The coordination of fresh agricultural product supply chains is a key pathway to reducing circulation losses and optimizing the matching of supply and demand. In response to the complex situation of overlapping stochastic output and demand, this paper constructs a three-level supply chain model composed of farmers, a single supplier, and a retailer, focusing on the coordination mechanism driven by dual efforts in production and preservation. By comparing centralized and decentralized decision-making models, this paper reveals that the total profit of supply chain members under decentralized decision-making is significantly lower than the system's total profit, highlighting an inherent contradiction. Based on this, an optimal decision-making framework centered on production effort, preservation effort, pricing, and order quantity is proposed. Further, a coordination optimization scheme combining a “revenue sharing + cost sharing” contract with risk-sharing strategies is designed to prove that this composite contract can effectively eliminate the double marginalization effect and bring the expected profit of decentralized decision-making to the Pareto optimal level of centralized decision-making. The research findings indicate that the realization of supply chain coordination depends on the precise positioning of member roles-suppliers can significantly increase the circulation scale of fresh agricultural products by deeply focusing on consumer utility, forming a win-win situation for all parties; enterprises' active sharing of farmers' production risks becomes a key lever to enhance the overall chain profit, and its risk compensation mechanism can simultaneously motivate farmers to increase production effort and product quality. This paper provides a “production-preservation-circulation” three-dimensional collaborative decision-making paradigm for the contract coordination of multi-level fresh agricultural product supply chains, offering theoretical support and practical references for mitigating the bullwhip effect in agricultural product supply chains and promoting the implementation of the rural revitalization strategy.

To address the diverse purchasing and returning needs of customers for different shared warehouses, unreasonable distribution of shared warehouse locations, and high total logistics costs, the issues of location selection of shared warehouses are studied with multiple suppliers and integrated forward and reverse logistics. A shared warehouse location model is built that integrates forward and reverse logistics, with the goal of minimizing the total logistics cost including shared warehouse location cost, third-party transportation cost, order cost, inventory cost, and return cost. An improved genetic algorithm is designed based on the characteristics of the model, and the monarchy scheme is used instead of traditional selection and crossover operations to enhance overall search capability. Finally, numerical examples for simulation experiments are introduced to analyze the impact of different parameters on the average running time, average cost, and minimum solution of the experiment, and the optimal location and minimum logistics cost of the shared warehouse are obtained. The experimental results have demonstrated the effectiveness of the model and the operational efficiency of the algorithm, reducing logistics costs and improving logistics efficiency.

The occurrence of emergencies is contingency.In order to solve the problem of excessive or insufficient reserves when the government reserves emergency materials alone over-or under-stocking of emergency supplies,a cooperation relationship is established between government and enterprises in the form of government-enterprise collaborative stockpiling.Considering the characteristics of material loss,the degree of material loss is reflected in the rotation and renewal cost generated by the loss.A decision-making model is constructed for the government-enterprise collaborative stockpiling with the objective of maximizing the expected profits of enterprises.The optimal form and amount of reserves is derived for enterprises through Stackelberg game theory.The results indicate that the optimal reserve decision of enterprises is influenced by three factors:the government procurement price,the probability of unexpected emergencies,and the cost of enterprise rotation and update.The willingness of enterprises to choose cooperation with the government increases with the probability of unexpected emergencies and government procurement price.Among them,as the cost of rotation updates increases,the physical reserves of the enterprise will correspondingly decrease,and the production capacity reserves will also increase accordingly.Finally,the conclusions obtained are verified through arithmetic numerical examples,providing a scientific basis for enterprise reserve decision-making.

