Abstract:
The rapid growth of digital streaming platforms has significantly changed the way
people consume entertainment content, especially among younger generations. With
the increasing availability of AI-driven recommendations and on-demand access,
binge-watching has become a dominant behavior among OTT (Over-The-Top)
platform users. The main objective of this study is to investigates the psychological
and technological factors influencing binge-watching behavior and its subsequent
impact on emotional burnout among Generation Z OTT platform users in Bangladesh.
Grounded in the Uses and Gratifications Theory (UGT), the research model integrates
traditional user-driven motives entertainment, escapism, and social influence
alongside a modern system-driven factor, AI recommendation quality, to explore their
direct and indirect effects on binge-watching and emotional outcomes. Using a
quantitative research design, data were collected from 302 valid respondents through
structured online and offline surveys. SmartPLS 4.0 was employed to analyze the
measurement and structural models, testing reliability, validity, and path coefficients.
The results show that entertainment, social influence, and AI recommendation quality
have a significant positive influence on binge-watching behavior. However, escapism
does not show a significant relationship with binge-watching. Most importantly,
binge-watching behavior has a strong and direct impact on emotional burnout,
indicating that excessive content consumption may lead to negative psychological
outcomes. The study contributes both theoretically and practically by bridging
user-centered media theories with algorithmic influence, and by identifying
binge-watching as a central behavioral mechanism linked to digital mental health
concerns. Practical implications include the need for ethical AI design, media literacy
education, and interventions promoting mindful media consumption among young
OTT users. While the study offers significant insights, it acknowledges, limitations
related to sample size, geographic scope, cross-sectional design, and the use of
self-reported online surveys. For future research, it is recommended to expand the
sample across more diverse regions, employ longitudinal or mixed-method
approaches, and explore other relevant psychological or behavioral variables. Data
could also be collected through in-person interviews or paper-based surveys for
broader insight.
