New energy vehicles' heterogeneous user demands analysis based on user profiles with personality traits prediction
Jiani Chen et al.
What the paper says
Purpose The analysis of user demand for new energy vehicles (NEVs) is crucial for corporate development. However, existing research often focuses on overall user demands, neglecting user heterogeneity. Therefore, this study aims to conduct user profiles and analyze user demands of NEV with a focus on heterogeneity. Design/methodology/approach Firstly, this study brings the Big Five personality traits based on CNN-BiLSTM as one of the labels into user profiling, using data collected from “Autohome.com”. K-means clustering is employed to group users using sentiment and personality traits. Secondly, using Kano and importance-performance analysis, the focus and satisfaction of different user groups on various attributes are explored. Findings The results reveal that user profiles can be categorized into three groups: shopping-oriented, career-oriented and family-oriented. Furthermore, the concerned attributes and priorities for improvement vary across user groups. Practical implications The method enables companies to better identify heterogeneous user demands and optimize personalized product design and services. Additionally, it informs government policy-making to stimulate NEV market vitality. Originality/value This paper applies the Big Five personality traits for user profiling to capture user heterogeneity and employs Kano-IPA analysis to prioritize NEV attribute improvements and provide optimization recommendations for different user groups.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.