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Blockchain technology (BT) is setting world-shattering standard in all type of transactions in business. BT has the prospective to drastically transform supply chain (SC). The main challenge is to enhance trust among the SC stakeholders. This paper aims to identify and prioritize the factors and its challenges that influence the adoptability of BT in SC. The prioritization of these factors will be helpful to the practitioners to decide the strategy of implementing the BT in SC.

The factors influencing adoption of BT are identified from the review of literature and expert opinion is used to rank the factors influencing the adoptability of BT in SC using grey relational analysis (GRA).

We identified and prioritized key factors: inter-organizational trust and relational governance as organizational challenge, data transparency and data immutability as technological challenge, interoperability and product type as operational challenge and social influence and behavioral intention as social challenge that influences adoptability of BT in SC.

The priority of these factors will guide future researchers and industry practitioners to plan rational and financial strategy for implementing BT in SC.

Research in agri-fresh food supply chain quality (AFSCQ) has been given less consideration in developing countries as compared to developed countries and its role in achieving organizational sustainability has not been researched yet. Thus, this study aims to determine and combine numerous significant factors to establish a framework for managing AFSCQ practices favorable to organizational sustainability in the Indian context.

To accomplish this, all-inclusive framework of AFSCQ has been established through succeeding phases of data collection, analysis using structural equation modelling along with refinement of data. The collection of data for this study was from the Indian food industry, which relates to agri-fresh food products.

The AFSCQ practices are conducive to enrich organizational sustainability, and then enhance economic, social and environmental performance indirectly. The study established relationships among the AFSCQ practices promising to enhance organizational sustainability.

AFSCQ practices have a huge impact on organizational sustainability by means of practices that sum up activities along the whole supply chain. The organizational sustainability consists of economic, social and environmental sustainability.

The manufacturing sector has been observing various benefits by the implementation of lean manufacturing practices. However, the manufacturing sector has neglected the significance of health and safety management system implementation. The purpose of this research is to propose and validate an occupational health and safety management systems (OHSMS) framework based on critical success factors and their relationships in the lean manufacturing organizations.

A critical literature review was conducted to identify the success factors of OHSMS. Subsequently, a questionnaire survey and semi-structured interviews were conducted with experts from process industries to consolidate the critical success factors. After consolidating the critical success factors, relationships among critical success factors were established with the help of interpretive structural modelling using a team of 12 experts from industry and academia. These established relationships helped in proposing the hierarchical implementation framework. Finally, the validation of the proposed implementation framework was carried out using structural equation modelling (SEM).

This study has identified nine broader critical success factors for implementation of OHSMS in lean manufacturing organizations, especially the process industry. Subsequently, this study has proposed an OHSMS framework with nine broader critical success factors to implement in lean manufacturing organizations. Finally, the proposed framework has been validated using SEM with an appropriate sample size.

This study is helpful to the organizations to implement OHSMS without losing the essence of lean manufacturing strategy. This study has proposed a framework for implementation of OHSMS in the lean manufacturing organizations, especially process industry sector. This study also provided confidence to the organization through the validation of proposed framework in the process industry.

To the best of the authors’ knowledge, this study is first of its kind in this field of OHSMS in lean manufacturing organizations, especially the process industry. This study has involved both academicians and industry experts to bring more robust outcomes. This study proposed a unique framework to implement OHSMS in lean manufacturing organizations. This study has considered a comprehensive literature to develop a framework for OHSMS in lean manufacturing organizations. An implementation framework was proposed by considering both the academicians’ and industry professionals’ opinions. The proposed framework was statistically validated. This will be helpful in effective implementation of OHSMS strategy in lean manufacturing organizations, especially process industry sector.

Collaboration methods are unique strategies that can help organizations hedge against external and internal supply chain risks without stressing their relationships with supply chain partners. However, selecting the most appropriate collaboration method from a given set of strategies is a multifaceted challenge. This paper aims to address this issue.

The decision maker's dilemma of fighting data uncertainty in input parameters to check the efficacy of a given collaboration or mitigation approach is tackled by the integration of Grey theory with the technique for order of preference by similarity to ideal solution (TOPSIS) method. The proposed technique is applied and tested for an Indian diesel generator-set manufacturer to identify the most apposite set of sustainable collaboration strategies.

