Luxury Car Purchase Prediction Based on Cross-industry Big Data——A Case Study of Car-buying Users in Tianjin

This study aims to explore the characteristics and influencing factors of luxury car purchasing behavior and solve the problem of insufficient understanding of luxury car consumers by automobile manufacturers. This study integrates industry data resources to construct an auto-user related big data and extracts Tianjin users to form a research sample. The sample covers 545 pieces of luxury car data and nine types of population information from 2014 to 2022. Probabilities were calculated based on the law of large numbers and Bayes' theorem. The results show that the probabilities of mature women without elderly or children and newly married young families purchasing luxury cars are relatively high, reaching 17.70% and 16.06% respectively. Family structure, gender and consumption level are closely related to purchasing decisions. For example, the probability of three-generation local families purchasing luxury cars is 15.48% because of their family stability and pursuit of quality; the probability of multi-child nuclear families purchasing luxury cars is 13.36% due to their space needs. This study provides a basis for market strategies for automobile enterprises to enhance the attractiveness of future high-end automobile products to consumers.