Considering the supply chain composed of a single manufacturer and a single platform, where the manufacturer implements the emission reduction strategies and the platform fulfills CSR(corporate social responsibility), the Stackelberg game models between manufacturer and platform are built under four combination cases that the government subsidizes the manufacturer based on the R&D cost for emission reduction and based on the low-carbon production, and the platform supply chain adopts the wholesale mode and the agency mode, respectively, together with the optimal pricing and emission reduction decisions of the supply chain by solving the models. Based on comparative analysis, the optimal subsidy strategy of the government and the optimal sales model of the platform supply chain are obtained. Through numerical simulation, we analyze the impacts of the subsidy coefficient, consumers low-carbon preference, platforms fulfillment of CSR, and low-carbon promotional efforts on the supply chains decision-making and social welfare under the two subsidy modes. The research shows that: the level of carbon emission reduction, the total profit of manufacturers and supply chain, the degree of environmental improvement and the level of social welfare are higher in the agency mode than in the wholesale mode. In the wholesale model, the retail price of low-carbon products and platform profits are higher. The subsidy strategy based on the low-carbon production is more conductive to increasing manufacturers profits, while the strategy based on emission reduction cost is more favorable to platforms profits. From the dimensions of improving the level of carbon emission reduction, the degree of environmental improvement and the level of social welfare, the subsidy strategy based on the R&D cost is optimal strategy of government, and the improvement of the level of social welfare is more significant under the subsidy strategy based on the low-carbon production.

This paper examines the choice of recycling channels and low carbon emissions reduction in a closed-loop supply chain consisting of a manufacturer and a retailer in an omni-channel retail model. A demand function influenced by sales price and level of abatement technology under the omni-channel retail model was quantified, taking into account that manufacturers regulated by carbon tax policies reduce carbon emissions by investing in abatement technology. An omni-channel closed-loop supply chain game model is constructed for the manufacturer-recycling and retailer-recycling scenarios, and the corresponding joint pricing and abatement strategies are solved separately. The optimal strategy for the closed-loop supply chain is then compared with that of the closed-loop supply chain without technological inputs, and it is concluded that manufacturers technological inputs can improve the profitability and environmental performance of the closed-loop supply chain system under the omni-channel retail model. Finally, numerical examples are used to further analyse the impact of different recycling methods, emission reduction technology levels and carbon tax policies on supply chain decisions. It is found that manufacturers are responsible for recycling their products, resulting in higher profits and lower carbon emissions in the closed-loop supply chain of the omni-channel retail model than if retailers were to recycle their products; an appropriate increase in the carbon tax would not only increase the incentive for manufacturers to invest in reducing emissions, but would also increase the recycling rate of used products.

Under carbon emission constraints, this paper addresses the complexity of a dual-channel supply chain with bidirectional fairness concerns between manufacturers and retailers. A multi-period dynamic game model is developed to analyze the effects of decision-variable adjustment speed, fairness concern intensity, and carbon trading price on supply chain decision-making and profitability from a systemic complexity perspective. The research reveals the evolutionary behavior of the economic system and proposes chaos control strategies. Key findings include: Excessively high adjustment speeds in decision variables can induce a chaotic state in the system via period-doubling bifurcation. A dominant retailer influences the overall stability of the supply chain, whereas a follower manufacturer only affects local stability. System chaos harms the party causing it but benefits the other. Fairness concerns and carbon pricing impact member profits, though the extent depends on system stability. A parameter-based control method is proposed to effectively suppress chaos and restore stability.

