Closed-loop Supply Chain Management Research Articles

Modeling the Decision and Coordination Mechanism of Power Battery Closed-Loop Supply Chain Using Markov Decision Processes

With the rapid growth of the new energy vehicle market, efficient management of the closed-loop supply chain of power batteries has become an important issue. Effective closed-loop supply chain management is very critical, which is related to the efficient utilization of resources, environmental responsibility, and the realization of economic benefits. In this paper, the Markov Decision Process (MDP) is used to model the decision-making and coordination mechanism of the closed-loop supply chain of power batteries in order to cope with the challenges in the management process, such as cost, quality, and technological progress. By constructing the MDP model for different supply chain participants, this paper investigates the optimization strategy of the supply chain and applies two solution methods: dynamic programming and reinforcement learning. The case study results show that the model can effectively identify optimized supply chain decisions, improve the overall efficiency of the supply chain, and coordinate the interests among parties. The contribution of this study is to provide a new modeling framework for power battery recycling and to demonstrate the practicality and effectiveness of the method with empirical data. This study demonstrates that the Markov decision-making process can be a powerful tool for closed-loop supply chain management, promotes a deeper understanding of the complex decision-making environment of the supply chain, and provides a new solution path for decision-making and coordination in the supply chain.

Forecasting e-commerce consumer returns: a systematic literature review

AbstractThe substantial growth of e-commerce during the last years has led to a surge in consumer returns. Recently, research interest in consumer returns has grown steadily. The availability of vast customer data and advancements in machine learning opened up new avenues for returns forecasting. However, existing reviews predominantly took a broader perspective, focussing on reverse logistics and closed-loop supply chain management aspects. This paper addresses this gap by reviewing the state of research on returns forecasting in the realms of e-commerce. Methodologically, a systematic literature review was conducted, analyzing 25 relevant publications regarding methodology, required or employed data, significant predictors, and forecasting techniques, classifying them into several publication streams according to the papers’ main scope. Besides extending a taxonomy for machine learning in e-commerce, this review outlines avenues for future research. This comprehensive literature review contributes to several disciplines, from information systems to operations management and marketing research, and is the first to explore returns forecasting issues specifically from the e-commerce perspective.

Metaheuristic-driven extended exergy accounting for sustainable closed-loop food supply chain management

In this research, an exergetic mathematical model is proposed for closed-loop food supply chain network design considering economic, environmental, and social aspects. The studded closed-loop food supply chain consists of six echelons, four echelons for forwarding the products (suppliers, factory, distribution centers, and customers), and two echelons for returning the products (collecting centers and disposal centers). The exergetic model is based on the extended exergy accounting method, which calculates the consumed exergy in all six echelons by considering the equivalents of labor and capital exergy. This model aims to minimize both the economic and exergetic costs associated with the food supply chain. To solve the proposed mathematical model, an ensemble global–local search metaheuristic algorithm utilizing a combined whale optimization algorithm (WOA) and simulated annealing (SA), called CWOASA, is proposed. In the CWOASA algorithm, first, WOA is used to search the entire search space. Next, SA is applied to further improve the best solution obtained by WOA. A real dataset of a dairy supply chain is used to evaluate the efficiency of the proposed metaheuristic-driven exergy analysis model and claim its benefits over the existing methods. Simulation results revealed that the proposed method leads to a 6.74% reduction in the total exergy consumption of the supply chain. The proposed methodology offers valuable insights, shedding light on the prospective gains in terms of mitigated environmental impact for each incremental economic expenditure, thus laying the foundation for promising avenues of future research.

