Ordering the chaos of sustainable supply chains: A q-rung fuzzy hypersoft framework for multi-attribute green supplier selection

ABSTRACT Against the backdrop of increasing uncertainty and sustainability pressures, sustainable supply chain management (SSCM) has become critical for balancing economic, environmental, and social performance. Failure mode and effect analysis (FMEA) is widely used in SSCM, yet traditional FMEA is limited in handling uncertain linguistic information, deriving reasonable risk factor weights, and capturing intrinsic correlations among failure modes. To address these gaps, this study proposes a novel three‐stage FMEA‐based decision model for SSCM risk assessment. In the first stage, trapezoidal interval type‐2 fuzzy sets (TrIT2FSs) are employed to represent uncertain expert assessments. In the second stage, an integrated deck of cards with decision‐making trial and evaluation laboratory (DOC‐DEMATEL) method is developed to determine risk factor weights by considering dual interactions among risk factors and experts. In the third stage, a TrIT2FS‐based grey relational analysis (Tr‐GRA) method is constructed to rank failure modes while capturing their intrinsic relationships. Finally, an SSCM case is analyzed, followed by sensitivity and comparative analyses to validate the model. Results show that operation complexity, opportunity loss, and lack of trust are the highest‐priority failure modes. The proposed model outperforms traditional FMEA and multi‐criteria decision‐making methods in robustness and rationality. These findings provide clear managerial insights to help enterprises strengthen risk detection, improve supply chain collaboration, and optimize operational processes toward sustainable development.

The rising demand for a sustainable industrial development has led to the implementation of digitalization and Circular Economy (CE) methods. This review examines the combination of Industry 4.0 technologies (i.e., Internet of Things (IoT), Artificial Intelligence (AI), big data analytics, cyber-physical systems, blockchain, additive manufacturing, and cloud computing) with CE principles to enhance the Triple Bottom Line (TBL) performance in industrial firms. This research explores the impact of digital technology on resource efficiency, waste reduction, closed-loop production, prolonging product life, and sustainable supply chain management. The results demonstrate that the synergistic integration of Industry 4.0 and CE provides a significant enhancement in environmental sustainability by reducing emissions and resource consumption, economic performance improvement by increasing operational efficiency and value recovery, and social sustainability improvement by improving workplace safety, transparency, and skill development. The assessment also points to important implementation challenges, including technological complexity, cybersecurity concerns, significant investment requirements, and gaps in labour capability. Finally, future research directions including empirical TBL assessment, digital product passports, human-centric industry 5.0 techniques and policy frameworks are outlined. The report provides an integrated framework for industries to achieve sustainable, resilient and competitive growth through digital-circular transformation.

A two-warehouse inventory model is introduced with the manufacturer and retailer. They both use two warehouses for storing and selling products, with their own and a rental warehouse. The manufacturer produces both perfect and imperfect products. Defective products returned from the retailer are sent for remanufacturing. All remanufacturing products are shifted to the secondary retail stores. Every product has a lifespan, and to reduce deterioration, the manufacturer and the retailer invest in preservation technology. Both players offer trade credits to their customers. To achieve environmental sustainability, both the manufacturer and the retailer calculate and pay for their carbon emissions. The retailer advertises products in the market, as advertising policy is a significant policy for enhancing any business by attracting customers. A sustainable supply chain management model is developed to optimize the production rate, remanufacturing rate, and cycle time. A numerical experiment is performed to validate the study, and a sensitivity analysis is conducted to provide insights to managers. From numerical findings, if the holding cost increases to 20%, the profit decreases to 0.03%. The numerical results indicate the importance of remanufacturing, carbon emissions, and product quality control within a sustainable supply chain.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-026-43484-x.

