Purchasing intention of new energy vehicle consumers: A discrete choice analysis

Abstract

With the intensification of global environmental problems and the development of the automobile industry, new energy vehicles have gradually been praised by many governments in the world. With the promotion of the Chinese government in the upstream and downstream of the new energy vehicle industry, the sales volume of new energy vehicles in the Chinese market increased by 32% in the first half of 2024. Many previous studies were based on analyzing questionnaires from regional censuses, which deviated greatly from the actual purchase. To make up for the lack of this field, this paper constructs a linear regression model, a logit regression model, and a discrete choice model based on the sales data of new energy vehicles in the first half of 2024 and the parameters of nearly 80 popular models in the Chinese market (e.g., endurance, maximum speed, charging time). Research objectives: To explore the willingness of leading consumers to purchase new energy vehicles, to distinguish the popular new energy vehicle models in the Chinese market according to RMB 300,000 and power modes, and to analyze the consumer willingness in different situations in detail. In order to improve the stability of the data, the study merged 80 data points, removed outliers based on the standard squared difference of sales volume, and added brand information and the market share of each car as variables. After these adjustments, regression analysis was conducted again, and it was found that the positive correlation between the existing variables and sales volume reached 81.64%, and the adjusted R-squared value was also within the normal range of 53.8%, indicating that these factors can explain the changes in sales volume of 53.8%.