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Industry 4.0 (I4.0) influences the supply chain, including innovation, structure, availability and communication. It influences the supply chain by modifying how products are designed, manufactured, delivered and discarded for the sustainability of an organization. Sustainability emphasizes the use of optimal raw materials, efficient storage and delivery, on-time supply, productivity development, recycling, remanufacturing and refurbishing. The aim of this study is to identify and establish causal relationships among the key aspects that contribute to the success of I4.0-enabled sustainable supply chain (I4eSSC). The objective is to classify these components into discrete categories according to their causal and consequential linkages.

This paper presents a three-phase hybrid Criteria Importance Through Inter-criteria Correlation and Grey Decision-Making Trial and Evaluation Laboratory (G-DEMATEL) framework to achieve the stated objectives. A study is conducted to empirically examine the Indian automobile sector in order to illustrate the suitability of the suggested framework.

During the initial stage, a total of 26 success factors have been identified for the I4eSSC implementation. During the second part of the study, a total of 20 success factors were found and deemed critical success factors (CSFs). During the concluding stage, it was seen that out of the total of 20 chosen CSFs, nine were categorized in the cause group, whereas the remaining 11 were classified under the effect group. The analysis revealed that the element of “adoption of emerging technology for sustainable product and process development” was assigned the greatest level of importance.

This study aims to motivate professionals to enhance the integration of I4.0 into sustainable supply chains to maximize the advantages offered by these two separate concepts. It is imperative to devote genuine consideration to the examination of causal group variables in the context of I4eSSC, since these elements possess a direct influence on the overall performance of systems and exert a significant impact on the components within the effect group.

This study presents an extensive compilation of CSFs pertaining to the implementation of I4eSSC. The primary objective is to determine the relative relevance of these factors and explore the intricate causal relationships that exist among them. Furthermore, this study stands out due to its novel application of a specific decision-making methodology within the field of I4eSSC.

The existing literature reflects that the connection between enablers of Industry 4.0 (I4.0), Supply Chain (SC) sustainability and reliability is understudied. To cover this gap, the purpose of this study is to identify and benchmark the enablers of I4.0 for SC sustainability to build a Reliable Supply Chain (RSC).

This study benchmarks the I4.0 enablers for SC sustainability for building a RSC and analyses them with a multi-method approach. The identified potential enablers are validated empirically. A multi-method approach of Analytical Hierarchy Process (AHP), Decision Making Trial and Evaluation Laboratory (DEMATEL) and Preference Ranking for Organization Method for Enrichment Evaluation (PROMETHEE-II) was used to investigate the influence of the identified benchmarking enablers and develop an interrelationship diagram among the identified enablers.

This study benchmarks the potential enablers of I4.0 to achieve high ecological-economic-social gains in SCs considering the Indian scenario. Digitalization of the supply chain, decentralization, smart factory technologies and data security and handling are the most prominent enablers of I4.0 for SC sustainability to build a RSC.

The findings from the study may benefit managers, practitioners, specialists, researchers and policymakers interested in I4.0 sustainability applications.

This study aims to explore and address critical aspects of IoT adoption within supply chains by identifying the key enablers and barriers, examining the drivers and challenges, and assessing the benefits and drawbacks associated with IoT implementation. Additionally, the study aims to provide insights into how organizations can leverage IoT to enhance supply chain performance across economic, operational, social, and environmental dimensions.

This study employed a systematic literature review strategy to identify relevant research published between 2009 and 2024. Using the Scopus database, an initial search yielded 369 publications. Preliminary selection criteria were then applied to narrow down the articles for further detailed evaluation. This process led to an in-depth review of 123 publications, from which data were meticulously extracted, organized into tables and analyzed. Finally, the authors developed a categorization system based on the scope and temporal aspects of IoT implementation.

This study developed a comprehensive model that identified six themes influencing IoT implementation in supply chains: pre-implementation enablers and barriers, drivers and challenges during implementation, and post-implementation benefits and drawbacks. Recommendations were mapped into four performance dimensions: environmental, social, operational, and economic. The analysis showed that IoT can enhance supply chain risk management, process integration, sustainability, collaboration, resilience, and performance measurement. Key technologies aiding IoT implementation include blockchain, radio frequency identification (RFID), enterprise resource planning (ERP), and cloud computing.

This study is one of the few to conduct a comprehensive review of widely cited papers on IoT adoption in supply chains. It systematically summarizes the enablers, barriers, drivers, challenges, benefits, and drawbacks associated with such adoption. Furthermore, it proposes a distinctive model designed to assist organizations in successfully implementing IoT technologies, thereby filling a critical gap in the existing literature.