Although many organizations have started to adopt sustainable supply chain management (SSCM), many organizations still face challenges in achieving their long-term sustainability goals due to pressures such as ever-changing environments and stakeholder conflicts, which are wicked sustainability problems. This present study develops a value-driven sustainable supply chain management (VSSCM) framework that advances existing integrative SSCM conceptual models by adopting an open-system perspective. This developed framework differs from previous frameworks that focus primarily on sustainability practices or performance dimensions. Based on the General System Theory and Mindsponge Framework approaches, the VSSCM framework presented describes the mechanism by which sustainability values are deeply embedded in organizational culture, translated into sustainable supply chain management practices, and transformed into adaptive and buffering capabilities that drive the performance of sustainable supply chains. The output eventually creates long-term values of stakeholder satisfaction, stakeholder well-being, and brand equity. Along with the feedback loop process, the system allows the organization’s values and beliefs to be continuously reviewed and developed to respond to and address the dynamic environmental changes. Finally, this VSSCM theory provides theoretical propositions, practical implications, and directions for future research development.

The art of sustainable supply chain management: Inspiring supplier behavior through managerial practices and justice

The role of artificial intelligence in enhancing non-invasive quality monitoring in fresh food products supply chains: A comprehensive review.

The utilization of livestock manure is a crucial area for reducing pollution and carbon emissions. However, current research focuses mainly on the impact of individual actors, overlooking a system view. This study uses system dynamics to develop a regional supply chain model for manure resource utilization, examining its overall effects through the water-energy-food-carbon emissions-waste Nexus. The main findings are as follows. (1) Within the Business-as-usual baseline scenario supply chain, comprising small- and medium-sized livestock and poultry farmers (SMS-LPFs), third-party companies (TPCs), and regional crop farmers, water, energy, food, and waste quantities all increase significantly over the simulation period. However, carbon emissions first decrease and then rise, underscoring the need for sustainable supply chain management. (2) Investing in water-saving facilities for manure treatment by SMS-LPFs can significantly reduce water use, energy consumption, carbon emissions, and waste. However, excessive investment may reduce livestock numbers and grain yield growth, whereas modest investment can improve the profits of SMS-LPFs. (3) There is no direct proportional relationship between manure treatment water-saving rates and the supply chain's carbon reduction. Although higher initial water savings enhance carbon reduction, further increases in water savings may eventually hinder carbon mitigation. (4) Improving the precision of government supervision reduces manure leakage and environmental pollution but can paradoxically lead to increased carbon emissions in the supply chain. These insights highlight the importance of adopting a system dynamics approach and integrated management strategies to promote sustainable manure resource use.

Purpose This study investigates whether supply chain transparency through sustainable supply management (SSM) disclosure influences consumer purchase behavior. When firms understand this behavior, they can optimize operations and craft clearer, more impactful supply-chain sustainability disclosures. Design/methodology/approach Two controlled laboratory experiments and a natural field experiment are used to evaluate various elements of SSM disclosures. The first laboratory experiment examines consumer willingness to pay a premium for products with SSM disclosures, when compared across firms. The second laboratory experiment examines consumer response to SSM disclosures across different products offered within the same firm. The field experiment evaluates whether consumers are willing to buy or pay a premium in actual market situations where SSM information is disclosed. Findings Results demonstrate significant consumer preferences for products accompanied by SSM disclosures. The analysis of the natural field experiment indicates that consumers are inclined to purchase more from firms that transparently communicate their SSM practices. Further, we find that at least some consumers are willing to pay a premium for products with SSM disclosure. The laboratory experiments, on the other hand, fail to provide significant evidence that consumers are willing to pay more for products with SSM disclosures. These results offer insights into how signaling and legitimacy concerns within the downstream supply chain shape consumers' purchasing behavior and, in turn, firm performance. Practical implications A proactive communication strategy on firm SSM engagement can gain market share and build competitive advantage. The costs associated with gathering SSM information can potentially be offset by greater market share and premium pricing. Regulators and policymakers can support efforts for supply chain transparency by providing impetus for consumer requests for such information and encouraging firms to supply it. Originality/value This research uniquely integrates a series of behavioral experiments to robustly assess the influence of supply chain transparency on consumer purchasing behavior. Through legitimacy and signaling theoretical lenses, our study shows the reason for firm strategic communication in SSM efforts. There is an emphasis on how supply chain decisions related to collaboration and facilitating transparency are critical to organizational market competitiveness due to consumer preferences and behavior. The role of transparency and legitimacy in sustainable supply chain management is further advanced.

