The sustainable transformation of electronics supply chains (ESCs) increasingly relies on effective green supply chain planning under carbon pricing and demand uncertainty. However, prior studies often lack an integrated framework that jointly considers carbon taxation, green technology investment, and profitability—environment trade-offs in forward and reverse supply chains. To address this gap, this study proposes a fuzzy multi-goal optimization model using linear goal programming under progressive carbon taxation. The model incorporates fuzzy demand (triangular fuzzy numbers), carbon emissions, carbon taxes, and green investment costs and is converted into a solvable linear form via a defuzzification-based procedure to simultaneously achieve multiple aspiration levels for economic and environmental objectives. A real-world ESC case validates the model. The results show that carbon taxation and green investments can reduce emissions while maintaining profitability, with total cost and emission sensitivity of ±10–20% across different policies and demand uncertainty settings. The findings support adaptive, policy-aware planning by guiding green investment intensity and forward–reverse logistics decisions to balance cost efficiency and emissions reduction and provide actionable insights for managers facing progressive carbon pricing regulations.

Transforming the reverse supply chain: Leveraging a platform for enhanced recycling and remanufacturing

Nowadays, remanufacturing is a sustainable and cost-effective process that restores used products or components to their original performance standards, often making them as good as new. This article focuses on the process of remanufacturing used products, emphasizing their restoration to the original functionality and performance standards and finding a cost-effective solution. It considers various aspects of the remanufacturing process, including collection, inspection, repair, and reassembly, while highlighting the environmental benefits associated with this sustainable practice. We have presented a detailed analysis of all cost components and carbon emissions associated with each process in the system, including costs incurred at the primary manufacturer, primary retailer, collection centre, and other relevant stages. The main aim of this article is to optimize total system cost and carbon emissions associated to each process. To get the model optimum, we have solved the bi-objective problem by NSGA II, which ensures an optimal balance between the two objectives. The major novelties of this work include imperfect screening, quadratic demand, and unequal shipment. For model validation, a numerical example has been analyzed on the basis of a case study, which results in a set of Pareto optimal solutions for the problem. A sensitivity analysis has been presented to evaluate the impact of varying parameters on the outcomes. The findings of this study reveal that it is possible to achieve up to 65.21% reduction in costs through the proposed approach.

The rise of “Internet + Recycling” platforms is transforming the domestic waste management landscape, creating dual-channel reverse supply chains where new platforms interact with traditional recyclers. However, these platforms face critical strategic decisions regarding their service portfolios (convenient but costly door-to-door vs. economical fixed-point drop-off) and their relationship with incumbents (cooperation vs. competition). This study aims to determine the optimal pricing, service level, and relationship strategies for an “Internet + Recycling” center to maximize profitability under the influence of consumer channel preferences and government subsidies. We developed four Stackelberg game-theoretic models representing different scenarios of service modes (fixed-point only vs. fixed-point with door-to-door) and relationship structures (cooperation vs. competition). We derived equilibrium solutions for recycling prices, service levels, and profits. Our results reveal that while cooperation generally leads to higher systemic profits, the addition of a door-to-door service significantly alters the strategic landscape. We find that a higher consumer preference for the platform channel allows the center to lower prices while increasing profits, and that government subsidies are the most effective at enhancing service levels in cooperative models. Crucially, intense competition incentivizes recycling centers to reduce rather than increase their service levels to cut costs. This research provides a decision-making framework for recycling enterprises to select optimal service and competitive strategies. It also offers insights for policymakers on how to design subsidies to effectively promote high-convenience recycling services and foster a more efficient circular economy.

The application of blockchain to supply chain finance (SCF) can, to a certain extent, solve the problems of expensive and difficult financing for the small and medium-sized enterprises (SMEs) at the end of the supply chain. This paper develops a three-level game model with the core enterprise as the leader (retailer), SMEs as followers (supplier and manufacturer). It analyzes the investment cost threshold of the blockchain. Under the blockchain, this paper proposes a Nash bargaining mechanism and a goal programming coordination mechanism to allocate the total revenue. The research shows that under specific circumstances where blockchain costs are met, there is a consequential enhancement in the system revenue, coupled with a notable mitigation in supplier financing expenditures. Conversely, surpassing a designated threshold in blockchain costs precipitates a rise in retail prices and an ensuing loss in revenue. Secondly, when the creditworthiness of the SME supplier is at a medium-high level, the members’ adoption of the Nash coordination mechanism. When the creditworthiness is lower, the members’ adoption of the goal planning coordination mechanism is also lower. Finally, SMEs with more initial capital are more conducive to rapid enterprise development and enhancing their bargaining power to obtain more revenue.

