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The agricultural supply chains (ASCs) are exposed to unprecedented risks following COVID-19. It is necessary to investigate the impact of risks and to create resilient ASC organisations. In this study, we have identified and assessed the ASC risks caused by disruptions. These threats were assessed using Fuzzy Linguistic Quantifier Order Weighted Aggregation (FLQ-OWA). The findings reveal that supply risks, demand risks, financial risks, logistics and infrastructure risks, management and operational, policy and regulation, and biological and environmental risks have a significant impact in ASC depending upon the organisations scope and scale. Various strategies such as adoption of industry 4.0 technologies, supply chain collaboration and shared responsibility is identified for sustainable future. Theoretical and managerial implications are provided based on the outcomes of the study. [ABSTRACT FROM AUTHOR]

The digital supply chains enabled by Big Data Analytics (BDA) capabilities have become a business significance to develop a competitive and sustainable supply chain. The implementation of BDA for sustainable supply chains introduces various organisational challenges for the manufacturing firms demanding complementary capabilities. This study presents an investigation of the linkages between BDA capabilities, circular economy (CE) practices, and sustainable supply chain (SSC) flexibility on the SSC performance. Based on a survey of 320 manufacturing organisations, the study presents very interesting results. It is revealed that the BDA does not have a direct effect on sustainable performance. The CE practices and SSC flexibility are significant mediating variables between the BDA capabilities and SSC performance. The BDA is found to drive the implementation of CE practices. Further, CE practices are found to develop SSC flexibility with the BDA complementing these flexibilities. [ABSTRACT FROM AUTHOR]

Cutting-edge technologies like big data analytics (BDA), artificial intelligence (AI), quantum computing, blockchain, and digital twins have a profound impact on the sustainability of the production system. In addition, it is argued that turbulence in technology could negatively impact the adoption of these technologies and adversely impact the sustainability of the production system of the firm. The present study has demonstrated that the role of technological turbulence as a moderator could impact the relationships between the sustainability the of production system with its predictors. The study further analyses the mediating role of operational sustainability which could impact the firm performance. A theoretical model has been developed that is underpinned by dynamic capability view (DCV) theory and firm absorptive capacity theory. This model was verified by PLS-SEM with 412 responses from various manufacturing firms in India. There exists a positive and significant influence of AI and other cutting-edge technologies for keeping the production system sustainable. [ABSTRACT FROM AUTHOR]

In a highly competitive and changing environment, manufacturers are called to adopt the paradigms of smart, sustainable, resilient, and lean manufacturing (SSRL). However, despite the growing interest in the topic and the potential of smart manufacturing features to enable sustainable development, little is known about these interactions in the system of SSRL. Therefore, to address this gap, this study investigates the moderating effect of SM on lean manufacturing and resilient manufacturing for SP while examining the existing relationship between lean and resilience. Drawing upon a hybrid methodology including the partial least squares‐structural equation modeling (PLS‐SEM) and machine learning algorithms, this research paper develops and tests the hypothetical model using collected data from 399 organizations in China, Africa, and Europe. The findings reveal important implications regarding the fostering effect of SM on the components of the SSRL system and how firms can be both lean and resilient and achieve high sustainable performance simultaneously. [ABSTRACT FROM AUTHOR]

For several reasons, recent attention has focused on urban agriculture in the context of sustainable and smart agriculture. Most of the global population has relocated from rural to urban areas. The ecological impact of agriculture is a rising concern. Furthermore, food insecurity, particularly food availability, remains a significant issue. Satisfying rising food demand with minimal environmental impact is a significant barrier to more sustainable food production. In this article, we study a sustainable location for urban farming that optimally balances economic and environmental objectives. We formulate the problem as a multi‐objective linear program that considers maximizing the ecological benefit and crop production yield and minimizing transportation cost, sensor cost, and CO2 emissions. The proposed mathematical model is then solved using a two‐phase method. The first phase uses several multi‐objective optimization (MOO) methods (weighted sum, epsilon‐constraint, augmented epsilon) to generate a pool of compromise solutions. The second phase uses multi‐criteria decision‐making (MCDM) methods (MARCOS, VIKOR, and Possibility Degree) to rank compromise solutions. We performed a sensitivity analysis first by studying the effect of different criteria weights (balanced, environmentally, and economically oriented) and then by investigating the rank reversal. Furthermore, we developed a thorough validity test that examines the impact of the dynamic elements of rank reversal by changing the importance of the model's input parameters. To provide a fusion ranking of the MCDM rankings, we devised an aggregated ranking approach using the half‐quadratic (HQ) method. [ABSTRACT FROM AUTHOR]

