With the rapid growth of e-commerce, platform-based financing in electronic business (EB) has emerged as an innovative solution for online retailers facing capital constraints. This study develops a Stackelberg game-theoretic framework to analyze strategic financing decisions in a two-tier e-commerce supply chain, where an electronic business platform (EBP) , as the leader, assumes leadership by setting financing interest rates, while a capital-constrained, loss-averse online retailer (LOR), as the follower, optimizes order quantities and financing participation under behavioral risk preferences. A hierarchical game-theoretic framework is established to examine strategic interactions between an EBP and a LOR, and the equilibrium outcomes are given. The model derives optimal decisions for both financing rates and ordering strategies. Results demonstrate that when the retailer's initial capital grows, their necessity for external financing diminishes correspondingly, leading to smaller order quantities due to reduced bankruptcy risk. Moreover, higher levels of loss aversion cause retailers to order less and avoid financing, reflecting risk-sensitive behavior. The study also presents comprehensive numerical analyses to explore additional managerial implications, offering insights into how capital availability and behavioral factors like loss aversion shape decision-making in EB financing environments.

Under the rapid development of the global economy, environmental pollution has intensified significantly. The evolving external environment presents both opportunities and challenges to traditional supply chains. As an innovative management philosophy and practical approach, the green supply chain has rapidly become an integral component of corporate sustainable development strategies. However, the transition from traditional supply chain to green supply chain necessitates effective collaboration and coordination among supply chain members. Contractual coordination has therefore emerged as an effective methodology to enhance operational efficiency and profitability across supply chain participants. To investigate the impact of various coordination mechanisms on the optimal decision-making of green supply chains, we construct a Stackelberg game model involving bilateral green investments by both manufacturer and retailer within a two-echelon green supply chain system. Considering the bilateral green efforts from both manufacturer and retailer, we comparatively analyze game equilibrium solutions under three scenarios: non-coordination, cost-sharing contract coordination, and two-part contract coordination. Specifically，we examine how these coordination mechanisms influence pricing strategies, green investment levels, and profit distributions within the supply chain network. Finally, the results are validated and illustrated using numerical simulation. It is discovered that 1) the cost-sharing contract cannot simultaneously increase the Pareto improvement of producers' and retailers' revenues; 2) the cost-sharing contract cannot increase the social utility and additive greenness of products; however, it can improve the marketing effort; and 3) When retailers maintain an optimistic stance toward manufacturers' green initiatives, the two-part tariff contract enables concurrent Pareto improvements in both parties' profits while simultaneously enhancing product greenness, marketing efforts, and social welfare, thereby achieving efficient supply chain coordination.

This paper investigates a closed loop supply chain (CLSC) encompassing a manufacturer, a retailer, and consumers operating within the carbon trading scheme. Employing the focus theory of choice, we analyze the decision-making processes of the retailer, considering various personality traits. A Stackelberg game is formulated, wherein the manufacturer assumes responsibility for recycling activities. The research explores the impact of the retailer’s optimism and confidence levels on optimal decision-making within a positive evaluation system. Numerical examples are employed to elucidate equilibrium solutions, illustrating the correlation between the retailer’s personality traits and the manufacturer’s optimal decisions. Furthermore, a sensitivity analysis is conducted on the carbon trading price and the manufacturer’s carbon emission quota allocation within a single cycle under the carbon trading scheme. The investigation concludes with an examination of the influence of recycling prices on the manufacturer’s optimal revenue. The findings indicate that retailers with distinct personality traits adopt varied pricing strategies. Decreases in optimism and self-confidence levels prompt the retailer to opt for relatively lower retail profit pricing. Simultaneously, the manufacturer demonstrates a preference for collaborating with a retailer characterized by optimism and lower confidence levels, thereby enhancing overall manufacturing revenue. Notably, under the carbon trading scheme, fluctuations in carbon trading and recycling prices distinctly influence the manufacturer’s decisions.

