensure the robustness and resilience of the system.

Originality/value

This research uses empirical data to identify, categorize and validate risk factors in emergency supply chains. This study contributes to the theory of supply chain risk management. The study also adopts the fuzzy-AHP technique to evaluate and prioritize these risk factors to inform practitioners and policymakers of the most significant risk factors. Furthermore, this study serves as the first phase of managing risk in emergency supply chains since it motivates future studies to empirically identify, evaluate and select effective strategies that can eliminate or minimize the effects of these risk factors.

Developing an evidence-based TISM: an application for the success of COVID-19 Vaccination Drive

The study illustrates an application of evidence data for performing Total Interpretive Structural Modeling (TISM). TISM is widely used to analyze the critical success factors or inhibitors and their interlinkages. This study uses learning from evidence data, specifically social media analytics, to identify the relationship between the elements. Thus, it leads to the advancement of the TISM-P methodology with evidence-based TISM (TISM-E). This study uses Twitter as a source of evidence data. Further, 2,60,297 tweets were used to illustrate the process of TISM-E. The paper demonstrates the application of TISM-E for the success of the COVID-19 vaccination drive. The pandemic effects are long-term; therefore, the hierarchical model developed shows a sustainable approach for vaccinating maximum population. Further, the framework developed will ensure the distribution efficacy of vaccines. In addition, it will aid practitioners in developing future vaccination policies. The enhanced model provides evidence for polarity (positive/negative) of relationships and can help to build propositions for theory development. The study contributes to healthcare, modeling research, and graph-theoretic literature.

Lean Entrepreneurship and SME Practice in a Post COVID-19 Pandemic Era: A Conceptual Discourse from Nigeria

This study investigates lean principles among Nigerian entrepreneurs and SME managers in the operational process in the aftermath of COVID-19 pandemic in Nigeria. It offers the panacea to the challenge of social-economic shocks and their adverse effects on SMEs' business activities in Nigeria. The study adopts a conceptual approach to investigate lean entrepreneurship practice by SMEs in Nigeria. It relies on data from extant literature, using a conceptual approach to examine the social-economic effects of COVID-19 pandemic and critical environmental factors on the lean entrepreneurship practice in Nigeria. Furthermore, the study explores the influence of lean practice among SMEs and entrepreneurs in Nigeria and suggests a broad model for lean entrepreneurial practice in post-COVID-19 pandemic Nigeria. Findings highlight the broad social-economic effects of COVID-19 pandemic and other challenges such as theft, host community pressure, weak legal system, and inadequate government policy support affect lean entrepreneurship practice. These factors constitute complex operational issues that would require the adoption of a more comprehensive approach to address. It also highlights crucial factors for post-COVID-19 pandemic SMEs' operational success in Nigeria due to deficits in infrastructure and regulatory efficiency for SMEs' operations to address the various challenges of business failures in Nigeria. The study suggests a lean SME and Entrepreneurial Practice model in the post-COVID-19 pandemic era. It emphasises the need to refocus the active interest of the lean entrepreneur on critical business sustainability. The study recommends a critical review of the internal operational process among practicing entrepreneurial businesses and a re-modification of public policies system that governs the operational functions of entrepreneurial practices for reasonable and resilient post-COVID-19 pandemic entrepreneurship practices that can support the SMEs and economic growth in Nigeria.

Promoting sustainability through green innovation adoption: a case of manufacturing industry

Green innovation is becoming more common among researchers and practitioners around the world due to environmental and social issues. Green innovation minimizes wastes and pollution, and also leads to financial gains and better image if implemented effectively. Nowadays, developing countries pay greater emphasis on environmental issues as their manufacturing industries are considered major contributors to pollution. Considering the case of a developing country (Pakistan), the study empirically identified the drivers of green innovation in the manufacturing industry. A hybrid methodology-Fuzzy Delphi method (FDM), interpretive structural modeling (ISM), and cross-impact matrix multiplication applied to classification (MICMAC)-was used to develop a novel framework for analyzing the green innovation drivers. At first, green innovation drivers were selected from past studies; they were further screened by applying Fuzzy Delphi approach. The MICAMAC and ISM results indicate that "cost reduction" and "government support" are the most important drivers motivating green innovation implementation in the Pakistani manufacturing industry, while a green image appeared as the least significant driver of green innovation adoption. The study's findings have significant implications for managers and policymakers to develop green strategies for manufacturing sector.

