The Chinese automobile industry is undergoing structural transformation driven by technological disruption, decarbonisation pressures, and geopolitical and social factors. Although China leads global vehicle production and mineral processing, it faces multiple challenges linked to sustainability, labour practices, technological dependence, and declining foreign investment. This research unpacks these issues using an integrated multi-criteria strategic management method, with insights from industry experts, enabling a balanced approach and generating 25 strategies addressing market scale, supply-chain integration, technological autonomy, mineral security, Environmental, Social and Governance (ESG) expectations, and global competition. The findings lead to the development of an evidence-based roadmap to inform decision-making for policymakers and leaders through an increasingly complex operating environment. Hence, this study contributes by integrating multi-criteria strategic tools with expert insights to produce an evidence-based roadmap for strengthening the long-term competitiveness and sustainability of the Chinese automotive industry.

As conventional land-based protein sources become increasingly costly, additional solutions are needed to help meet future global food requirements. We examine the potential of macroalgae (seaweed) as an alternative protein source, providing insights into key market enablers and inhibitors. The global seaweed market has grown significantly in recent years, with Asia dominating both production and consumption. However, despite its long-standing dietary significance in Asia, macroalgae applications are underdeveloped in European markets. In this research, we investigate why macroalgae applications are underdeveloped in the food industry in Europe. Value chain mapping allowed us to capture the involved stakeholders, operations, and outcomes, while a PESTEL analysis enabled us to identify contextual enablers and inhibitors. Key findings highlight the industry's strengths, including the high nutritional value of products and the rapid growth rate of macroalgae businesses, alongside weaknesses such as industry fragmentation and regulatory gaps. Two workshops with food supply chain experts confirmed the findings, resulting in six strategic recommendations to speed up macroalgae adoption: (i) harmonising regulations across EU Member States, (ii) educating consumers to increase awareness and reduce food neophobia, (iii) targeted research and development investment in macroalgae cultivation and processing, (iv) improving supply chain integration, (v) establishing multi-stakeholder collaboration platforms, and (vi) providing sustainability incentives aligned with the EU Blue Economy Strategy. This research is among the first to identify key enablers, inhibitors, and practical policy directions for the macroalgae sector, highlighting the importance of coordinated innovation and cross-sector collaboration to unlock its potential as a sustainable protein source.

Simulation modelling in Operations Research (OR) relies critically on data quality, yet multi-echelon supply chains (SC) often lack the timely, contextual information necessary for realistic model parameterisation and scenario generation. This research proposes the "Large Language Models (LLM)-Integrated Simulation Data Framework", a domain-agnostic methodology that systematically integrates unstructured narratives with structured datasets to enhance simulation model realism and contextual relevance. The framework employs a Retrieval-Augmented Generation pipeline powered by LLMs to extract, structure, and validate intelligence from policy documents, news archives, and industry reports, transforming qualitative narratives into traceable model inputs for parameterisation, behavioural logic, and scenario specifications. We demonstrate the framework's applicability through India's strategic development of its lithium carbonate reserves processing 972 documents to generate 668 validated insights that inform agent behaviours, numerical parameters, and scenario specifications. The methodological contribution establishes a novel collaborative interface between OR and Generative Artificial Intelligence, demonstrating how automated extraction of contextual knowledge at scale enables the combination of quantitative baselines with qualitative intelligence to enhance simulation empirical grounding. The lithium stockpiling case validates the framework's applicability in data-sparse, multi-echelon contexts, yielding policy insights on strategic reserve development whilst demonstrating broader applicability to geopolitically sensitive, resource-constrained SCs.