Addressing the optimal design of sustainable and personalized supply chain networks for new energy vehicle(NEV)parts under the context of carbon neutrality, a robust optimization model based on a sustainable and personalized closed-loop supply chain network is established to tackle uncertainties within the supply chain network. Firstly, uncertain parameters are described using uncertainty sets, and a mixed-integer programming model is formulated for the NEV parts supply chain network structure, aiming to minimize transportation costs, processing costs, operational costs, and carbon emission costs. Additionally, a personalized evaluation mechanism for supply chain products is proposed based on the hypergeometric distribution method. Secondly, the execution strategy parameters of the original wild dog algorithm(WDA)are dynamically adjusted, and the population group attack strategy is integrated with the Lévy flight strategy to enhance the algorithm's global optimization accuracy and convergence speed. Finally, numerical and simulation analysis conducted in MATLAB demonstrates that the proposed robust optimization model, combined with the improved WDA, exhibits significant advantages in solving the design problem of closed-loop supply chain networks for NEV parts.

The logistics platforms invest in blockchain services, which is conducive to improve the information credibility and system operation efficiency of platforms. To study the investment strategy of blockchain service of logistics platforms in competitive environment, this paper constructs a game decision model of different investment strategy combination of blockchain service of competitive logistics platform based on Hotelling model and considering the trust gain and transaction time reduction degree of blockchain service. The study found that regardless of whether competitors invest in blockchain services, logistics platforms with more information disclosure are more willing to invest in blockchain services, and the willingness of platforms to invest in blockchain services will decrease with the increase of the degree of difference between logistics platforms and the fixed cost of investment. If the rival platform does not invest in blockchain services, the willingness of the logistics platform to invest in blockchain services is positively correlated with the trust gain and transaction time reduction of blockchain services; if rival platforms invest in blockchain services, the willingness of logistics platforms to invest in blockchain services is negatively correlated with trust gain and transaction time reduction.

The impact of financial subsidies and green consumption intention on corporate green innovation is considered. It constructs three game models to analyze the influence of financial subsidies and green consumption intention on product prices and levels of green innovation from the perspective of social welfare, and explores the possibility of subsidy reduction. The research shows that when environmental positive externalities are significant, green consumption intention can drive up product prices and sales volumes. If consumer surplus accounts for a high proportion of social welfare, green consumption intention will promote corporate green innovation and profit growth. When green consumption intention and financial subsidies act simultaneously, green product prices, sales volumes, levels of green innovation, corporate profits, and social welfare are maximized. At this point, there exists an optimal subsidy level; when subsidies exceed this level, the government should adopt a subsidy reduction policy. Additionally, using development data from the Chinese new-energy vehicle industry as a sample, this paper empirically tests the impact of financial subsidies and green consumption intention on the level of core technological innovation in new-energy vehicles. It finds that the effect of green consumption intention on product innovation levels is greater than that of financial subsidies, and the combined effect of both is even more significant.

This study investigates a two-tier low-carbon supply chain consisting of manufacturers and retailers. A Stackelberg game model is constructed, and backward induction method is applied for solution. Under the carbon tax policy, the study analyzes the impact of consumer environmental preference level and skepticism on manufacturers' equilibrium decision-making and carbon label selection. The research results indicate:(1)Consumer environmental preference levels and degrees of skepticism exert positive influences on the low-carbon attributes of products, wholesale prices, retail prices, and promotional efforts intensity.(2)When consumers have low levels of doubt, manufacturers choose to self label; When consumers have a high level of doubt, manufacturers choose certification labels. Under the carbon tax policy, manufacturers prefer to self label to compensate for the cost loss caused by the carbon tax, while retailers do not need to pay additional costs to follow manufacturers in making carbon label choices.(3)Under the carbon tax policy, manufacturers would only actively choose certification labels when consumers environmental awareness is high, carbon tax rates, and emission reduction difficulty coefficients are high, otherwise the self labeling strategy is better.

