Investigating AI Personalization in Music Streaming
2025 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Student thesis
Abstract [en]
Background: Previous research has discussed the increase of AI and its influence on consumer perception and decision-making in various contexts which has created a gap in research regarding how consumers behave and more specifically how their behavioral intentions are influenced through AI. Despite AI’s increasing influence, there has been limited research in how consumers perceive these personalized features and how those perceptions influence their intention to retain subscription.
Purpose: The purpose of the study is to investigate consumer perceptions regarding AI personalization on Spotify and its influence on consumers' behavioral intentions to retain their subscription to the platform. Through the lens of Ajzen's (1991) Theory of Planned Behavior the research seeks to understand how consumers’ behavioral intentions are influenced and contribute to the TPB and AI personalization literature with its findings.
Method: A qualitative study with the use of semi-structured interviews that was conducted from a consumers perspective regarding the music streaming platform Spotify. The study follows interpretivism with a phenomenological research design with a deductive approach as this paper is being investigated through the lens of TPB.
Conclusion: The findings showcase that consumers' perceptions of AI personalization are multi-dimensional, context driven and that personalization has a role in influencing consumers' behavioral intentions. However, AI personalization was found to not be the sole influencing aspect but perceived value in convenience. Further on, it was found that all three aspects of TPB contribute to behavioral intention through perceived value.
Place, publisher, year, edition, pages
2025. , p. 85
Keywords [en]
AI Personalization, Spotify, Music streaming, Perception, Theory of Planned Behavior, Subscription, Retention
National Category
Business Administration
Identifiers
URN: urn:nbn:se:hj:diva-67949OAI: oai:DiVA.org:hj-67949DiVA, id: diva2:1962199
Subject / course
JIBS, Business Administration
Supervisors
Examiners
2025-06-252025-05-282025-10-13Bibliographically approved