Purpose This study aims to examine blockchain technology’s transformative potential in advancing circular economy practices, specifically focusing on reverse logistics. This study investigates how supply chains may become more transparent, traceable and trustworthy by using blockchain’s secure and unchangeable data exchange capabilities. Design/methodology/approach This study identifies and validates important circular economy behaviors using the Delphi technique and Grey Influential Analysis (GIA). GIA analysis helps in identifying the most influential circular economy practices through blockchain technology in reverse logistics. Findings This study highlighted the GIA technique, indicating that a more holistic conceptual framework is necessary to capture the complex interactions between technological, organizational and social factors for enabling blockchain-enabled reverse logistics. This study further contributes to the literature that is growing daily on the role of “emerging technologies” in the management of sustainable supply chains by uniquely placing in context how blockchain addresses the key challenges related to reverse logistics and the implementation of the circular economy. Research limitations/implications This study’s limitations include potential bias in practice assessment, relying on literature and expert opinions. Practical implications This research will be very helpful and valuable to organizations that intend or seek to use blockchain technology in their circular economy and reverse logistics operations. The ranking of practices allows the business world to have a prioritized roadmap on which they can focus their efforts and resources on the most influential applications of blockchain technology. Originality/value Blockchain is a groundbreaking, innovative technology with immense potential to revolutionize industries. Past research has explored the benefits and challenges of blockchain implementation in various industries, but very little in the circular economy, specifically in reverse logistics. This creates a gap in research regarding systematically classifying and ranking the importance of blockchain in reverse logistics. The research would bridge the gap in identifying the gap and recognizing the prominent principles using the Delphi technique and GIA techniques.

This study analyzes the relationships between knowledge sharing culture, information technology support, and process innovation on supply chain sustainability in Indonesia's digital printing SMEs, with market uncertainty as a moderating variable. Employing an explanatory approach, the research utilizes a cross-sectional survey involving 225 SME owners. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that knowledge sharing culture has a significant positive impact on both process innovation and supply chain sustainability. Conversely, information technology support negatively affects these two variables. Process innovation positively contributes to supply chain sustainability, albeit with a small effect. Market uncertainty strengthens supply chain sustainability but weakens the relationship between process innovation and sustainability. The mediating role of knowledge sharing culture through process innovation highlights a critical pathway for enhancing supply chain sustainability. This study offers theoretical and practical implications regarding the importance of knowledge sharing culture and process innovation, alongside challenges in technology adoption. The study's limitations include its cross-sectional approach and focus on digital printing SMEs in Indonesia. Future research is recommended to adopt a longitudinal approach to explore dynamic changes in this context. The novelty of this study lies in its integrated understanding of factors influencing supply chain sustainability amid market uncertainty.

This paper presents a framework for reverse logistics aimed at managing reusable items within supplier-buyer relationships to promote sustainability and reduce environmental impact. In this model, the supplier produces and inspects items, shipping only perfect items to buyers, while recycling or disposing of imperfect ones. Returned items from consumers are categorized as either reusable or damaged at a collection center. The concept of a circular economy encourages the return and refilling of reusable items, while damaged items are recycled. Additionally, the model incorporates carbon emissions considerations across production, storage, transportation, and landfilling, emphasizing the importance of environmental factors. To evaluate the sustainability and economic efficiency of the supply chain network, both Stackelberg and Nash equilibrium strategies are employed. The paper provides a mathematical framework based on lemmas to analyze the impact of the network and promote sustainable supply chain practices. In this cycle, consumers use the items and eventually discard them. To support a zero-waste policy, the supplier labels the bottles with barcodes to identify used items upon collection. The supplier has two different rates at which they purchase used bottles from consumers. Refilled bottles are sent back for reuse, while damaged bottles are either repurposed as raw materials or disposed of. The research paper aims to develop a mathematical model that determines the buyer's cycle time and the number of deliveries from the supplier to the buyer, ensuring that the buyer's demand is met without shortages.

