Proceedings of the 4th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2022, December 9-11, 2022, Chongqing, China

Research Article

How Item-based Recommendation Affects E-commerce Platform Satisfaction ——Measurement of Mediating Effect of SPSS Analysis Method

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  • @INPROCEEDINGS{10.4108/eai.9-12-2022.2327637,
        author={Zhaoxia  Liu and Jinsong  Chen},
        title={How Item-based Recommendation Affects E-commerce Platform Satisfaction ------Measurement of Mediating Effect of SPSS Analysis Method},
        proceedings={Proceedings of the 4th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2022, December 9-11, 2022, Chongqing, China},
        publisher={EAI},
        proceedings_a={MSIEID},
        year={2023},
        month={3},
        keywords={item-based recommendation; perceived information value; platform satisfaction},
        doi={10.4108/eai.9-12-2022.2327637}
    }
    
  • Zhaoxia Liu
    Jinsong Chen
    Year: 2023
    How Item-based Recommendation Affects E-commerce Platform Satisfaction ——Measurement of Mediating Effect of SPSS Analysis Method
    MSIEID
    EAI
    DOI: 10.4108/eai.9-12-2022.2327637
Zhaoxia Liu1,*, Jinsong Chen1
  • 1: Guizhou University of Finance and Economics College of Business Administration Guiyang
*Contact email: 962111790@qq.com

Abstract

In the era of the digital economy, each e-commerce platform has adopted a personalized recommendation service strategy to cope with the fierce competition. From the perspective of customer perceived information value, this paper explores the influence mechanism of personalized recommendation service on e-commerce platform satisfaction. The questionnaire data were collected online and offline, and SPSS was used for reliability and validity analysis. The structural model analysis path and hierarchical regression analysis were used to analyze the mediating effect. Finally, it is concluded that to win customer satisfaction. The platform needs to present personalized suggestions with high information value to specific users through an intelligent recommendation algorithm to meet the personalized needs of users.