Closed-loop Supply Chain Research Articles

Sustainable optimisation of SMEs closed-loop supply chain for lithium battery manufacturing

Maintaining the sustainability of small and medium-sized enterprises (SMEs) supply chain has positive impact on society. Under the ripple effect, the vulnerability of the SMEs supply chain and the collaboration uncertainty of participants have potentially negative impact on the sustainability that cannot be ignored. We consider the closed-loop SMEs supply chain network design based on the risk propagation to improve the triple sustainability. The basis of the simulation model structure is a bi-level multi-objective mixed-integer linear programming model that aims to maximise triple sustainability, and an improved dynamic non-dominated genetic algorithm (DNSGA2) is designed to solve the problem. An SMEs supply chain for closed-loop manufacturing of lithium batteries in China was considered. The results show that the centralised SMEs supply chain preform better when the supply-demand imbalance, and the distributed network structure is preform better in maintaining sustainability when manufacturer capacity imbalances. Supply chain managers should develop more flexible strategies based on the structure of downstream demand, increasing upstream manufacturers' participation to enhance their viability and improve the sustainability of the supply chain.

Navigating the Challenges and Seizing Opportunities in Implementing Closed-Loop Supply Chains

Closed-Loop Supply Chains (CLSCs) present a transformative solution for industries seeking sustainability by reintegrating returned products through recycling, refurbishment, and remanufacturing, reducing waste and dependency on added resources. While offering substantial benefits, CLSC adoption faces challenges, including high infrastructure costs, complex reverse coordination, and inconsistent regulatory support, which hinder widespread application. Through a mixed-method approach using surveys and case studies, this study reveals barriers such as financial constraints and operational restructuring needs, while highlighting enablers like digital tools (e.g., blockchain, IoT) that enhance efficiency and transparency. Furthermore, it emphasizes the critical role of regulatory incentives (subsidies, tax breaks, and extended producer responsibility mandates) and strategic partnerships that pool resources and share risks, essential for small and medium-sized enterprises (SMEs) aiming to implement CLSCs effectively. By proposing a practical CLSC framework, informed by empirical data, this research provides actionable insights for businesses to embrace circular economy principles, aligning environmental responsibility with corporate resilience, profitability, and consumer expectations. CLSCs, therefore, are not only an environmental solution but also a strategic opportunity that addresses sustainability imperatives while meeting regulatory requirements and advancing competitive advantage.

Special Issue on Design and Manufacturing for Environmental Sustainability

This is the seventh special issue on Design and Manufacturing for Environmental Sustainability. As the first special issue on the topic was issued in 2009, the topic has a fifteen-year history in this journal. Environmental sustainability was recognized as important for manufacturing even at that time, which is why the special issue was started in this journal. The seriousness of this topic has been increasing not only in Europe but also in Japan and other countries. A recent critical trend has been the way in which companies’ attitudes toward this issue, including their positions on carbon neutrality, a circular economy, and biodiversity, determine their value. Furthermore, particularly striking trend is the promotion of various policies to realize a circular economy, including the adoption of international standards for a circular economy and new eco-design regulations in Europe. These movements indicate the need to transform production and consumption in society as a whole beyond the boundaries of individual companies and industries. The seventh special issue contains seven well-written papers. The papers cover the following topics: - Circular economy - Life cycle design and management - Environmentally conscious design of products and services - Low-energy and low-emission manufacturing - Closed-loop supply chain management - Sustainable consumption and production From the fifteen-year history of this special issue, we have been able to learn viewpoints specific to the series in this journal. Most of the papers, revised and enhanced in response to the editor’s invitation, were originally presented at EcoDesign 2023, the 13th International Symposium on Environmentally Conscious Design and Inverse Manufacturing, held in Nara, Japan. The editor sincerely thanks the authors and reviewers for their contributions in making this special issue possible. We hope that these articles encourage further research on design and manufacturing for environmental sustainability.

Review of Uncertainty, Carbon Emissions, Greenness Index, and Quality Issues in Green Supply Chains

The ability of closed-loop supply chains (CLSC) and reverse logistics (RL) to improve the triple bottom line (economic, social and environmental values) has increased the development of design and management models for CLSCs and RL. Consequently, there exists an extensive body of literature dedicated to exploring these supply and logistics issues. This paper reviews recent and relevant literature on CLSC and RL with an emphasis on uncertainty, carbon emissions, greenness index, return product quality and reliability considerations. The selected references are organized, reviewed, and analyzed to establish valuable mapping to highlight major findings. Finally, the outcomes are synthesized, and the primary research gaps are emphasized, pointing toward potential avenues for future investigation. These findings reveal that research efforts must be directed towards the development of multi-criteria greenness indices and multi-objective robust optimization models for uncertain quality and reliability of returns.