Barriers for adoption of Industry 4.0 in sustainable food supply chain: a circular economy perspective

Purpose

Food supply chains (FSCs) are fast becoming more and more complex. Sustainability is a necessary strategy in FSCs to meet the environmental, economic and societal requirements. Industry 4.0 (I4.0) applications for a circular economy (CE) will play a significant role in sustainable food supply chains (SFSCs). I4.0 applications can be used in for traceability, tracking, inspection and quality monitoring, environmental monitoring, precision agriculture, farm input optimization, process automation, etc. to improve circularity and sustainability of FSCs. However, the factors integrating I4.0 and CE adoption in SFSC are not yet very well understood. Furthermore, despite such high potential I4.0 adoption is also met with several barriers. The present study identifies and analyzes twelve barriers for the adoption of I4.0 in SFSC from an CE context.

Design/methodology/approach

A cause-effect analysis and prominence ranking of the barriers are done using Rough-DEMATEL technique. DEMATEL is a widely used technique that is applied for a structured analysis of a complex problems. The rough variant of DEMATEL helps include the uncertainty and vagueness of decision maker related to the I4.0 technologies.

Findings

“Technological immaturity,” “High investment,” “Lack of awareness and customer acceptance” and “technological limitations and lack of eco-innovation” are identified as the most prominent barriers for adoption of I4.0 in SFSC.

Originality/value

Successful mitigation of these barriers will improve the sustainability of FSCs through accelerated adoption of I4.0 solutions. The findings of the study will help managers, practitioners and planners to understand and successfully mitigate these barriers.

Innovation Trajectories for a Society 5.0

Big Data, the Internet of Things, and robotic and augmented realities are just some of the technologies that belong to Industry 4.0. These technologies improve working conditions and increase productivity and the quality of industry production. However, they can also improve life and society as a whole. A new perspective is oriented towards social well-being and it is called Society 5.0. Industry 4.0 supports the transition to the new society, but other drivers are also needed. To guide the transition, it is necessary to identify the enabling factors that integrate Industry 4.0. A conceptual framework was developed in which these factors were identified through a literature review and the analytical hierarchy process (AHP) methodology. Furthermore, the way in which they relate was evaluated with the help of the interpretive structural modeling (ISM) methodology. The proposed framework fills a research gap, which has not yet consolidated a strategy that includes all aspects of Society 5.0. As a result, the main driver, in addition to technology, is international politics.

The Effects of Green SCM Implementation on Business Performance in SMEs: A Longitudinal Study in Electronics Industry

The evolution of green supply chain management (GSCM) in small and medium-sized enterprises (SMEs) remains underexplored in the literature. Specifically, this study assesses the changes in the effects of GSCM implementation on employee job satisfaction, operational and relational efficiency, and business performance of SMEs that serve as suppliers to large buying firms. The present study collected survey data from 193 electronics manufacturers in South Korea twice in a seven-year time gap, evaluated the reliability and the validity of individual measures, and employed structural equation modeling (SEM) to test the model hypotheses. The results commonly found in the two studies with the time gap are (1) the positive effects of GSCM implementation on employee job satisfaction and operational and relational efficiency, (2) the positive effects of both operational and relational efficiency on business performance, and (3) the positive relationship between operational efficiency and relationship efficiency. Moreover, the positive effect of employee job satisfaction on business performance is found only in the latter study (Study II). The results suggest that GSCM implementation is a critical factor for SME suppliers to establish sustainable long-term relationships with buying firms in the electronics industry, and it also helps manufacturers improve employee job satisfaction and operational efficiency over time. The present study is believed to enhance an understanding of key factors in association with GSCM that positively influences the business performance of SME suppliers.

Sustainable supply chains under risk in the manufacturing firms: an extended double normalization-based multiple aggregation approach under an intuitionistic fuzzy environment

Purpose

In recent years, a number of researchers have attempted to make an integration of sustainability with supply chain risk management. These studies have led to valued insights into this issue, though there is still a lack of knowledge about the mechanisms by which sustainability-related issues are materialized as risks in the supply chain management.

