New Energy Vehicle Brand Sales Trend Forecast and User Evaluation Research

In the context of green economic development, new energy vehicles, as one of the representatives of innovation-driven development and environmental protection and energy conservation, are currently in a leading position in the market. This paper selects eight representative well-known brands, namely BYD, Li Auto, Xiaopeng, Geely, NIO, Changan Automobile, SAIC-GM and ORA, for quantitative analysis, with the aim of identifying future sales trends and conducting a precise business evaluation of new energy vehicles, as well as exploring the key factors affecting sales. The study was empirically tested using ARIMA time series forecasting, principal component analysis, linear regression analysis and neural network models. The results showed that brand identification behavior and personalized products have the most significant positive impact on sales. Therefore, this study believes that car brand collection, forwarding, personalized production and quality control are the key factors and improvement priorities that will affect future sales.

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Publication Details

Journal
IC-ITECHS
Published
2024-12-03
DOI
https://doi.org/10.32664/ic-itechs.v5i1.1637
Citations
1
Primary Topic
Vehicle emissions and performance
Type
article
Field-Weighted Citation Impact
0.20
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New Energy Vehicle Brand Sales Trend Forecast and User Evaluation Research

Hao Zheng, Yiyi Zhou, Na Tang, Yan Guo et al.
1 citations
IC-ITECHS
Vehicle emissions and performance
0.20
article

New Energy Vehicle Brand Sales Trend Forecast and User Evaluation Research

Hao Zheng, Yiyi Zhou, Na Tang, Yan Guo, Ying Jiang, Xuesi Zeng
article en
1 citations

Abstract

In the context of green economic development, new energy vehicles, as one of the representatives of innovation-driven development and environmental protection and energy conservation, are currently in a leading position in the market. This paper selects eight representative well-known brands, namely BYD, Li Auto, Xiaopeng, Geely, NIO, Changan Automobile, SAIC-GM and ORA, for quantitative analysis, with the aim of identifying future sales trends and conducting a precise business evaluation of new energy vehicles, as well as exploring the key factors affecting sales. The study was empirically tested using ARIMA time series forecasting, principal component analysis, linear regression analysis and neural network models. The results showed that brand identification behavior and personalized products have the most significant positive impact on sales. Therefore, this study believes that car brand collection, forwarding, personalized production and quality control are the key factors and improvement priorities that will affect future sales.

IC-ITECHSVol. 5(1)
Openalex Percentile: Top 46%
Vehicle emissions and performance
0.20
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