Integrated multi-manned disassembly line balancing problem with reverse supply chain design strategies by considering lot sizing

ABSTRACT Due to strict governmental regulations, manufacturers have increasingly focused on recovering end-of-life (EoL) products through disassembly lines, aiming to achieve economic benefits while addressing the environmental aspects of supply chain sustainability. Disassembly line balancing (DLB) has become a key challenge for enterprises seeking to perform environmentally conscious manufacturing as part of a closed-loop supply chain policy. Therefore, designing a sustainable closed-loop supply chain requires analyzing interrelated problems by focusing on strategic-, tactical-, and operational-level decisions simultaneously. This study introduces an integrated problem that addresses multi-manned DLB, lot sizing, and reverse supply chain (RSC) design problems. To mathematically represent the problem, a generic optimization model is developed to minimize overall costs, including station opening, inventory holding, shortage, transportation, and collection center/facility opening costs. This study addresses several research questions to explore the impact of distribution strategies (centralized and decentralized) on multi-manned DLB and lot size decisions within the context of reverse supply chain design.

Power Battery Recycling Model of Closed-Loop Supply Chains Considering Different Power Structures Under Government Subsidies

With the rapid growth of the electric vehicle industry, the recycling of power batteries has attracted significant attention. In light of current circumstances, the question of how the government can incentivize relevant stakeholders to actively engage in recycling and improve its efficiency has become increasingly pressing. In this context, this study analyses and develops four closed-loop supply chain recycling models to investigate how different government subsidy recipients under varying power structures influence recycling efficiency, profitability, and the overall supply chain structures. The following conclusions are derived from numerical simulations: (1) Government subsidies serve to elevate recycling prices, expand profit margins, and consequently boost the volume of recycled batteries, thus incentivizing corporate engagement in recycling initiatives. (2) When the processor assumes the role of the leader in the Stackelberg game framework, it can maximize the overall efficiency and profitability of the supply chain. (3) The sensitivity coefficient and the competition coefficient are closely interrelated, exerting opposing impacts on the recycling decision made by enterprises. (4) The supply chain leader plays a crucial role in ensuring orderly supply chain development, with government subsidies of the supply chain being transmitted to its members through the leader. Consequently, this study offers a theoretical foundation for the government to enhance policy-making and for enterprises to make informed decisions. It also holds significant practical relevance in addressing the challenges associated with power battery recycling.

Global sustainable closed-loop supply chain considering Incoterms rules and advertisement impacts

Industrial information integration plays a crucial role in modern supply chains by ensuring the smooth flow of data across all stages, including recovery, recycling, and disposal, which is essential for the successful implementation of a closed-loop supply chain (CLSC) model. Building on this, our paper addresses a global CLSC problem by incorporating International Commercial Terms (Incoterms) and international transportation modes, bridging global supply chain operations with sustainability criteria. This innovative approach advances the development of a globally sustainable CLSC by focusing on the integration of economic, environmental, and social factors, i.e., the triple bottom line of sustainability. Specifically, we address environmental concerns through the introduction of carbon taxation and enhance social sustainability by exploring the impact of advertising on customer satisfaction. To further refine this model, we classify customers based on their sustainability engagement and apply a fuzzy programming approach to account for uncertainty in customer demand influenced by advertising. To solve this complex global CLSC model, we conduct a thorough analysis of constraints and develop a robust Lagrangian relaxation reformulation. While the initial solution may result in infeasibility, we propose a heuristic algorithm that ensures feasible solutions. Our efficient Lagrangian-based heuristic, incorporating an adaptive strategy, is capable of solving large-scale networks with an approximate 10% optimality gap. Ultimately, this research provides both a comprehensive framework for practitioners to improve the environmental performance and global operations of their supply chains, as well as significant theoretical contributions to the field of industrial information systems.

