New energy vehicles' heterogeneous user demands analysis based on user profiles with personality traits prediction

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.

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Publication Details

Journal
Kybernetes
Published
2026-01-15
DOI
https://doi.org/10.1108/k-11-2024-3152
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
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article

New energy vehicles' heterogeneous user demands analysis based on user profiles with personality traits prediction

Yujia Liu, Kainan Tu, Yuwei Song, Jin Fang et al.
Kybernetes
Electric Vehicles and Infrastructure
article

New energy vehicles' heterogeneous user demands analysis based on user profiles with personality traits prediction

Yujia Liu, Kainan Tu, Yuwei Song, Jin Fang, Jiani Chen
article en

Abstract

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.

Kybernetes
Artificial Intelligence in Medicine (Canada) (CA), Shanghai Maritime University (CN)
Openalex Percentile: Top 87%
Electric Vehicles and Infrastructure
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