Purpose This study uses cybernetic theory to examine the integration of predictive artificial intelligence (AI) and the ship-then-shop model in fashion supply chains. The study examines how predictive systems can enhance adaptability, reduce waste and promote sustainability by incorporating real-time feedback loops into operational and consumer-facing processes. Design/methodology/approach A structured literature review was conducted across peer-reviewed sources and supported by a thematic coding matrix. This matrix classifies insights into five key phases of the supply chain: sourcing, production, warehousing, distribution and reverse logistics. The review also incorporates cybernetic and systems theory to conceptualize AI as a control mechanism within adaptive feedback systems. Findings AI can enhance the sustainability and efficiency of the fashion supply chain by enabling dynamic decision-making. The ship-then-shop model decouples production from immediate purchases, aligns output with demand and reduces overproduction. However, the review also identifies gaps in empirical validation and ethical risks, including algorithmic opacity, labour displacement and consumer surveillance. Originality/value This study makes an original contribution by framing AI as a cybernetic enabler of system-level transformation in fashion logistics. Unlike existing literature, it synthesizes predictive intelligence, consumer behaviour and adaptive operations within an integrated conceptual model that highlights opportunities and ethical challenges for sustainable innovation.

Towards sustainable closed-loop photovoltaic supply chains: A hybrid framework integrating reinforcement learning and mathematical models

Dynamics and resilience for design of sustainable processes, industrial networks, and supply chains: Review and perspective

The efficient management of reverse supply chains, particularly the collection and remanufacturing of defective products, plays a critical role in reducing production costs and determining the final pricing of remanufactured products. While existing research extensively explores warranty policies and maintenance services to enhance customer satisfaction and profitability, the integration of vehicle routing for product collection and sustainability advertising strategies remains underexplored. Addressing this gap, this study introduces a comprehensive two-stage reverse supply chain model that captures the interactions between manufacturers (MFRs) and remanufacturers (RMFRs) through a Stackelberg game framework. Methods: The proposed model incorporates interactive production constraints, vehicle routing problem (VRP) for optimizing collection logistics, and sustainability advertising to influence consumer behavior towards remanufactured products. Utilizing mixed nonlinear programming (MINLP) and nonlinear programming (NLP) techniques, the model simultaneously optimizes pricing strategies, collection efforts, and advertising investments for both MFRs and RMFRs. Numerical analyses are conducted to solve the optimization problems, accompanied by sensitivity analyses to evaluate the impact of key parameters such as production costs, defect rates, and routing constraints. The numerical results demonstrate that increases in production costs for MFRs lead to higher selling prices, thereby reducing their profit margins and negatively impacting RMFR profitability due to decreased demand for remanufactured products. Sensitivity analysis reveals that higher defect rates (α ≥ 0.8) significantly diminish overall supply chain profitability by lowering customer acceptance of RMPs. Additionally, expanding the allowable vehicle routing distance L effectively reduces collection costs, enhancing RMFR profits and enabling greater investment in sustainability advertising. The study shows that the integration of VRP and advertising strategies proves crucial in balancing cost efficiencies and market competitiveness, ultimately fostering a more sustainable and profitable reverse supply chain.

Sustainable and resilient semiconductor supply chain optimization via hybrid deep reinforcement and generative learning

Integrating AI for sustainable healthcare supply chains

Integrating machine learning and distributionally robust optimization for sustainable agricultural supply chains under global warming uncertainty

Towards an intelligent waste management system: An adaptive and sustainable medical waste supply chain for infectious and hazardous risk reduction

The sustainability mindset with Blockchain technology in Industry 5.0: towards a framework for sustainable supply chain management

Does Sustainable Supply Chain Management Practice Drive Manufacturing Success in an Emerging Economy