Pride or Guilt? Impacts of Consumers’ Socially Influenced Recycling Behaviors on Closed-Loop Supply Chains

Problem definition: Social influenced emotions of pride and guilt have been identified by the environmental psychology (EP) literature as crucial drivers impacting recycling behavior, but they have mostly been overlooked in operations management (OM) research. In contrast, EP studies often ignore firms’ operational decisions. We analyze the impacts of both social influence and firms’ operational decisions to provide a comprehensive understanding of consumers’ recycling behaviors, which is essential for realizing remanufacturing’s full potential. Methodology/results: We consider a closed-loop supply chain consisting of a manufacturer selling a single product to a consumer community. Consumers’ recycling behavior depends on both the recycling reward offered by the manufacturer, as well as intrinsic and socially influenced pride (guilt) from recycling (not recycling). We develop an evolutionary game to model consumers’ recycling behavior and characterize the resulting equilibrium recycling rate, which is then integrated into the manufacturer’s decision problem. We characterize the manufacturer’s optimal strategy and the equilibrium recycling rate in four distinct regions defined by both the product’s overall difficulty of remanufacturing and the underlying strengths of consumers’ socially influenced pride and guilt. We show that in settings where the product has a moderately high difficulty of remanufacturing and consumers have stronger socially influenced pride than guilt, the manufacturer optimally induces an interior recycling rate. In such scenarios, there exist win-win pathways in using social influence–based interventions to increase both the manufacturer’s profit and the recycling rate. However, misalignment may occur when consumers substantially care for the product’s recyclability. Managerial implications: This study bridges sustainable OM and EP literature by analyzing how consumers’ socially influenced emotions of pride and guilt affect a manufacturer’s optimal decisions, profits, and the resulting recycling rate. We provide important insights for designing effective and efficient social influence–based interventions to improve recycling rates. Funding: W. Chen was supported by the National Natural Science Foundation of China [Grant 71902017], and C.-L. Tseng was supported by the University of New South Wales UNOVA Knowledge Hub. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2023.0721 .

A Stochastic Sustainable Closed-Loop Supply Chain Networks for Used Solar Photovoltaic Systems: Meta-Heuristic Comparison and Real Case Study

This research presents a novel approach to setting up a sustainable Closed-Loop Supply Chain (CLSC) network for used solar photovoltaic (PV) systems, addressing end-of-life product waste from solar panel installations and manufacturing centers. The model accounts for uncertainties in PV systems and aims to efficiently collect, refurbish, and recycle used solar PV systems, promoting a circular and environmentally responsible waste management strategy. The supply chain network comprises vendors, collection centers, hybrid centers, distribution centers, and manufacturing centers, with objectives to maximize total profit, minimize environmental risk, and maximize service levels by demonstrating the profitable reuse of used solar photovoltaic systems by manufacturers. The epsilon-constraint method is utilized to handle the model's multi-objectiveness and identify Pareto optimal solutions. A case study in Iran is conducted to validate the methodology's performance, comparing results obtained from three meta-heuristic methods: Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO), and Multi-Objective Gray Wolf Optimization (MOGWO). The average error rates are 0.0358 for MOGWO, 0.1248 for MOPSO, and 0.2066 for NSGA-II. Sensitivity analysis highlights the significant impact of demand variations on all objective functions. Lastly, the numerical results are discussed to provide managerial insights for informed decision-making.

Repairing smarter: Opportunistic maintenance for a closed-loop supply chain with spare parts dependency

Repairing smarter: Opportunistic maintenance for a closed-loop supply chain with spare parts dependency

Electric vehicle battery closed-loop supply chain pricing and carbon reduction decisions under the carbon cap-and-trade and reward-penalty policies

Recycling end-of-life electric vehicles (EVs) batteries to conserve resources and reduce carbon emissions has obtained a great deal of concern. This paper studied how carbon cap-and-trade and reward-penalty measures jointly impacted EV battery pricing and decarbonization strategies. Three recycling modes covering single-participator, mixed-participator, and joint recycling are established. Optimal pricing and carbon mitigation strategies, total revenue, and recycling percentage are solved and compared. The dynamic effects of target recycling percentage and rewards and punishments on total revenue and recycling percentage are analyzed by numerical examples. Results show that: (1) The factory price, selling price, collection price, and carbon emission mitigation scale of power batteries are affected by cap-and-trade and reward-penalty mechanisms; (2) Reward-penalty can improve both total revenue and recycling percentage; (3) The cap-and-trade mechanism optimizes the total revenues, showing that the total revenue increase with the increasement of carbon quota and carbon price, while the increase of carbon price leads to worse recycling percentage; (4) The supply chain performance under different recycling modes is affected by policy intervention, and the joint recycling mode is better.