Research on Optimization Strategies for Closed-Loop Supply Chain Management Based on Deep Learning Technology

This study explores the integration of deep learning (DL) technology and the guided simulated annealing algorithm (GSAA) to optimize closed-loop supply chains (CLSC) for sustainable development. By applying DL for predictive analysis and GSAA for optimization, the research aims to enhance CLSC operational efficiency and environmental sustainability. The methodology combines a review of the CLSC framework with practical applications of DL and GSAA, aiming to reduce waste, maximize resource utilization, and minimize environmental impact. An experimental comparison of this approach against traditional optimization strategies demonstrates the proposed method's superior effectiveness and efficiency. The findings reveal that the DL-GSAA optimization significantly improves CLSC sustainability and efficiency, with GSAA showing promising convergence properties. This study underscores the importance of advanced technological solutions in achieving sustainable supply chain management, offering practical insights for businesses and supply chain managers.

The circular supply chain: a paradigm shift towards sustainable resource

In light of recent studies, we find that the circular economy has become a key component in corporate strategies to promote environmental sustainability. In this regard, corporations are increasingly adopting the circular economy perspective to review their supply chain management practices in a sustainable manner. This paradigm shift suggests the need for a circular approach to supply chain management, moving from simple efficiency and waste reduction to a philosophy that promotes product redesign, reuse and transformation. The circular supply chain approach involves a number of interlinked elements, including product design for circularity, reverse logistics, remanufacturing (re-manufacturing), recycling and waste management. These components are integrated at different stages of the supply chain with the aim of maximising resource recovery and minimising environmental impact. Particular emphasis is placed on supply chain collaboration, which is considered one of the key drivers of the circular economy and circular supply chains. The analysis of the circular supply chain management concept highlights five dimensions of circular supply chain management: closed-loop supply chain management, reverse supply chain management, remanufacturing supply chain management, recycling supply chain management and industrial symbiosis.

Çok Seviyeli Rekabetçi Kapalı Döngü Tedarik Zinciri Ağ Tasarımı: Karşılaştırmalı Bir Analiz

Kısıtlı doğal kaynaklar ve bunların bilinçsizce tüketilmesi, son yıllarda hammadde yerine atık malzemenin işlenme oranının artmasına yol açmış ve endüstriyel ortamı daha rekabetçi hale getirerek, Tedarik Zinciri Yönetiminin (TZY) dinamiklerini değiştirmiştir. Kullanım ömrü sonu ürün sayısının artması ve bunlarla ilgili çevresel kaygılar, aynı zamanda müşteri baskılarına cevap verebilmek adına lojistiğin tersine çevrilmesine büyük özen gösterilerek Kapalı Döngü Tedarik Zinciri (KDTZ) tasarımı ve optimizasyonu üzerine ilgi artmıştır. KDTZ, geniş bir literatüre sahiptir ve bu çerçevede tedarik zinciri maliyetlerini optimize etmek için pek çok model geliştirilmiştir. Literatürün çoğu tekil tedarik zinciri ile ilgilidir ve mevcut rakip tedarik zincirlerini görmezden gelir. Ancak, günümüzün rekabetçi pazarlarında, tedarik zincirleri birkaç rekabetçi şirket tarafından birbirine entegre şeklinde oluşturulmakta ve daha fazla pazar payı elde etmek için birlikte rekabet ederek çalışmaktadır. Böyle bir ortamda, tedarik zincirleri içinde ve arasında farklı rekabet biçimleri vardır. Bu bağlamda, makale ürün geri kazanımı için bir takım teşviklerle kullanılmış ürünleri iade etme isteğini artırarak sürdürülebilir tüketimi iyileştirmeye çalışan iki üretici, bir toplama&geri dönüşüm merkezi ve müşterilerden oluşan çok seviyeli rekabetçi KDTZ yönetiminde dağıtım ağlarının tasarımı ve optimizasyonu problemini ele almaktadır. KDTZ yönetiminde farklı amaçlara sahip karar vericiler için uzlaşık çözüme ulaşmak için dört farklı Etkileşimli Bulanık Programlama (EBP) yaklaşımı kullanılmış ve sonuçlar analiz edilmiştir.

