Closed-loop Supply Chain Research Articles

Optimal pricing and collection decisions in a two-period closed-loop supply chain considering channel inconvenience

Improving recovery efficiency is a key concern for collectors in a closed-loop supply chain (CLSC) with remanufacturing, as customers often consider the inconvenience of recycling channels when returning used products. This issue profoundly affects collectors’ capacity to recover materials. In a two-period CLSC with remanufacturing, including a manufacturer and a retailer, we develop game-theoretical models in the centralized and decentralized scenarios and compare the optimal solutions, consumer surplus, social welfare and environmental impact of different models through analytical and numerical analysis. Our aim is to examine firms’ dynamic pricing strategies and collection investment decisions by considering customers’ perception of channel inconvenience. There are four main findings. Firstly, in the centralized model and the retailer collection model, the decision-maker lowers the retail price in the first period. However, in the competitive collection model, the manufacturer and the retailer raise the wholesale and retail prices in the first period, respectively. Secondly, in the retailer collection model, as the recycling revenue increases, the manufacturer, although not involved in collecting, the profit also increases due to the free-rider behavior. Thirdly, in the competitive collection model, when the remanufacturing cost savings is relatively high, the collection investment of the manufacturer is much larger than that of the retailer, resulting in the retailer failing to collect any product and giving up collecting. Finally, the collection competition improves the total collection rate and environmental performance but reduces the profit of the manufacturer and the retailer, as well as the consumer surplus and social welfare. Therefore, we design a two-part tariff contract to coordinate the decentralized model and effectively improve the performance of the supply chain.

Cooperative Recycling Strategy for Electric Vehicle Batteries Considering Blockchain Technology

The rapid growth of new energy vehicle has led to an urgent need for efficiently recycling used power batteries. In addition, battery suppliers can adopt blockchain technology to enhance efficiency in recycling. This article constructs a closed-loop supply chain (CLSC) consisting of a power battery supplier, a new energy vehicle manufacturer, and a third-party recycler, and studies the optimal collaborative recycling mode considering blockchain adoption and recycling competition. Firstly, we identify five alliance recycling models and derive the equilibrium results for each model. Secondly, we use the Shapley value mechanism in cooperative game to allocate alliance profits reasonably. Some interesting conclusions are obtained. (1) The supplier-manufacturer alliance is the optimal recycling strategy under moderate recycling competition, which challenges the common assumption that the major-alliance dominates others in CLSC. (2) Alliances, especially manufacturer-3rd party alliance, are not always beneficial to the CLSC, but are beneficial under low recycling competition and blockchain cost. (3) The proposed four stable profit allocation cases can coordinate the CLSC, where all alliance members achieve higher profits than the decentralized model, with the supplier gaining the largest profit share and the manufacturer obtaining the most profit increment.

A dynamic analysis of a green closed-loop supply chain with different on-line platform smart recycling and selling models

Global warming and waste product recycling have become increasingly serious. Green innovation of a closed-loop supply chain (GCLSC) and selection of on-line platform recycling and sales models need to be solved as a matter of urgency. To achieve this purpose, dynamic influences of green innovation, platform smart marketing, and recycling investments on goodwill are considered. Dynamic game models are used to solve the equilibrium solutions and optimal trajectories under different models, and influences of commission rates on the profits and key variables are compared via numerical simulations. The results show that the evolution paths of goodwill under the four decision models all descend at first, then stabilize; the optimal strategy can be selected based on the intervals of sales and recycling commission rates. Under the dual-agency model (agency selling and platform agency recycling (Model AP)), the higher the sales commission rate (SCR) is, the more likely the manufacturer chooses the reselling and platform agency recycling (Model RP), which, however, may lead to insufficient green innovation investment. The higher the RCR, the greater the platform profit when selecting agency selling. The system profit first increases, then decreases with growing sales commission, and Model AP represents the optimal strategy. The research offers reference for the selection of operation models and investment decision, is conducive to improving the enterprise goodwill, and promotes the sustainable development of the GCLSC.

Assessing the economic and environmental performance of a closed-loop supply chain for waste tires: an industrial case study.

Recovery strategies for end-of-life (EoL) and end-of-use (EoU) products, such as reuse, remanufacturing, and recycling, present opportunities to enhance profitability and lower emissions while fostering new business prospects. However, significant uncertainties and stochasticity affect the quantity and quality of returned waste tires, costs associated with used tires and the retreading process, and the selling prices driven by second-hand market dynamics. This paper investigates the economic and environmental performance of a closed-loop supply chain (CLSC) for waste tire retreading and recycling considering the impact of these uncertainties using a Monte Carlo simulation-based methodology. The proposed methodology is implemented on an industrial case study in the United Arab Emirates (UAE) for quantifying the impact of uncertainties involved in the CLSC for tire retreading and recycling large tires of the 12R24 type, which are extensively used by buses and trucks in the UAE. The findings reveal that for an average of 13,200 tires reaching their EoL, the processes of retreading and recycling yield an average profit of $ 487 K. Furthermore, these initiatives are expected to result in the reduction of an average of 1457 tons of CO2 emissions. A scenario analysis is conducted to evaluate the impact of improvements in key operational parameters on the CLSC performance. Consequently, all stakeholders engaged in tire retreading would benefit by reducing costs, generating higher profits, and reducing emissions while creating new business opportunities.