This paper considers a dual-channel supply chain with two members, comprising a manufacturer and an online platform. We mainly investigate the influence of various key system variables on manufacturer encroachment strategy and all members’ optimal decisions through Stackelberg game models. Our findings show that, regardless of the size of each parameter, the encroachment strategy is always optimal to the manufacturer; the manufacturer may be motivated to choose the direct selling channel and the platform may opt for the agency selling channel due to a high commission rate. Moreover, when the inter-channel substitution rate is high, the encroachment strategy has a diminishing positive effect on the manufacturer and an increasing negative effect on the platform so that the platform may temporarily benefit from the manufacturer encroachment; in cases where the inter-channel substitution rate is not high, the encroachment strategy always yields advantages for the manufacturer while causing disadvantages for the platform. In addition, if the elasticity coefficient is large, both the manufacturer and the platform are inclined to the reselling channel, that is, if the platform service cost is high, it is advisable for the platform to reduce its investment of service to avoid negative effect.

The efficient management of reverse supply chains, particularly the collection and remanufacturing of defective products, plays a critical role in reducing production costs and determining the final pricing of remanufactured products. While existing research extensively explores warranty policies and maintenance services to enhance customer satisfaction and profitability, the integration of vehicle routing for product collection and sustainability advertising strategies remains underexplored. Addressing this gap, this study introduces a comprehensive two-stage reverse supply chain model that captures the interactions between manufacturers (MFRs) and remanufacturers (RMFRs) through a Stackelberg game framework. Methods: The proposed model incorporates interactive production constraints, vehicle routing problem (VRP) for optimizing collection logistics, and sustainability advertising to influence consumer behavior towards remanufactured products. Utilizing mixed nonlinear programming (MINLP) and nonlinear programming (NLP) techniques, the model simultaneously optimizes pricing strategies, collection efforts, and advertising investments for both MFRs and RMFRs. Numerical analyses are conducted to solve the optimization problems, accompanied by sensitivity analyses to evaluate the impact of key parameters such as production costs, defect rates, and routing constraints. The numerical results demonstrate that increases in production costs for MFRs lead to higher selling prices, thereby reducing their profit margins and negatively impacting RMFR profitability due to decreased demand for remanufactured products. Sensitivity analysis reveals that higher defect rates (α ≥ 0.8) significantly diminish overall supply chain profitability by lowering customer acceptance of RMPs. Additionally, expanding the allowable vehicle routing distance L effectively reduces collection costs, enhancing RMFR profits and enabling greater investment in sustainability advertising. The study shows that the integration of VRP and advertising strategies proves crucial in balancing cost efficiencies and market competitiveness, ultimately fostering a more sustainable and profitable reverse supply chain.

Due to the deep integration of modern information technology, supply chain management has moved into a new stage of a smart supply chain. Considering the dual smart innovation of the manufacturer's production and retailer’s service, the manufacturer-led Stackelberg game model is constructed in the smart supply chain. Under the single and coordinated government subsidy strategies, the optimal decisions of the smart supply chain are researched, and the impacts of manufacturers' risk aversion on the government subsidy strategies and supply chain decisions are analysed. In addition, the efficiencies of different government subsidy strategies are compared and analysed by numerical simulation. Finally, the results show that: (i) The moderate risk aversion by the manufacturer can improve social welfare and help provide consumers with more affordable products. (ii) The government expenditure and product prices are highest under the coordinated subsidy strategy. (iii) Subsidising manufacturers is more beneficial than subsidising retailers among the two single government subsidy strategies. (iv) In general, the coordinated government subsidy strategy is more effective than the single subsidy strategy for the innovative development of a smart supply chain. In conclusion, the research provides a significant practical reference for jointly building the smart supply chain.

