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Finance  2024 

Analysis on Influencing Factors of Rural New Energy Vehicles Purchase Decision Based on Text Mining Technology

DOI: 10.12677/FIN.2024.141002, PP. 7-13

Keywords: 新能源汽车,TF-IDF算法,农村地区
New Energy Vehicles
, TF-IDF Algorithm, Rural Areas

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In order to promote the development of new energy vehicle industry and environmental protection, the Chinese government has implemented a policy of new energy vehicles going to the countryside to encourage consumers in rural areas to buy new energy vehicles. The purpose of this paper is to explore the factors that affect the adoption of electric vehicles in rural areas of China. TF-IDF algorithm is used to extract the characteristic words of rural consumers’ car purchase comments and make word frequency statistics, so as to analyze the factors of consumers’ car purchase decision. By analyzing the emotional fluctuation of rural electric vehicle consumers’ composite comments, we can not only expand the research depth of consumer perceived value theory, but also provide content information and data reference for manufacturers and consumers to help them adjust their production behavior and optimize their purchase decisions. The research results show that in rural markets, consumers pay more attention to factors such as car price, space, maintenance cost, driv-ing experience and fuel consumption. The research results are of great significance for promoting the promotion and popularization of new energy vehicles in rural markets.


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