Wang Piaoran1*, Wang Feifan2
1Farabi International Business School, Al-Farabi Kazakh National University, Almaty,
Kazakhstan
* Corresponding author: wangpiaoran7@gmail.com
ORCID: https://orcid.org/0009-0009-9412-5720
2Farabi International Business School, Al-Farabi Kazakh National University, Almaty,
Kazakhstan
Email: wangfeifan969@gmail.com
ORCID: https://orcid.org/0009-0003-4197-0492
Abstract
Closed-loop supply chain (CLSC) is an important paradigm for sustainable supply chain management. This paper systematically reviews domestic and international literature to summarize the evolution of this field from linear supply chains to the circular economy transition. The study identifies three major trends in CLSC research: a shift from single-link optimization to whole-chain collaborative governance; an evolution from cost-orientation to value co-creation; and a move from deterministic modeling to robust optimization and intelligent decision-making. This paper further analyzes typical cases including new energy vehicle power battery recycling, electronic product remanufacturing, and apparel reverse logistics to reveal the application mechanisms and practical values of CLSC in different industrial contexts. The results show that the effective operation of CLSC requires systematic governance supported by government policies, enterprise strategic coordination, technological innovation, and consumer participation. Future research should focus on cutting-edge topics such as artificial intelligence-enabled intelligent decision-making and supply chain resilience mechanisms.
Keywords: Closed-loop supply chain; Reverse logistics; Power battery recycling; Sustainable development
1. Introduction
Traditional supply chains have long followed the linear model of “extract–make–use–dispose”. While promoting economic development, this model has also led to resource depletion, environmental pollution, and other problems (Guide & Van Wassenhove, 2009). At present, more than 50 million tons of electronic waste are generated globally each year, and large amounts of waste clothing are incinerated or landfilled. Low resource utilization has become a key bottleneck restricting sustainable development.
Against this background, the closed-loop supply chain has emerged. Unlike traditional linear supply chains, CLSC emphasizes the closed-loop flow of materials. After their service life, products are not simply discarded but recycled, remanufactured, redistributed, or safely disposed through reverse logistics networks (Fleischmann et al., 1997). Its core lies in creating “value recovery” opportunities to extend product life cycles through remanufacturing, reuse, and recycling, thereby generating economic benefits while reducing environmental burdens and achieving the unity of commercial and social values.
In recent years, research on CLSC has grown rapidly. Early studies mainly focused on reverse logistics network design and cost optimization, and gradually expanded to multiple directions such as supply chain coordination mechanisms, carbon emission constraint optimization, and intelligent decision support systems (Rodríguez‑Escoto et al., 2024). Notably, the booming new energy vehicle industry has triggered a large-scale wave of decommissioned power batteries, making power battery recycling and echelon utilization a new hotspot in CLSC research. This paper aims to systematically sort out the theoretical evolution of CLSC research, summarize the main research themes and methodological characteristics, and reveal the practical application mechanisms of CLSC through typical case studies. The research provides important references for promoting the theoretical development of CLSC and guiding enterprise practice and decision-making.
2. Literature Review
Research on closed-loop supply chains has evolved from conceptual initiation to systematic improvement. In the early 1990s, scholars began to focus on end-of-life product management and proposed the conceptual framework of “reverse logistics” (Dell, 1998; Rogers & Tibben‑Lembke, 1999). Subsequent studies recognized the need to systematically integrate forward and reverse logistics, giving rise to the concept of closed-loop supply chains. Guide and Van Wassenhove (2009) pointed out that the core of CLSC is “value recovery”, extending product life cycles through remanufacturing, reuse, and recycling.
From the perspective of research evolution, CLSC studies can be roughly divided into three stages. The first stage (1990–2000) focused on basic issues such as reverse logistics network design, recycling channel location, and inventory optimization. The second stage (2000–2015) shifted to supply chain coordination mechanisms, profit-sharing contracts, and incentive mechanism design under information asymmetry. The third stage (2015–present), driven by the sustainable development agenda, has focused on carbon emission constraints, green procurement, and ecological design. Meanwhile, the rapid development of artificial intelligence has brought new research opportunities for CLSC (Sahamie et al., 2013).