Design/methodology/approach

The paper aims to provide a comprehensive framework to evaluate the sustainability risk in the supply chain management mechanism. To do so, a novel approach using the double normalization-based multiple aggregation (DNMA) approach under the intuitionistic fuzzy (IF) environment is extended to identify, rank and evaluate the sustainability risk factors in supply chain management.

Findings

To provide comprehensive sustainability risk factors, this study has conducted a survey using interview and literature review. In this regard, this study identified 36 sustainability risk factors in supply chain management of the manufacturing firms in five different groups of risk, including sustainable operational risk factors, economic risk factors, environmental risk factors, social risk factors, and sustainable distribution and recycling risk factors. The results of this paper found that the poor planning and scheduling was the important sustainability risk in supply chain management of the manufacturing firms, followed by the environmental accidents, production capacity risk, product design risk and exploitative hiring policies. In addition, the results of the study found that the extended approach was effective and efficient in evaluating the sustainability risk factors in supply chain management of the manufacturing firms.

Originality/value

Three aggregation methods based on the normalization techniques are discussed. A DNMA method is proposed under intuitionistic fuzzy sets (IFSs). To propose a broad procedure for identifying and classifying sustainability risk factors (ESFs) in supply chain management. To rank the sustainability risk factor, the authors utilize a procedure for evaluating the significance degree of the sustainability risk factor in supply chain management.

Addressing the Challenges to Sustainable Initiatives in Value Chain Flexibility: Implications for Sustainable Development Goals

The value chain refers to the source of competition to facilitate organizations to maximize and sustain value for their consumers. Value chain flexibility is necessary to build sustainable initiatives in addressing ambiguity. In the literature, there is a lack of framework to highlight the challenges to sustainable initiatives in value chain flexibility. This study fills this research gap by suggesting a framework for challenges to sustainable initiatives in value chain flexibility. In this study, thirteen potential challenges to sustainable initiatives in value chain flexibility are identified and an integrated model is developed. It adopts the modified Total Interpretive Structure Model and the Cross-Impact Matrix Multiplication Applied to Classification methodology. The mixed approach is used as the modified Total Interpretive Structure Model organizes the binary interactions among the challenges, while Cross-Impact Matrix Multiplication Applied to Classification analysis organizes specific precise assessments of the driving power and dependence of the challenges. The results of the study reflect that (i) lack of supplier commitment to sustainable products and (ii) lack of knowledge toward sustainability in value chains are the challenges that achieved the highest driving power. The challenge ‘inadequate communication among the suppliers in the value chain’ is at the highest level in the analysis. The proposed framework could help government and non-government bodies to formulate policies to efficiently address challenges to sustainable initiatives in value chain flexibility.

Flexibility and Resilience in Corporate Decision Making: A New Sustainability-Based Risk Management System in Uncertain Times

Risk management plays a key role in uncertain times, preventing corporations from acting rashly and incorrectly, allowing them to become flexible and resilient. A global turbulence such as the COVID-19 pandemic has had a strong impact on individual companies and entire economic sectors, raising the question of whether a paradigm shift is necessary, in order to enable a new cycle of development that is much environmentally, socially and economically sustainable. This environmental and socio-economic context of profound uncertainty forces organizations to consider more carefully the risk factors affecting their business continuity, as well as how these factors relate to sustainability issues. However, there is a gap in knowledge about how risk management systems relate to sustainability management systems, and how both of them exert influence on business performance, especially from a theoretical point of view. The aim of this study is to address this gap, by developing a new interpretative framework for the analysis of risk management strategies in organizations. This approach has been identified in economic hermeneutics as an innovative methodological tool to improve the knowledge of risk and design the most appropriate management strategies. The paper provides two main results: the first one is the construction of a theoretical model that relates risk management to sustainability management; the second one is an operational framework of multidimensional risk assessment useful for analysis at different levels (business, competitive scenario and system). Finally, the model also makes it possible to carry out a sustainability assessment through risk evaluation in the perspective of the sustainable development goals.