Multi-Objective Green Closed-Loop Supply Chain Management with Bundling Strategy, Perishable Products, and Quality Deterioration

This study presents a four-objective mathematical model to improve closed-loop supply chain (CLSC) management. The aim of this research is to reduce the costs of the entire chain, risk, emission of pollutants, and time to deliver the product to the customer in uncertain demand condition. In this paper, the NSGAII algorithm is used to solve the model. In this algorithm, among the answers of each generation, a number of them are selected using the two-run tournament selection method. In the binary selection method, the answers are randomly selected from the population, and then a comparison is made between these two answers, and whichever is better is finally selected. The selection criteria in NSGA-II are, firstly, the rank, and secondly, the crowding distance related to the answer. Also, the performance of the NSGA-II algorithm on the same model and data has been compared with the MOPSO algorithm. In the proposed algorithm, if it encounters an impossible solution, it exits the local mode and solves the problem in global conditions. The results show that the proposed method strikes a better balance between discovery and efficiency criteria and avoids falling into local optima. Therefore, in addition to its effectiveness in discovering optimal answers, the genetic-based method has high speed and subsequently, high convergence and diversity rates compared to the particle swarm method. Also, compared to previous methods in the green closed-loop supply chain, the proposed method is better than the modified genetic algorithm, reducing the costs of the chain by about 2.38%.

A closed-loop supply chain operation decision under life cycle: Ecological design, service design and recycling effort perspectives

The commercial, environmental and social value of closed-loop supply chain (CLSC) has been widely recognised in the literature. Enterprises are increasingly aware of the importance of product life cycle management; that is, enterprises conduct CLSC management of the production, use and recycling of products. Existing research lacks research on CLSC operation decision under product life cycle. This paper introduces ecological design, service design and recycling into a CLSC with the manufacturer, retailer and recycler. Stackelberg models considering different leadership structures and service design providers are constructed using game theory, and we use backward induction to solve the game in different cases. Results show that from the system-operating efficiency and total profits maximisation perspectives, the recycler-led is always the most effective. However, for the selection of the optimal service design provider, when the manufacturer (retailer) is the leader, the retailer (manufacturer) providing the service design should be the dominant strategy. When the recycler is the leader, the effect is the same no matter who provides the service design. Finally, we find an interesting conclusion that in the case of retailer provides service design, supply chain members do not always achieve the highest profits under their own leadership structure. The numerical analysis shows that when the consumer’s preference for service design is greater than 6.3, the manufacturer can obtain greater profits under the recycler-led structure, and when consumer’s preference for ecological design is greater than 7.1, the retailer can gain greater profits under the recycler-led structure.

Pricing decisions in a two-period closed-loop supply chain game under asymmetric information and uncertainty

AbstractStrategies to increase sustainability are of growing relevance for supply chains and especially for the management of production processes. In this paper, we build on existing literature in closed-loop supply chain management and consider a two-period game-theoretic model in which product returns are reused in the manufacturing process. In all scenarios, we assume that the return rate of used products is random and not known to the players at the beginning of the planning horizon, thus, they have to deal with uncertainty in period 1. In contrast to existing literature, we will also address the circumstance that the players’ level of information in period 2, after the returns have been realized, can be linked to the collection mode in the supply chain. In Scenario A, the retailer is involved in the collection of the used products and transfers them to the manufacturer, so that symmetric information is available. In Scenario B, on the other hand, the used products reach the manufacturer directly from the customer, so that the manufacturer has an information advantage over the retailer. By comparing these scenarios and a vertically integrated supply chain benchmark case, it becomes clear that, depending on the actual return rate, the presence of private information can be either beneficial or detrimental to the manufacturer. The retailer, on the other hand, can compensate for information disadvantages in most cases over the multi-period planning period due to its position as a Stackelberg leader. Regardless of the amount of a transfer payment offered to it by the manufacturer, it prefers the collection of the goods by the manufacturer itself. These findings contribute to literature on symmetric information, where, for example, a retailer-led collection is preferred (Savaskan et al. Manage Sci 50(2):239–252, 2004) or the decision depends on the amount of the transfer payment (Modak et al. J Clean Prod 171:512–528, 2018). However, we show that cooperation between the players leads to the best results not only economically but also from an ecological point of view.

