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The paper proposes a two-level closed-loop supply chain (CLSC) dynamic competitive model based on different competitive cooperation situations, and explores the impact of competitive cooperation methods on the pricing strategies, recycling and remanufacturing strategies and competitive model selection strategies of supply chain firms.

This paper establishes a CLSC game consisting of a manufacturer and two retailers. Firstly, five CLSC models are established in both horizontal and vertical dimensions, each of which competes with one another. Secondly, the recycling and remanufacturing pricing strategies are analyzed under different competition or cooperation models. Finally, the results are verified through numerical analysis.

The overall profitability of the CLSC is highest when the manufacturer–retailer partnership alliance is in place. The relationship between retailers and manufacturers is also found to be the best way to achieve overall optimization of the CLSC.

The paper investigates the relationship between the competitive partnership and the total profit of the CLSC, taking into account how to optimize the overall benefit, and focusing on how to optimize the individual interests of each participating enterprise. The results can provide basis and guidance for managers' pricing decision and competition cooperation.

Rapid innovation and developments in personal electronic technology have encouraged users to change users' devices more frequently than ever, which has resulted in creating a massive increase in the amount of electronic waste. The study focuses on identifying the barriers to closed-loop supply chain (CLSC) in the electronic industry.

A framework for analyzing the relationships among CLSC adoption barriers is designed. The authors adopted the decision-making trial and evaluation laboratory (DEMATEL) technique to determine the critical barriers of electronic CLSC from the opinion of experts in the field.

The outcome from the analysis suggests that cost barriers, financial barrier, process barriers and supplier-side barriers are the main causal factors that prevent the adoption and implementation of e-waste CLSC. The causal relationship indicates that financial barrier is the most influential factor, while phycological barrier is the most flexible barrier to the adoption of e-waste CLSC.

This study is restricted to CLSC adoption barriers in the electronic industry by evaluating 36 sub-barriers grouped into 8 main dimensions related to different members of the supply chain.

Closed-loop adoption barriers have been proposed to understand the crucial barriers to implementation of CLSC in the electronic industry. The cause-and-effect relationship indicates the critical factors to be improved to increase adoption of e-waste CLSC, helping managers and regulatory bodies to mitigate the problem areas.

This study contributes to the literature on CLSC by adopting a multi-criteria decision-making (MCDM) technique which captures the critical barriers of e-waste CLSC adoption in Indian scenario.

The purpose of this paper is to investigate the optimal production and financing strategies for the closed-loop supply chain (CLSC) composed of a capital-constrained original equipment manufacturer (OEM) and a risk-averse authorized remanufacturer (RM).

The authors formulate four models with different scenarios, namely, the OEM has sufficient capital; the OEM has limited capital without financing; the OEM adopts debt financing strategy; and the OEM adopts equity financing strategy. The equilibrium solutions of each scenario are obtained by backward induction method, the influences of risk aversion coefficient on the equilibrium solutions are examined and the OEM's optimal financing strategy is found by comparison analysis.

When the OEM's initial capital is limited and the equity dividend ratio is less than a certain threshold, the equity financing strategy is more advantageous for the OEM. However, if the OEM's initial capital is extremely scarce and the dividend proportion is large, the OEM prefers the debt financing strategy. When considering financing, consumer surplus always decreases as the risk aversion factor increases; the debt financing strategy is more environmentally friendly compared with the equity financing strategy. Only the debt financing strategy can make both members in the CLSC achieve a win-win situation in a certain region when the dividend ratio is sufficiently large.

It will be more fascinating if the model extends to such a case that the production operation situation in the CLSC composed of multiple OEMs in multiple periods. Furthermore, the remanufacturer's risk-averse information is asymmetry may be more realistic in our daily life.

There are three main differences from the existing research. One is that the remanufacturer's risk aversion originates from the uncertain remanufacturing cost instead of the uncertain market demand. Another is that the boundary conditions of the OEM prefer to adopt debt financing is obtained through the envelope theorem with Lagrange multiplier method. Last but not the least, this paper provides a good theoretical reference and practical guidance for the OEM to make the rational financing strategy selection in face of different degree of capital scarcity in the CLSC system. The value of the three aspects provides a theoretical basis for the optimal operation decisions of capital-constrained manufacturer considering the remanufacturer's risk aversion in the CLSC operation system.

This study advocates the importance of taking an evolutionary perspective in the strategic configuration of closed-loop supply chains (CLSC) in the transition to a circular economy. Building on the supply chain management and industrial dynamics research domains, an evolutionary analytical framework was developed and applied in the empirical context of the ongoing industrial transition to e-mobility.

