共享平台推荐系统对消费者行为影响的实证研究

An empirical study on the impact of sharing platform recommendation system based on consumer behavior

推荐系统(RS)通过分析用户(消费者)数据而向其提供感兴趣的产品信息,这些推荐的产品信息通过改变消费者的(后续)浏览路径以实现推荐目的.由于相关研究数据的稀缺,以往研究鲜有在考虑“用户(消费者)-平台”关系情况下,探讨RS对平台消费者行为影响的成果.为弥补这一研究空白,本文提出三个理论假设并实际验证了在“用户(消费者)-平台”亲近性下RS对消费者的信息处理效率、平台访问频率以及购买频率的影响.提出假设时充分考虑了共享平台的特点,并利用一个家庭厨房共享平台的独特数据集进行实证检验.研究结果表明,与未采用RS服务的消费者群体相比,采用RS服务的消费者的信息处理效率反而显著降低。此外,研究结果进一步证实,与平台关系密切且采用RS的消费者具有更高的访问频率和购买频率。

Recommender systems(RS)are based on analyzing user(consumer)data to provide them with information about products of interest,and these recommended products change consumers'browsing paths to achieve the purpose of recommendation.Due to the scarcity of relevant research data,few research have been conducted to explore the impact of RS on consumer behavior(path)of the platform considering the"user(consumer)-platform"relationship.To fll this research gap,this paper proposes three theoretical hypotheses to verify the impact of RS on consumers'information processing efficiency,platform access frequency and purchase behavior considering the"user(consumer)-platform"closeness.The hypotheses are formulated by taking into account the characteristics of the sharing platform and are tested using a unique dataset of a homekitchen sharing platform.Interestingly,the results of the study show that consumers who adopt RS services have significantly lower information processing efficiency compared to consumers who do not adopt RS services.In addition,the findings further confirm that consumers with a close relationship with the platform and who also adopt RS have higher visit frequency and purchase intention.