The results showed that when a firm is bidding for different horizontal collaboration strategies across its supply chain system technology and resource-sharing-centered collaboration strategies are the prominent option. In the case of the company's vertical collaboration deployment, the focus should be kept on information sharing to achieve impactful collaboration. The outcome of the analysis helped the Indian manufacturer to adopt transparent order and production information sharing with its regional distributors and core suppliers within its supply chain.

This study demonstrates from a methodological perspective the successful application of the Grey-TOPSIS approach that effectively captures data uncertainty. It also integrates sustainability parameters in collaboration strategy criteria selections.

The Indian marble and stone industry has got the potential to contribute well to the development of the emerging economy. However, unlike the other Indian industries, stone and marble industries are highly underrated sectors, which may become a critical factor for development. This paper analyses the sustainability factors in supply chain management practices.

A literature review is used to identify the barriers and drivers in sustainable supply chain management practices. Interpretive structural modeling has been used to obtain a hierarchy of barriers and drivers along with driving power and dependence power analysis. Further, MICMAC analysis is used for segregating the barriers and drivers in terms of their impact on sustainability.

The findings of the work of this research are that the attention of society, government, and commercial banks should be more toward the unorganized condition of stone and marble sector. There should be an increase in the commitment of stakeholders to reduce pollution and install safety, by enforcing more relevant laws and regulations and creating the importance of environmental awareness.

The main contribution of this research is to identify the barriers and drivers of sustainable supply chain management in a stone and marble industry. The paper proposes a sound mathematical model to prioritize the critical factors for responsible production and consumption of resources from sustainability perspectives of stone industry.

The purpose of this paper is to deliver a structured literature review of existing literature on agri-fresh food supply chain quality (AFSCQ) over a period of 23 years (1994 to mid-2016) and provide a platform for practitioners and researchers trying to identify the existing state of work, gaps in current research, and future directions in the field of AFSCQ.

The existing literature is classified on the basis of several classes like number of publications per year, journal-wise publications, studies across various countries, growth of empirical research, data analysis methods or tool used, issues related to supply chain quality as well as performance measurement (with respect to entity of analysis, level of analysis and element of exchange).

Most of the research publications discuss issues in developed countries, while relatively lesser publications are available on issues in developing countries. Hence, larger opportunities in the field of AFSCQ are available in developing countries. Empirical research is also growing in the field of AFSCQ. Largely research publications make use of “case study” research approach and “statistical analysis” as a quantitative tool of research. The literature is also categorized under the various issues of supply chain quality such as sustainability management, information management, logistic management, collaboration and coordination management, strategic management, demand management, inventory management, food safety, performance management, supply chain integration, supplier management, quality management, etc. It was found that in the majority of articles, information management, sustainability management, and logistics management are very critical issues as far as AFSCQ is concerned. Performance measurement of agri-fresh food supply chain is also on a growing stage. It is also an integral part of AFSCQ.

Most of the prior reviews are concentrated on a particular issue as production and distribution planning for agri-foods, temperature monitoring, corporate and consumer social responsibility, traceability system and ignore the wider perception. There exists a necessity of having a detailed review to cover up all the issues in AFSCQ. This review fills this gap in the extant AFSCQ literature.

It is worth mentioning that in supply chain management (SCM), managerial decisions are often based on optimization of resources. Till the early 2000s, supply chain optimization problems were being addressed by conventional programming approaches such as Linear Programming, Mixed-Integer Linear Programming and Branch-and-Bound methods. However, the solution convergence in such approaches was slow. But with the advent of Swarm Intelligence (SI)-based algorithms like particle swarm optimization and ant colony optimization, a significant improvement in solution of these problems has been observed. The purpose of this paper is to present and analyze the application of SI algorithms in SCM. The analysis will eventually lead to development of a generalized SI implementation framework for optimization problems in SCM.

A structured state-of-the-art literature review is presented, which explores the applications of SI algorithms in SCM. It reviews 56 articles published in peer-reviewed journals since 1999 and uses several classification schemes which are critical in designing and solving a supply chain optimization problem using SI algorithms.