This study examines sustainable practices in the child immunisation vaccine supply chain (VSC) in Uttar Pradesh, India, to support the UN’s Sustainable Development Goals (SDGs). This analysis examines the impact of social, economic, and environmental sustainability practices on the VSC’s efficacy and efficiency, as well as their contribution to achieving SDG goals, including improved healthcare access and enhanced community resilience. This study employs Structural Equation Modelling (SEM) to analyse the relationships between sustainability practices and vaccine supply chain performance. Data were collected through a structured survey from different stakeholders, including healthcare workers, supply chain managers, and policymakers involved in vaccine distribution, storage, and delivery. A total of 180 valid responses were analysed to assess the direct and indirect effects of sustainability practices on the VSC. The findings highlight the interrelated nature of sustainability factors across the VSC. Social sustainability emerged as the most influential component (path coefficient: 0.868), emphasising the importance of fair labour practices, community well-being, and ethical leadership. Economic sustainability had a moderate-to-high impact (0.666), highlighting the importance of profit optimisation and cost reduction. Meanwhile, environmental sustainability had a smaller effect (0.542), indicating that, while important, it must be supported by social and economic policies for maximum benefit. The study emphasises the value of external collaboration and integrated sustainable practices in building the VSC. The research provides evidence for developing targeted interventions and policies that improve vaccine supply chain sustainability, supporting broader healthcare goals and sustainable development. Unlike previous research, which has mostly focused on logistical issues in vaccine delivery, this study incorporates sustainability factors into the examination of vaccine supply chains. This study provides policymakers, healthcare professionals, and stakeholders with valuable guidance for developing sustainable immunisation strategies in Uttar Pradesh and other similar regions worldwide, offering a comprehensive framework that connects sustainability practices to improved healthcare outcomes.

In the era of Industry 4.0, the formulation of sustainable supply chain systems is important for enhancing both efficiency and competitiveness. This paper introduces a manufacturer-retailer sustainable supply chain model that incorporates smart production strategies for deteriorating items alongside investments in automation technology, facilitated by radio frequency identification (RFID) technology. So, using RFID an environmental and social partnership between the maker and seller, the manufacturer is more efficient and responsive. The model addresses key challenges related to product deterioration, inventory control, and real-time information exchange between manufacturers and retailers. By integrating autonomy and automation with a human element through radio frequency identification technology, the system enables intelligent inspection, thereby reducing waste and operational costs. The human involvement is implicitly represented through the autonomation investment function, which reflects investments in intelligent inspection, monitoring, and human-assisted quality control mechanisms. The smart production allows manufacturers to dynamically adjust production rates in response to demand fluctuations and deterioration rates. Analytical and numerical results indicate that radio frequency identification technology-based autonomation enhances decision-making, reduces total system costs, and improves responsiveness throughout the supply chain. This framework offers valuable insights for managers seeking sustainable, technology-driven inventory solutions in contexts involving deteriorating items. The model is numerically validated using the software Mathematica, and robustness analysis is conducted to examine the impact of various parameters on optimal results. This study is important; increasing environmental regulations and production waste in the rubber industry require sustainable and smart supply chain solutions. The purpose of this study is to develop a manufacturer–retailer sustainable supply chain model for deteriorating items using RFID-enabled autonomation technology. The proposed model is solved analytically using Hessian matrix conditions and validated through numerical and sensitivity analyses. By conducting this study, we developed a model cost reduction, and waste reduction, RFID benefits. This study demonstrates that RFID-enabled autonomation significantly improves sustainability and operational efficiency.

Global supply chains (SCs) face critical vulnerabilities from disruptions, regulatory changes, and sustainability pressures, increasing the need for robust data and information processing capabilities to support end-to-end coordination and accountability. Visibility, traceability, and transparency across end-to-end SCs are intended to address these challenges, yet they are often used interchangeably. This creates ambiguity about which SC data elements, such as demand patterns, inventory levels and material flow records, are required and how these data should be analysed to operationalise these capabilities effectively. This study conducts a combined narrative review of 32 conceptual definitions and a systematic review of 72 empirical studies to develop a data-centric framework that clarifies the concepts of SC visibility, traceability, and transparency from a data perspective. Findings reveal that: (i) visibility requires real-time operational data to support operational decisions; (ii) traceability demands historical, product-level data to enable retrospective analysis (tactical decisions); and (iii) transparency necessitates contextual disclosure data for stakeholder accountability (strategic decisions). This research contributes to the Operations Management field by defining SC visibility, traceability, and transparency as distinct information-processing capabilities enabled by specific data requirements. A proposed data-centric framework supports SC managers in identifying data gaps, aligning data requirements and pertinent investments with strategic objectives, and designing SC stakeholder-specific implementation pathways.

