Research on Dual-Channel Marketing Decisions for New Energy Vehicles Based on Privacy Computing

In the context of big data, the market for new energy passenger vehicles is highly competitive with diverse marketing and information channels. Consumers need to make choices from a vast amount of information during their car-buying process. This study introduces the framework of bounded rationality, suggesting that individual information processing capabilities are limited and decisions are influenced by corporate marketing strategies. In this research, automotive companies can collaborate with dealers and communication companies to build a big data privacy computing platform for the automotive industry, integrating human-vehicle data to analyze consumer characteristics. The study includes two main areas of research: one involves privacy computing technology using Multi-Party Computation (MPC) and Federated Learning (FL), and the other focuses on the development of a privacy computing platform based on cloud services and computational resources. This paper examines how companies can make marketing decisions based on big data, interact with consumers who have bounded rationality through online and offline dual-channel information flows, and thus influence their purchasing behavior and outcomes. Based on user characteristics derived from big data analysis, we established a game theory model to describe the automotive sales market. The equilibrium analysis reveals that online and offline channels are not completely independent; they interact with each other. It is not the case that more information released by the company always leads to a shorter vehicle purchasing decision process for consumers. Instead, there is a non-linear relationship where the consumer vehicle purchasing decision process first increases and then decreases with the amount of information released. This indicates that if the online marketing channel is underdeveloped, it might squeeze the offline channel and reduce overall profits. When online information exceeds a certain threshold, it positively affects the acceleration of the purchasing decision cycle. Our conclusions extend the application of bounded rationality in market research and offer deep insights into dual-channel marketing decisions for companies.