The paper revels growth of swarm-based algorithms and seems to be dominant among all nature-inspired algorithms. The SI algorithms have been used extensively in most of the realms of supply chain network design because of the flexibility in their design and rapid convergence. Large size problems, difficult to manage using exact algorithms could be efficiently handled using SI algorithms. A generalized framework for SI implementation in SCM is proposed which is beneficial to industry practitioners and researchers.

The paper proposes a generic formulation of optimization problems in distribution network design, vehicle routing, resource allocation, inventory management and supplier management areas of SCM which could be solved using SI algorithms. This review also provides a generic framework for SI implementation in supply chain network design and identifies promising emerging issues for further study in this area.

This study is centered on the identification of the most appropriate Technology Adoption (TA) model for investigating the adoption of Industry 4.0 technologies within pharmaceutical and related enterprises. The aim is to facilitate a smooth transition to advanced technologies while concurrently achieving environmental sustainability.

Selection of a suitable TA theory is carried out using a hybrid multi-criteria decision-making (MCDM) approach incorporating PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) and Fuzzy Measurement of alternatives and ranking according to Compromise solution (F-MARCOS) methods. A group of three experts is formulated for the ranking of criteria and alternatives based on those criteria.

The results indicate that out of all six TA models considered unified theory of acceptance and use of technology (UTAUT) model gets the highest utility function value, followed by the technical adoption model (TAM). Further, sensitivity analysis is conducted to confirm the validity of the MCDM model employed.

Challenging times like COVID-19 pointed out the importance of technology in the pharmaceutical and healthcare sectors. TA studies in this area can help in the identification of critical factors that can assist pharmaceutical firms in their efforts to embrace emerging technologies, enhance their outputs and increase their efficiency.

The novelty of this research lies in the fact that the utilization of a TA theory prior to its implementation has not been witnessed in existing scholarly literature. The utilization of a TA theory, specifically within the pharmaceutical industry, can assist enterprises in directing their attention toward pertinent factors when contemplating the implementation of emerging technologies and achieving sustainable development.

This research aims to update the literature about the importance of reliability in supply chain (SC) and to find out the SC determinants.

This research surveys while contributing to the academic grasp of supply chain reliability (SCR) concepts. The study found 45 peer-reviewed publications using a structured survey technique with a four-step filtering process. The filtering process includes data reduction processes such as an evaluation of abstract and conclusion. The filtered study focuses on SCR and its determinants.

One of the major findings is that most of the study has focused on mathematical and conceptual studies. Also, this study provides the answer to a question like how can reliability be better accepted and evolved within the SC after finding the determinants of SCR.

The observed methodological gap in understanding and development of SCR was identified and classified into three categories: mathematical, conceptual and empirical studies (case studies and survey’s mainly). This research will aid academics in developing and understanding the determinants of SCR.

The manufacturing industry is one of the most disrupted systems as a result of the global spread of the Covid-19 pandemic. Manufacturing firms are looking for strategies and policies to deal with the situation while also meeting customer demands. This study aims to discuss and analyze the barriers that have impacted manufacturing systems during this period.

The barriers and performance measures were extracted from the extant literature and further discussed with academic and industry experts. Based on the response of experts, a list of ten barriers and five performance measures were selected for further analysis. The interpretive ranking process (IRP) is applied to analyze the inter-relationship among the barriers with respect to performance variables. The cross-interaction matrices and the dominance profile are created to prioritize the barriers. Based on dominance value, an IRP-based manufacturing barrier evaluation model is developed for validation.

The impact of the pandemic on the manufacturing industry is analyzed through the list of barriers and a structured ranking model is proposed. The research findings of the study indicate that “Financial constraints” is the most influential barrier to manufacturing due to the outbreak of Covid-19, followed by “Government imposed restrictions” and “Setbacks in logistics services.”

The ranking of barriers and developed interpretive ranking process model would be helpful for practitioners and policymakers to formulate strategies for manufacturing organizations to deal with the pandemic situation. The finding can be beneficial as it promotes similar studies in other sectors.

This study contributes to the manufacturing sector by developing a contextual relationship among the set of identified barriers against various performance measures. As per the author's knowledge, this is the first study that provides a relationship and ranking of manufacturing barriers due to the outbreak of Covid-19.