Supply chain resilience (SCRES) remains a key concern for many industries due to the increasingly dynamic, unpredictable, and complex business environment. The automotive industry is particularly vulnerable, with high dependence on critical minerals essential for net-zero goals. Despite increasing scholarly interest, there is limited empirical clarity from the practitioner's point of view on how individual resilience capabilities contribute across different disruption phases. For long-term success, the industry must identify, prioritise, organise and integrate these capabilities. This study empirically investigates SCRES across three disruption phases: anticipation, responsiveness, and recovery. Through systematic literature review and discussions with 25 industry experts, twelve resilience capabilities were identified and aligned with theoretical perspectives, then evaluated through a survey of 124 practitioners. Findings show that all twelve capabilities support resilience, though their importance varies across phases. Results underscore that resilience depends on integrating anticipatory, responsive, and recovery-orientated capabilities into a holistic framework, offering policy and process oriented implications for strengthening the automotive ecosystem.

Customer expectations for quick delivery have shifted significantly. Today, speed is the new currency, with customers wanting faster delivery while prioritising cheaper delivery. Hence, some changes have been made to address this faster delivery process in the retail industry. This research will address what factors need to be considered in adopting the quick-commerce service in retail and address the interdependence among factors and subfactors using supply chain agility. To address these problem the information was gathered from experts in the retailing area from academics and industry and proposed a hybrid multiple criteria decision-making model incorporating the Decision-Making Trial and Evaluation Laboratory (DEMATEL)-based Analytic Network Process (DANP). The findings result in 19 subfactors categorised into five factors from the literature review, which might be important in adopting a q-commerce service. The cause-and-effect relationship has been drawn among the factors and subfactors. The top subfactor, based on the influencing weights, is classified into three tiers, in which the first tier factors are core critical factors, the second tier is for enhancing the efficiency of the organisation, and the third tier is for enhancing customer satisfaction, engagement and trust for q-commerce (quick commerce) service. To successfully adopt q-commerce in retail, artificial intelligence and machine learning facilitate advanced demand forecasting, route optimization, and inventory management, thereby enhancing operational responsiveness in highly dynamic urban environments. Additionally, real-time order tracking, intelligent warehousing, and temperature-controlled transportation are made possible by Internet of Things technology, guaranteeing product quality and supply chain transparency. This knowledge helps to clarify how managers and merchants can use these elements to improve the q-commerce service. This study is novel in that it highlights the factors that contribute to the retail adoption of q-commerce and explores the interdependencies between these aspects.

Semiconductor supply chains (SCs) depend on geographically concentrated rare earth element inputs and face systemic risks from geopolitical disruption, policy intervention, and capacity constraints across multiple decision-making layers. Existing stress testing approaches often quantify fulfilment loss without attributing it to strategic capacity shortages, tactical sourcing-access constraints, or operational congestion, even though each requires a different intervention. This study develops a hybrid simulation modelling framework integrating System Dynamics (SD), Agent-Based Modelling (ABM), and Discrete Event Simulation (DES) as necessary analytical approaches per decision-making layer: SD captures long-term capacity stocks and policy feedback (macro-level); ABM captures heterogeneous monthly sourcing and inventory decisions (meso-level); and DES captures stochastic weekly fabrication and shipment execution (micro-level). Applied to India's cerium-centric semiconductor SC through 247 experiments, 12,350 simulation runs and an additional 1,400 runs of sensitivity analysis, the results show that upstream cerium capacity disruptions are largely buffered, whereas loss of qualified fabrication capacity causes severe fulfilment collapse. Stable DES cycle times further confirm that this failure arises from sourcing access rather than operational congestion. This cross-layer diagnostic signal is only detectable when all three modelling layers are present. Managerially, the hybrid simulation modelling framework reframes stress testing as a multi-level tool that identifies not only whether an SC fails, but also where failure emerges and which interventions are appropriate.

