Asia Pacific Journal of Information Systems (APJIS)

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Past Issue

Date	December 2025
Vol. No.	Vol. 35 No. 4
DOI	https://doi.org/10.14329/apjis.2025.35.4.1035
Page	1035~1055
Title	The Impact of an AI-based Recommendation Algorithm on User Satisfaction Across Domains: A Dual-path Approach
Author	Won-jun Lee, Seongtae Hong, Il Im
Keyword	Artificial Intelligence, Recommendation Service, Dual-path Model, Algorithm Avoidance, Technology Trust, Domain Difference
Abstract	The importance of recommendation algorithms is underscored by the advancement of AI technology and the growing demand for personalized services. However, there is a lack of empirical studies that analyze differences in algorithmic services across markets. The objective of this study is to draw attention to discrepancy in this field and develop a dual-path model to examine the factors that influence satisfaction with recommendations. By analyzing 641 respondents’ data through Partial Least Squares (PLS), it identifies differences in user attitudes towards algorithms across domains. e-commerce firms and content providers can improve personalized recommendations through the research, which highlights the importance of understanding consumer satisfaction and trust in technology to adapt to evolving AI innovations.