This paper focuses on the issue of product returns in live-streaming e-commerce supply chains, exploring the effectiveness of return shipping insurance strategies under different live-streaming models and the optimal decisions for brand owners in addressing consumer returns. By constructing four game theory models involving brand owner influencer streamers, and online retailers, the study systematically analyzes the adoption of return shipping insurance strategies and pricing strategies across various live-streaming operational modes, while also proposing optimal live-streaming mode choices for brand owners. The research shows that return shipping insurance can significantly reduce return handling costs for brand owners in high return rate scenarios, though its effectiveness is constrained by the level of shipping subsidies and related costs. Influencer live-streaming, supported by return shipping insurance, demonstrates a clear advantage; however, in cases of high return handling costs, brand-owned live-streaming, particularly when combined with technologies such as AI streamers, offers more pronounced benefits. The conclusions of this study provide important theoretical foundations and practical guidance for brand owners in managing product returns in live-streaming e-commerce.

In the supply chain management of fresh agricultural products, the performance of cold chain logistics supply chain is one of the important factors for the sustainable development of fresh enterprises. However, there are few researches on performance evaluation and prediction at present. Therefore, considering the final output of cold chain logistics operation, combined with the characteristics of recycling in sustainable development and cross-period operation of supply chain, A Dynamic Cyclic Network Data Envelopment Analysis model is designed for performance evaluation. It is found that the changes of expected output and unexpected output have a significant impact on the performance of cold chain logistics supply chain. The model considers the interaction between different time periods, provides a perspective for managers to examine the changes of relevant factors in supply chain performance, and provides help for managers to make resource allocation and decision. Meanwhile, Levenberg-Marquard algorithm is used to im-prove Convolutional Neural Networks to predict performance with minimum absolute error. The results show that LM-CNN effectively improves the accuracy of model prediction results. By using artificial neural network to predict the performance of supply chain in the future period, it helps managers to take active measures before the inefficiency, so as to improve the efficiency of supply chain operation.

This paper combines a third party logistics(TPL)providers preservation efforts with a fresh e-commerce companys pricing and inventory decisions. A Stackelberg game model is built, covering a fresh product supplier, a TPL provider, and a fresh e-commerce company. The effects of consumers freshness sensitivity coefficient, a TPL providers preservation cost, and a fresh e-commerce companys demand forecasts on product prices, freshness, and supply chain members profits are analyzed and solved, with numerical simulation support. Results show that when a fresh e-commerce company overorders, the supplier and TPL provider benefit, while the e-commerce company may suffer losses due to full-scale demand forecast risks. As consumers become more sensitive to freshness, product prices and a TPL providers preservation efforts rise. This boosts the suppliers and TPL providers profits but may increase the fresh e-commerce companys losses. Therefore, a fresh e-commerce company should adopt a conservative product demand forecasting strategy when determining order quantities.

To solve the problem of traceability in the vaccine supply chain, a dual effect of blockchain-enabled in monitoring vaccine flow and affecting consumers’ risk perception is considered and the Stackelberg game is used to compare and analyze the blockchain introduction decision of vaccine manufacturer and the pricing decision of vaccine supply chain. The research shows that:(1)The harm of the vaccine gray market is reflected in disrupting the market price order and reducing the profits of vaccine manufacturer and vaccine supply chain.(2)Vaccine manufacturer is always willing to introduce blockchain to suppress the vaccine gray market. However, vaccine manufacturer refuses to build blockchain to the extent required to completely suppress the vaccine gray market, which explains why the introduction of blockchain still cannot completely suppress the gray market in reality.(3)The introduction of blockchain by vaccine manufacturer helps to increase immunization coverage and rebuilt vaccine trust, but contrary to the intuitive feeling, it will reduce consumer surplus and social welfare in some cases.

In order to analyze the impact of altruistic preference(AP)and government subsidy on the closed-loop supply chain(CLSC)of power batteries, this paper constructs a CLSC of power batteries composed of the battery manufacturer, retailer, and third-party recycler. In the context of the battery manufacturer exhibiting AP towards the third-party recycler, this paper utilizes game theory to establish three decision models: without subsidy policy, subsidy for battery manufacturer in eco-design, and subsidy for third-party recyclers in recycling cost. The research results show that:(1)AP of the battery manufacturer can increase the recycling rate and social welfare, and maintain the stability of the supply chain system, but at the cost of the manufacturers profits;(2)When the government implements a subsidy policy for the recycling cost of the third-party recycler, the recycling rate of used power batteries is the highest. However, when the battery manufacturer exhibits strong AP, the recycling cost subsidy policy may have adverse effects on social welfare;(3)In the model of the government providing subsidy for the battery manufacturer in eco-design, social welfare is significantly higher than in the other two models, but the recycling rate of used power batteries is the lowest.