Existing research on supply chain resilience (SCRES) has advanced significantly; however, without considering cost, resilience remains a myopic concept detached from practical implementation. This study examines the relationship between resilience and cost from a resources, competencies, and capabilities perspective. Our systematic literature review and qualitative analysis of 129 peer-reviewed articles identify the constructs and trade-offs between SCRES and cost. Our findings suggest that the level of SCRES is determined by how companies configure existing and new resources and competencies to develop resilience capabilities.This study proposes an integrated framework for cost-effective SCRES and a practical guideline to support companiesbalance the level of SCRES within cost constraints, considering specific contexts, trade-offs, and the maturity level of resilience. It contributes to the Operations Management field by linking the maturity level of SCRES to firms' resources, competencies, and capabilities,assisting organisations in making informed decisions to build proactive resilience in uncertain environments.

Purpose Food loss, climate variability, resource constraints and growing demand are placing agri-food supply chains (AFSCs) under mounting pressure to deliver sustainable food security (SFS). Digital twin (DT) technology is a promising approach to overcoming these challenges through capabilities such as real-time monitoring, increased visibility and data-driven decision-making. Nevertheless, the implementation of DTs in AFSC is still in its early stages and faces significant challenges. Design/methodology/approach Using Resource Orchestration Theory (ROT), the paper elaborates on how the failure to structure, bundle and leverage resources limits the implementation of DT. Moreover, this paper also investigates the interactions and hierarchical links among these challenges by employing a hybrid approach that combines the Delphi method with the Interpretive Structural Model (ISM) and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology. Findings From a review of the literature and expert insights, the study identifies 13 key challenges. To effectively implement DT and address food security concerns, special attention must be paid to key structuring challenges, such as high costs and the Lack of a single digital platform and standard architecture, which become fundamental factors restricting the diffusion of DT. Research limitations/implications This research provides a critical theoretical and practical framework for policymakers, technology providers and agri-food firms to strategically orchestrate their resources, thereby overcoming adoption hurdles and harnessing DT technology to make substantive progress towards Sustainable Development Goal 2 (SDG 2), i.e. Zero hunger through SFS. Originality/value Unlike the previous studies on DT adoption in AFSCs, which mainly determine the challenges to DT adoption through descriptive or single-method approaches (e.g. Yadav and Majumdar, 2024). To the best of the authors’ knowledge, this study is the first to apply the ROT to a Delphi–ISM–MICMAC–DEMATEL approach, systematically modeling the hierarchical and causal relationships among DT adoption challenges. This provides not only a profound theoretical explanation but also decision-oriented insights for SFS.

With the global shift towards a carbon-neutral supply chain (CNSC), blockchain technology (BT) is becoming increasingly significant. The food supply chain (FSC) significantly generates carbon emissions. This study evaluates how the integration of blockchain technology (IBT) is feasible to attain a CNSC. This study also finds the nexus among the sustainable development goals and how they behave between IBT and CNSC. This study presented a new framework based on the resource-based view and dynamic capability, which was tested using structural equation modeling (SEM). A comprehensive online survey was conducted utilizing a questionnaire that gathered responses from 200 individuals employed in the agricultural and food sectors. The finding reveals that the implementation of disruptive BT has a beneficial impact on the FSC by reducing emissions, ensuring safety, improving supply chain performance, minimizing food waste, and boosting consumer trust. Nonetheless, two variables, namely enhance supply chain performance, and build consumer trust, do not contribute to achieving a CNSC, as they enhance operational efficiency and trust, which might not directly result in a decrease in carbon emissions. The study enriches the literature on IBT in FSC to attain a CNSC while making the supply chain network more transparent, agile, and sustainable. It also challenges conventional wisdom by revealing factors that do not lead to a CNSC and guides policymakers to develop strategies to attain a CNSC.

In the era of rapid technological advancement and growing global challenges, the interaction between sustainability, digital technology (DT), and sustainable development goals (SDGs) presents a vital opportunity for transformative action. This convergence opens doors to innovative solutions for addressing critical environmental and societal issues while advancing economic progress. Therefore, this study aims to explore the intricate relationship between sustainability, digital technology, and SDGs. A systematic literature review and Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol have been used to comprehend the impact of DT on promoting SDGs across diverse sectors while enhancing sustainability. By analyzing the 141 articles, it could be concluded that achieving sustainability by adhering to the SDGs requires effective integration of DT and a thorough understanding of the policy reforms and SDG knowledge that support both sustainability goals and digitalization. The findings also indicate that achieving the SDGs in the era of digitalization relies on the collective and collaborative ability to leverage digital technology as a crucial tool and resource for positive transformation while mitigating its adverse impacts. Furthermore, the successful integration of DT with SDGs requires a comprehensive approach that encompasses technological innovation, a supportive governance framework, and capacity building.