What is the role of product services in the dual-channel closed-loop supply chain?

With the continuous development of Internet technology and the increasing awareness of environmental protection among consumers, the dual-channel closed-loop supply chain management combining online direct sales channel and retail channel has received more and more attention, however, the existing research has neglected the service research of the dual-channel closed-loop supply chain, so this paper focuses on the service strategy in the dual-channel closed-loop supply chain. In this paper, we propose three service strategy models for dual-channel closed-loop supply chains, including when there is no service provision, after-sales service and recycling service provided by retailers and after-sales service provided by manufacturers and recycling service provided by retailers, compare and analyze the optimal decisions of supply chain members under the three service strategy models, discuss the role of service generated in dual-channel closed-loop supply chains, and propose a service cost-sharing strategy to achieve a Pareto improvement in the effectiveness of a dual-channel closed-loop supply chain. The study finds that service plays a positive role in the dual-channel closed-loop supply chain; the model of manufacturer providing after-sales service and retailer providing recycling service is the best service strategy choice in terms of economic and social benefits; the service cooperation mechanism of service cost sharing can achieve Pareto improvement of the supply chain within a reasonable range.

A waste reduction strategy through autonomation under a closed-loop supply chain management

Currently, apart from manufacturing processes, the remanufacturing of products is also considerably important. Appropriate remanufacturing requires the operation of long-run manufacturing systems. However, in long-run processes, the production system may convert to an ``out-of-control" state due to machine breakdowns. Then, defective products are frequently produced; this increases wastage and disrupts environmental sustainability. In this model, a smart autonomation policy is deliberated for error-free inspection in separating defective products during production. The autonomation policy facilitates waste reduction through remanufacturing. This paper also concentrates on customer awareness and service dependent demand, which directly improves the overall profitability of the system. A discrete investment to reduce setup cost, continuous investment to collect used goods, and cap-and-trade strategy to limit carbon emission are considered to obtain a more realistic model. Classical optimization method is applied for global optimality test of the profit function with respect to cycle length, customer awareness, service investment, discrete investment to reduce setup cost, number of shipments, and container capacities. Numerical testing, sensitivity to total profit in different cost parameters, and comparisons with previous research are explained. Some special scenarios including graphical representations are discussed to prove that a large investment is more beneficial than the cost of specific setup and collection.

Developing a resilient and sustainable non-linear closed-loop supply chain management framework for the automotive sector industry using a gaussian fuzzy optimization based non-linear model predictive control approach

ABSTRACT Efforts to merge sustainability and resilience within the automotive industry’s supply chain models have proven challenging. This paper proposes a novel non-linear closed-loop supply chain management framework tailored to the tire industry supply chain from the automotive sector to address the issue of exploring interrelationships. Framework employs trapezoidal linguistic cubic fuzzy Z-score technique for order of preference by similarity to the ideal solution ranking approach to prioritize resilience strategies to maintain sustainability performance during sudden disturbances. Furthermore, Gaussian fuzzy optimization-based non-linear model predictive control acts as a feedback controller to integrate sustainability and resilience by providing a stable output based on the objective function related to sustainability dimensions. An experimental study assesses the impact of resilience strategies on total supply chain costs, highlighting significant cost savings. Adopting strategies like multiple sourcing, information sharing, and improved design quality of the supply chain keeps total expected costs optimal for various sustainability levels.

