%0 Journal Article
%T 绿动中国，双碳先行——基于济南市新能源汽车市场机会挖掘<br>Green China, Double Carbon First—Based on the Opportunity Mining of New Energy Vehicle Market in Jinan
%A 陈心雨
%A 孔悦
%A 滕文珍
%A 李茵茵
%A 宫慧
%J Statistics and Applications
%P 335-350
%@ 2325-226X
%D 2024
%I Hans Publishing
%R 10.12677/sa.2024.132034
%X 发展新能源汽车是保障能源安全和实现双碳目标的重要举措。团队从新能源汽车的市场现状入手，从新能源汽车的发展现状、消费者对新能源汽车的购买意愿、消费者的主要需求三个方面展开调研。首先，团队利用大数据文本挖掘，绘制出新能源汽车博文与评论的词云图；其次，基于聚类分析进行目标客群挖掘，使用对购买分数贡献较大的特征归纳出五类客户群体。分析表明，女性、35岁左右、高学历、企业职员、拥有城镇户口、家庭年收入较高且有燃油汽车无新能源汽车的群体更倾向于购买新能源汽车。最后，构建研究新能源汽车购买意愿的结构方程模型，选择九个潜变量及相应观测变量，并提出研究假设。研究结果表明各潜变量对新能源汽车购买意愿的影响均显著，各潜变量与其观测变量之间也是显著的。情境因素、新能源汽车态度和感知行为控制对新能源汽车购买意愿的影响较大。为进一步探究上述三个潜变量的观测变量对购买意愿的影响，建立XGBoost模型对购买意愿进行回归预测，得到消费者购买意愿的变化趋势。结果表明，政府应注重对新能源汽车的宣传推广，加大对充电桩的建设并增加对新能源汽车的购买补贴。 <br />
The development of new energy vehicles is an important measure to ensure energy security and achieve the goal of dual carbon. The research team starts from the market status of new energy vehicles, and conducts research from three aspects: the development status of new energy vehicles, consumers’ willingness to purchase new energy vehicles, and consumers’ main needs. First of all, the team uses big data text mining to draw a word cloud map of new energy automobile blog posts and comments; secondly, based on cluster analysis, the target customer group is mined, and five types of customer groups are summarized by using the characteristics that contribute more to the purchased score. The analysis shows that women, about 35 years old, highly educated, corporate employees, urban household registration, high annual household income and fuel vehicles without new energy vehicles are more inclined to buy new energy vehicles. Finally, a structural equation model is constructed to study the purchase intention of new energy vehicles, nine latent variables and corresponding observation variables are selected, and research hypotheses are proposed. The results show that the influence of each latent variable on the purchase intention of new energy vehicles is significant, and the latent variables and their observed variables are also significant. Situational factors, new energy vehicle attitudes and perceived behavioral control have a greater impact on the purchase intention of new energy vehicles. In order to further explore the influence of the observed variables of the above three latent variables on the purchase intention, an XGBoost model is established to predict the purchase intention, and the changing trend of consumers’ purchase intention is obtained. The results show that the government should pay attention to the promotion of new energy vehicles, increase the construction of charging piles and increase the purchase subsidy of new energy vehicles.
%K 新能源汽车，文本挖掘，聚类分析，结构方程，XGBoost<br>New Energy Vehicle
%K Text Mining
%K Cluster Analysis
%K Structural Equation
%K XGBoost
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=84460