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How Personalized Recommendations Shape User Immersion in Serialized Content : Evidence from a Digital Comics Platform

  • 간행물
    한국경영정보학회 정기 학술대회 바로가기
  • 권호(발행년)
    2025 한국겨영정보학회 추계학슬대회 (2025.10) 바로가기
  • 페이지
    pp.181-187
  • 저자
    Jiwon Lee, Gunwoong Lee
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A476028

원문정보

초록

영어
Immersion—the state of sustained cognitive and affective absorption during continuous media consumption—is a key determinant of user engagement in serialized digital content platforms. Although recommender systems mediate most user interactions in these environments, their effects on immersion remain theoretically ambiguous. Personalization reduces can search costs and promote narrative continuity, yet it may also lower switching barriers, potentially diverting attention toward alternative titles. To examine how personalization shapes immersive engagement, we conduct a large-scale field experiment on a serialized digital comics platform, comparing personalized recommendations with popularity-based displays. We measure immersion behaviorally as continuous session-level consumption within each narrative series and distinguish between the phases of initial discovery and subsequent continuation. Preliminary results suggest that personalization enhances discovery engagement but may attenuate sustained immersion during continuation, reflecting a tension between curiosity-driven exploration and narrative commitment. These findings advance understanding of recommender system research by clarifying when personalization fosters versus fragments immersion, offering both theoretical refinement and design implications for algorithmic curation in serialized media contexts.

목차

Abstract
Introduction
Literature Review
RSs and User Behavior
Serialized Digital Content and Immersive Consumption
Personalization, Flow, and the Exploration–Commitment Tension
Hypothesis Development
Data and Measurements
Experiment Design
Key Research Variables
Preliminary Results
Immersion Upon Discovery
Immersion for Previously Discovered Titles
Expected Implications
References

저자

  • Jiwon Lee [ Korea University Business School, Information Systems ]
  • Gunwoong Lee [ Korea University Business School, Information Systems ]

참고문헌

자료제공 : 네이버학술정보

    간행물 정보

    • 간행물
      한국경영정보학회 정기 학술대회 [KMIS Conference]
    • 간기
      반년간
    • 수록기간
      1990~2025
    • 십진분류
      KDC 325 DDC 658