A Bibliometric Analysis of Sustainability and Risk Management

Sustainability practices in a working environment represent superior quality performances, while risks remain to be a challenge. Our study’s primary purpose is to deploy the bibliometric method to analyze the related literature. Bibliometric parameters analyzed using the VOSviewer software were employed to identify citations relevant to sustainability and risk contexts’ critical themes. From 1990–2020, a reflection of 1233 documents appeared in Scopus on sustainability practices and risk management. We searched the current papers, authors, institutes, and keywords on VOSviewer. The bibliometric search provided us an understanding, which reflected that the collected works on literature of sustainability and risk factors, in general, is suggestively increasing. Mainly, in our report, we highlighted six major streams, related to topics such as the moral responsibilities and sustainability development, blockchain technology and minimization of risks, social sustainability and supply chain, environmental impacts, safety engineering and risk identification, and optimization and sustainability practices. The primary purpose of using streams was to cite the key authors and their contributions to the related literature. This bibliometric analysis was developed to obtain further understanding regarding the importance of sustainability to the individual, firms, and the entire economy. Moreover, the factors associated with risk also sought to be examined to prevent or at least minimize its negative impact. It was identified in this paper that sustainability remains an issue in the global perspective that has been challenging the individual and/or the organization’s point of views. Risk factors were also identified as inevitable; hence, everyone must be socially responsible to minimize the negative impact on the economy.

Modelling the enablers of industry 4.0 in the Indian manufacturing industry

Purpose

The vision of Industry 4.0 concept is to create smart factories that will change the current processes of production and manufacturing system using smart machines to produce smart and intelligent products. The main aim of this research is to explore the enablers with regard to Industry 4.0 application in manufacturing industry in India as the available literature shows that manufacturing sector is still doubtful about the implementation of Industry 4.0.

Design/methodology/approach

Seventeen enablers that can affect the adoption of Industry 4.0 in the manufacturing industry in India have been explored through an extensive review of available literature and viewpoints of industry and academic experts. Total Interpretive Structural Modelling methodology (TISM) has been used to evaluate the interrelationships among these factors. A TISM model has been developed to extract the key enablers influencing Industry 4.0 adoption.

Findings

The result shows that Internet facility from government at reduced price, financial support and continued specialized skills training are the major enablers as they have strong driving power.

Practical implications

Proper understanding of these enablers will help the managers and policymakers to explore the impact of each enabler on other enablers as well as the degree of relationships among them and to take concrete steps so that Industry 4.0 can be implemented successfully in the manufacturing sector in India.

Originality/value

This study is pioneer in exploring the enablers Industry 4.0 which is the most advanced concept that has the capability to change the future of Indian manufacturing sector if implemented judiciously and cautiously.

Modeling the enablers of supply chain strategies and information technology: improving performance through TISM approach

Purpose

This study aims to investigate the hierarchical relationship between industry-specific attributes of supply chain (SC) strategies and information technology (IT) to improve the performance of firms in textile industry in Pakistan.

Design/methodology/approach

This study presents a mix of enablers through literature review and experts’ opinions. Next, the driving and dependence powers of enablers were identified, using the interpretive structural modeling (ISM) approach.

Findings

The ISM model suggests eight levels, with customer satisfaction at the top of the model. Process automation and TQM are placed at second and third level, respectively, whereas flexible sourcing and flexible capacity are positioned at fourth level. The key enablers of IT have high driving power, hence positioned at the bottom of ISM model.

Originality/value

This study has value for firms in garment manufacturing and exporting industry to invest into IT and sustainable SC design for competitive performance. The theoretical and managerial implications are provided.

Supply chain risk mitigation in South Africa: a case study of Eskom

Purpose

Interferences to supply chains (SC), regardless of whether they are regular, unplanned or intentional, are progressively distorting SC execution. As such, risk mitigation in SCs has received sufficient attention in the academic literature. However, there is scant research done on this topic within the African context, and none on the SC of electrical energy on that continent. In an effort to address this gap, the purpose of this paper is to focus on the SC department of Eskom, the primary utility company of South Africa and one of the largest on the continent.