Sustainable supply chain management has attracted growing scholarly attention. Despite the expanding focus on environmental sustainability, social sustainability—encompassing employee relations, product responsibility, diversity, and corporate social engagement—remains a critical yet underexplored challenge. Drawing on Resource Dependence Theory (RDT), this study examines how digital technologies adopted within supply chains generate interfirm spill-overs that shape focal firms’ social sustainability performance. Using a sample of Chinese listed firms from 2007 to 2024, we find that greater digital technology innovation by both upstream suppliers and downstream customers is positively associated with the social sustainability performance of focal firms. Further analyses show that this relationship is moderated by supply chain structure and technological characteristics. Specifically, supply chain concentration and network centrality weaken this effect, whereas geographic proximity within the supply chain strengthens it. In addition, the effect is more pronounced when suppliers or customers possess stronger technological advantages, as well as among high-tech firms. Decomposing social sustainability into multiple dimensions, we find that supply chain digital technologies exert significant and broad-based effects across various aspects of social sustainability. Overall, our findings highlight the importance of supply chain digitalisation in shaping firms’ social sustainability.

ABSTRACT Amid accelerating global climate governance and sustainable development, understanding the role of supply chain digitisation (SCD) in reducing corporate carbon emissions is increasingly prominent. It offers a potential pathway for firms seeking to overcome emission challenges and achieve green transformation. Grounded in the resource-based view, this study explores a causal relationship between SCD and corporate carbon emissions. This paper leverages the supply chain pilot policy issued by the Chinese government in 2018 as a quasi-natural experiment to test our hypotheses. Using data from A-share listed industrial enterprises spanning 2012 to 2022, we find that SCD promotes corporate carbon reduction by facilitating energy transition, alleviating financing constraints, and fostering green technology innovation. Additionally, the effect of SCD on carbon reduction is more pronounced among SOEs, firms with high supply chain concentration, and low industry competition. This research makes substantive contributions to the emerging literature on sustainable supply chain management and corporate environmental performance, while offering practical implications for enterprises seeking to optimise supply chain operations and achieve carbon neutrality.

Purpose This study investigates how dynamic capability (DC) relationships and deployment patterns enable firms to transition from sustainable supply chain management to circular supply chains (CSC). Design/methodology/approach A mixed-methods, exploratory sequential design combined a multiple case analysis of four multinational manufacturing firms with quantitative validation. The qualitative phase analyzed semi-structured interviews and corporate documents to identify DCs and their deployment patterns. The quantitative phase employed Ward's hierarchical clustering on academic expert evaluations to examine relationships among capabilities, refining case-derived patterns into generalizable configurations that enable CSC transitions. Findings This research identifies Circular DCs into three groups, with their relationships facilitating the adoption of circularity. Foundational Innovation DCs (Technology Management, Product Design Management, Process Innovation) establish an internal infrastructure to enable circularity. Transitional Collaboration DCs (Supply Chain Collaboration, Supply Market Orientation) facilitate integration across the supply chain partners. Scaling Enablement capabilities (Human Resource Management, Marketing) support ongoing transformation. These groups enable firms to progress through three practice types supporting circularity strategies. Foundational practices emerge from complementary relationships among Foundational Innovation DCs deployed at balanced levels of reconfiguring and seizing. Transitional practices emerge when Transitional Collaboration DCs form integrative relationships with established Foundational Innovation DCs. Scaling practices require reconfiguring the dominant deployment of both Foundational Innovation and Transitional Collaboration DCs, with support from Scaling Enablement capabilities. Research limitations/implications The limited longitudinal analysis and sample size suggest caution in generalization. Future research should examine DCs across diverse contexts and timeframes. Practical implications The framework directs the sequencing of capability development, starting with establishing Foundational Innovation DCs through balanced deployment, then adding Transitional Collaboration DCs once the foundations are in place, and finally developing Scaling Enablement capabilities for ongoing transformation. Social implications The research highlights ways to improve societal well-being by emphasizing collaboration among supply chain partners. These findings support sustainable employment and shape public attitudes toward circular practices. Originality/value This study advances DC theory by showing that adopting circularity depends on specific relational configurations and deployment patterns rather than individual capability strength. It reveals how complementary, integrative, and enabling relationships across deployment levels facilitate collaborative transitions to CSC practices.

