关键词: 车联网平台, 汽车后市场, 服务供应链, 博弈论

Abstract: The automotive aftermarket shows growth potential due to rising vehicle ownership and aging vehicles. However, demand uncertainty challenges aftermarket stores in attracting customers. Some aftermarket stores have been integrated into Internet of Vehicles (IoV) platforms to monitor vehicle operations, provide alerts, and recommend services, attracting customers to aftermarket stores. Companies like AliOS and SAIC are implementing this model. To expand the user base of IoV service platforms, three cooperation modes exist within the “IoV+aftermarket” service supply chain: (1)Promotion mode, where the IoV platform promotes itself through sending car repair and maintenance advertisements accurately, increasing user numbers. (2)Subsidy mode, where the platform offers subsidies to owners and users to enhance their utility and encourage platform usage. (3)The “promotion+subsidy” model, a combination of the first two, which simultaneously provides precision marketing and offers subsidies to attract more car owners and users. However, the current “IoV+aftermarket” cooperation model faces several issues: (1)The supply chain cooperation between IoV platforms and aftermarket manufacturers lacks clarity and standardization, leading to the inefficiency and potential conflict. (2)The long-term sustainability of these cooperation models is uncertain due to factors such as changing market demands, technological advancements and evolving customer preferences. (3)There is a need for more robust model analysis and insights to inform us of decision-making and optimize the effectiveness of these cooperation models.
Therefore, this paper researches the service supply chain involving the IoV platform and aftermarket stores, and finds optimal supply chain strategies in the context of Stackelberg games led by aftermarket stores and Stackelberg games led by IoV platforms by building mathematical models in the promotion mode, subsidy mode and “promotion+subsidy” mode. The study is also based on revenue sharing contracts, which is the current mode used by IoV platforms and aftermarket stores. In order to study the influence of external factors such as network externalities, promotion and service effort costs, and subsidy on supply chain decisions, this paper explores them through theoretical and numerical analysis. The findings are as follows:
(1)When the Stackelberg game is led by the IoV platform, if the unit cost of promotion is below a certain threshold, the subsidy mode should be adopted for the supply chain; whereas, if the unit cost of promotion exceeds the threshold, the promotion mode or the “promotion+subsidy” mode should be chosen. However, when the aftermarket store leads the Stackelberg game, the cooperation mode selection strategies among supply chain members may diverge, necessitating negotiation between the parties.
(2)The modes with subsidies or changing subsidy amount have a relatively weak impact on decision variables and profits. Except in scenarios where the aftermarket store leads the Stackelberg game, whether subsidies are combined with promotional activities only affects the service price of the IoV platform, but not profits. Additionally, when managers plan to adjust the service price of the IoV platform, they can achieve their goals by adjusting the subsidy amount. However, this approach cannot be used to increase profits.
(3)Regardless of the game-playing method employed, the simultaneous increase in service sensitivity and network externality effects significantly boosts the supply chain profits, but may potentially harm the profits of supply chain members. When the IoV platform leads Stackelberg game, as service sensitivity and network externality effects increase simultaneously, the “IoV+Aftermarket” supply chain can only increase profits of both the IoV platform and the aftermarket store by choosing a lower profit-sharing ratio. Otherwise, the aftermarket store’s profits may suffer significant losses, which will hinder the “IoV+aftermarket” supply chain cooperation.

Key words: IoV platform, automotive aftermarket, service supply chain, game theory