基于决策树模型的电动汽车目标客户销售策略
Targeted Customer Selling Strategy for Electric Vehicles Based on Decision Tree Modeling
摘要: 针对消费者对于购买新能源汽车的意愿存在很大的不确定性的问题,基于顾客满意度以及个人特征信息为影响的主要因素进行分析,采用决策树模型对顾客的购买意愿进行研究。通过案例分析,得出影响各品牌顾客购买意愿的主要因素,即对于品牌1和品牌3,影响顾客购买意愿的主要因素为电动汽车的质量和驾驶感受,而对于品牌2,主要影响因素为经济问题。并由Kano模型满意度对各品牌营销给出了营销建议。
Abstract: There is great uncertainty about consumers’ willingness to buy new energy vehicles. Based on customer satisfaction and personal characteristics as the main factors of the analysis. The decision tree model is used to study the purchase intention of customers. Through case analysis, we identify the main factors that affect customers’ purchasing intentions for various brands. For brands 1 and 3, the main factors affecting customer purchase intention are the quality and driving experience of electric vehicles, while for brand 2, the main influencing factor is economic issues. And the satisfaction of the Kano model was used to provide marketing recommendations for each brand’s marketing.
参考文献
|
[1]
|
Olasanmi, O.O. (2019) Online Shopping and Customers’ Satisfaction in Lagos State, Nigeria. American Journal of Industrial and Business Management, 9, 1446-1463. [Google Scholar] [CrossRef]
|
|
[2]
|
章凯兵. 基于神经网络的用户满意度预测研究[D]: [硕士学位论文]. 赣州: 江西理工大学, 2020.
|
|
[3]
|
李燕仪. 基于数据挖掘方法的汽车客户画像分析及流失客户预测[D]: [硕士学位论文]. 广州: 华南理工大学, 2017.
|
|
[4]
|
谢兆贤, 邹兴敏, 张文静. 大型数据集的高效参数剪枝决策树算法研究[J]. 计算机工程, 2024, 50(1): 156-165.
|
|
[5]
|
黄诗瑶. 聚类分析在移动通信用户行为分析中的研究与应用[D]: [硕士学位论文]. 广州: 广东工业大学, 2013.
|
|
[6]
|
Leung, C.W., Chan, S.C., Chung, F. and Ngai, G. (2011) A Probabilistic Rating Inference Framework for Mining User Preferences from Reviews. World Wide Web, 14, 187-215. [Google Scholar] [CrossRef]
|
|
[7]
|
Malik, A.J. and Khan, F.A. (2017) A Hybrid Technique Using Binary Particle Swarm Optimization and Decision Tree Pruning for Network Intrusion Detection. Cluster Computing, 21, 667-680. [Google Scholar] [CrossRef]
|
|
[8]
|
Sawant, S.S., Wiedmann, M., Göb, S., Holzer, N., Lang, E.W. and Götz, T. (2022) Compression of Deep Convolutional Neural Network Using Additional Importance-Weight-Based Filter Pruning Approach. Applied Sciences, 12, Article 11184. [Google Scholar] [CrossRef]
|
|
[9]
|
白一凡. 基于SARIMA和BP神经网络的新能源汽车销售预测[D]: [硕士学位论文]. 湘潭: 湘潭大学, 2019.
|
|
[10]
|
陈建凯, 王鑫, 何强, 等. 区间值属性的单调决策树算法[J]. 模式识别与人工智能, 2016, 29(1): 47-53.
|