The intelligent transformation of logistics plays a significant role in meeting the diverse needs of customers, improving operational efficiency, and reducing carbon emissions in logistics activities. Therefore, to achieve sustainable development, logistics enterprises need to face the decision-making problem of intelligent logistics transformation. In this paper, we construct a Stackelberg game model between a financially constrained logistics-service provider (LSP) and a well-funded logistics-service integrator (LSI) and discuss the impact of the wholesale price contract, the cost-sharing contract, the revenue-sharing contract, the two-part tariff contract, and the hybrid cost-sharing and revenue-sharing contract on the intelligence level of logistics services, the profits of supply-chain members, and the channel for logistics-service demand. We found that the cost-sharing contract and the revenue-sharing contract cannot achieve Pareto improvement in the profits of supply-chain members. In addition, the increase in bank-loan interest rates would seriously weaken the level of intelligence and market demand for the entire logistics service. However, when consumers do not have high requirements for the intelligence of logistics services, the two-part power–price contract can create a win–win situation for supply-chain members and increase market demand within a certain range; on the contrary, a hybrid contract of cost sharing and revenue sharing is the best choice. Moreover, in the process of contract design for the intelligent transformation of logistics services, it is necessary to pay attention to the influence of the price-sensitivity coefficient on decision-making.

A logistics service integrator (LSI) usually requires a logistics service provider (LSP) to carry out smart transformation in order to improve the level of logistics service. However, LSP’s smart transformation faces uncertainty in terms of investments and income, which seriously hinders LSP’s enthusiasm for logistics service innovation. In this paper, we construct a logistics service supply chain (LSSC) consisting of an LSI and an LSP to explore the incentive mechanism for LSPs to undergo smart transformation. As a benchmark for comparison, we first obtain the equilibrium results under centralized decision making and wholesale price (WP) contracts. Then, cost-sharing (CS), revenue-sharing (RS), and cost sharing–revenue sharing (CS-RS) hybrid contracts are proposed. It is found that when the CS coefficient is in a certain interval, the CS contract can increase the profit of LSI and the smart level of logistics service, but it will decrease the profit of LSP. With the exception that the wholesale price of logistics services will decrease, the equilibrium results under the RS contract and WP contract remain consistent. Only the CS-RS hybrid contract can achieve the perfect coordination of LSSC. In addition, by conducting numerical analysis, we find that the enhancement of the smart effect can encourage LSP to improve the smart level and increase the overall revenue of LSSC. To the best of our knowledge, this paper is the first study to explore the incentive mechanism between LSI and LSP in the context of logistics service smart transformation. Our findings guide the LSI in implementing an effective contract.

This paper explores the logistics strategy selection of a manufacturer that uses two sales channels (resale and agency channels) to sell the same product through an E-commerce platform. The agency channel offers two logistic strategies, low-quality logistics services provided by third-party enterprises (Strategy N) and high-quality logistics services provided by the platform (Strategy S). When the manufacturer opts for Strategy S, a portion of the market share of the resale channel shifts to the agency channel, which results in the platform logistics effect. We developed a game-theoretic model to investigate the equilibrium results of a manufacturer under different logistics strategies. The results show that there exists a threshold for the platform logistics effect. When the platform logistics effect is lower than this threshold, the manufacturer prefers Strategy N. Otherwise, the manufacturer prefers Strategy S. However, when the platform logistics price reaches a certain level, the manufacturer will always prefer Strategy N. Our study provides valuable insights for manufacturers and e-commerce platforms to optimize their operational decisions based on different logistics strategies. It also helps manufacturers make rational choices about logistics strategies.

This study adopts an evolutionary game theory framework and focuses on the strategic interaction between brands and KOLs. It examines how the two parties interact under conditions of uncertainty and risk, especially when the KOLs’ contract fulfillment capability is low, and how they adjust strategies to achieve sustainable collaboration. Different from previous studies, this paper not only examines objective parameters such as commission rate, brand value, return cost, and reputation risk, but also introduces behavioral factors, including risk preference, loss aversion, and the psychological perception of gains and losses. By modeling the decision-making process of KOLs and brands under uncertainty and risk, the key factors affecting the evolution of cooperation strategies are identified. The simulation results show that although the cooperation strategy (such as information disclosure and truthful promotion) can achieve stability under certain conditions, the system is highly sensitive to external factors (such as environmental uncertainty) and internal psychological factors (such as risk preference and loss sensitivity). This study provides practical suggestions for brands and KOLs to promote long-term cooperation, emphasizing the importance of incentive coordination, reputation risk management, commission structure optimization, and psychological perception regulation. These findings provide practical guidance for enhancing the sustainability of brand–KOL collaborations.