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This paper aims to address the conceptual and practical challenges in integrating triple bottom line (TBL) sustainability in the agriculture supply chain (ASC). It identifies the key enablers for each of the three dimensions of TBL sustainability, analyses their causal relationships as well as cross-dimensional interactions under each TBL dimension. Further, it develops a decision support framework (DSF) for the assessment of TBL sustainability practices and policies in ASC and validates it through a case study.

An interpretive structure modelling (ISM) methodology is deployed to establish the interrelationships among all TBL enablers and to identify the enablers with high driving power on sustainable ASC. Brainstorming by a group of experts was used to identify the relevant enables. Finally, a DSF was developed as a resultant of ISM.

The paper provides a set of enablers with high driving power that can significantly influence the sustainability practices and policies in ASC. The social enablers directly help to enhance the effect of economic enablers and collectively these enhance the effect of environmental enablers. If agriculture firms and supply chains design innovative policies and develop practices based on these enablers, they can achieve sustainable ASC. Consequently, the living standards of the people directly or indirectly associated with the agriculture firm or supply chain can be improved without compromising on economic performance.

The paper consolidates the fragmented knowledge of sustainable supply chain management in the agriculture sector and suggests a DSF to policymakers, managers and practitioners for assessing TBL sustainability practices and policies. The DSF has wide applicability in other sectors of production and operations management as these sectors also face the challenge of achieving TBL sustainability across their supply chain.

The DSF, developed in the paper, is a useful tool for practitioners to frame and analyse sustainability initiatives and policies for ASC. A firm or supply chain may achieve TBL sustainability if it succeeds in uplifting the social status of its stakeholders.

It is a first step towards addressing the practical challenge of integrating sustainability in the agriculture sector of emerging economies and provides a path to improve the livelihood of people in the agriculture sector. Stakeholder engagement with a focus on collaboration and awareness may lead to the desired social and environmental consequences. Potential adverse social effects also need to be considered.

This paper focusses on the so far rather neglected but essential aspect of integrating TBL sustainability in the agriculture sector of emerging economies. The hierarchal representation and classification of the TBL sustainability enablers of sustainability is a unique effort in the field of ASC. Development of DSF is one of the first attempts to create a mapping between various enablers of TBL sustainability. The novelty of the study lies in the sector-specific, holistic evaluation of TBL sustainability policy measures that may lead to improvements in practice.

This study aims to identify and analyse the main enablers of knowledge management (KM) in improving the logistics capabilities of Indian organisations and develop a model based on the contextual relationship among the identified enablers.

Initially, this study uses a systematic literature review and questionnaire-based survey approach to identify the enablers of KM; and later, total interpretive structural modelling (TISM) was used to evolve mutual relationships among the identified 11 enablers for developing a hierarchical model.

The results of the analysis show that enablers, namely, organisational structure and leadership, application of advanced information and communication system, collaboration with established stakeholders and organisational learning and innovative approaches are identified as main enablers for improving the logistics capabilities of Indian organisations.

This study provides useful implications for the researchers working on exploring the role of KM enablers in improving the logistics capabilities of organisations.

This study provides rich practical implications for the manufacturers, supply chain managers, logistics service providers and logistics consultants involved in the decision-making process. They can focus majorly on knowledge creation and knowledge storage processes to improve the logistics performance of their respective organisations.

This study is an attempt to identify the enablers of KM that could improve the logistics capabilities of Indian organisations. The application of the TISM method to develop a theoretical framework is the novel contribution of this study.

This study aims at modelling the enablers of dairy supply chain (DSC) in Indian context.

Interpretive structural modelling (ISM) approach has been used to model the enabler of dairy supply chain. The opinion has been taken from the industry experts and experienced academicians. Further, Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) used to classify the enablers based on driving and dependence power.

Findings show that stakeholder trust and top management support/leadership are the very crucial enablers in dairy supply chain; they are at a lower level of hierarchical structure and work as primary enablers to development of DSC. While customer satisfaction and financial performance are at top of the digraph, it shows these enablers are the outcome of a smooth supply chain. The MICMAC analysis suggests that the identified enablers are largely classified into dependent and independent enablers; there are no autonomous enablers in the dairy supply chain.

The study can aid businesses in the dairy processing industry in managing demand fluctuations, enhancing product quality, implementing effective information systems and adapting procedures, thereby enhancing supply chain performance.

There is very limited study on enablers of the dairy supply chain in general, while in the Indian context, there is no specific study on modelling the enablers of dairy supply chain.

