Earticle

초록

영어

The performance of recommender systems (RS) has been measured mainly in terms of accuracy. However, there are other aspects of performance that are difficult to understand in terms of accuracy, such as coverage, serendipity, and satisfaction with recommended results. Moreover, particularly with RSs that suggest multiple items at a time, such as YouTube, user satisfaction with recommended results may vary not only depending on their accuracy, but also on their configuration, content, and design displayed to the user. This is true when classifying an RS as a single RS with one recommended result and as a multiple RS with diverse results. No empirical analysis has been conducted on the influence of the content and distribution of recommendation items on user satisfaction. In this study, we propose a research model representing the content and distribution of recommended items and how they affect user satisfaction with the RS. We focus on RSs that recommend multiple items. We performed an empirical analysis involving 149 YouTube users. The results suggest that user satisfaction with recommended results is significantly affected according to the HHI (Herfindahl-Hirschman Index). In addition, satisfaction significantly increased when the recommended item on the top of the list was the same category in terms of content that users were currently watching. Particularly when the purpose of using RS is hedonic, not utilitarian, the results showed greater satisfaction when the number of views of the recommended items was evenly distributed. However, other characteristics of selected content, such as view count and playback time, had relatively less impact on satisfaction with recommended items. To the best of our knowledge, this study is the first to show that the category concentration of items impacts user satisfaction on websites recommending diverse items in different categories using a content-based filtering system, such as YouTube. In addition, our use of the HHI index, which has been extensively used in economics research, to show the distributional characteristics of recommended items, is also unique. The HHI for categories of recommended items was useful in explaining user satisfaction.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Theoretical Foundations
2.1. Definitions
2.2. Performance Measures for RSs
2.3. User Satisfaction
Ⅲ. Research Model
3.1. User Satisfaction with Recommendations
3.2. Distribution of Recommended Items
3.3. Content of Recommended Items
3.4. Control Variables
Ⅳ. Research Methodology
4.1. Experimental Design
4.2. Results
Ⅴ. Discussion and Results
5.1. Main Findings
5.2. Contributions
5.3. Limitations
5.4. Conclusion
Acknowledgements

키워드

저자

• Janghun Jeonga [ M.S. Student, School of Management, Kyung Hee University, Korea ]
• Kwonsang Sohn [ Ph.D. Candidate, School of Management, Kyung Hee University, Korea ]
• Ohbyung Kwon [ Professor, School of Management, Kyung Hee University, Korea ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  Asia Pacific Journal of Information Systems

• 간기

  계간

• pISSN

  2288-5404

• eISSN

  2288-6818

• 수록기간

  1990~2026

• 등재여부

  KCI 등재,SCOPUS

• 십진분류

  KDC 325 DDC 658