The current literature claims the direct effects of industry 4.0 technologies (I4 T) on lean manufacturing practices (LMP) and sustainable organisational performance (SOP). LMP are also found to have a positive influence on SOP. However, the integrated effect of I4 T and LMP on SOP has not been empirically investigated. To address this gap, this research study investigates the indirect effects of I4 T on SOP with LMP as the mediating variable; furthermore, it aims to confirm or not the direct effects of I4 T on LMP and SOP. The study is based on data collected from 205 managers, working in 115 manufacturing firms. The findings suggest significant direct and indirect effects of I4 T on SOP and confirm the presence of LMP as a strong mediating variable. The results of the study extend the literature on I4 T by identifying I4 T as an enabler of LMP, leading to enhancement of the SOP. Implications and future research directions for academicians, practitioners, and consultants are provided. [ABSTRACT FROM AUTHOR]

The focus of Industry 4.0 (I4) technologies is to address the issue of scarce resources and improve productivity by providing solutions to economise the use of limited resources and find other substitute raw materials. Circular economy (CE) is also identified as a solution to manage the increasing pressure of environmental regulations, price volatility in resources, and supply uncertainty. However, the relationship between I4 technologies, CE and sustainable performance (SP) is still unexplored and demands a more conceptual and empirical investigation on understanding how the I4 technologies favour the transition towards CE practices and what impact they have together on SP. Based on a survey of 238 manufacturing practitioners from India, the study investigates the mediating and moderating role of CE practices on the relationship between I4 technologies and SP. The findings reveal that developing an environment of CE is not a prerequisite for implementing I4 technologies. However, I4 technologies support developing efficient CE environment, which, leads to the achievement of sustainable organisational goals. Future research directions and implications for practitioners are provided. [ABSTRACT FROM AUTHOR]

Industry 4.0 and its other synonyms like Smart Manufacturing, Smart Production or Internet of Things, have been identified as major contributors in the context of digital and automated manufacturing environment. The term industry 4.0 comprises a variety of technologies to enable the development of the value chain resulting in reduced manufacturing lead times, and improved product quality and organizational performance. Industry 4.0 has attracted much attention in the recent literature, however there are very few systematic and extensive review of research that captures the dynamic nature of this topic. The rapidly growing interest from both academics and practitioners in Industry 4.0 has urged the need for review of up-to-date research and development to develop a new agenda. Selected 85 papers were classified in five research categories namely conceptual papers on Industry 4.0, human-machine interactions, machine-equipment interactions, technologies of Industry 4.0 and sustainability. The review primarily attempted to seek answers to the following two questions: (1) What are different research approaches used to study Industry 4.0? and (2) What is the current status of research in the domains of Industry 4.0?. We propose a sustainable Industry 4.0 framework based on the findings of the review with three critical components viz., Industry 4.0 technologies, process integration and sustainable outcomes. Finally, the scope of future research is discussed in detail. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to present a research model that explore strategic outsourcing practices for sustainable competitive advantages. In this paper, a decision support system (DSS) for sustainable performance measurement of carry and forward agents (CFAs) is proposed. Design/methodology/approach – The importance of seven criteria as a means of selecting the best CFA for warehouses under the aspect of sustainable environment is analyzed. The criteria are compared and ranked using analytic hierarchy process (AHP) with the combined assistance of literature review and expert opinions. This study makes use of unstructured interviews of Regional Distribution Manager and senior strategic leaders of the firms. Findings – This paper discusses how strategic outsourcing can help firm to achieve desired business outcomes. The selection of best CFA gives a direction to the company to move toward excellence and provides the key areas to work upon to achieve competitive advantage. The main contribution of this paper includes modeling the performance evaluation problem within the context of a sustainable supply chain based on triple bottom line (TBL) concept. Research limitations/implications – The identified selection criteria are bound with Indian transportation and logistics industry. Further, it is suggested to conduct a real-life application of this study to other companies from different countries, to obtain criteria based on globally acceptable norms. The results may yield the network-specific evaluation criteria and their evaluations. Practical implications – The developed excel-based tool could be used to record the inspection data, compare the CFAs and determine the best CFAs on the basis of selected criteria. With the help of this tool, CFAs know their position and ranking among all the CFAs and the focus areas they need to work upon to perform well. The training module could be used to keep the CFA staff on the right track which is very essential in a typical manufacturing industry warehouse. The improved performance of CFAs will in turn help to improve the manufacturing process, thus maximizing the gains along with environmental benefits. Originality/value – This paper provides a priority of sustainable issues for evaluating the performance of the best CFA. The paper presents a strategic outsourcing model, which suggest both theoretical and managerial implications showing how to implement successful outsourcing practices in the global market by analyzing the performance of outsourcing partners, i.e. CFAs. [ABSTRACT FROM AUTHOR]