This study intends to recognize and prioritize the work-family balance (WFB) enablers for working sole mothers by employing total interpretive structural modelling (TISM) and “Matrice-d’impacts-croisés-multiplication-appliqués-à-un-classment” method (MICMAC).

This paper utilizes the integrated approach in two stages. In initial stage, strategic literature review and expert mining technique have been conducted to recognize and validate WFB enablers. In subsequent stage, TISM has been applied to observe the contextual relationships among WFB enablers in the direction to construct a TISM-based structural model. Furthermore, MICMAC technique has been employed to categorize the WFB enablers based on their driver and dependence power.

This paper has identified novel 13 key enablers of WFB among working sole mothers and constructed a unique TISM-based hierarchical model. Moreover, WFB enablers have been categorized into four clusters using MICMAC analysis. In the developed TISM model, working sole mother-related WFB personal enablers are primarily at the upper level, family-related WFB enablers are in the center and work-related WFB enablers are in the lowest level.

The developed framework on WFB enablers among working sole mothers can provide a resolution to difficulties faced by sole mothers in managing WFB by providing a pathway to enhance their performance by improving the organizational effectiveness through improving WFB policies.

Based on the best of authors' awareness, this study first incorporates the TISM-MICMAC technique to recognize and prioritize the WFB enablers for working sole mothers.

This will not be an overstatement to state that the micro, small and medium enterprise (MSME) industry is crucial and the vital driver of the world economy. It covers different fields and dimensions such as defense products, electrical components and low-cost products. The sector plays a vital role in rendering work with low capital expenditure and is one of the emerging pillars of the Indian economy. Given the significance of this sector in contributing towards India's gross domestic product (GDP), it becomes appropriate to resolve all the issues related to MSME on a primary basis for ensuring required support. The recent global pandemic of COVID-19 has impacted this sector to a great extent. This research study targets the MSME industry and points out the directly linked enablers adding to improve the sector's resiliency and sustainability. Therefore, identification and the interrelationship between the MSME enablers need to be studied, which helps make a preliminary list that deals with their impedance benefaction towards resiliency increment.

The writers have done a comprehensive literature analysis of the enablers for the MSME sector to enable effectively and efficiently during emergencies and pandemics. An endeavor has been made on the enablers to order them by utilizing the modified Total Interpretative Structure Modelling (m-TISM) technique. Authentication of this research work highlights the significance of enablers and their position in a hierarchical structure. Further, MICMAC investigation on the recognized enablers is performed to arrange them in the four quadrants on their dependence and driving power.

The authors have attempted to predict the significance of the MSME sector and its essential contribution to the development of India's economy. The result of m-TISM in the current research work revealed the essential commitment of a hierarchical design dealing with the MSME considering the viewpoint of future development. The well-planned traditional design in the MSME helps establish better government policies and programs and transport infrastructure.

Every research study has a few restrictions. Likewise, the boundaries of the current study are that inputs collated for fostering the models are from a few specialists that may not mirror the assessment of the whole MSME sector.

The MSME sector is the developing sector in the current day, and it is needed to keep supporting the sector for the country's development. The current study has set out the functional establishment to improve MSME practicality. In addition, the research highlights the accountability of the MSME authorities to go with the identified enablers having solid driving power for successful usage of the available resources. This will help the MSME development and add value to practitioners and policymakers in the future.

The growth of this sector is essential for the development of the economy and the development of a nation. The current study presents a unique structure that gives a superior comprehension of the enablers. It will help play a crucial role in developing the MSME area. The structure model developed with the assistance of m-TISM and MICMAC examine the identified enablers with inputs from experts in the field. The hierarchy developed from the study recognized the enablers located on their commitment of suitability development of the MSME field.

The paper aims to present a systematic literature review to analyze interrelated enablers of Industry 4.0 for implementation. Industry 4.0 is an integrated manufacturing strategy embedded with disruptive technologies. Adapting these technologies with the present industrial scenario is dependent on understanding the dynamics of various critical enablers in the existing literature. In this paper, an effort has been taken to validate and reinforce these enablers by experts in the field of Industry 4.0 for implementation.

A mixed-methodology is designed in this paper. A text mining approach with an expert’s linguistic assessment method is planned to discover the enablers from literature 2010 to 2019. The most critical enablers and their dependencies on other enablers are studied by using correlation analysis.

The research explores the power driving enablers in three groups: technology, features and requirements for implementing Industry 4.0 in the existing factory. In each group, a high degree of associated and dependent enablers is fragmented in detail.

