电商平台产品共同购买网络的影响因素研究

易闽琦; 刘洪伟; 高鸿铭

doi:10.12052/gdutxb.210076

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电商平台产品共同购买网络的影响因素研究

更新时间：2026-05-27

- 电商平台产品共同购买网络的影响因素研究
- Research on the Factors Influencing the Co-purchase Network of Products on E-commerce Platforms
- 广东工业大学学报 2022年39卷第3期页码：16-24
- 作者机构：
  
  广东工业大学管理学院,广东,广州,510520
- 作者简介：
  
  易闽琦(1997–)，女，硕士研究生，主要研究方向为消费者行为决策
  高鸿铭(1993–)，男，博士研究生，主要研究方向为数据挖掘和消费者行为，E-mail：hm.gao.normal@gmail.com
- 基金信息：
  
  国家自然科学基金资助项目(71671048);国家自然科学基金青年基金资助项目(71901075)
- DOI：10.12052/gdutxb.210076
  中图分类号： TP391.4;F713.8
- 网络首发：2022-05-10，
  
  纸质出版：2022
- 稿件说明：
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易闽琦, 刘洪伟, 高鸿铭. 电商平台产品共同购买网络的影响因素研究[J]. 广东工业大学学报, 2022, 39(3): 16-24.

Yi Min-qi, Liu Hong-wei, Gao Hong-ming. Research on the Factors Influencing the Co-purchase Network of Products on E-commerce Platforms[J]. 2022, 39(3): 16-24.
易闽琦, 刘洪伟, 高鸿铭. 电商平台产品共同购买网络的影响因素研究[J]. 广东工业大学学报, 2022, 39(3): 16-24. DOI： 10.12052/gdutxb.210076.

Yi Min-qi, Liu Hong-wei, Gao Hong-ming. Research on the Factors Influencing the Co-purchase Network of Products on E-commerce Platforms[J]. 2022, 39(3): 16-24. DOI： 10.12052/gdutxb.210076.

摘要

共同购买网络的推荐系统应用越加广泛，仅基于网络内生结构变量研究其共同购买链接的经济意义已有局限，故加入网络口碑这一外生变量，进行更全面的分析。采用了社会网络方法中指数随机图模型进行建模，主要围绕产品销售量、产品入度、差评率和评论数4个方面因素，探究其对共同购买网络中共同购买链接形成的影响。结果显示，销售量、产品入度和评论数对共同购买链接形成的影响呈正比关系，而差评率则会显著地降低产品共同购买的几率。该指数随机图构建出的共同购买网络为在线电商平台管理网络口碑和推荐系统优化设计提供有益参考。

Abstract

As the recommender system of co-purchase network is more and more widely used

there are certain limitations in studying the economic significance of co-purchase link only based on the endogenous structure variable of network. Therefore

the exogenous variable of network word-of-mouth is added to make a more comprehensive analysis. The exponential random graph model in the social network method is used to build the model

mainly focusing on the four factors of product sales volume

product indegree

poor evaluation rate and the number of comments

to explore its influence on the formation of co-purchase links in the co-purchase network. Among them

sales volume

product indegree and comments have a positive correlation with the formation of co-purchase links

but the rate of poor reviews will significantly reduce the probability of co-purchase. The co-purchase network constructed by the exponential random graph model provides a reference for the optimization design of online e-commerce platform management network word-of-mouth and recommendation system.

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references

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