Analysis of the Effect of AI Personalization on User Trust and Perceived Price Value and Its Implications for Subscription Intention to Music Streaming Services - Frando Adolian Pella; Tuga Mauritsius (Equivalent: Jurnal Ilmiah Sosial Teknik, 2026)
Background: This study examines the influence of artificial intelligence (AI)-based personalization systems and user trust on the intention to subscribe to music streaming platforms in Indonesia. Objective: The research objectives include analyzing the impact of personalization on Price Value, Performance Expectancy, and Trust in AI; as well as the mediating effect of trust and expectation on Intention to Subscribe. Methods: The research method is quantitative using a questionnaire survey distributed purposively to active users of Spotify and YouTube Music in Indonesia. The sample was determined using the Slovin formula, resulting in 420 valid respondents consisting of both free tier and premium tier users. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS software. Results: The results show that AI Personalization has a significant effect on Trust in AI and Price Value. Trust in AI is proven to be an important mediator that increases Performance Expectancy and Effort Expectancy. It was found that Price Value is the most dominant determinant influencing subscription intention, followed by Performance Expectancy and Habit. Conclusion: This study concludes that algorithm transparency and user control are key to building trust, which ultimately drives the perceived value worth subscribing to.