In this paper, we address the problem of choosing an appropriate channel for the marketing channel structure of remanufactured fashion products. To be specific, we consider a remanufacturer who has two options for selling the products: (1) provide the remanufactured products to a manufacturer, then the manufacturer sells both new products and the remanufactured products to customers, and (2) sell the remanufactured products directly to customers. Because of the relatively low acceptance of remanufactured products and environment consciousness of customers in developing countries like China, we model the two scenarios as decentralized remanufacturing supply chains, with the manufacturer being the Stackelberg leader and the government offering subsidy to the remanufacturer to incentivize remanufacturing activities. We find that the subsidy can incentivize remanufacturing activity regardless of the remanufacturer’s channel choice. A “too high” or “too low” subsidy makes the remanufacturer compete with the manufacturer, and an intermediate subsidy results in cooperation between the two members of the remanufacturing supply chain. Meanwhile, if the customers’ acceptance for remanufactured products is higher, the remanufacturer will be more likely to compete with the manufacturer. However, the remanufacturer’s optimal channel choice may be inefficient in the sense of social welfare and environmental protection.

As the sustainable economy has become more of a consensus, supply chain members, both manufacturer (e.g., Apple, Huawei, Xiaomi, Nike, and P&G) and retailer (e.g., Uniqlo, Walmart, and Bravo), are concentrated on corporate social responsibility (CSR). The literature in this area has investigated the role of CSR, but the optimal preference for CSR concern of supply chain members is not well understood, especially when manufacturer sells directly by implementing encroachment. This paper studies the optimal preference for CSR concern of supply chain members with considering manufacturer encroachment. We develop the supply chain with a manufacturer (M) and a retailer (R), where the manufacturer sells products via a retail channel which in turn sells them to the final consumers. The manufacturer can also implement encroachment to meet consumers directly. Meanwhile, by considering the manufacturer or retailer may have CSR concern, we explore four scenarios using a game‐theoretic framework. Several interesting findings are as follows. First, for the sake of profits, retailer CSR should be encouraged, which may achieve Pareto improvement under certain conditions. Notably, manufacturer encroachment may narrow the “win–win” situation. While for the sake of environmental protection and consumer well‐being, manufacturer CSR should be encouraged. Second, manufacturer implementing encroachment may not be blind, because it may be worse for itself when retailer has CSR concern. Third, manufacturer CSR may aggravate the cannibalization effect of encroaching, while retailer CSR may relieve it.

Public transportation scheduling aims to optimize the allocation of resources, enhance efficiency, and increase passenger satisfaction, all of which are crucial for building a sustainable urban transportation system. As a complement to public transportation, bike-sharing systems provide users with a solution for the last mile of travel, compensating for the lack of flexibility in public transportation and helping to improve its utilization rate. Due to the characteristics of shared bikes, including peak usage periods in the morning and evening and significant demand fluctuations across different areas, optimizing shared bike dispatch can better meet user needs, reduce vehicle vacancy rates, and increase operating revenue. To address this issue, this article proposes a comprehensive decision-making approach for spatiotemporal demand prediction and bike dispatch optimization. For demand prediction, we design a T-GCN (Temporal Graph Convolutional Network)-based bike demand prediction model. In terms of dispatch optimization, we consider factors such as dispatch capacity, distance restrictions, and dispatch costs, and design an optimization solution based on genetic algorithms. Finally, we validate the approach using shared bike operating data and show that the T-GCN can effectively predict the short-term demand for shared bikes. Meanwhile, the optimization model based on genetic algorithms provides a complete dispatch solution, verifying the model’s effectiveness. The shared bike dispatch approach proposed in this paper combines demand prediction with resource scheduling. This scheme can also be extended to other transportation scheduling problems with uncertain demand, such as store replenishment delivery and intercity inventory dispatch.