The booming development of electric vehicle (EV) adoption in Vietnam has worsened the problem of end-of-life EV battery management in a sustainable and economically feasible way. Reverse supply chain management (RSCM) plays a critical role in reducing environmental risks, resource dependency, and circular economy goals. However, the choice of suitable reverse supply chain strategies is impaired by several economic, environmental, technical, and policy-related barriers. This study proposes an integrated AHP-TOPSIS framework for the evaluation and prioritization of reverse supply chain alternatives for EV batteries in the Vietnamese context. Ten key barriers were identified, from an extensive literature review and expert consultation by twelve domain specialists. High collection and transportation costs (weight = 0.244) and high recycling and processing expenses (weight = 0.162) were shown to be the most significant barriers when AHP was applied to determine their relative importance. The four options—Direct Recycling, Second-Life Applications, Centralized Recycling, and Decentralized/Hybrid Recycling—were then ranked using TOPSIS. According to the findings, Decentralized/Hybrid Recycling had the highest closeness coefficient, followed by Second-Life Applications, while Direct Recycling had the lowest. The results show how adaptable and localized reverse supply chain topologies can help solve the issue of cost-related barriers. In order to promote sustainable EV battery management in Vietnam, the suggested framework provides policymakers and industry stakeholders with useful insights.

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.

From Compliance Motives to Intelligent Reverse Supply Chains: Three Decades of Evolution and Future Research Directions

The current retired recycling system suffers from “systemic coordination failure”, primarily due to ambiguous responsibility boundaries hindering interenterprise collaboration, unequal profit distribution discouraging technological innovation investment, and low participation from both consumers and recycling enterprises undermining the efficiency of recycling channels. However, the simplified tripartite game models commonly adopted in existing research exhibit significant limitations in explaining and addressing the above practical challenges, as they fail to incorporate consumers and third-party recyclers as strategic decision-makers into the analytical framework. To address these issues, this study develops, for the first time, a five-party evolutionary game model involving governments, vehicle manufacturers, battery producers, third-party recyclers, and consumers within a reverse supply chain framework. We further employ system dynamics to simulate the dynamic evolution of stakeholder strategies. The results show that: (1) When tri-party synergistic benefits exceed 15, the system transitions from resource dissipation to circular regeneration. (2) Government subsidies reaching the threshold of 2 effectively promote low-carbon transformation across the industrial chain. (3) Bilateral synergistic benefits of 12 can stimulate green technological innovation and industrial upgrading. (4) Establishing a multi-stakeholder governance framework is key to enhancing resource circulation efficiency. This research provides quantitative evidence and policy implications for constructing an efficient and sustainable power battery recycling system.

The growing global focus on environmental sustainability has driven manufacturing industries to adopt innovative strategies that reduce waste and improve resource utilization. Inverted supply chains have emerged as a key approach to managing product returns, recycling, and remanufacturing processes. This study focuses on the role of inverted supply chains in promoting environmental sustainability within the Sama Baghdad factory for the production of healthy water and juices. Through 65 questionnaires obtained from the factory's workers, analyzed using the advanced AMOS statistical software version 26, the study demonstrated how inverted supply chain practices—such as product recovery, material recycling, and waste reduction—contribute to reducing environmental impact and improving operational efficiency. The results highlight that integrating inverted logistics into the factory's supply chain significantly reduces carbon emissions, conserves raw materials, and aligns with global sustainability standards. Furthermore, the study provides practical recommendations for improving inverted supply chain processes, thereby supporting the economic and environmental goals of the Iraqi manufacturing sector.

The consumption of electronic products is growing rapidly, resulting in considerable amounts of electronic waste (e-waste). In addition, economic, environmental, and social perspectives increased the need to develop an effective reverse supply chain (RSC). This study, therefore, formulates a stochastic model for a multi-objective, multi-product, multi-period RSC for electronic waste (e-waste) under uncertainty in returns’ quantity, quality, and availability to repair. Three objective functions are considered: maximizing profit, maximizing social impact, and minimizing CO2 emissions. The end-of-life (EOL) household appliance firm was considered for illustration. Results showed that selling products’ parts and generating 123.025 tons of raw materials are expected to generate profit and revenue averages of USD 547,750 and USD 220,207, respectively. The multiple-product RSC is expected to increase profit by 2.3 times that of a single-product RSC. Finally, the effects of uncertainty in model parameters on the objective functions are examined. In conclusion, the proposed RSC of e-waste can effectively enhance sustainability.