This study maps the intellectual structure of global electronic supply chain management (e-SCM) research through a bibliometric analysis of Scopus-indexed publications published between 2015 and 2025. The retrieval workflow began with the Scopus query TITLE-ABS-KEY ("supply chain management") and was followed by structured interface-based refinement using pub- lication period, subject area, and document type constraints to construct the final analytical corpus. Bibliometric performance indicators were analyzed using the Bibliometrix R- package, while science mapping and network visualization were conducted using VOSviewer. The findings show that the e-SCM literature is organized around five major thematic concen- trations: sustainability in supply chain management, environmental and circular-economy integration, operational decision support and risk analytics, sectoral and stakeholder coordi- nation, and the recent acceleration of blockchain, Industry 4.0, and digital transformation. Co-authorship and country-level mappings indicate a multicentric global research structure led by China, India, and the United Kingdom, while temporal overlay visualization shows a marked shift toward digitally enabled governance and resilience-oriented research during 2022–2023. These results provide an evidence-based synthesis of the evolution of the field and a replicable bibliometric foundation for future sector-specific studies in sustainability- sensitive supply networks.

ABSTRACT Lean Six Sigma (LSS) helps to enhance environmental performance (EP), which helps to adopt environmental sustainability-related practices and augment operational productivity by focusing on organizational waste elimination and defect reduction. Although the successful adoption of LSS has numerous benefits for small and medium-sized enterprises (SMEs), which ultimately help improve EP. This study examines Organizational Cultural Practices (OCP) and Sustainable Supply Chain Management (SSCM) as the mediating variables between LSS and EP. Our dataset is extracted from 382 respondents from Pakistani SMEs, whom we approached through LinkedIn, an industrial engineering consultancy, and professional training centers. We used three different software packages for data analysis, including Smart-PLS, Jamovi, and the Statistical Package for the Social Sciences. We executed Structural Equation Modeling, Confirmatory Factor Analysis, and an Artificial Neural Network Modeling (ANNM) to analyze relationships among LSS, OCP, SSCM, and EP. The results confirm that LSS positively influences EP at ( β = 0.245 , p < 0.001 ) , with OCP and SSCM acting as partial mediators at ( β = 0.173 , p < 0.001 ) , and ( β = 0.201 , p < 0.001 ) respectively, and R2 for EP is 0.649. Moreover, we found that the ANNM results have RMSE of 0.429 for training and 0.428 for testing. This study extends the literature of Goal Setting Theory.

Purpose The research aim was to work on the discrepancies and ambiguities that have emerged with the application of individual multi-criteria decision-making (MCDM) methods in the determination of key factors in sustainable supply chain management. It aims at improving reliability of the decision-making process by suggesting an aggregation procedure to combine the various decision outcomes. Design/methodology/approach Several decision methods, including analytic hierarchy process (AHP), best-worst method (BWM) and fuzzy AHP, were employed to assess and rank the factors for achieving sustainability in steel supply chain. These methods produce different ranking since they make different assumptions, have different preference structures and different data processing mechanisms. To counter this, we made use of the half quadratic (HQ) theory to enable us to compile these rankings. HQ-based method combines varying expert estimation and methodological opinion into single final ranking. Findings The HQ-based aggregation can improve consistency and sturdiness of the final ranking; it eliminates the difference in approach. This method facilitates stable and consistent decision-making and helps in consistent strategic planning and policy making of sustainable supply chain management. Originality/value The novelty of this study lies in the use of HQ theory in aggregating the ranking based on two or more decision-making methods. It shows how this method is effective in eliminating the uncertainty that comes with single method methods as well as reveals how aggregating is important in enhancing the validity of MCDM in the use of sustainability in analysing a supply chain.

