Yuxiang Yang

With both frequent extreme weather events and unpredictable international situations, the fresh agricultural product supply chain is highly vulnerable to severe disruptions due to their perishable nature and strict quality requirements. Efficient network design under such conditions is essential to balance cost efficiency and service performance. This study proposes a hybrid fuzzy-stochastic multi-objective resilient supply chain network design model for fresh agricultural products with explicit consideration of quality deterioration under disruption. The model integrates triangular fuzzy numbers and stochastic optimization methods to handle parameter ambiguity and scenario-based disruption uncertainty, while five resilience strategies tailored to fresh agricultural products—multi-sourcing, temporary cold storage construction, direct transportation, facility fortification, and intelligent cold chain transportation—are applied to enhance the model’s risk resistance. With the objectives of minimizing economic costs and maximizing demand fulfillment, an improved hybrid genetic algorithm is employed to solve large-scale mixed-integer nonlinear programming (MINLP) problems, demonstrating superior computational efficiency via a foundational case analysis. Numerical experiments show that the hybrid fuzzy-stochastic optimization strategy outperforms other comparative methods. And the results further reveal that different disruption types exhibit heterogeneous impact mechanisms, and the effectiveness of resilience strategies varies significantly across scenarios. A real-world case study based on Hema Fresh in Shanghai further validates the generalizable findings derived from the numerical analysis and provides targeted managerial insights. Specifically, temporary cold storage offers notable cost advantages in mitigating storage disruptions, direct transportation significantly alleviates unbalanced transportation disruptions, and multi-sourcing serves as a foundational strategy with broad applicability. Moreover, analysis of combined strategies suggests adopting multi-sourcing as the structural framework complemented by capacity expansion at the core, while implementing intelligent temperature-controlled cold chain transportation in conjunction with facility fortification to effectively reduce product spoilage. This study contributes to the literature by integrating quality deterioration and disruption-specific resilience strategies into a unified optimization framework, providing decision support for targeted and cost-effective resilience planning in perishable supply chains.

The development of global operations and procurement leads to the popularity of cross-border supply chain network (CBSCN). Various economic and sustainability-related factors and policies from different countries further complicate the CBSCN management. This paper addresses the issues of carbon tax (CT) policy and tariff policy in a CBSCN, including original equipment manufacturers (OEMs), local demand markets, and overseas suppliers, to investigate the impact of CT and tariff on the OEMs’ pricing, production, and carbon emissions decisions. First, we analyzed the behavior of OEMs and suppliers with CT and tariff, and then their optimal conditions and equilibrium conditions of markets were given. An equilibrium model with an exogenous local CT rate was developed. Then, when considering the local CT rate as endogenous, we provided the equilibrium conditions of the local CT rate to control carbon emissions and extended the above model to an equilibrium model with an endogenous local CT rate. We find that an increase in the local CT rate leads to the decline of carbon emissions of OEMs and the rise of carbon emissions of suppliers, but the total carbon emissions of the network decrease. Higher tariffs bring a surge in the local CT rate and a reduction in the total carbon emission of the network. Our findings provide managerial insights for supply chain participants to make the optimal operational decisions to improve their profits and policy implications for governments to implement appropriate CT rate and tariffs to encourage firms’ carbon emission abatement.

With the increasing requirements for environmental protection, authorities have enacted different carbon policies to promote sustainable practices. This study considers the competition among different manufacturers and multiple demand markets in the supply chain network. We examine and compare their equilibrium decision conditions under three common carbon policies: carbon cap, carbon cap‐and‐trade, and carbon tax. Results suggest that under lower carbon caps, manufacturers greatly reduce their carbon emissions by reducing production quantities, which causes a decrease in profits. However, an appropriate carbon cap size can not only motivate manufacturers to reduce carbon emissions but also improve their profits. Under a certain price for carbon credit, the effectiveness of a carbon cap‐and‐trade policy is similar to that of a carbon cap policy, but it has more flexibility. Carbon tax is effective, but it brings more tax burden to manufacturers. We provide implications for companies to optimize their production methods to achieve sustainability.

Due to the increasing awareness of sustainable manufacturing, remanufacturing has been widely accepted by enterprises in many countries. In the process of Closed-Loop Supply Chain (CLSC) development, to stimulate the demand for remanufactured products, the Chinese government’s interventions such as the “Trade old for Remanufactured” program cannot be ignored. However, prior research has not answered the questions of whether governments should offer consumption subsidies and how to determine the optimal subsidy value. This paper investigates the optimal government consumption subsidy policy and its impact on the operation of Closed-Loop Supply Chain (CLSC) where an Original Equipment Manufacturer (OEM) produces new products, while a Third-Party Remanufacturer (TPR) remanufactures the used products collected from consumers. A game model with a leader (government) and two followers (OEM and TPR) is then introduced. The government determines the consumption subsidy to maximize the social welfare, while the TPR and OEM attempt to maximize their own profit functions. Game theoretic models are proposed to explore and compare the scenarios, i.e., CLSC with a consumption subsidy policy and without a consumption subsidy policy. The equilibrium characteristics with respect to the government’s consumption subsidy decisions and the price decisions for chain members are derived. Based on the theoretical and numerical analysis, the results show that: (1) governments should not always offer a consumption subsidy; (2) the consumption subsidy cannibalizes demand for new products while boosting the demand for remanufactured products; (3) the consumption subsidy should be shared between the TPR and consumers when the TPR raises the sales price of remanufactured product; (4) the members of the CLSC do not always benefit from the consumption subsidy policy.

A closed‐loop supply chain network including multi‐manufacturing/remanufacturing firms and multi‐demand markets is considered. We present equilibrium conditions for decision‐makers in the network and develop a static model with marketable pollution permits and noncompliant behavior, using the variational inequality theory. We provide qualitative analysis of the model. Then, using the projected dynamical system, we propose a dynamic model. The results show that the set of stationary points of dynamic model coincides with the set of solutions of static model. Finally, numerical examples are proposed. The equilibrium results including production output of new products, the forward and reverse product flows, the prices of product, the prices of license, the number of licenses, and the possible noncompliant overflows and underflows of the waste are obtained. We find that increase in the unit penalty cost contributes to decrease in waste emission from firms in the network, and when the unit penalty cost increase to a certain level, they no longer choose excess emission of waste. © 2018 American Institute of Chemical Engineers Environ Prog, 38:e13021, 2019