Kazakhstan’s mining sector, a vital pillar of the national economy, generates significant volumes of waste. This waste has been found to hold considerable residual value, presenting a substantial opportunity for resource recovery and economic benefit. To unlock this value, establishing efficient reverse logistics operations is fundamental, as it enables the recovery, recycling, and reuse of materials in a cost-effective and sustainable manner. This paper introduces a conceptual optimization framework tailored to Kazakhstan’s mining industry to explore the feasibility of reverse supply chain processes. The implementation of strategies informed by this model can improve resource utilization, reduce environmental impact, and deliver long-term economic benefits. The study also identifies potential challenges to adoption and suggests pathways for further refinement of the model to adapt to the evolving needs of Kazakhstan’s mining sector. The model provides a robust analytical foundation to support discussions on developing a holistic strategy for waste management in the sector. It offers key insights into optimizing waste handling, advancing material recovery technologies, and promoting collaboration between public and private stakeholders. By aligning these insights with the regulatory and economic landscape of Kazakhstan, the model serves as a reference point to shape a broader national framework. The outcomes of this study contribute to the achievement of Sustainable Development Goals (SDGs) 9 and 12 by promoting industrial innovation, resource efficiency, and responsible production practices within Kazakhstan’s mining sector.

This study aims to provide a global bibliometric review of scholarly research concerning the drivers and constraints in the domain of remanufacturing, which also seeks to provide a blueprint of the intellectual structure and thematic evolution, along with collaboration patterns in this important area of sustainability. This study reviews 1,162 publications from Scopus’s 2015–2025 database, employing bibliometric methods using VOSviewer and Harzing’s Publish or Perish software. This study measures the trends in publications, authorship, subject areas, and keyword co-occurrence networks. The results show an exponential increase in research output since 2019, with Environmental Science and Engineering dominating the publications. Research output stems from the drivers which include the absence of policy and regulatory support, economic incentives and profitability, sustainability and resource efficiency, market demand and consumer behaviour, and technological improvement. The constraints of research output include consumer perception and acceptance, high initial investment and financial viability, lack of skilled workforce, product design and technical obstacles, and reverse logistics and supply chain uncertainty. Research also shows the strong interdisciplinary nature of the field. The primary focus of research is still concentrated in Europe and East Asia. By integrating ten years of worldwide research, this study aims to create a systematic evidence base for academics and practitioners. In closing, it advocates for research on remanufacturing to be more inclusive, context-sensitive, and transdisciplinary so that remanufacturing can develop as a scalable, equitable, and transformative component of the circular economy.

The retail business in South Africa contributes significantly to national GDP and has undergone fast changes in logistics and supply chain processes, making effective logistics management critical to cost reduction and profitability. This study investigates the impact of reverse logistics, warehousing, and supply chain networks on logistics service quality, as well as how logistics service quality influences overall supply chain effectiveness in the retail sector. A quantitative study design was used, with data collected from 300 respondents in Gauteng, including managers, departmental personnel, and supply chain professionals. To validate the hypothesised associations, the data were analysed with descriptive statistics, exploratory factor analysis, and structural equation modelling. The study found that reverse logistics (β = 0.71) and supply chain networks (β = 0.20) have a considerable favourable impact on logistics service quality, while warehousing had a minor effect (β = 0.08). Logistics service quality significantly predicts supply chain effectiveness (β = 0.94), highlighting its importance in improving retail logistics performance. These findings imply that the efficacy of reverse logistics systems and the strength of supply chain networks are critical variables in obtaining higher service quality and, eventually, supply chain effectiveness. The report suggests that South African retailers must improve reverse logistics and optimise supply chain network integration to remain competitive, as well as solve warehousing inefficiencies. In practice, retailers should undertake focused training programs, pursue strategic recruitment to improve leadership ability, and invest in modernised storage infrastructure. Furthermore, the implementation of enterprise resource planning (ERP) systems is suggested to increase information flow, coordination, and operational efficiency across logistics functions.