The growing popularity of aggregation platforms has attracted widespread attention in the ride-hailing market in recent years. In order to obtain additional orders by charging commissions and slotting fees, many ride-hailing platforms choose to bundle with aggregation platforms. Unlike traditional reseller electronic channels, the bundle channels may affect pricing of platforms, service levels of drivers, market demands and they may further impact on profits. These different attitudes raise an interesting and key question about the influence of bundle channels in ride-hailing platforms. In this paper, we propose an analytical framework for pricing strategies of ride-hailing and aggregation platforms under bundle mode and analyze their pricing process from the perspective of Nash and Stackelberg games, where the platforms serve as leaders to determine optimal prices through Nash equilibrium and the drivers serve as followers to provide optimal service levels. Through sensitivity analysis of service levels and costs, we capture the distribution trends of profits between the platforms. Based on some numerical examples and results analysis, some interesting managerial insights on pricing of ride-hailing and aggregation platforms are gained.

As a useful strategy to improve the flexibility of the system to manage uncertainty in supply and demand and to improve the sustainability of the supply chain, vendor-managed inventory (VMI) programs have attracted widespread attention in the field of supply chain management. However, a growing body of empirical literature has shown that participants’ decisions deviate significantly from the standard theoretical predictions. Under a VMI program, the supplier bears not only the production cost, but also the risk of leftover inventory. Moreover, the inequality among participants and different personalities of decision-makers in VMI programs may lead to the divergence of decision-making. To understand the supplier’s replenishment decision in view of the behavioral pattern, we propose a new inventory model for the supplier with the focus theory of choice. The proposed model conceives that the retailer evaluates each replenishment quantity based on the most salient demand for him/her instead of calculating the expected utility. By employing this inventory model, we construct a two-tier supply chain model with revenue-sharing contract and theoretically derive the optimal sharing percentage of the revenue and replenishment quantity. Results analysis gains managerial insights into the strategic selection of the retailer who faces suppliers with different personalities. Comparisons between the classic revenue-sharing contract model and the proposed model are also carried out by illustrative examples. This research provides a new perspective to analyze individual supplier’s behavior in a VMI program with revenue-sharing contracts.

As customers' orientation towards environmental products increases, manufacturers and other members of the supply chain are looking for ways to conduct their operations in an environmentally and cost-effective manner. To find a solution that compensates these requests, a game theoretical approach is developed for a two-stage green supply chain consisting of a supplier and a producer. A Stackelberg game model based on asymmetric information structure is developed to find the optimal lot sizes and raw material sales price for raw material supplier, and the product sales price and the environmental cost for the producer. The developed approach is illustrated on a real-world case study that deals with production and raw material procurement processes of a plastic plug and compared to a scenario in which no environmental expenditures exist. The effect of changes in the model has been observed by tuning some significant parameters with the experimental design approach.

The major challenge, which the financially insufficient firm tries to overcome, is the uncertain demand during the sales season and the possible bankruptcy due to the lower demand than the initial order quantity. Most traditional studies on the operational decision problem address this challenge by assuming that the retailer has enough capital to procure as many products as necessary. However, small and medium size firms with insufficient capital or even startup companies are generally financially constrained for procuring or producing the product. Thus, to address the financially constrained problem, in this study we model a financially constrained two-level supply chain consisting of a financially-deficient retailer and a bank. In this supply chain, the supplier can sell a product at two wholesale prices to the retailer before and during the sales season, respectively. Then the retailer makes an initial order to the supplier with this loan from the bank and then sells the product to its customers at a selling price during the sales season. Moreover, if the realized demand is more than the initial order quantity, the retailer can make the second order at a higher wholesale price than the initial wholesale price. The analytical results from this model can be summarized as follows: First, the retailer’s optimal initial ordering decision is a non-increasing function of the bank’s decision, interest rate. Second, as the procuring cost through the quick response increases, the retailer’s initial ordering quantity increases and thus the amount of loan from the bank increases. Third, as the retailer’s initial capital increases, the amount of loan from the bank decreases. Forth, the retailer’s initial ordering quantity with the quick response strategy is almost surely less than without the quick response strategy.