Optimizing Green Strategy for Retired Electric Vehicle Battery Recycling: An Evolutionary Game Theory Approach

As the global new energy vehicle (NEV) industry rapidly expands, the disposal and recycling of end-of-life (EOL) power batteries have become imperative. Efficient closed-loop supply chain (CLSC) management, supported by well-designed regulations and strategic investments, plays a crucial role in sustainable waste power battery recycling. In this study, an evolutionary game theory (EGT) methodology is used to construct a tripartite game model to investigate the interactions among manufacturers, recyclers, and the government to study the decision-making dynamics of green investments. In addition, numerical simulations are performed to evaluate the sensitivity of the relevant parameters on the stability of the evolution of the system. The results reveal that government green subsidies can stimulate early period investments in advanced recycling technologies. However, as the battery recycling industry matures, a ‘free-rider’ behavior emerges among enterprises, which can be mitigated through the imposition of a carbon tax. Eventually, as the industry reaches maturity, manufacturers and recyclers autonomously invest for enhanced profitability. This research provides valuable insights for government policy formulation, facilitating the formal recycling of retired batteries and fostering sustainability in the NEV sector.

Recycling Versus Leasing in Closed-Loop Supply Chain: A Comparative Analysis Anchored on Consumer Ownership Perceptions

Manufacturers increasingly recycle end-of-life products to realize residual economic value and mitigate environmental impacts on the economic system. Concurrently, with the burgeoning growth of the product-service system, leasing models offer an alternative method to complete the material loop without direct collection. While prior research has delved into recycling channels, incentive mechanisms, and remanufacturing within closed-loop supply chain management, a comparative analysis between recycling and leasing strategies remains under-explored. This study seeks to bridge this gap by elucidating the manufacturer’s strategic decision-making process, factoring in consumers’ product ownership perceptions. We propose a manufacturer decision model anchored on consumer choices and segment it into three scenarios based on varying ownership perceptions. Our analysis contrasts market demand and profit outcomes across these scenarios. Notably, we discern that a hybrid strategy is optimal when ownership perception is low; however, when such perception is heightened, a dedicated recycling strategy proves more advantageous. Importantly, introducing a leasing option does not entirely overshadow the conventional sales market but is susceptible to being overshadowed itself. From a managerial standpoint, while integrating a leasing program might augment revenue streams, sole reliance on it is inadvisable. Furthermore, reshaping consumption paradigms to emphasize product functionality over ownership can pave the way for more expansive leasing strategies, optimizing revenue generation within a closed-loop framework.

A customized multi-neighborhood search algorithm using the tabu list for a sustainable closed-loop supply chain network under uncertainty

Environmental pollution and social inequalities have prompted the agricultural industry to implement sustainable supply chain management practices. However, supply chain operations and planning in developing countries such as Iran are often not economically, environmentally, and socially sustainable. To address this challenge, this paper presents a practical optimization model for sustainable closed-loop supply chain (SCLSC) management in the agricultural industry of Iran, with a focus on the olive crop. Based on the triple bottom line concept, which considers economic, environmental, and social sustainability, the proposed model makes location, allocation, and inventory decisions under uncertainty by developing a scenario-based robust optimization model. To solve this complex network design problem, we propose a metaheuristic algorithm with a multi-neighborhood procedure that efficiently handles the complexity of the problem. Specifically, we develop a customized Simulated Annealing (SA) algorithm using a tabu list to improve the initial solution found by a constructive heuristic algorithm. Our extensive analysis and comparison of our metaheuristic algorithm against the exact solver and two other powerful metaheuristic algorithms demonstrate the applicability of our SCLSC model for the agricultural industry in Iran and the high performance of the proposed metaheuristic algorithm for solving large-scale networks.

Impact of transportation and carbon emissions on reverse channel selection in closed-loop supply chain management

Remanufacturing has gained significant attention as a way to combat global warming and natural resource depletion due to its potential environmental and economic benefits. However, transportation and logistics activities in the reverse supply chain, a critical component of the closed-loop supply chains (CLSC), have been largely overlooked by both academics and businesses. This work aims to bridge the gap by mapping the impacts of transportation distances and costs on the environmental and economic performance of CLSC management. We develop a hybrid manufacturing–remanufacturing model under different reverse-channel structures and examine the relationships between transportation distances and costs, the remanufacturing rate, the optimal reverse channel, and the net emissions of the system. The results show that the optimal remanufacturing rate decreases with an increase in transportation distances of the reverse supply chain only, and forward distance has no impact on the remanufacturing rate. However, increasing market demand reduces the impacts of long reverse distances. Furthermore, the cost of transportation also affects the remanufacturing rate. We also found that increasing remanufacturing rate increases total emissions due to higher reverse transportation distances.