Regarding research content, scholars have explored the design of recycling networks including topology, node location, and capacity allocation. Due to widespread demand uncertainty and recycling rate fluctuations, robust optimization has attracted attention for its ability to handle uncertain problems (Elsevier, 2026a). Rodríguez‑Escoto et al. (2024) constructed a multi-objective optimization model considering economic cost, environmental impact, and social benefits. They found that introducing environmental objectives increases operating costs by 15%–20% but significantly reduces carbon emissions. In addition, the impacts of policy tools such as carbon subsidies and tax incentives on remanufacturing decisions have been studied, showing that moderate carbon subsidies can encourage enterprises to carry out remanufacturing (Zhang & Li, 2023).
The connection between CLSC and sustainable development has become increasingly close. A World Economic Forum (2025) report states that CLSC is a key path to industrial circular transformation, and leading enterprises can reduce waste emissions by 30%–50% by building closed-loop networks. The application of artificial intelligence has become a new trend, with machine learning, deep learning, and reinforcement learning applied to demand forecasting, inventory optimization, and reverse logistics routing (IEEE, 2024a). Decision support systems can improve operational efficiency by 20%–30% (Elsevier, 2024a). Risk modeling addresses disruptions, quality fluctuations, market changes, and policy adjustments (IEEE, 2024b).
3. Research Methods
This study adopts a combined paradigm of systematic literature review and case analysis.
For the literature review, major databases including Web of Science, Scopus, Elsevier ScienceDirect, and Google Scholar are used. Search keywords include “closed-loop supply chain”, “reverse logistics”, “remanufacturing”, “battery recycling”, and “reverse supply chain”. The inclusion criteria are peer-reviewed journal or conference papers directly related to CLSC published after 2000. Non-Chinese/English papers, purely methodological studies without empirical applications, and full-text-unavailable documents are excluded. Content analysis is used to code the included literature and extract research questions, theoretical perspectives, methodologies, and core findings.
For case analysis, a multiple-case study method is adopted. Three typical cases are selected: new energy vehicle power battery recycling, electronic product remanufacturing, and apparel reverse logistics. Cases are chosen for representativeness, covering different industries and including both mature applications and emerging practices.
The literature review provides theoretical perspectives and research contexts, while case analysis presents application mechanisms and value creation paths in practice. The two approaches verify and complement each other, supporting a systematic review and in-depth understanding of CLSC research.
4. Research Results
4.1 Distribution of Research Themes
Through literature analysis, CLSC research covers six major thematic areas. These themes are interrelated and progressive, forming a complete knowledge system.
Table 1 Distribution of Research Themes in Closed-Loop Supply Chain Studies
| Theme | Proportion | Main Content |
| Network Design and Optimization | 25% | Topology, node location, capacity allocation |
| Coordination Mechanisms | 20% | Contract design, profit distribution, information sharing |
| Remanufacturing Decisions | 20% | Feasibility assessment, process routes, quality control |
| Recycling and Reverse Logistics | 15% | Channel design, routing optimization, pricing strategies |
| Sustainable Development | 12% | Carbon constraints, green procurement, eco-design |
| Intelligent Decision and Risk | 8% | AI applications, blockchain, risk identification |
4.2 Typical Cases
4.2.1 Power Battery Recycling
The rapid development of the new energy vehicle industry has led to a large number of decommissioned power batteries, making their treatment increasingly prominent. Power batteries contain scarce metals such as lithium, cobalt, and nickel, so recycling has important economic and environmental value.
Representative enterprises such as CATL and BYD have established full-life-cycle power battery management systems. Brunp Recycling under CATD has built a closed-loop system: “battery production–use–echelon utilization–recycling”, achieving a recovery rate of over 99% for nickel, cobalt, and manganese. This model reduces raw material costs and environmental pollution, verifying the practical value of CLSC in the power battery field.