With the rapid development of Internet technology, the problem of fake reviews in e-commerce platforms has become increasingly serious, causing damage to both consumer rights and interests and market order. Even though the detection technology of platforms is constantly upgraded, many unscrupulous merchants still induce consumers to post fake reviews, making such behaviors more covert and damaging consumers′ interests and their trust in platforms. This paper employs the evolutionary game theory to construct a tripartite evolutionary game model involving merchants, consumers, and e-commerce platforms and explores the key factors affecting the strategy selection of each party through the stability analyses of the strategies and equilibrium points of the system. Using Matlab R2018a software for numerical simulation, this paper simulates the impact of the initial probability on evolutionary results and initial evolution paths, verifies the stability of the model and the accuracy of the theoretical analysis, and then conducts a parameter sensitivity analysis in order to find effective strategies for governing fake review behaviors in e-commerce platforms. The findings reveal that the active intervention and supervision of e-commerce platforms facilitate merchants′ evolution toward non-induced positive review strategies and consumers′ evolution toward objective review strategies; when one party′s decision-making probability of fake reviews fluctuates around a specific threshold, the strategies of other decision-making subjects will change accordingly; and the punitive measures of e-commerce platforms are more effective than the incentive measures in curbing merchants′ induced positive review behavior. This paper provides e-commerce platforms with scientific strategies for governing fake review behaviors, helping to enhance user trust, maintain market order, and promote the healthy development of e-commerce.

Digital twin technology, as a key technology to break through the core bottleneck of interaction and integration between the physical and information worlds in manufacturing, is an important means to achieve intelligent manufacturing. To deeply explore the influencing factors of digital twin technology adoption in manufacturing enterprises and reveal its internal mechanism and driving logic, a four-dimensional index system of technology, organization, environment, and economy is constructed based on literature analysis and expert interviews. The DEMATEL-ISM method is adopted to systematically analyze the causal relationship and hierarchical structure of the influencing factors, and ultimately 16 main influencing factors are identified. These factors are distributed in the four quadrants of the causal relationship coordinate, forming an 8-level hierarchical explanation structure model. The research results show that government incentive policies, data security and privacy protection, and digital twin maturity exhibit the highest influence degree and are the root factors of the system; industrial chain collaboration and cooperation and application benefits demonstrate the highest centrality, while intelligent infrastructure represents the lowest-level root factor. Factors in the technological and economic dimensions constitute the main influencing paths, while factors in the environmental dimension connect and act on the main paths, ultimately affecting the surface-level organizational dimension factors. Specifically, intelligent infrastructure, data security and privacy protection, and digital twin maturity, three factors in the technological dimension, are the key factors driving manufacturing enterprises to adopt digital twin technology. At the same time, government incentive policies, application benefits, and industrial chain collaboration and cooperation in the environmental, organizational, and economic dimensions play an important role in the decision-making process. Based on this, targeted suggestions are put forward, aiming to provide strong theoretical support and practical guidance for the digital transformation and intelligent upgrading of the manufacturing industry.

In the context of major changes unseen in a century, opportunities and risks coexist. Organizational resilience, which refers to an enterprise′s ability to resist, respond to, and recover from internal and external shocks and challenges, is a key support and guarantee for the high-quality development of enterprises. With the rapid development of the digital economy, the connection between digital transformation and organizational resilience has become increasingly close. To deeply study the impact of enterprise digital transformation on organizational resilience and further explore the mediating and moderating roles of dual innovation and corporate social responsibility in this relationship, based on the dynamic capability theory, this paper takes listed manufacturing companies on the Shanghai and Shenzhen A-share markets from 2010 to 2022 as samples and uses multiple regression methods for empirical testing. This paper finds that enterprise digital transformation can significantly enhance organizational resilience. Notably, the impact of each stage of enterprise digital transformation on organizational resilience varies, with the basic data layout in the initial stage exhibiting the greatest positive impact. Moreover, the impact of enterprise digital transformation on organizational resilience also shows industry heterogeneity, with the technology-intensive industry demonstrating the greatest impact, followed by the capital-intensive industry, and the labor-intensive industry showing no significant effect. Further analysis reveals that enterprise digital transformation can significantly enhance organizational resilience through dual innovation, and corporate social responsibility positively moderates the promoting effect of enterprise digital transformation on dual innovation. In the mediation effect test, exploitative innovation plays a dominant role, with its contribution far exceeding that of exploratory innovation, and it is the key path for digital transformation to enhance organizational resilience. The research conclusions not only deepen enterprises′ understanding of the mechanism of the interaction between digital transformation and organizational resilience, encouraging them to accelerate the process of digital transformation but also provide useful decision-making references for government departments to formulate effective policies.