Dynamic corporate social responsibility adjustment strategies of a closed-loop supply chain with fairness concerns and supply chain financing

Taking corporate social responsibility (CSR) behavior into account, this paper investigated the equilibrium strategies for a dyadic closed-loop supply chain (CLSC) consisting of one manufacturer, one fairness-concerned retailer and one capital-constrained recycler in the static and dynamic frameworks, respectively. Based on the operational practice, both supply chain financing and fairness concerns issues are incorporated into the CLSC. The static decision-making model is firstly built to study the optimal single-period strategies. Then, according to the bounded rationality rule the dynamic decision-making model for the CLSC members is established and described as a discrete dynamic system. We examine the complex dynamics it admits, such as period-doubling bifurcation, chaotic phenomena and the parameter basins by means of applying the nonlinear theory and numerical simulations, and observe the dynamical model experiences more complex behavior than the static scenario. Furthermore, the periodic, bifurcation or chaotic changes and largest lyapunov exponent (LLE) in the wholesale price, retail price, CSR level and return rate are presented, respectively. Besides, the profit (utility) of the manufacturer, the retailer and the recycler are discussed. It is found that both the fairness-concerned parameter and the interest rate in trade credit financing have impacts on the dynamic decision-makings, such as the local stable, bifurcations and the route to the chaotic state etc. In addition, it is obvious that the adjustment speeds of the members have influences on system stability and profit (utility). Finally, some suggestions to CLSC management are also provided.

An environmental decision support system for manufacturer-retailer within a closed-loop supply chain management using remanufacturing

<abstract> <p>Industries face many challenges when emergencies arise. In emergency, there is an increasing demand for self-administered products that are easy to use. The decay rate of these products decreases with time. Moreover, the lack of disposal of used products increases waste and carbon emissions. By observing the scenario, this study develops a closed-loop supply chain management that considers the collection and remanufacturing of used products. The manufacturing rate is linear and the demand is ramp-type and carbon emissions dependent. The model is solved by a classical optimization and calculates the optimal total cost. The results show that the retailer can handle a shortage situation when the demand becomes stable (Case 2) and the total cost increases with the production rate. A sensitivity analysis shows the changes in the total cost with respect to the parameters.</p> </abstract>

Decision Analysis of Manufacturer-Led Closed-Loop Supply Chain Considering Corporate Social Responsibility.

With the rapid development of the economy, a growing number of consumers and enterprises are paying attention to corporate social responsibility (CSR). Meanwhile, there exist a variety of conflicts in closed-loop supply chain management. To analyse and deal with the decision problems of the manufacturer-led closed-loop supply chain with CSR, by using the manufacturer Stackelberg game, we construct some basic models considering CSR, and exploit them to analyse the optimal decisions of supply chains with and without CSR under centralized and decentralized decision making and explore the influence of CSR on supply chain, and then we establish a coordination mechanism through two-part tariff.

Knowledge mapping of e-commerce supply chain management: a bibliometric analysis

E-commerce supply chain management is a considerably hot research topic in recent decades, and the research findings have been widely published in various well-known international journals. To explore its research status and trend, we employ a bibliometric analysis approach to conduct performance analyses and reveal the publication trend, the main discipline categories, the top contributing countries, institutions, authors, the most influential documents and the dominant academic journals. Furthermore, we shed light on the dynamic evolution tendency of research topics and hotspots in this field. The keywords co-occurrence analysis reveals implications into 7 major clusters including e-commerce operations, supply chain management, pricing strategy, coordination mechanism design, sustainable development management, cross-border e-commerce management, and closed-loop supply chain management. The research gap analysis suggests that future research directions could combine live-streaming, emerging technologies, disruption risk and behavioral preference into the e-commerce supply chain management research.