The paper examines the critical success factors for integrating environmental protection and human safety into supply chain operations for a sustainable future. Ninety-one supply chain managers and sustainability officers from the retail, logistics, and industrial sectors completed a questionnaire-based data collection process. The survey examined organizational procedures, perceived obstacles, and facilitators for the integration of environmental and human safety. A thematic analysis of the responses revealed that successful integration requires strong leadership commitment, comprehensive safety management systems, supplier cooperation, and continuous training. Lack of resources and inconsistent standards appeared as major obstacles, although regulatory compliance and stakeholder pressure were also noted as important drives. The results highlight the significance of proactive supplier engagement, integrating environmental and safety objectives into procurement procedures, and cultivating a shared responsibility culture across the supply chain. By highlighting practical elements that businesses can use to improve both environmental protection and human safety in their operations, for a sustainable future, this study contributes to the growing body of knowledge on sustainable supply chain management.

The growing environmental concerns and regulatory pressures have compelled organizations to adopt sustainable practices across all functional areas. Green Human Resource Management (Green HRM) has emerged as a strategic approach to embed environmental consciousness within organizational culture. This paper explores the relationship between Green HRM practices and sustainable supply chain management (SSCM) in the Indian context using secondary data. The study synthesizes findings from academic literature, reports, and case-based evidence to evaluate how HR practices contribute to environmental sustainability in supply chains. The findings suggest that Green HRM acts as a catalyst in promoting eco-friendly procurement, production, and logistics practices. However, challenges such as lack of awareness, cost constraints, and limited integration hinder its effectiveness. The paper concludes with practical recommendations for strengthening Green HRM initiatives in India.

Decarbonizing downstream steel logistics remains underexplored in sustainable supply chain management. This study proposes a machine learning-enhanced tri-objective optimization framework for the ship stowage planning problem (SSPP). The framework handles heterogeneous finished steel products, including coils, plates, ingots, tubes, and sections. The model simultaneously maximizes deadweight utilization and minimizes a novel Adaptive Weighted Moment Balance (AWMB) index. It also minimizes voyage carbon emissions through a trim-and-heel resistance penalty. A spatial-to-sequential discretization strategy transforms the NP-hard placement problem into a tractable permutation optimization. A deep neural network (DNN) surrogate achieves a 3.57-fold speedup with only 1.52% hypervolume degradation. An improved NSGA-III algorithm with adaptive operators ensures Pareto front exploration. Embedded step-wise moment verification guarantees dynamic stability throughout loading and unloading. Validated on real data from a Chinese steel enterprise, the framework achieves 99.88% deadweight utilization, reduces transverse and longitudinal imbalance by 48.27% and 90.54%, and cuts CO2 emissions by 95.5% per voyage. SOLAS constraints, load line limits, and CII/FuelEU targets are addressed through embedded stability and capacity constraints. Multi-route and weather-dependent validation remains necessary before fleet-scale deployment.

A Multi-Objective Operations Research Model for Sustainable and Resilient Supply Chain Management

Purpose Sustainable supply chain management (SSCM) research has often adopted instrumental logic whereby sustainability helps defend profitability. Recently, environmental justice (EJ) has been proposed as grounds for a new approach to SSCM. This research aims to explore Schlosberg’s environmental justice framework to aid theorization via the empirical investigation of a major international supply chain sustainability initiative. Design/methodology/approach Using multimodal critical discourse analysis, the authors examined 142 videos published by the Roundtable on Sustainable Palm Oil, a multi-stakeholder initiative (MSI) actively promoting elements of EJ across multiple supply chain levels. Findings EJ principles (distributional, recognitional, procedural and the capability approach) are strongly embedded in the MSI discourse but operationalized as instrumental. This means achieving EJ is seen as helping to defend profitability. The study further found various contradictions presented in the EJ discourse and that public policy interventions, notably the 2023 European Union Deforestation-free Products Directive, have been seen as risking EJ, leading to concern. The interplay between instrumental profit-maximization and noninstrumental public goals (e.g. on climate and biodiversity) for advancing supply chain justice are discussed to aid future research. Originality/value This study provides empirical evidence on how environmental justice is framed and enacted through instrumental propositions. This counters prior claims suggesting justice is inherently noninstrumental. Furthermore, evidence on how EJ outcomes are affected by changes to public policy highlights the importance of mandatory requirements.