Construction and demolition waste (CDW) constitute a significant environmental and socio-economic challenge, particularly in developing countries where rapid urbanization and inadequate waste management infrastructure exacerbate negative impacts. The construction industry, a major contributor to global pollution, generates a lot of waste, impeding the transition to a circular economy and sustainable urban development. In this context, reverse supply chains (RSCs) present a promising approach to improve CDW management by integrating stakeholders and optimizing resource recovery. This study aimed to review the literature until July 2024 on RSC for CDW and to identify and characterize the main stakeholders involved and their typical activities. Employing a systematic literature review (SLR) methodology, an initial search identified 89 articles in the Scopus, Web of Science, and ScienceDirect databases. After the selection process, 58 articles were retained and analyzed in the subsequent stages of the SLR. The findings reveal a diverse taxonomy of stakeholders, including generators, reclaimers, and those responsible for final disposal, each fulfilling distinct roles within the RSC. Essential activities identified include integration of RSC processes, regulatory compliance, and material recovery, while notable gaps persist in physical and technological infrastructure and environmental training. Theoretically, this study organizes and systematizes fragmented knowledge on RSC for CDW, highlighting underexplored areas such as the allocation of stakeholder responsibilities. Practically, the results underscore the need for strengthened public policies and enhanced collaboration among stakeholders to promote recycling and reuse. By compiling and analyzing current research, this study provides a foundation for future investigations and supports the advancement of circular economy practices in the construction industry.

Reverse logistics (RL) plays a crucial role in promoting circularity and sustainability in supply chains, particularly in the face of increasing waste generation and growing environmental demands. In recent years, machine learning (ML) has emerged as a strategic tool to enhance processes, decision-making, and outcomes in RL. This article presents a systematic review of ML applications in reverse logistics, highlighting trends, challenges, and research opportunities. The analysis covers 52 articles retrieved from the Scopus and Web of Science databases, following the PRISMA protocol. The results show that the most frequently employed techniques are supervised models, followed by unsupervised methods and, to a lesser extent, reinforcement learning. The main ML applications in RL focus on return and waste generation forecasting, process optimization, classification, pricing, reliability assessments, and consumer behavior analysis. The studies examined predominantly use traditional evaluation metrics, such as MAPE and F1-score, while few consider multidimensional indicators encompassing long-term social or environmental impacts. Key challenges identified include data scarcity and quality, inherent uncertainties in reverse supply chains, and the high computational cost of models. This article also points to research gaps concerning metadata standardization, the absence of public benchmarks, model explainability, and the integration of ML with simulations and digital twins, indicating pathways toward more robust, transparent, and sustainable RL.

A Reverse Supply Chain Model with Modern Technology Dependent Production Rate and Low-Carbon Emission Environment

Copper is a critically important metal for economic security, and its supply chain is influenced by various factors, particularly market prices. This paper aims to uncover the impact of high uncertainty in copper prices on the copper supply chain (CSC) configuration and propose strategies for CSC construction. To achieve this goal, this study presents a closed-loop supply chain (CLSC) network, simulates copper market volatility using the geometric Brownian motion (GBM) model, and establishes a two-stage stochastic programming (TSSP) model. An empirical study was conducted using geographical and economic data of the CSC in the Chinese province of Hunan. The research results indicate that there is a threshold in copper prices that can lead to the construction of a reverse supply chain (RSC). However, significant fluctuations in copper prices introduce uncertainty into the supply chain network configuration. Therefore, policy measures to encourage copper scrap recycling should be implemented to maintain the safety of the CLSC during market instability. The proposed modelling framework for addressing fluctuation factors in supply chain design has been validated and can be promoted to other similar industries affected by markets.

Integrating blockchain with digital product passports for managing reverse supply chain

Technological advancement and the obsolescence of electronic equipment have significantly increased the generation of electronic waste (e-waste), with serious environmental and social impacts. The aim of this study is to propose a management and control model that integrates governance principles and current environmental legislation, in order to improve companies’ environmental performance by incorporating the concept of Life Cycle Assessment (LCA) into the sustainable management of e-waste. The research adopts a qualitative methodology, based on bibliographic and documentary review. Initially, existing models in the academic literature on e-waste were reviewed, along with an examination of how organizational models for the reverse supply chain have been disseminated. Two industry leaders—Apple® and Samsung®—were selected for analysis. Subsequently, a management tool and evaluation protocols were proposed to classify organizations according to their level of sustainable practices, using the Control Objectives for Information and Related Technology (COBIT®) framework for IT governance as a reference, due to its wide applicability and global acceptance. As results and contributions, this study presents an adaptation for the reverse e-waste chain, with particular emphasis on smartphone and computer batteries, aiming to provide greater visibility and transparency regarding the sustainability policies adopted. The sustainability metric developed was named the Electronic Waste Innovation and Maturity Model (MILE). The study also seeks to advance academic and scientific knowledge by encouraging further research and debate on the need for regulations, the adoption of structured governance and reverse logistics practices that generate environmental and institutional benefits, while at the same time fostering innovation, transparency, and responsible cooperation in managing electronic devices after the end of their life cycle. Future research is planned to further develop and validate the proposed instrument.