Taking a two-tier supply chain composed of a supplier and a manufacturer as the research object, this paper explores the impact of blockchain technology on low-carbon technology sharing strategies within the supply chain. By introducing the time factor, differential game models are constructed for six scenarios: scenarios without incentive contracts, with cost-sharing contracts, and with revenue-sharing contracts, both before and after blockchain implementation. A comparative analysis reveals that before blockchain implementation, the level of low-carbon technology sharing effort by both the supplier and the manufacturer under a cost-sharing contract is higher than that under no incentive contract, while the implementation of a revenue-sharing contract depends on the proportion of revenue shared by the manufacturer with the supplier. Furthermore, given determined cost-sharing and revenue-sharing ratios, the manufacturers selling price after blockchain implementation is higher than before under any contract type. The selling price under a cost-sharing contract is the same as that under no incentive contract. When the blockchain cost exceeds a certain threshold, the selling price under a revenue-sharing contract is higher than under the other two contracts; otherwise, it is lower. The study also finds that with appropriate blockchain usage costs, a cost-sharing contract can enhance the level of low-carbon technology sharing in the supply chain without affecting the manufacturer's selling price or the level of sharing effort. However, if the blockchain usage cost is too high, it may instead reduce the supply chain's technology sharing level.

This paper establishes a two-stage fuzzy logic reasoning system. In the first stage, the model expresses the factors that affect the attackers behavior through fuzzy sets. In the first stage, fuzzy logic system inputs those fuzzy sets and outputs the results based on fuzzy inference rules. In the second stage, the output results obtained in the first stage and the defender's benefit parameters are used as input parameters for the fuzzy logic system, and the final defender deployment strategy is inferred through fuzzy logic inference system.

Based on the logical analysis framework of “e-commerce industry and urban-rural development,” this study first establishes a comprehensive evaluation index system to measure the level of urban-rural integrated development in 16 prefecture-level cities in Shandong Province from 2014 to 2023. Then, using a mediation effect model, the impact of e-commerce development on urban-rural integrated development is verified, and action paths and policy recommendations are proposed. The results indicate that the integrated development of urban and rural areas in Shandong Province is characterized by “overall improvement and multidimensional differences.” Economic integration and ecological integration are the main growth drivers. The mediation effect test shows that e-commerce development significantly promotes urban-rural integration, partially through the mediating effect of industrial structure upgrading. For every 1% increase in the level of e-commerce development, the level of urban-rural integrated development increases by 0.015 6 units, of which 0.007 6 units are attributed to the mediating effect of industrial structure upgrading, accounting for 48.7% of the total effect. These results reveal the inherent mechanism of the impact of e-commerce on urban-rural integration, providing empirical evidence for promoting urban-rural integrated development through the synergy of e-commerce development and industrial structure optimization.

This paper studies the impacts of government subsidies, altruistic preferences, and cost-sharing contracts on the new energy vehicle(NEV)supply chain. By employing Stackelberg game theory, we construct five decision-making models to analyze how subsidies and altruistic preferences influence supply chain decisions. The findings reveal that:(1)The profitability of the NEV supply chain is jointly shaped by government subsidy mechanisms and suppliers R& D investments, and their synergy can lead to Pareto improvements in stakeholders profits.(2)Consumers preference for green driving range capability serves as a key market driver, promoting simultaneous growth in price and profit while encouraging supply chain participants to enhance environmental performance.(3)Battery suppliers altruistic behavior exhibits a threshold effect on supply chain equilibrium, generally exerting a positive influence on green outcomes and coordination performance, moderated by R& D costs.(4)Cost-sharing contracts have multi-dimensional effects on technological upgrades, price dynamics, and profit distribution, with an optimal cost-sharing ratio existing to maximize overall utility. The results provide a theoretical paradigm and practical pathway for precision formulation of government industrial subsidy policies and dynamic optimization of corporate R&D cooperation strategies in the NEV sector.