Recent worldwide developments have altered how businesses operate. As a result, when making business decisions, the emphasis for many industries has shifted towards digital adoption to ensure sustainability, and the food supply chain is no exception. However, a substantial gap exists in assessing the barriers to a digitised food supply chain enabled by Industry 5.0 technologies. This study strives to bridge the gap by identifying and assessing the barriers to improved traceability.

For this study, a mixed method approach was used encompassing both qualitative and quantitative techniques, including an online survey, exploratory factor analysis (EFA), and the fuzzy evidential reasoning approach (FERA). The literature survey and expert opinion first yielded a list of 18 barriers, which were subsequently examined using EFA. As a result, four barriers were removed. The remaining 14 barriers were then assessed using FERA from the perspectives of the Technology, Organisation and Environment (TOE) framework. Further, a sensitivity analysis was performed to test the model’s reliability.

The present study resulted in the prioritisation of barriers from the TOE perspective. According to the findings, the top three barriers that impede the traceability of Industry 5.0-enabled digital food supply chains are Limited Digital and Physical Infrastructure, Inadequate Capital Investment, and the Intricate Supply Chain Framework.

The findings from this research will prove valuable for decision-makers, practitioners and policymakers in developing methods for improving traceability within the digital food supply chain. Concerned stakeholders may use the findings to identify and take immediate action for better decision-making.

This study’s originality lies in its position as one of the first to identify and examine the challenges to better traceability in an Industry 5.0-enabled digital food supply chain. It also adds value by broadening the TOE framework’s scope in the Industry 5.0-enabled digital food supply chain context.

This research is designed to meet two research objectives: firstly, to weigh up the criteria of Internet of Things (IoT) adoption in warehousing startups; secondly, to rank warehousing startups on the basis of benefits they derive from IoT adoption catering to an unorganized sector in the food supply chain.

A blend of analytic hierarchy process (AHP) and complex proportional assessment (COPRAS) methods of multi-criteria decision-making techniques were applied. AHP determined the weights of various criteria using pairwise comparison, and COPRAS technique ranked the 10 warehousing startups on account of performance indicators. The study has been conducted at the warehousing startups of Bangalore, a hub of food warehousing startups.

The critical findings of the study revealed that these food warehouse startups attain improved productivity in terms of enhancing efficiency when implemented with IoT adoption. When evaluated using both AHP and COPRAS techniques, the combined results show WH5 as the best performing and WH10 as the least performing warehouse startups.

Warehouses that are embarking on their business opportunity in food storage can strategize to leverage the benefits of IoT in terms of food safety and security, capacity planning, layout design, space utilization and resilience.

Despite the numerous research works on food supply chain, the research on IoT in warehousing startups is limited. The rankings for the 10 food warehousing startups integrated with IoT using AHP-COPRAS approaches are the novelty of this work.

The objective of this paper is to investigate how Industry 4.0 technologies can contribute to solve the problems of managing materials and medicines in the hospital supply chain, identifying opportunities for their adoption, evaluating their potential and impacts on this segment. This paper also plans to investigate the challenges involving change management, financial impacts and major changes in the process with the introduction of new technologies.

The research carried out a literature review using the CAPES Periodicals portal, which includes renowned scientific bases, like Scopus and Web of Science. The intention was to identify problems in the logistics of materials and medicines in hospital pharmacy. In addition, a second search was carried out in papers related to Industry 4.0 and the supply chain. Subsequently, it was listed how Industry 4.0 technologies could influence the management of the hospital supply chain, on materials and medicines.

The new technologies of Industry 4.0 identified in the research can contribute to the improvement of the hospital management supply chain, benefiting from a higher level of automation, control and security presented in the research. Thus, the article addresses a new perspective in the management of materials and medications in hospital pharmacy, adding value to the topic, as new technologies can provide more safety to patients, savings for hospital management, reducing waste and environmental impacts.

The automation of the supply chain, in the materials and medicines segment, in hospital environments, adopting Industry 4.0 techniques, will make it possible to differentiate hospital management, generating great added value, benefiting the entire chain. The combination of technologies such as IoT, BigData and artificial intelligence, applied to the management of materials and medicines, will allow real-time management; consumption and stock estimates; more agile and reliable decision-making process; greater economic efficiency, in addition to contributing to patient safety.

The present study identifies and analyses the circular supply chain (CSC) enablers concerned with industrial organizations to understand the interconnectedness of CSC enablers.

