In the logistics sector, price competition is no longer the only form of horizontal competition between logistics service integrators; instead, it frequently takes the form of service efficiency competition among chains. Facing fierce market competition, vertical resource integration gradually becomes the trend in logistics industry integration. Using the inverse derivation method and comparative analysis, this study examines the relationship between the overall profit of its chain and that of the rival chain under service efficiency competition with or without the integration strategy. Furthermore, it builds two parallel competition logistics service supply chain models based on the inter-chain Nash competition and Stackelberg game of the chain members. The study results demonstrate that when the cost per unit of service efficiency is fixed, the greater the intensity of competition between chains, the more managers should tend to choose an integration strategy to maximize their profits. More interestingly, we find that the optimal integration decision of the supply chain is independent of the competitive intensity when the cost required to improve the unit service efficiency is extremely high.

Multiple production lines can work together to efficiently manufacture certain products. Thus, when capacity is insufficient, it is necessary to decide whether to develop new production lines to ensure the timely completion of all orders. For example, running a new production line for a small number of orders is not cost-effective. Therefore, decision-making involves choosing between paying tardiness costs for a few orders, abandoning some orders, or developing new production lines to maximize efficiency. Additionally, the timely transportation of completed orders is crucial and depends on vehicle usage efficiency. From a transportation perspective, fully loading vehicles is the most efficient, but this may impact the timeliness of orders, leading to potential tardiness costs. By comprehensively considering these aspects, a multi-machine production model is constructed that incorporates transportation batch sequences and uses heuristic algorithms to solve the problem. Finally, designed case examples validate the effectiveness of the model and algorithm.

In the context of globalized and complex supply chains, supply uncertainty occurs frequently. To reduce dependence on suppliers, retailers often consider holding strategic inventory and introducing private brands. To explore the relationship between private brands and strategic inventory strategies, and to determine the optimal strategic decisions, this paper constructs a two-stage supply chain model. Using game theory methods, we calculate the equilibrium outcomes of the supply chain under two scenarios: one with only national brands and the other with the introduction of private brands. The main findings are as follows. First, we identify the optimal decisions for both suppliers and retailers in each scenario. The influencing factors include perceived quality, inventory costs, and supply stability. Second, we find that there are constraints for retailers to activate strategic inventory, but these constraints are less restrictive when private brands are introduced. Finally, introducing private brands benefits retailers in implementing strategic inventory, although the extent of this impact depends on the conditions under which the strategic stockpile is implemented. These findings fill the gap in the existing literature on the impact of private brand introductions on strategic inventory under supply uncertainty and highlight valuable implications for business decision-makers.

The challenges in reducing emissions within agricultural supply chains mainly arise from the short-term self-interested behaviors of various stakeholders. To study the impact of the agricultural producer’s dual fairness concerns toward the manufacturer and retailer on profit distribution and emission reduction decisions, this paper develops a centralized model and two decentralized models (with and without dual fairness concerns) for a three-level agricultural supply chain. The paper derives the optimal emission reduction decisions, participant profits, and overall supply chain profits under different decision-making scenarios. The main findings are as follows: First, the centralized model results in higher supply chain profit, emission reduction, and market demand compared to decentralized models, where these factors remain unchanged regardless of fairness concerns. Second, in decentralized decision-making, fairness concerns raise the agricultural producer’s profit while reducing those of the manufacturer and retailer. The manufacturer always earns the highest profit, followed by the retailer. Finally, the agricultural producer’s fairness concerns do not affect emission reduction or overall profit, but they change profit distribution, with increasing concern toward one participant decreasing their profit and increasing the other’s. These findings fill the theoretical gap in existing research and provide valuable theoretical insights for governments and stakeholders in making decisions.