4.2.2 Electronic Product Remanufacturing
Electronic product remanufacturing is one of the most commercialized CLSC fields. Enterprises such as IBM and Dell have remanufacturing programs that refurbish retired enterprise servers and sell them at a discount to small and medium-sized enterprises. Compared with new manufacturing, remanufactured servers reduce energy consumption and carbon emissions by about 50%. A core challenge is product quality uncertainty: remaining life and condition vary widely, requiring strict quality assessment and pricing.
4.2.3 Apparel Reverse Logistics
The apparel industry is a typical linear economy sector and an important testing ground for CLSC innovation. Fast fashion brands such as H&M, Zara, and Uniqlo have launched clothing recycling programs where consumers can exchange old clothes for discount coupons. However, actual closed-loop effects are limited: most recycled clothes are exported to secondhand markets or used as industrial rags, with less than 1% recycled into new fibers. This shows that building recycling channels does not equal real closed-loop realization.
High-end outdoor brands such as Patagonia have explored high-value closed-loop models. Its “Worn Wear” program recycles, professionally refurbishes, and offers trade-ins. Refurbished products are sold at 70%–80% of the original price, effectively extending product life cycles. This case indicates that successful CLSC requires not only recycling networks but also deep value connections with consumers to achieve both commercial and environmental benefits through product servitization.
4.3 Summary
Based on literature and case analysis, three core findings are obtained. First, CLSC research has formed a relatively complete theoretical system, shifting from single-link optimization to whole-chain collaborative governance, reflecting deeper systematic understanding. Second, CLSC shows differentiated characteristics and diverse values across industries, requiring industry-specific design. Third, effective CLSC operation demands multi-stakeholder coordination: government policy support, enterprise strategic coordination, technological innovation, and consumer participation are all indispensable. Systematic thinking is key to understanding and advancing CLSC.
5. Discussion
The literature review reveals three theoretical contributions of CLSC research: constructing a CLSC analytical framework that integrates forward and reverse supply chains from a systems perspective; developing supply chain coordination theory with rich contexts of multiple uncertainties; and expanding sustainable supply chain management theory by incorporating environmental externalities into decision-making, leading to carbon-constrained supply chain optimization and green supply chain performance evaluation.
The findings have important practical implications. For enterprises, CLSC has become a strategic tool for competitive advantage. They should actively apply AI, IoT, and blockchain to improve CLSC intelligence. For supply chain governance, reasonable profit-sharing mechanisms and long-term stable reverse logistics networks are needed. Government support is critical: carbon subsidies, tax incentives, and extended producer responsibility can effectively promote CLSC practices, but balance between environmental goals and economic efficiency is required.
This study has limitations: qualitative literature evaluation involves subjectivity; it focuses on academic literature and does not fully include industry reports and enterprise practices. Future CLSC research can focus on: AI-enabled intelligent decision-making and deep reinforcement learning for dynamic optimization; supply chain resilience and risk management under emergencies; digital CLSC with digital twin and industrial internet for full-process visualization and intelligent scheduling.
6. Conclusion
Through systematic literature review and case analysis, this paper sorts out the theoretical evolution, research themes, and methodological characteristics of CLSC research. It covers network design, coordination mechanisms, remanufacturing decisions, recycling optimization, green transformation, and intelligent decision-making, forming a complete theoretical system. Three major trends in CLSC research reflect the deepening understanding of its complexity. Cases such as power battery recycling, electronic product remanufacturing, and apparel reverse logistics show that CLSC presents differentiated features and diverse values in different industrial scenarios. Enterprises should select suitable CLSC business models and operational strategies according to their industry characteristics and resource endowments.
With the promotion of circular economy and sustainable development goals, CLSC will play an increasingly important role in corporate strategy and industrial policy. Especially under the rapid development of artificial intelligence, the effective integration of intelligent technology and CLSC operations will be an important direction for theoretical research and practical exploration.
References
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