Risk-averse supply chain management via robust reinforcement learning

Classical reinforcement learning (RL) may suffer performance degradation when the environment deviates from training conditions, limiting its application in risk-averse supply chain management. This work explores using robust RL in supply chain operations to hedge against environment inconsistencies and changes. Two robust RL algorithms, Qˆ-learning and β-pessimistic Q-learning, are examined against conventional Q-learning and a baseline order-up-to inventory policy. Furthermore, this work extends RL applications from forward to closed-loop supply chains. Two case studies are conducted using a supply chain simulator developed with agent-based modeling. The results show that Q-learning can outperform the baseline policy under normal conditions, but notably degrades under environment deviations. By comparison, the robust RL models tend to make more conservative inventory decisions to avoid large shortage penalties. Specifically, fine-tuned β-pessimistic Q-learning can achieve good performance under normal conditions and maintain robustness against moderate environment inconsistencies, making it suitable for risk-averse decision-making.

Demand Information Forecasting and Sharing in a Remanufacturing Closed‐Loop Supply Chain

ABSTRACTWe delve into the incorporation of demand information forecasting and the subsequent information sharing in a closed‐loop supply chain (CLSC). We consider the competition between an original equipment manufacturer (OEM) and an independent remanufacturer (IR). The OEM autonomously determines whether to forecast demand information and further considers whether to disseminate the realized demand signal to the IR. We find that the IR adopts either a partial‐ or a full‐remanufacturing strategy to compete with the OEM. The OEM shares negative demand signals with the IR, as such signals decrease the retail prices and increase the production quantity of all‐new products. Additionally, the sharing of negative demand signals helps alleviate the cannibalization effect caused by the introduction of remanufactured products. When examining the optimal sharing strategy in equilibrium, the OEM only invests in forecasting demand if the forecasting cost is relatively low. Furthermore, the numerical studies reveal that, in equilibrium, the OEM does not necessarily benefit from possessing more precise demand information. Additionally, we assess the influence of consumers' environmental awareness on the production decisions of both companies. The findings indicate that heightened environmental awareness prompts the IR to adopt a full‐remanufacturing strategy, and the information management strategies remain robust.

A closed-loop dual-channel supply chain network for leather products: An integrated simulation optimization clustering approach

The leather industry is pivotal to the economic development of certain countries; however, it also poses significant environmental challenges. Thus, this study aims to design a closed-loop leather supply chain network that incorporates waste recycling and product regeneration processes. In light of the growing prevalence of both in-store and online shopping, the concept of a dual-channel supply chain is examined. Furthermore, as advertising through traditional and social media continues to expand, this research uniquely investigates the impact of two advertising modalities—SMS and social networks—alongside the design and layout of retail environments, considering their effects on product sales within the supply chain context. Additionally, outlet stores are integrated into the model to facilitate the sale of products that may become outdated over time, thereby enhancing the model's real-world applicability. To achieve this, a multi-product, multi-period mathematical model is developed to minimize costs and maximize customer responsiveness in both forward and reverse supply chain flows. The K-means clustering method is employed to categorize customers based on recency, frequency, and monetary (RFM) features. Through simulation, demand parameters are derived for each customer cluster across various scenarios. Moreover, the Aghezzaf approach is utilized to address scenario-based uncertainties within the model, and the proposed multi-objective model is solved using the Augmented Epsilon constraint method. A real-world case study is conducted to apply the proposed model, and critical parameters are examined through sensitivity analysis to validate its effectiveness. The findings suggest that incorporating return flows into the supply chain can significantly enhance both producer profitability and customer responsiveness regarding leather products.

Design and Site Selection of Reverse Logistics Network for Iron and Steel Enterprises from the Perspective of Green Supply Chain

The iron and steel industry is not only one of the most important components of China's national economy, but also a typical resource-and-energy-intensive industry. Under the background of "Carbon Peaking and Carbon Neutrality Goals", it is of great significance for the iron and steel industry to improve the green closed-loop supply chain and develop circular economy. From the perspective of green supply chain, this paper puts forward the three-level network structure of waste steel reverse logistics based on the present situation of waste steel recycling in China, and uses k-means clustering algorithm and accurate center of gravity method to select locations for the primary and secondary nodes. The purpose of this paper is to provide a basis for iron and steel enterprises to carry out network optimization of reverse logistics.