This paper will benefit the research communities and practitioners to understand the significance of an integrated ecosystem of Industry 4.0 technologies, features and requirements for implementation.

The text mining approach integrated with expert’s linguistic assessment to explore the pairwise relationship among the enablers using word correlation is a novel approach in this paper. Moreover, to best of the authors’ knowledge, this is the first-ever attempt to conduct a structured literature review combined with text analysis and linguistic assessment to identify the enablers of Industry 4.0 for implementation.

Today the role of industry 4.0 plays a very important role in enhancing any supply chain network, as the industry 4.0 supply chain uses Big Data and advanced analytics to inform the complete visibility. Latest data are available to bring clarity and support real-time decision-making in the entire supply chain that’s why adopting optimization techniques such as lean manufacturing and lean supply chain concept for enhancing the supply chain network of the organizations is a good idea and would benefit them in increasing their cost efficiency and productivity. The purpose of this work is to develop a technique, which may be useful for future researchers and managers to identify and classification of the significant lean supply chain enablers.

In this paper, the authors considered hybrid analytical hierarchy process to find the ranking of the identified lean supply chain enablers by calculating their weightage. Interpretive structural modeling (ISM) is applied to develop the structural interrelationship among various lean supply chain management enablers. Considering the results obtained from ISM the Matrices d'Impacts Croises Multiplication Appliqué a un Classement (MICMAC) analysis is done to identify the driving and dependence power of Lean Supply Chain Management Enablers (LSCMEs).

Further, the best results applying these methodologies could be used to analyze their inter-relationships for successful Lean supply chain management implementation in an organization. The authors developed an integrated model after the identification of 20 key LSCMEs, which is very helpful to identify and classify the important enablers by ISM methodology and explore the direct and indirect effects of each enabler by MICMAC analysis on the LSCM implementation. This will help organizations optimize their supply chain by selective control of lean enablers.

For lean manufacturing practitioners, the result of the study can be beneficial where the manufacturer is required to increase efficiency and reduce cost and wastage of resources in the lean manufacturing process, as well as in enhancing the supply chain.

This paper is the first research paper that considered firstly deep literature review of identified lean supply chain enablers and second developed structured modeling of various lean enablers of supply chain with the help of various methodologies.

The purpose of this research paper is to study the significant enablers for a competitive supply chain and analyze the relationships among them by using multi-criteria decision-making (MCDM) techniques. The supply chain (SC) managers will get better insights from the models of this study to design their SCs that are more competitive for competitive advantage.

After an extensive review of literature followed by experts' opinions, 21 significant enablers for a competitive SC (CSC) were selected for structural modeling using MCDM techniques of total interpretive structural modeling (TISM), Impact Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC), followed by decision-making trial and evaluation laboratory (DEMATEL) approach.

Top management commitment is the most prominent causing enabler of a CSC; customer satisfaction is the topmost effect enabler; the operational performance of individual firms in the supply chain is a crucial enabler of a CSC.

The results and findings of this study would provide better insights to SC professionals and practitioners to comprehend the significant enablers of a CSC for designing and executing SC operations more competitively to achieve better customer satisfaction and sustainable business performance.

To the best of the authors’ knowledge, this is a foremost study focusing on the significant enablers of a CSC by utilizing the TISM along with MICMAC and DEMATEL methods. It is expected that this research will offer useful guidance for assessing and considering the SC enablers for achieving a CSC and facilitate new research in this area with more thrust.

The purpose of this paper is to identify and evaluate the relationships among the flexibility enablers and to prepare a hierarchy of these enablers to know their influences over each other in global supply chain. The framework suggests that the priority of enablers in supply chain should be determined on the basis of their driving power and dependency.

Various enablers used by researchers and practitioners for flexibility management of global supply chain have been identified. These enablers have been classified as strategic, operational and performance‐based enablers. Interpretive structural modeling (ISM) is used to establish mutual relationships among the flexibility enablers and to prepare a hierarchy‐based model.

It has been observed that some enablers having high‐driving power and low dependency are of strategic importance. These enablers require more attention while other enablers based on operations and performances are dependents of strategic enablers.

The index of enablers based on driving power and dependency provides an insight to supply chain managers to make the entire supply chain highly flexible and help them to respond to global uncertainties.

Presentation of enablers in the form of hierarchy using ISM and ranking them into various driving power and dependent categories is a good effort to make flexible global supply chain.

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.

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.

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.

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.

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.