This study uses the Resource-Based View (RBV) and technology, organization, and environment (TOE) theories to examine how smart supply chain (SSC) practices affect financial performance (FP) in enterprises of various sizes. Our results show that SSC benefits larger enterprises more financially than smaller firms. SSC has a statistically significant effect on green supply chain management (GSCM) and sustainable supply chain performance (SSCP), and the strength of the relationship declines with a decline in firm size. Smaller enterprises are more receptive to competitive pressure and implement GSCM alongside SSC. Our findings show that SSCP improves financial performance, while GSCM does not, even in large enterprises. Further, mediation effects show that GSCM mediates the relationship between SSC and SSCP, whereas it does not mediate between SSC and FP across all sizes. The impact of SSC on FP is sequentially mediated via GSCM and SSCP. Using a non-linear approach (ANN), we also rank independent variables for small, medium, and large firms. Our research provides important implications.

This study addresses optimizing the fruit and vegetable logistics chain at the Port of Valparaíso, Chile, a key hub for exports in the Southern Hemisphere. Through an integrated approach, it combines logistics platforms (in Limache and Quillota), blockchain technology, and a Capacitated Facility Location Problem (CFLP) mathematical model. These tools help mitigate traffic congestion, high logistics costs, and limited traceability, achieving up to a 25% savings in operating expenses, a 30% reduction in CO₂ emissions, and a 50% decrease in waiting times. Integrating blockchain ensures immutable records, improving supply chain trust and the quality of exported products. This proposal, aligned with Industry 5.0 principles, promotes economic resilience and sustainability, positioning the Port of Valparaíso as an international benchmark for logistics innovation. The framework can be replicated in other ports, contributing to more efficient and sustainable supply chains and reducing urban congestion. Finally, the paper discusses social and political risks associated with infrastructure development, compares MILP with other optimization methods (heuristics or metaheuristics), and expands on the model’s potential application to different ports, including dry ports or those with limited capacity.

Inadequate road networks, unstable power supply, and limited cold-chain capacity continue to undermine public health supply chains in Northern Ghana, contributing to delays in medical deliveries and stock-outs of essential medicines and vaccines. This study synthesised current evidence on integrating green logistics into health supply systems to develop a comprehensive framework for sustainable medical distribution in the region. A systematic search of five databases ProQuest, Scopus, Web of Science, PubMed, and Google Scholar identified literature published between 2010 and 2024 using keywords such as public health, green logistics, sustainable supply chain, medical distribution, health logistics, Ghana, and developing countries. After screening 612 records, 48 studies met the inclusion criteria. Data were analysed using thematic synthesis. Across these studies, green warehousing practices were reported in 62% of articles, emphasizing renewable energy adoption, solar-powered or energy-efficient cold chains, and structured medical-waste management. Green inventory management and packaging appeared in 54% of studies, highlighting data-driven demand forecasting and reusable or biodegradable packaging solutions. Green transportation strategies were reported in 47% of the literature, mainly route optimisation and the use of fuel-efficient or hybrid delivery vehicles. Notably, 71% of studies underscored persistent contextual barriers in Northern Ghana, including infrastructural deficits, limited funding, and capacity gaps that constrain the adoption of sustainable logistics. The resulting framework provides a structured pathway for policymakers, health administrators, and development partners to enhance medical distribution reliability while improving cost efficiency and reducing environmental impact. Strengthening green logistics within public health supply chains has the potential to significantly improve service delivery and population health outcomes. Future research should focus on piloting and validating the proposed framework under real-world operational conditions.

The rapid growth of e-commerce demands innovative solutions for resilient and sustainable supply chains. This study explores the role of AI-driven demand forecasting (AIDF) and AI-driven waste reduction (AIDWR) in enhancing supply chain efficiency, minimizing operational waste, and fostering sustainability. Analyzing data from 539 samples via PLS-SEM, the findings highlight how AIDF optimizes demand accuracy, reduces overproduction, and minimizes stockouts, while AIDWR lowers resource consumption and mitigates environmental impacts. Operational Waste Reduction mediates AI’s effectiveness, aligning efficiency with sustainability goals and promoting adaptable, environmentally conscious supply chains. These insights guide e-commerce managers in leveraging AI for resilience and sustainable growth. The study underscores the transformative potential of AI to meet dual objectives of operational excellence and sustainability.

