基于K-Means聚类的消费者直播购物偏好研究
Research on Consumers’ Preference for Live Shopping Based on K-Means Clustering
摘要: 本文针对消费者直播购物行为数据展开分析，采用K-means算法进行聚类，将具有相似购买行为的样本聚为一组，得到三种类别的直播购物偏好风格，进一步分析了各个偏好风格的群体特征，并为电商平台实施直播互动提供启示。
Abstract:
Based on the analysis of consumers’ live shopping behavior data, this paper uses K-means algorithm for clustering, gathers samples with similar purchasing behaviors into a group, obtains three types of live shopping preference styles, further analyzes the group characteristics of each preference style, and provides inspiration for e-commerce platforms to implement live interaction.
参考文献
|
[1]
|
罗雲潇, 张海瑞, 张振京, 宋亚栋, 屈亚祥. 基于SOM-Kmeans算法的司机驾驶风格研究[J]. 时代汽车, 2023(8): 189-192.
|
|
[2]
|
田俐. 基于Kmeans的12345问题热点分析[J]. 电子技术与软件工程, 2023(7): 244-247.
|
|
[3]
|
刘国华. 基于Kmeans算法的学生行为分析系统的设计与实现[D]: [硕士学位论文]. 石家庄: 河北科技大学, 2014.
|
|
[4]
|
凌玉龙, 张晓, 李霞, 张勇. 改进Kmeans算法在学生消费画像中的应用[J]. 计算机技术与发展, 2021, 31(10): 122-127.
|
|
[5]
|
杨尊琦, 张倩楠. 基于K-means算法的微博用户推荐功能研究[J]. 情报杂志, 2013, 32(8): 142-144+131.
|
|
[6]
|
易茹. 基于K均值聚类算法的数字媒体推荐方法研究[J]. 长春工程学院学报(自然科学版), 2020, 21(4): 99-102.
|
|
[7]
|
袁海霞, 黄丽雯. 电商直播互动模式对消费者购买意愿的影响研究[J]. 哈尔滨商业大学学报(社会科学版), 2022(6): 19-30.
|
|
[8]
|
韩琮师. K-means聚类算法优化及其在电商平台精准营销中的应用研究[D]: [硕士学位论文]. 青岛: 山东科技大学, 2020.
|
|
[9]
|
Jin, C. and Lee, S. (2022) The Effect of Self-Image Congruence with Live Commerce Influencer on Consumer Fanship and Brand Preference and Purchase Intention. Journal of Product Research, 40, 9-20.
|
|
[10]
|
Chen, T., Tang, S.D., Shao, Z.J., et al. (2023) Doing Well by Doing Good: The Effect of Purchasing Poverty-Alleviation Products on Consumers’ Subsequent Product Preference in Live Streaming Shopping. Computers in Human Behavior, 144, Article 107753. [Google Scholar] [CrossRef]
|
|
[11]
|
Liu, X.H., Wang, D.H., Gu, M., et al. (2023) Research on the Influence Mechanism of Anchors’ Professionalism on Consumers’ Impulse Buying Intention in the Livestream Shopping Scenario. Enterprise Information Systems, 17, 920-940. [Google Scholar] [CrossRef]
|