To comply with carbon reduction policies or reduce production costs, manufacturers of low-value products can adopt two green production strategies: remanufacturing alone or remanufacturing with additional carbon emission reduction(CER)technology investment.This paper develops a closed-loop supply chain(CLSC)model consisting of a manufacturer, retailer, third-party recycler, and carbon-conscious consumers. We analyze the manufacturers optimal production strategy under carbon tax policy, then extend the study to cap-and-trade policy and scenarios incorporating consumer preferences for remanufactured products.Key findings indicate:(1)Under uniform carbon policy, manufacturers consistently prefer CER-integrated remanufacturing when the technology investment proves profitable;(2)In hybrid policy scenarios where standard remanufacturing operates under cap-and-trade while CER remanufacturing falls under carbon tax, manufacturers choose conventional remanufacturing when CER costs exceed a threshold;(3)Under carbon tax, significant consumer preference for remanufactured products leads manufacturers to select standard remanufacturing, otherwise CER remanufacturing is preferred.These results provide operational guidance for manufacturers navigating carbon-regulated markets.

At present, many software developers not only sell software to users through downstream service providers, but also directly sell software and services to users. In this study, we build the models of "Authorization" and "Authorization+Direct Sales" respectively, and study the authorization sales and channel encroachment strategies of the developer, as well as the service quality investment and software sales strategies of the provider. Moreover, we analyze the impact of developers channel encroachment on the profits of supply chain members and the total supply chain profit. The conclusions show that:(1)in the "Authorization" mode, the decision of the developer will not affect the software sales pricing decision of the provider, but only affect the pre-sales service quality decision of the provider; in the "Authorization+Direct Sales" mode, the decision of the developer will affect the software sales pricing decision and pre-sales service quality decision of the provider; in addition, the channel encroachment of the developer can dampen the enthusiasm of the service provider and stimulate its enthusiasm.(2)Channel encroachment will cause the developers own software sales/authorized profit to decline, but it can increase the sales of software and extended warranty services(EWS)and improve the software developers EWS sales profit.(3)If the market size occupied by the developer is small, channel encroachment can improve the profit of the provider; however, if the developer occupies a large market and both parties conduct low-intensity software competition, channel encroachment will reduce the profit of the provider; in addition, when the developer occupies a large market, both parties carry out high-intensity software competition, and the developer has(loses)low-cost advantages, channel encroachment can reduce(improve)the profit of the provider.(4)If the market size occupied by the developer is small, channel encroachment can improve the total supply chain profit and also reduce the total supply chain profit; however, if the developer occupies a large market, channel encroachment will always reduce the total supply chain profit.

To solve the high cost and low efficiency of the intermodal transportation applied in long-distance and bulk transportation, this study explores an intermodal routing problem with fuzzy soft time window whose aim is to minimize the transportation costs. Meanwhile to improve the reliability of the intermodal routing in the actual transportation, this study formulates the uncertainty of the goods demand of the customer, and further explore the multiple uncertainty introduced by the uncertain demand that includes the uncertainty of transportation costs and time and of the service level constraints and capacity constraints. Based on the utilization of the trapezoidal fuzzy number to describe the uncertainty, this study establishes a fuzzy programming model to deal with the intermodal routing problem under multiple uncertainty, and utilizes the fuzzy chance-constrained programming method based on credibility measure to realize the crisp reformulation of the model to make the problem solvable. This study further develops an Ant Colony Optimization algorithm based on network transformation to solve the crisp model efficiently. The results of the numerical case demonstrate the feasibility of the chance-constrained programming model and Ant Colony Optimization algorithm. The influence of improving the service level and the confidence level on the costs of the intermodal transportation is clarified by using the sensitivity analysis. The experimental simulation of the numerical case further indicates the relationship between the confidence level and the reliability of the route that the reliability of the route trends to enhance with the improvement of the confidence level, however, they are not equivalent, and improving the confidence level will not lead to an absolute reliability enhancement. The numerical case simulation also verifies that considering demand uncertainty significantly improves the reliability of the routing in the actual transportation, and further reveals that the economy and reliability objectives of the routing are in conflict with each other. The customer and intermodal transportation operator can accordingly make tradeoffs among the economy, timeliness and reliability of the transportation to effectively improve the comprehensive level of the intermodal transportation.