This article aimed to examine sustainability within the agricultural supply chain, focusing on a collaborative project in orange supply chain implemented by a farmer extension group in Maesin, Si Satchanalai, Sukhothai province, Thailand. This study employed a qualitative research method, utilizing a semi-structured interview guide based on the three dimensions of sustainability (Economic, Social, and Environmental) and Actor-Network Theory (ANT). Thematic analysis was subsequently used to analyze the interview data and understand the actual sustainability of the agricultural extension project. The findings showed – Even with continuous support from the government policy in the collaborative large-scale agricultural extension project, the strong group leadership was instrumental in sustaining the group, particularly in retaining its members. High member participation is a key factor for sustainable development and the overarching sustainability of the group, which allows it to achieve five of the 17 Sustainable Development Goals (SDGs). This research was limited to a case study of only one of the seven groups involved in the orange farming extension collaborative project in Maesin, Sukhothai Province. The article fills the research gap by demonstrating the government's efficiency and sustainability in funding, using the agricultural extension project as a case study and applying Actor-Network Theory (ANT) and the Sustainable Development Goals (SDGs). Given the complexity and varying characteristics of agricultural supply chains for different fruits, the findings may not be generalizable to all types of farming collaborative projects. The practical implication is that understanding the group’s key operational factors provides valuable guidelines for sustaining the group and achieving the Sustainable Development Goals (SDGs) in similar collaborative extension projects in other areas. The findings offer guidelines for improving the efficiency and sustainability of the large-scale agricultural extension project by revealing previously undocumented real-world practices by Actor Network Theory (ANT) and Sustainable Development Goals (SDGs).

The effective management of energy consumption and the reduction of emissions are crucial to sustainable supply chain management. Sustainability can be approached in a new way through smart energy. Smart energy combines traditional and renewable energy sources through a smart system that is more efficient than conventional energy for sustainability. The model creates a closed-loop supply chain management for tires production to find the efficiency of smart energy utilization and the remanufacturing of end-of-life tires to achieve the sustainability goal. The model determines the policy for using smart energy by finding the ratio of renewable to traditional energy. The players include a manufacturer, multiple retailers, and third-party logistics that consume energy for production and management. The manufacturer follows a manufacturing-remanufacturing strategy to produce new and remanufactured tires and supplies those tires to all retailers by following an optimal delivery schedule. The formulated profit function of the developed model is a mixed-integer nonlinear function. A classical optimization method is used to solve the model. The most important finding is that using 42% smart energy increases total profit by 12.71% and pulls down emissions by 41.98%. A mixed production strategy with variable remanufacturing earns 13.91% more profit.

This research offers a comparative examination of how China and Pakistan’s recent port developments are revolutionizing the supply chain and logistics from the perspective of the interrelation of policy, law, and technology. It examines how these developments respond to the imperatives of sustainable development, aiming to reconcile economic development, environmental protection, and social justice. The extent to which policy and regulatory frameworks facilitate or undermine the adoption of technologies such as artificial intelligence and blockchain in port operations is also investigated. We provide a conceptual framework to examine the development of smartness in Chinese and Pakistani ports at the nexus of sustainability, emerging technologies, and supply chain logistics. This study engages in qualitative secondary data analysis, drawing on government policies, international reports, and the relevant literature. Against the backdrop of the peculiar development stages of Pakistani and Chinese ports, this study aims to identify the determinative policy and legal drivers that substantially improve both economic performance and environmental outcomes. This study aims to present a replicable model of sustainable port modernization, providing strategic direction to policymakers and port authorities in developing maritime countries.