Conducting a thorough literature review and utilizing a hybrid approach involving Robust-Best-Worst-Method (RBWM) and Interpretive Structural Modeling (ISM) methodologies, we assess the intensity and connectivity of Circular Supply Chain Enablers (CSCEs), incorporating expert opinions. Additionally, we employ fuzzy-MICMAC analysis to determine the driving-dependent power of the CSCEs.

The study identifies 30 CSCEs in a framework, excluding three low-impact enablers at the initial stage. An additional 30 CSCEs are introduced to enhance the framework for improved implementation. The Fuzzy MICMAC study underscores the high instability of four enablers in the linkage quadrant, signaling that minor adjustments negatively impact organizational performance.

This work holds practical significance for industry researchers and practitioners alike. The initial study introduces a structural hierarchy of CSCEs, aiming to provide a model for academics studying CSC and facilitate its practical implementation.

The cyber-physical system (CPS) is a well proven technology for improving system performance, resilience, and interconnectivity. In emerging nations like India, the logistics industry lacks practices connecting logistical equipment with cyberspace. This paper aims to bridge this gap by identifying and evaluating the performance metrics of connectivity solutions. Its goal is to establish an appropriate infrastructure that enables seamless connectivity within the CPS-enabled logistics ecosystem.

A novel integrated decision method is employed to classify the optimal connectivity solution for CPS. It integrates Regret Theory (RT) and Preference Ranking for Organization Method for Enrichment Evaluation (PROMETHEE-1) method in a Hesitant Fuzzy (HF) environment. This method considers the psychological traits of decision-makers and effectively incorporates their hesitancy for the classification.

The findings highlight security (c10) as the foremost critical performance metric, followed by cost (c6), scalability (c9), traceability (c2) and trustworthiness (c1) to build connective infrastructure for CPS. For extensive coverage scenarios, like freight transportation, cellular connectivity (a2) emerges as the most suitable connectivity solution.

This study provides a roadmap to logistics managers for selecting a suitable connectivity infrastructure to enhance seamless connectivity in logistics operations and processes. Technology providers can utilize the findings to develop the CPS infrastructure for effective freight logistics management.

This research introduces a novel decision-making tool for making choices related to advanced technology assessment. It holds significant value in facilitating well-informed decisions in the digital transformation era.

This study delves into the intricate dynamics between technological readiness, knowledge sources and their collective impact on firms' ability to achieve ambidextrous green innovation (GI). It specifically aims to dissect the moderating influence of resource orchestration capability (ROC) in this nexus, proposing a nuanced exploration into how technological preparedness and the strategic utilisation of both internal and external knowledge sources can significantly steer firms towards successful exploitative and exploratory GI endeavours.

The study draws upon resource orchestration theory, integrating a cross-sectional approach that incorporates primary data from Pakistani manufacturing firms. The data consisting of 452 responses was analysed employing Partial Least Squares Structural Equation Modelling (PLS-SEM).

The research verifies that technological readiness has a substantial influence on exploitative and exploratory GI. Moreover, it reveals that both internal and external knowledge resources mediate the link between technological readiness and ambidextrous GI. Notably, while ROC enhances the favourable impact of external knowledge resources on both types of GI, it does not significantly moderate the effect of internal knowledge sources.

Managers must prioritize enhancing technological preparedness and strategically coordinating knowledge resources to drive both exploitative and exploratory environmentally friendly innovation. Investments in technology and collaborations with external partners, guided by strong resource management capabilities, are crucial for achieving sustainable innovation.

This research contributes to ambidextrous GI literature by examining the roles of technological readiness, mediated by internal and external knowledge sources and moderated by ROC. It offers detailed insights into the mechanisms that promote sustainable innovation, enriching the current understanding of the subject.

This conceptual paper aims to present a perspective on how to engineer sustainability through the prism of Industry 4.0 technologies and outline propositions to guide future research.

This study presents a literature review developing four research propositions, focusing on the nine leading technologies underpinning Industry 4.0 to engineer economic, environmental and social sustainability dimensions.

The authors derive benefits and challenges of Industry 4.0 technologies across all three business model elements: value creation, value delivery and value capture. The authors derive those for the economic, environmental and social dimensions of sustainability. Thereupon, we develop several propositions for future research.

The authors provide suggestions to practice how to better achieve value in all three sustainability dimensions through implementing a business model perspective, ecosystem thinking, societal demands and Data Governance and AI integration.

By linking societal aspects of Industry 4.0 technologies with environmental, and economic aspects, the authors provide several suggestions how to implement Industry 4.0. For instance, policymakers are recommended to support entire ecosystems than isolated solutions.

The paper contributes to extant literature by conceptualising how Industry 4.0 can leverage value in reaching sustainability in all three dimensions and produce broader ecosystems-wide impacts.