This study examines the impact of parallel exports of new energy vehicles on competitive supply chains in a dual-market environment where consumer willingness to pay varies. By constructing game models for three scenarios of no parallel exports, authorized distributors participating in parallel exports, and third-party speculators engaging in parallel exports, we analyze how different export patterns influence pricing decisions, profits, and social welfare for manufacturers and authorized distributors. Findings reveal that when consumer willingness-to-pay in the low-willingness market falls below a specific threshold, authorized distributors will engage in parallel exports, boosting their own profits but harming the manufacturer's profits. When the price differential between the two markets is sufficiently large, third-party speculators will choose to engage in parallel exports, causing losses to both the manufacturer and authorized distributors. Furthermore, any form of parallel export diminishes social welfare and consumer surplus.

This paper constructs a two-tier supply chain model involving an intelligent system supplier and a new energy vehicle(NEV)manufacturer. Focusing on cooperation modes led by the manufacturer and the supplier, this study employs the Stackelberg game approach to derive the equilibrium strategies and profits of supply chain members, and further examines the selection of cooperation modes in the NEV supply chain. The findings reveal that:(1)When the sales revenue allocation ratio and the R& D cost coefficient exceed a certain threshold, the supplier-led mode results in a higher level of product intelligentization;(2)The R& D cost coefficient and elasticity coefficient exert a significant impact on equilibrium decisions;(3)For both the manufacturer and the supplier, the choice between cooperation modes is influenced by the sales revenue allocation ratio. Under the supplier-led mode, by setting a reasonable sales revenue allocation ratio, both the manufacturer and the supplier can achieve higher profits, thereby realizing a win-win outcome.

This paper develops a new multi-attribute decision-making method for hydraulic engineering based on the q-order orthogonal fuzzy zhenyuan integral(q-ROFZI)operator to tackle the complex nonlinear correlation between attributes. Frist, considering the vagueness and uncertainty of the evaluation information, the expert evaluation information was characterized using q-order orthogonal fuzzy numbers. Then, introducing the 2-additive fuzzy measures to fully identify and measure the complex association relationship among the decision attributes, determine the interaction degree and fuzzy measure value of the attribute sets. Then, the q-ROFZI operator is proposed by extending the Zhenyuan integral to q-order orthogonal fuzzy set theory. The correlation measurement information between attributes is comprehensively assembled, and the decision-making scheme is ranked according to the score function of the comprehensive utility value to determine the optimal scheme. Finally, the q-order orthogonal fuzzy Choquet integral operator was utilized for comparative analysis in real accident cases, through the analysis of the ideal scheme in the ranking and the analysis of the most relevant scheme.The results demonstrate that the propsed method can enhances the ability to accurately portray complex nonlinear relationships among attributes and can fully the fusion association measure information. The decision results are more consistent with the actual decision-making situation.

Using a complex systems perspective, this paper develops an integrated model combining interpretive structural modeling(ISM), decision experiment and evaluation laboratory(DEMATEL), and cross-impact matrix multiplication(MICMAC)methods to analyze the interactions of resilience factors under such impacts. The study finds that IoT, big data, and blockchain technologies are key drivers for enhancing resilience, with blockchain improving the reliability of information transmission. Key factors influencing supply chain operations include blockchain technology, risk preference, and internal cooperation.

The market-oriented promotion of recycled construction and demolition(C& D)waste products involves strategic interactions and co-evolution among multiple stakeholders. Based on multi-agent evolutionary game theory, this study systematically analyzes the payoff structures and behavioral incentives of four core stakeholders-government, production enterprises, user enterprises, and the public, and constructs a dynamic four-party evolutionary game model. Under differentiated government regulation scenarios, the study explores the evolutionary paths and behavioral stability of stakeholders in terms of supply-side incentives, demand-side market responses, and public perception of recycled products. Numerical simulations reveal that public acceptance of recycled products significantly influences strategic decisions of production and user enterprises. When the government regulation intensity threshold is p≥0.35 and the minimum procurement ratio of user enterprises is m≥0.1, the system can overcome the "low-level lock-in" and converge toward an effective equilibrium, thereby promoting efficient utilization of recycled products. The findings suggest that dynamic and precise subsidies should be based on the cost differential between traditional and recycled materials, and regulatory costs can be structurally transferred into incremental subsidies for recycling enterprises.