Design/methodology/approach

Adopting a non-probability sampling approach utilising the purposive sampling technique to choose the sampling components from the target population, data were collected through semi-structured interviews as well as additional documentation in various forms. Data interpretation and codification thereof were done using ATLAS.ti 8 from which ten themes emerged.

Findings

The ten themes that emerged from the analysis of data show that SC risks emanate from value streams, information and affiliations, SC activities and external situations. Furthermore, these are brought into relief within the African context through examples and quotes from Eskom managers.

Research limitations/implications

Based on the findings, the paper makes five major recommendations that would broadly apply not only to SC risk management (SCRM) in Eskom, but also other African utility companies.

Practical implications

Companies in emerging economies such as South Africa and other Sub-Saharan countries face a unique set of challenges with regards to SCRM. Some of these are identified in this paper and appropriate recommendations have been made.

Social implications

Being the largest utility provider in Africa, services offered by Eskom are vital for economic development of South Africa as well as neighbouring countries. As such, the findings of this paper as well as the recommendations have social implications for economic development in that country as well as the region.

Originality/value

While SC risk management has been studied extensively in the academic literature, to the best of the authors’ knowledge, this is the first paper that attempts to study it within the context of South Africa with focal emphasis on one of the largest corporations in that country.

Knowledge and Technology Transfer Influencing the Process of Innovation in Green Supply Chain Management: A Multicriteria Model Based on the DEMATEL Method

After performing a systematic review of the literature, it was noticeable that the discussion regarding Green Supply Chain Management (GSCM) along with Knowledge and Technology Transfer (KTT) and Innovation is scarce. To address this issue, the objective of this paper is to analyze the relationship between GSCM, KTT, and Innovation. To achieve this purpose, we developed a conceptual framework based on the literature review, which raised some hypotheses. In order to verify the hypotheses and validate the framework, we designed a multicriteria model called the KTT-GSCM Multicriteria Model, composed of two stages. The first stage describes factors that are relevant to GSCM, KTT, and Innovation, ascertaining which ones have influence over the others and which ones are influenced by the others, through the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. The second stage of the model analyzes the level of each perspective in each company and in the supply chain as a whole, thus verifying the hypotheses. This model was applied in 13 firms of a supply chain that has a rotomolding firm as a focal company. Through the development and application of the model, it was possible to verify the hypotheses raised and conclude that the perspectives of GSCM, KTT, and Innovation are, in fact, influenced by one another and that both Innovation and KTT promote greater development in GSCM.

A study on the influence of factors associated with organizational readiness for change in healthcare organizations using TISM

Purpose

The purpose of this paper is to identify, analyze and develop a model to measure the interactions among different factors of organizational readiness for change in service sector specific to healthcare organization. The total interpretive structural modeling (TISM)-based readiness for change is to build a theoretical framework to understand the mutual interactions among the factors and to identify the driving and dependence power of these factors.

Design/methodology/approach

TISM is used to identify factors that contribute to analyze the readiness state before starting a change implementation process in healthcare. Matrice d’Impacts croises-multiplication applique´ a classement analysis is used to find the driving and dependent factors of change in healthcare.

Findings

This paper identified 12 factors of readiness for change from literature review followed by expert interview to understand the inner connection of factors and study inner relationships. The result says that state of affairs, recent trends in healthcare sector, technology advancement and interdependence among departments are key factors for readiness of change.

Research limitations/implications

This research mainly focused on readiness factors for change in the healthcare sector.

Practical implications

This study will be useful for researcher and practitioners to understand the readiness factors for change.

Originality/value

In this research work, TISM-based readiness for the change framework structural model has been proposed for healthcare organizations which is a new effort in the area of organizational change management in this sector.

Modeling the factors affecting the quality of life in diabetic patients in India using total interpretive structural modeling

Purpose

Diabetes mellitus has become a major world health problem that has unenviable impacts on health of the people including quality of life (QOL) also and in which person’s physical and psychological state, social commitments and relationships and his interaction with the environment is affected. This shows that there is an urgent need for behavior change and considerable educational strategies for proper management and rehabilitation (Reddy, 2000). This research has identified and ranked the significant factors which affect the QOL in diabetic patients in India. The paper aims to discuss these issues.