Blockchain’s role in operation strategy of power battery closed-loop supply chain

With the rapid development of the electric vehicle industry, the issue of recycling retired power batteries is becoming increasingly prominent. Considering the adoption of blockchain technology to enhance information traceability for retired power batteries, we construct three closed-loop supply chain decision-making models: a supply chain that does not adopt blockchain technology, a manufacturing enterprise that independently bears the input cost of blockchain technology, and a scenario which both manufacturing and selling enterprises jointly bear the blockchain technology input costs. Through the comparative analysis of the equilibrium solutions of these models, including the profits of each supply chain member, consumer surplus, environmental impact, and social welfare, it is concluded that the level of information traceability increases with the increase of the blockchain technology input cost-sharing ratio λ by the selling enterprise. However, there is a threshold for λ and λ cannot be infinitely increased. The profits of both manufacturing and selling enterprises increase with the adoption of blockchain technology, yet the ladder-utilizing enterprise achieves the highest profits when not adopting blockchain technology. Furthermore, the adoption of blockchain technology can increase consumer surplus and social welfare while reducing the impact on the environment. These studies provide theoretical guidance on both economic and social environment for the operation decision of each member in the closed-loop supply chain of power batteries.

Dynamic game analysis of a green closed-loop supply chain with different on-line platform operation models

Dynamic game analysis of a green closed-loop supply chain with different on-line platform operation models

A Multi-objective Robust Scenario-based Stochastic Chance Constrained Programming Model for Sustainable Closed-loop Agri-food Supply Chain

The agri-food supply chain management plays a crucial role in ensuring the interests of supply chain components and food security in society. Additionally, due to the nature of agri-food products, sustainability dimensions have always been of concern to organizations engaged in this field. The importance of the timely and quality provision of agri-food products has doubled after the global crisis. Therefore, this study focuses on optimizing and analyzing the sustainable multi-objective closed-loop supply chain network for agri-food products, with a case study on the canned food under uncertainty. Strategic and operational decisions and other features are considered to achieve more accurate results. To address the various dimensions of sustainability, the problem is considered as a four-objective one, aiming to maximize the use of available production throughput for factories, maximize job opportunities created, minimize supply chain costs, and ultimately minimize unmet demands. The carbon cap and trade mechanism is used to control greenhouse gas emissions in the supply chain network. A robust scenario-based stochastic chance constrained programming approach is employed to deal with the uncertainty, and also validation is performed using various criteria. Moreover, an augmented ε-constraint optimization approach is used to solve the multi-objective problem and achieve Pareto optimal solutions. Finally, sensitivity analysis is employed to prepare for potential changes in some problem parameters.

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

Adopting a closed-loop supply chain enhances spare part provisioning through repair, remanufacturing, and recycling. However, poor maintenance of components can have severe consequences. Unlike traditional opportunistic maintenance methods that assume regular inspections or precise degradation monitoring, we propose a model that leverages historical repair data to replace worn components preventively. It considers the real-world workflow where parts are often restored only to a functional level. We study maintenance strategies for repeatedly repaired multi-component systems by applying preventive operations only during corrective repairs. Our model considers component ages, failure time distributions, and structural and economic dependencies, favoring collective over individual replacements for cost efficiency. Stochastic dependencies are mapped using Nataf transformation for component subsets, and a genetic algorithm identifies optimal maintenance strategies to reduce long-term operational costs by balancing maintenance against potential failure penalties. We demonstrate the effectiveness of our approach with a case study on MRI power supply machines, showing that preventive actions can cut early life failures by up to 50% and extend useful life by over a year. Sensitivity analysis reveals that logistic costs, interest rates, and planning horizons influence decisions. Opportunistic maintenance can reduce logistic costs and increase the lifetime of spare parts after repair. Integrating stochastic dependency is computationally efficient for industrial systems and can help predict failures more accurately.

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.

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.

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.

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.

Global sustainable closed-loop supply chain network 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 .

On cost and revenue in circular supply chains: Where to close the loop?

Environmental sustainability is a main research topic in supply chain management, including sustainable, green, closed-loop, and circular supply chain management concepts. A distinctive feature in concept evolution is the increase in tiers of a supply chain included in the reuse or recycling loop. However, most research focuses on dyadic or triadic supply chain structures. Where to close the loop, i.e., where to position the recycler, repurposer, remanufacturer, refurbisher, repairer, and/or reuser, in multi-tier supply chains remains largely unanswered. In response, this study assesses cost and revenue sharing by analytically modeling monetary flows in linear and circular multi-tier supply chains using linear and circular supply chain models and cost-profit theory to derive equations describing monetary flows between the supply chain tiers and external entities. Results show that firms upstream of the loop-closer are negatively affected by the reuse of material, which leads to an increasingly negative impact on the total profit of the supply chain the further downstream the loop-closer is positioned. This has important theoretical and practical implications since upstream suppliers may leave circular supply chains for linear ones if no offset mechanism is provided. There is no difference between linear and circular supply chains for tiers downstream of the loop-closer level. This effect is normally not considered in the literature, focusing on shorter supply chain structures where all firms are connected to the loop. The most important findings and implications are: If the loop-closer is positioned near the OEM tier or external customer, the total personnel, assets costs and total profits decrease in the circular supply chain compared to the linear supply chain. If the loop-closer is positioned at the most upstream tier level, the total personnel and assets costs, and total profits increase.

Closed-loop supply chain design considering quantity-dependent price and decentralized local waste management

With the increasingly widespread use of household plastic products, environmental pollution caused by plastic waste has emerged as a severe problem. Despite the efforts of academia and government bodies, plastic recycling rates worldwide remain low. Thus, this study aims at establishing a closed-loop supply chain design model for household plastic recycling. We develop a bilevel optimization model to reflect decentralized decision-making between a manufacturer and public sectors and propose a strategy to obtain optimal solutions. The proposed model considers two critical aspects of the problem: decentralized local waste management and quantity-dependent price. Numerical experiments are conducted based on real annual operation data, and various managerial insights are derived from sensitivity analyses. Additionally, we recommend various strategies to mitigate potential social conflicts arising from increasing volumes of plastic waste as well as directions for government policy aimed at enhancing the plastic recycling rate.