To solve these pricing and channeling issues, we consider a dual-channel supply chain consisting of the manufacturer producing new and remanufactured products simultaneously, the independent retailer selling new products, and the manufacturer selling remanufactured products, then investigates optimal pricing strategies for the new and remanufactured products between the centralized and decentralized decision-making models by applying optimization and game theory. By comparing the two models we find that the optimal prices of the new and remanufactured products not only depend on the government's subsidy level of remanufacturing, but also relate to the unit cost saving of producing remanufactured products with respect to new products and the decision-making methods in the dual-channel supply chain. Meanwhile, it is found that there is also a “double marginalization” in the decentralized situation, thus we coordinate the dual-channel supply chain using a two-part tariff contract. Specifically, only the manufacturer adjusts dynamically the wholesale price and fixed fee within the coordinating contract according to the government's subsidy level of remanufacturing. Finally, we obtain several interesting conclusions from the numerical examples and provide managerial insights and policy implications from the analytical results. In particular, our finding of the economic, social, and environmental benefits of remanufacturing operations managed by the dual-channel supply chain has implications for both academics and managers.

Purpose: Motivated by the real-world practice of the thriving e-commerce, manufacturers are transcending traditional boundaries of merely producing and selling directly by implementing encroachment. Concurrently, supply chain (SC) members who overlook the corporate social responsibility (CSR) sharing will be left behind, which is closely linked to their profits. This paper aims to investigate a better way to share CSR under the scenarios of manufacturer encroachment and no-encroachment.Design/methodology/approach: This paper constructs game-theoretic models in a SC consisting of a manufacturer (M) and a retailer (R), where the manufacturer can sell products by retailing, and may sell directly by implicating encroachment. The manufacturer and retailer jointly consider whether to share CSR and the proportion of it by taking consumer surplus into account. Furthermore, equilibriums for each model are derived using backward induction. Then, the authors analyse the impact of CSR sharing proportion and compare the equilibrium outcomes under different scenarios. Finally, the numerical analyses are presented to verify the results.Findings: Several interesting results are found in this paper. First, the retailer shares more CSR can benefit SC members and social welfare when the manufacturer does not implement encroachment. However, the results may change which is decided by the unit cost of encroachment when the manufacturer does so. Second, the proportion of CSR shared by manufacturer and the unit cost of encroachment has an interactive impact on equilibrium outcomes. Finally, both manufacturer encroachment and SC members share CSR may be the best for the perspective of SC members and consumers.Practical implications: Based on the analytical results, this paper provides novel managerial implications to assist manufacturer and retailer in determining the optimal strategies for CSR sharing and encroachment. Furthermore, the appropriate proportion of CSR shared by manufacturer and the unit cost of encroachment may let manufacturer, retailer and consumer surplus achieve a win-win-win situation.Originality/value: To the best of the authors’ knowledge, this paper is the first attempt to explore the strategy of CSR sharing under the scenarios of manufacturer encroachment and no-encroachment.

Public transportation scheduling aims to optimize the allocation of transportation resources, enhance transportation efficiency, and increase passenger satisfaction, which is crucial for building a sustainable urban transportation system. As a complement to public transportation, shared bikes provide users with a solution for the last mile of travel, compensating for the lack of flexibility in public transportation and helping to improve its utilization rate. Due to the characteristics of shared bikes, such as peak usage periods in the morning and evening and significant fluctuations in demand across different areas, the optimization of shared bike dispatch can better meet user needs, thereby reducing vehicle vacancy rates and increasing operating revenue. Addressing this issue, this paper designs a comprehensive decision-making approach for spatio-temporal demand prediction and bike dispatch optimization. For demand prediction, we designed a T-GCN based bike demand prediction model. In terms of dispatch optimization, we considered factors such as dispatch capacity, distance restrictions, and dispatch costs, and designed an optimization solution based on genetic algorithms. Finally, this paper validates the approach using shared bike operating data, shows that T-GCN can effectively predict short-term demand for shared bikes. Meanwhile, the optimization model based on genetic algorithms provides a complete dispatch solution verifying the model’s effectiveness. The shared bike dispatch approach proposed in this paper, which combines demand prediction with resource scheduling. This scheme can also be extended to other transportation scheduling problems with uncertain demand, such as store replenishment delivery and intercity inventory dispatch.