Blockchain in Closed-Loop Supply Chain: A Systematic Review and Future Research Agenda

This article investigates the potential applications of blockchain technology (BCT) in a closed-loop supply chain (CLSC) using a systematic review of the literature. As a result, this study has used the Scopus database for a detailed search strategy to identify relevant studies on different applications of BCT in the context of CLSC. This article has employed a theme analysis approach and focuses specifically on peer-reviewed documents. Based on the themes and sub-themes, the CLSC literature has been divided into four clusters: ‘Barriers and enablers of blockchain implementation’, ‘Blockchain application in sustainability’, ‘Blockchain application in enabling soft supply chain dynamics’ and ‘Blockchain application in addressing inventory and other problems’. These four clusters are analysed to present future research areas on BCT applications in a CLSC, using a ‘results-systematization framework’. This study will provide valuable insights and understanding to researchers in advancing BCT-CLSC research. Moreover, practitioners and policymakers, who are interested in the implementation and execution of firm-level BCT in CLSC, will be greatly benefitted in terms of sustainable and efficient CLSC operations.

Blockchain-enabled supply chain finance model: a study of the dual-channel closed-loop supply chain of electronic products

Blockchain-enabled supply chain finance model: a study of the dual-channel closed-loop supply chain of electronic products

Supply Chain Management for Electric Vehicles: Challenges, Opportunities, and the Path to Scalability

Abstract—As electric vehicles (EVs) gain momentum as a solution to reduce greenhouse gas emissions and fossil fuel dependence, their supply chains become increasingly complex, particularly for lithium-ion batteries (LIBs), which are crucial for EV performance, safety, and longevity. This paper reviews existing literature on several key aspects of the EV supply chain, focusing on thermal management systems (TMS), lifecycle environmental assessments, closed- loop supply chains (CLSCs), and the impacts of global disruptions like the COVID-19 pandemic. Research by Murugan et al. (2022) underscores the importance of improving TMS for LIBs, noting that experimental validation remains sparse despite advances in numerical modeling. In addition, Rüdisüli et al. (2022) highlight the environmental benefits and limitations of different mobility technologies, emphasizing the need for advancements in seasonal energy storage systems. Gu et al. (2018) discuss the challenges of establishing profitable CLSCs for EV batteries, where reuse improves sustainability, but recycling faces economic hurdles. Finally, the analysis of Wen et al. (2021) on the COVID-19 pandemic’s impact shows significant disruptions to the Chinese EV market and raises concerns about the global EV supply chain’s resilience. This review identifies gaps in the literature, such as the need for real-world validation of models, exploration of alternative battery chemistries, and improved supply chain governance, all of which are essential for advancing the EV industry toward sustainability. Keywords—Electric Vehicles, Supply Chain Management, Lithium-ion Batteries, Thermal Management Systems, Closed-Loop Supply Chains, Sustainability, Greenhouse Gas Emissions, Lifecycle Assessment, Resource Dependencies, Circular Economy.

Optimization modelling for a sustainable closed-loop supply chain network using IoT: multiobjective metaheuristic algorithms

Optimization modelling for a sustainable closed-loop supply chain network using IoT: multiobjective metaheuristic algorithms

A sustainable semiconductor supply chain under regulation

Modern life would not exist without semiconductors as all electronic components used in computers, telecommunications, health care, transportation, and energy systems are equipped with chips. To examine both backward and forward activities in semiconductor industry, this paper formulates the industry as a closed-loop supply chain. It articulates how old semiconductors are processed and recycled to manufacture new silicon and chips, and examines the impact of a commonly applied subsidy scheme on the performance of semiconductor firms which operate in upstream and downstream layers of the industry. Specifically, the proposed semiconductor supply chain involves (i) a return function sensitive to monetary incentives; (ii) a subsidy legislation rewarding end-users for recycling; (iii) upstream industry where silicon is produced using virgin and scrap materials; (iv) downstream industry in which semiconductor manufacturers (such as TSMC, Samsung, Intel) buy silicon and other materials, hire workers, and then produce and sell chips. We characterize Stackelberg equilibrium silicon and semiconductor prices and outputs and calibrate model parameters using actual data to quantify the effects of subsidy and collection channels on silicon and semiconductor firms’ performance. We find that the subsidy scheme neither distorts firms’ strategies nor causes any inefficiency for the semiconductor industry. It stimulates circular economy activities and provides economic and environmental benefits.