This study is designed as an in-depth exploratory case study to capture the multi-layer dynamic complexities and their interplay in CSLC development. The empirical investigation was based on two-year interactions between the authors and various departments in a leading European heavy vehicle manufacturer. The proposed evolutionary analytical framework was used for investigating the dynamics of four CLSC configurations through ten possible trajectories.

The findings demonstrate that the evolution of each CLSC configuration comes with multiple challenges and requirements and point out the necessity for the co-development of technologies, product design and production, and infrastructure through long-term relationships among key supply chain actors. However, this evolutionary journey is associated with multiple dilemmas caused by uncertainties in the market and technology developments. All these factors were properly captured and critically analyzed, along with their interactions, thanks to the constructs included in the proposed evolutionary analytical framework.

The proposed evolutionary framework is applicable for examination of SC transformation in the context of market and technology development, and is particularly relevant for transitioning from linear SC to CLSC. The framework offers a single actor perspective, as it does not directly tackle dynamics and effects of actions taken by SC actors.

The developed framework can support SC managers in identifying, framing, and comparing alternative strategies for CLSC configuration in the transition process.

This study proposes the framework for understanding and guiding the evolutionary process of CLSC development. Its uniqueness lies in the integration of concepts from innovation and evolutionary theories coming from industrial dynamics and SCM literature streams.

Supply chain management (SCM) research has contributed to the transition to a circular economy (CE). Still, confusions exist on the related terms, and no review has mapped out the development trends in the domain. This research clarifies the boundaries of the relevant concepts. Then, it conducts a comprehensive review of the circular SCM (CSCM) literature and identifies opportunities for future research.

Using relevant keywords, 1,130 journal articles published in December 31, 2021 were identified. Unlike the published reviews, which mainly relied on content analysis, this review uses bibliometric analysis tools, including citation analysis, co-citation analysis and cluster analysis. The review identifies general trends, influential researchers, high-impact publications, citation patterns and established and emergent research themes.

The extant CSCM literature includes five prominent clusters: (1) reverse channel optimization; (2) CSCM review and empirical studies; (3) closed-loop supply chain (CLSC) and consumers; (4) CLSC and inventory management and (5) CLSC and reverse logistics (RL). Significant research gaps exist in the use of secondary and longitudinal data, a wider range of theories, mixed-methods, multi-method, action research and behavioral experiment. The least researched topics include zero waste, industrial symbiosis, circular product design, sourcing and supply management and reuse.

This is the first bibliometric analysis-based literature review on CSCM. It clarifies the interrelated supply chain sustainability terms and thus reduces related confusion. It offers insights into the patterns in the CSCM literature and suggests important research directions.

The purpose of this study is to develop a holistic optimization model for an integrated sustainable fleet planning and closed-loop supply chain (CLSC) network design problem under uncertainty.

A novel mixed-integer programming model that is able to consider interactions between vehicle fleet planning and CLSC network design problems is first developed. Uncertainties of the product demand and return fractions of the end-of-life products are handled by a chance-constrained stochastic program. Several Pareto optimal solutions are generated for the conflicting sustainability objectives via compromise and fuzzy goal programming (FGP) approaches.

The proposed model is tested on a real-life lead/acid battery recovery system. By using the proposed model, sustainable fleet plans that provide a smaller fleet size, fewer empty vehicle repositions, minimal CO₂ emissions, maximal vehicle safety ratings and minimal injury/illness incidence rate of transport accidents are generated. Furthermore, an environmentally and socially conscious CLSC network with maximal job creation in the less developed regions, minimal lost days resulting from the work's damages during manufacturing/recycling operations and maximal collection/recovery of end-of-life products is also designed.

Unlike the classical network design models, vehicle fleet planning decisions such as fleet sizing/composition, fleet assignment, vehicle inventory control, empty repositioning, etc. are also considered while designing a sustainable CLSC network. In addition to sustainability indicators in the network design, sustainability factors in fleet management are also handled. To the best of the authors' knowledge, there is no similar paper in the literature that proposes such a holistic optimization model for integrated sustainable fleet planning and CLSC network design.

This study aimed to develop the integration of the multiperiod production-distribution model in a closed-loop supply chain involving carbon emission and traceability. The developed model was for agricultural food (agri-food) products, considering the reverse flow of food waste from the disposal center (composting center) to producers.

The results indicate that integrating the production and distribution model considering food waste recycling provides low carbon emissions in lower total costs. The sensitivity analysis also found that there are trade-offs between production and distribution rate and food waste levels on carbon emission and traceability.

This study focuses on the mathematical modeling of a multiperiod production-distribution formulation for a closed-loop supply chain.

The model of the agri-food closed-loop supply chain in this study that considers food recycling and carbon emissions would help stakeholders involved in the agri-food supply chain to reduce food waste and carbon emissions.

