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Study on the influence of brand perception of new energy vehicles on purchase intention based on Random Forest

Year: 2025

Type: conference-paper

Abstract: To explore the influence mechanism of new energy vehicle (NEV) brand awareness on users’ purchase intention, this study adopt machine learning methods to conduct a questionnaire survey among 560 users who have recent NEV purchase intention. The data were collected through the brand awareness scale, perceived value scale, purchase intention scale, and green consumption value scale. The prediction model was constructed by Random Forest (RF) algorithm. The results show that: (1) After controlling gender and age, brand awareness significantly positively predicts the purchase intention of NEV users; (2) Perceived value plays an intermediary role between brand awareness and purchase intention; (3) Green consumption value has a moderating effect on the relationship between brand awareness and purchase intention. The higher the green consumption value, the stronger the influence of brand awareness on purchase intention. Machine learning analysis further revealed that brand awareness, quality dimension of perceived value and green consumption value were key features in predicting purchase intention, and the model accuracy reached 89.7% (F1=0.86). The findings of this study provide data-driven theoretical support for NEV brand marketing strategy.

Source: International Conference on Computer Information and Big Data Applications (CIBDA)

DOI: 10.1145/3746709.3746922

Authors: Yue Meng, Chunlei Fan, Ligang Wang, Ting Tao, Wenbin Gao

Institutions: Chinese Academy of Sciences, Institute of Psychology, Chinese Academy of Sciences, University of Chinese Academy of Sciences

Language: English

Topic: Electric Vehicles and Infrastructure

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4413845157

FWCI:

Cites: 6

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Related to: 10