ABSTRACTOptimizing routes in road networks is crucial for smooth transportation and economic progress. Different methods exist for finding the best routes, including genetic algorithms, particle swarm optimization, and simulated annealing. Ant Colony Optimization (ACO) stands out for its efficiency. In this study, we introduce a modified version called MACO, which considers accidents when determining optimal routes. Evaluating different ACO versions reveals differences in solution quality, runtime, and number of iterations. Performance metrics including maximum obtained solution, runtime, and iteration number were evaluated for each method. In Case 1, TACO, and AACO both achieved a maximum of 21 solutions from the available possible solution of 24, exhibiting run‐times of 0.4359 and 0.4575 s, respectively. Meanwhile, MACO attained a maximum of 22 solutions from available possible solution 24, in a runtime of 0.5345 s and 10 iterations. In the second scenario, TACO, AACO, and MACO achieved maximum solutions of 20 with obtained solutions of 15, 16, and 17, respectively. TACO demonstrated a runtime of 0.1853 s with 26 iterations, AACO ran in 0.1749 s with 22 iterations, and MACO completed in 0.5799 s with 15 iterations. These findings highlight the varying performance of the optimization methods and suggest MACO as a promising approach for balancing solution quality and computational efficiency in road network path optimization.

Purpose - This study identifies and analyses the critical core competencies and strategies required to build supply chain resilience for a high-value manufacturing industry - industrial valve manufacturer. Design/methodology/approach - Initially, nine core competencies and nine strategies for establishing supply chain resilience during the post-COVID-19 era are identified through literature. A neutrosophic analytical hierarchy process (NAHP) is utilised to evaluate the relative weights of all strategies and competencies. Later, the strategies and competencies are prioritised according to their relative weight to determine the most critical strategies and competencies for the firm under study. Findings - The findings from the study revealed that to achieve supply chain resilience, "operations and risk management and circular and leagile supply chain" are the essential competencies the firm under study should possess. While "creating resilient supply chain actors/stages and bringing sustailient operations" are the critical strategies the case should adopt under study. Research limitations/implications - The authors manifest the key role of the core competencies of resilience and the critical strategies required for building resilience in a high-value manufacturer using the case of industrial valve manufacturers. Originality/value - The novelty of this work is associated with the consideration of the type of industry, i.e. high-value manufacturer. This is the early attempt in the body of knowledge to demonstrate the core competencies and strategies that are required to build supply chain resilience for a high-value manufacturer.

The circular economy is crucial in promoting environmental justice by reducing the uneven burden of environmental hazards on marginalized communities and low-income individuals. The circular economy transition is increasingly a pivotal strategy for achieving carbon neutrality. Recent shifts in stakeholder focus towards carbon neutrality have made net-zero and environmental social and governance (ESG) hot topics to study, as they can lead to environmental justice. This research delves into the significance of net-zero policies and stakeholder pressure in integrating circular economy concepts into supply chains, aiming to establish a carbon-neutral supply chain within the environmental justice framework. Even though there is a lot of literature about the circular economy, not much is known about how it affects the adoption of the circular economy, the involvement of stakeholders, and net zero policy. Specifically, the role of innovation capability in this context has not been fully explored. This research aims to clarify the role of stakeholders in promoting circular economic practices in supply chains and their impact on carbon neutrality. It also examines how net-zero policies and innovation capabilities affect each other. To achieve this, we used structural equation modeling on data from 217 manufacturing firms from October 2023 to January 2024. Findings highlight a positive relationship between stakeholder pressure and circular economy integration, contributing to carbon-neutral supply chain outcomes. Results show net-zero policies moderate the stakeholder and circular economy relationship, with innovative capabilities acting as a partial mediator. This study adds to the literature by explaining the complex relationships between stakeholder pressures, circular economy practices, and the role of net zero policies and innovation capabilities in advancing carbon-neutral supply chains. This research makes a unique contribution to theory by examining the impact of circular economy practices on social well-being and environmental benefits, particularly regarding environmental justice.