• The research mainly addresses digital twin for sustainable manufacturing supply chains. • A systematic literature review of 70 research papers on various dimensions of a digital twin for sustainable manufacturing is presented. • Technologies such as IoT, cloud computing, and blockchain have increased the potential of digital twin and the digital twin should include the "things" and "humans" from the entire supply chain. • A sustainable digital twin implementation framework for the supply chain is presented as an outcome of this study. A digital twin is an integration of virtual and physical systems using disruptive technologies. More precisely, it is a method of developing sustainable, intelligent manufacturing systems for attaining robust quality, reducing time, and customized products using real-time information throughout the product life cycle. This paper presents a systematic literature review of 98 research papers on various digital supply chain twin dimensions with sustainable performance objectives. The selected papers were reviewed and classified into three broad categories: components of the digital twin, applications in the manufacturing supply chain, and sustainability. Based on the review and future perspectives from the study, we suggest that advancements in technologies such as IoT, cloud computing, and blockchain have increased the potential of digital twin applications in the supply chain. The results indicate that a digital supply chain twin should include the things and humans from the entire supply chain and not be restricted to the local manufacturing systems. Based on our review findings, we present a sustainable digital twin implementation framework for supply chains. The proposed framework will guide future practitioners and researchers. [ABSTRACT FROM AUTHOR]

• A large group decision-making technique is used to rank big data-driven circular economy (BDDCE) practices. • Multi-group included 90 decision makers from purchasing, manufacturing, and logistics & marketing department. • BDDCE practices focused on improving internal supply chain integration were highly ranked. • BDDCE practices such as green purchasing and sale of excess inventory were ranked low. • Developing recycling systems for end-of-life products and materials were ranked low. The present study uses a large group decision-making technique to identify and rank the best big data-driven circular economy (BDDCE) practices in the auto-component industry. The data pertaining to the BDDCE practices were collected from the decision-makers in three groups, namely, purchasing, manufacturing, and logistics & marketing function from the auto-component manufacturing industry. First, the consensus on the BDDCE practices within the group was ascertained followed by determining the decision weights using the percentage distributions and subjective weights. This was followed by the by computing the dominance degrees on pairwise comparisons of the BDDCE practices and ranking them using the PROMETHEE II method. The findings indicated that the BDDCE practices that were more inclined towards the enhancement of internal supply chain integration were most preferred and highly ranked by the decisionmakers in the auto-component industry as compared to the practices that were focused on improving the supplier and customer interfaces such as green purchasing, sale of excess inventory, and developing recycling systems for end-of-life products and materials. The high ranked BDDCE practices included minimization of the raw material consumption, plan for reuse, recycle, recovery of material, parts, and reduction of the process waste at the design stage. [ABSTRACT FROM AUTHOR]

Healthcare supply chain management (HCSCM) is a network of different systems, tools, and processes. This system works in a seamless manner to ensure healthcare related materials such as medicines, hospital supplies, and so on. These materials are manufactured in the firms, distributed through agents, and eventually reach patients on time. During COVID-19, HCSCM was severely impacted in many countries. Many patients had to face severe difficulties during the pandemic. But post pandemic and after the adoption of several modern technologies like Industry 4.0, the performance of HCSCM was more reliable. Not many studies are available which have examined the influence of Industry 4.0 in HCSCM during such a crisis. In such context, the study aims at examining the influence of Industry 4.0 in HCSCM with moderating role of environmental dynamism. A conceptual model is proposed with the support of theories and literature. This was later validated by PLS-SEM approach considering 312 respondents from people of HCSCM system. The study ascertained that Industry 4.0 has greatly improved the performance of HCSCM system after COVID-19 crisis. In addition, this study highlighted that environmental dynamism has a significant moderating role on the linkage between adoption of industry 4.0 technology with HCSCM. [ABSTRACT FROM AUTHOR]

This paper proposes a self-assessment model to evaluate the level of readiness of organizations to implement Green Lean initiatives. A systematic literature review was conducted to synthesize the key elements of the implementation of Green Lean, barriers and its critical success factors. The proposed instrument was validated through semi-structured interviews and workshops with experts from academia and industry and applied in four manufacturing companies in a developing country. The results revealed that the proposed self-assessment model is an appropriate instrument to determine the readiness of organizations for effectively implementing Green Lean. The proposed self-assessment model was able to display the potential challenges a company will face if it aims to integrate Green and Lean and implement it. The results of this paper will help the practitioners to conduct a diagnostic of requirements for Green Lean adoption, thereby increasing the probability of success of such an initiative before a company spends its resources on the project. Consequently, this paper will contribute to encouraging the effective implementation of Green Lean initiatives and serving as implications for further exploration and contribution to this area. [ABSTRACT FROM AUTHOR]