Supply chains (SCs) have been growingly virtualized in response to the market challenges and opportunities that are presented by new and cost-effective internet-based technologies today. This paper designed a virtual closed-loop supply chain (VCLSC) network based on multiperiod, multiproduct and by using the Internet of Things (IoT). The purpose of the paper is the optimization of the VCLSC network.

The proposed model considers the maximization of profit. For this purpose, costs related to virtualization such as security, energy consumption, recall and IoT facilities along with the usual costs of the SC are considered in the model. Due to real-world demand fluctuations, in this model, demand is considered fuzzy. Finally, the problem is solved using the Grey Wolf algorithm and Firefly algorithm. A numerical example and sensitivity analysis on the main parameters of the model are used to describe the importance and applicability of the developed model.

The findings showed that the Firefly algorithm performed better and identified more profit for the SC in each period. Also, the results of the sensitivity analysis using the IoT in a VCLSC showed that the profit of the virtual supply chain (VSC) is higher compared to not using IoT due to tracking defective parts and identifying reversible products. In proposed model, chain members can help improve chain operations by tracking raw materials and products, delivering products faster and with higher quality to customers, bringing a new level of SC efficiency to industries. As a result, VSCs can be controlled, programmed and optimized remotely over the Internet based on virtual objects rather than direct observation.

There are limited researches on designing and optimizing the VCLSC network. This study is one of the first studies that optimize the VSC networks considering minimization of virtual costs and maximization of profits. In most researches, the theory of VSC and its advantages have been described, while in this research, mathematical optimization and modeling of the VSC have been done, and it has been tried to apply SC virtualization using the IoT. Considering virtual costs in VSC optimization is another originality of this research. Also, considering the uncertainty in the SC brings the issue closer to the real world. In this study, virtualization costs including security, recall and energy consumption in SC optimization are considered.

1. Investigates the role of IoT for virtual supply chain profit optimization and mathematical optimization of virtual closed-loop supply chain (VCLSC) based on multiperiod, multiproduct with emphasis on using the IoT under uncertainty.

2. Considering the most important costs of virtualization of supply chain include: cost of IoT information security, cost of IoT energy consumption, cost of recall the production department, cost of IoT facilities.

3. Selection of the optimal suppliers in each period and determination of the price of each returned product in virtual supply chain.

4. Solving and validating the proposed model with two meta-heuristic algorithms (the Grey Wolf algorithm and Firefly algorithm).

Investigates the role of IoT for virtual supply chain profit optimization and mathematical optimization of virtual closed-loop supply chain (VCLSC) based on multiperiod, multiproduct with emphasis on using the IoT under uncertainty.

Considering the most important costs of virtualization of supply chain include: cost of IoT information security, cost of IoT energy consumption, cost of recall the production department, cost of IoT facilities.

Selection of the optimal suppliers in each period and determination of the price of each returned product in virtual supply chain.

Solving and validating the proposed model with two meta-heuristic algorithms (the Grey Wolf algorithm and Firefly algorithm).

This paper studies how government subsidies (GS) and extended warranties (EW) feed decision-making about low-quality recycled used products (RUP) in closed-loop supply chains (CLSC).

The authors use the Stackelberg game and numerical simulation to analyze how the quality of RUP affects decision-making about remanufacturing and EW.

The results show that (1) low-quality RUP will weaken the environmental and economic value of EW and harm the profits of the CLSC, and the retailer is more vulnerable to low-quality RUP than the manufacturer; (2) the participation of GS can weaken the negative impact of low-quality RUP on the CLSC, while the participation of EW cannot; (3) the participation of GS or EW can increase the recycling rate of used products and revenues of the CLSC; (4) the linkage of the two can further enhance the economic and environmental value of EW and significantly improve the resource utilization efficiency and benefits of the CLSC.

The authors study the impact of GS, EW and the linkage between the two on resource utilization and revenue of the CLSC.

In the last few years, environmental issues have become a matter of survival. In this sense, e-waste management is among the major problems since it may be a way of mitigating mineral depletion. In this context, the literature lacks e-waste supply chain studies that systematically map supply chain challenges and risks concerning material recovery.

Given this context, the authors' paper conducted a systematic literature review (SLR) to build a framework to identify the constructs of e-waste supply chain risk management.

The paper revealed the theoretical relationship between important variables to achieve e-waste supply chain risk management via a circular economy (CE) framework. These variables include reverse logistics (RL), closed-loop supply chains (CLSC), supply chain risk management, supply chain resilience and smart cities.

The literature contributions of this paper are as follows: (1) a complete list of the risks of the e-waste supply chains, (2) the techniques being used to identify, assess and mitigate e-waste supply chain risks and (3) the constructs that form the theoretical framework of e-waste supply chain risk management. In addition, the authors' results address important literature gaps identified by researchers and serve as a guide to implementation.