The circular economy concept has gained significant attention in the academic and industrial discourse. Yet, the widespread adoption of circular business models is still outstanding, with a lack of customer acceptance representing a critical barrier. Recently, there has been a growing interest in the potential of digital technologies to expedite the circular economy's broader implementation. This study investigates the role of digital technologies in enhancing customer acceptance of circular business models in consumer-facing industries. To extract insights from practice, we conducted 41 semi-structured interviews with experts from companies that have implemented circular economy principles, management consulting firms, and academia. As a result, we provide thematical structures of (1) 35 factors affecting customer acceptance of circular business models, (2) 36 practices that organizations can deploy to address these factors and enhance customer acceptance, and (3) 19 digital technologies to facilitate such practices. Our findings combine and extend insights from the distinct research streams of behavioral science and theory of digital technology management by adding a technology dimension to the behavior change wheel, highlighting the interplay between sources of behavior (factors), intervention functions (practices), and technological enablers (digital technologies). This extended framework will support researchers investigating the role of digital technologies and inform companies about the use of digital technologies in circular business model innovation as an enabler of customer acceptance.

Ensuring traceability in the perishable food supply chain (PFSC) is crucial for safeguarding consumer rights, food quality, and safety. Blockchain technology (BT), with its decentralized and immutable attributes, offers significant potential to enhance this traceability. However, its widespread adoption faces considerable roadblocks due to industry regulations and operational obstacles. This study aims to identify and analyze these roadblocks for BT adoption in the food industry to support strategic decision-making. Through a comprehensive literature review and expert discussions, 14 key roadblocks to blockchain adoption were identified, and a Grey DEMATEL integrated ANP methodology was applied. Findings reveal that the three most significant roadblocks to BT-based traceability adoption are a 'data security concern: lack of technological maturity and acceptance' (prominence value 4.219), 'threat to data privacy' (4.035), and 'lack of digital infrastructure' (3.971). Addressing these top three roadblocks in order of importance is crucial for accelerating BT adoption. This study provides theoretical contributions to methodological technologies and offers practical insights for professionals to overcome these roadblocks, thereby enhancing food security and safety within global PFSCs through robust, end-to-end encrypted traceable systems. For the successful implementation of blockchain technology strong rule and regulation against data security, creating centre or excellence and standardisation is advisable.

By assessing carbon footprints and raising awareness of carbon labelling, the food sector is setting long-term targets to reduce carbon emissions and accelerate the transition to low-carbon food production. Carbon labelling, also known as carbon labelling, informs customers about a product's production, distribution, and disposal carbon emissions. This study examines how customers view carbon labelling and how it affects their purchases. The study also examines the complex food industry, identifying the biggest carbon emitters and proposing sustainable alternatives. The study collects qualitative and quantitative data using mixed methodologies. An overview of the literature shows how carbon labelling promotes sustainable consumption. Life Cycle Assessment (LCA) is used to evaluate two sandwich recipes' carbon footprints, focusing on emissions per item. LCA results indicated that carbon footprint of a cheese and mayonnaise sandwich ranged between 700 and 750 g CO2 eq, while a ham and cheese sandwich ranged between 1053 and 1070 g CO2 eq., and the primary contributors for these emissions were ingredient production, packaging and energy consumption. A sandwich maker partnership simplifies case study data collection, providing a complete carbon footprint analysis throughout production. This study suggests ways to minimise food industry carbon emissions for a sustainable future. Consumer knowledge and relevance of carbon labelling vary, according to our results. Survey findings revealed that 68.6 % of respondents recognise the significance of carbon labelling, however, only 26.9 % reported that their purchasing decisions are influenced by carbon labelling. This indicated a gap between consumer awareness and behavioural change. Consumers are concerned about carbon footprints; thus, carbon labels affect shopping decisions differently. This study suggests that consumer education, standardisation of carbon labelling and recipe modifications could increase effectiveness of carbon labelling in the food industry and its potential to change consumer behaviour towards greener choices and lower carbon footprints.