How do users contribute to YouTube channels' revenue? An empirical analysis of Korean beauty channels

  • Eom, Sewon; 
  • Park, Jaeyoung; 
  • Choi, Eugene; 
  • Park, Jinho; 
  • Kim, Seongcheol
Citations

WEB OF SCIENCE

2
Citations

SCOPUS

2

초록

The platform economy has transformed digital media, making platforms like YouTube central spaces for participation and economic exchange. Unlike conventional media models that focus solely on audience size, YouTube's monetization system relies on user engagement metrics that shape algorithmic visibility, directly impacting revenue generation through advertising and commerce. In this context, users are active agents and cocreators of value, influencing YouTube's success through their interactions. This study explores user agency in beauty-focused YouTube revenue through a four-stage framework: cognitive, affective, conative, and active agency. This study analyzed panel data from 50 beauty channels using fixed-effects regression and examined how engagement metrics-new viewer watch time, returning viewer watch time, subscriber watch time, and likes-affect monthly revenue. The analysis employs fixed-effects regression models to capture both the static and dynamic effects of user engagement. Results show that watch time significantly predicts revenue, with returning viewer watch time (affective agency) as the most significant factor. New viewer (cognitive agency) and subscriber (conative agency) watch time contribute positively but less so, while likes (active agency) showed no statistically significant effect. The findings emphasize fostering affective agency by engaging returning viewers while balancing all engagement stages. These insights offer actionable strategies for creators and platforms to optimize revenue in the competitive digital content landscape.

키워드

User agency; YouTube; Digital platform; Platform economy; Content monetization
제목
How do users contribute to YouTube channels' revenue? An empirical analysis of Korean beauty channels
저자
Eom, Sewon; Park, Jaeyoung; Choi, Eugene; Park, Jinho; Kim, Seongcheol
DOI
10.1016/j.chb.2025.108741
발행일
2025-11
유형
Article
저널명
Computers in Human Behavior
권
172