Design/methodology/approach

In this paper, nine factors which affect the QOL in diabetic patients in India have been identified through review of the literature and evaluated by total interpretive structural modeling (TISM) approach, i.e. an extended version of ISM. In this approach, interpretations of the interrelationship among factors have been discussed. Therefore, TISM approach has been used to develop the model and the mutual interactions among these factors.

Findings

The results of the model and MICMAC analysis indicate that diet restriction, body pain and satisfaction with treatment are the top-level factors.

Practical implications

Identification of the factors that have a remarkable effect on the QOL in diabetic patients is very important so that the doctors and other healthcare professionals may handle these factors efficiently and proper rehabilitation can be provided to such patients.

Originality/value

This paper has used an application of the TISM approach to interpret the mutual relationship by using the tool of interpretive matrix and has developed a framework to calculate the drive and the dependence power of factors using MICMAC analysis. The issues related to QOL are extremely important, as they can strongly anticipate a person’s capability to govern his lifestyle with disease like diabetes mellitus and maintain good health in the long run. This shows the urgent requirement of an optimized model which can predict and interpret the relationships among these factors. In this research, the interrelationships among these factors have been developed and interpretations of these interactions have been given to develop a comprehensive model so that QOL of diabetic patients may be improved.

Emissions from international transport in global supply chains

Purpose

This paper aims to highlight the importance and need to include carbon emissions from international transport in the sourcing decisions of corporate organizations and the calculation of national emissions inventories (NEIs).

Design/methodology/approach

The paper proposes a method of attributing emissions from international transportation in global supply chains and calculating their impact on the economic sustainability of corporate organizations through a carbon price.

Findings

An application of the original model developed in this paper showed that international transport emissions can have an important effect on NEIs. An example of the imports of manufactured items from China and Germany to the USA showed a 3 per cent increase in emissions from manufacturing activities in the USA.

Research limitations/implications

Introducing carbon pricing on international transport emissions is expected to motivate corporate leaders to include emissions from international transport as a factor in their sourcing decisions.

Practical implications

Inclusion of international transport emissions along with the imposition of a carbon tax are designed to act as disincentives to generating emissions from supply chain activities. It is argued that the implementation of the model may provide long-term benefits associated with reduced emissions and a level playing field to organizations which use efficient technologies in manufacturing.

Social implications

It is recognized that the implementation of a carbon tax on international transport emissions may face resistance from several stakeholders, including governments of exporting countries, corporations and customers, due to an increase in cost.

Originality/value

This paper provides an original method to include emissions from international transport in supply chain decisions.

Social sustainability in the supply chain: analysis of enablers

Purpose

– This study aims to identify various enablers and the inter-relationships among them in adopting social sustainability measures in the supply chain. Social sustainability in the supply chain has received growing attention in the recent years, due to growing awareness on equity, health and safety, education, child and bonded labor and ethical practices in corporates.

Design/methodology/approach

– Various enablers and their contextual relationships were identified. The enablers were classified based on dependence and driving power (DP) with the help of MICMAC analysis. In addition to this, a structural model of the enablers to the social sustainability problem has been put forward using the interpretive structural modeling technique.

Findings

– In this study, 14 relevant enablers were identified from literature review and subsequent discussions with experts from academia and the industry. Competitive pressure leads at the bottom of the digraph with high DP, followed by customers ' requirements, financial liquidity and social concern. Social sustainability awareness was found to be at the last level with less DP.

Research limitations/implications

– Enablers were developed based on literature survey and expert opinions. Hence, the model is not statistically validated. This model also does not quantify the adverse effect of each of the variables on social sustainability practices in the supply chain.

Practical implications

– The development of a hierarchy not only helps the supply chain managers to understand the enablers better, based on their importance, but also helps in decision making in the supply chain, which in turn enables the corporations to be competitive.

Social implications

– Findings of this article will help the corporations to be more socially sustainable by understanding the various enablers and their contextual relationships in the supply chain.

Originality/value

– The structured social sustainability model helps supply chain managers and experts to understand interdependence of the enablers. This also helps in identifying different enablers with different degree of importance, which will be very much useful in adopting social sustainability measures in the supply chain.