With the rapid expansion of OTT services across China, theyhavepermeated the daily lives of Chinese people. OTT services have brokenfreefrom the constraints of traditional television's fixed schedules and locations, gradually becoming the primary plat...
With the rapid expansion of OTT services across China, theyhavepermeated the daily lives of Chinese people. OTT services have brokenfreefrom the constraints of traditional television's fixed schedules and locations, gradually becoming the primary platform for content consumption. OTTplatforms not only diversify viewing methods but also attract users of varyingages, professions, and interests through their extensive content libraries. However, as OTT content catalogs continue to expand, selecting preferredcontent from vast libraries becomes increasingly challenging, often leadingtocontent choice paralysis. Consequently, it is evident that user viewing habitsand media psychological structures are evolving within the current OTTenvironment. This study aims to deeply explore which factors can reduce selectiondelay for Chinese users when selecting from rich and diverse content
resources while using OTT services. To this end, we categorize content
selection factors into three dimensions: “Usage Motivation (Entertainment, Convenience, Social Interaction, Companionship, Time-Killing)”,
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“Algorithm Recommendation Perception”, and “Social Influence”, analyzing each factor's impact on OTT content selection delay. Second, weexamine how these factors—specifically “usage motivation (entertainment, convenience, social interaction, alleviating loneliness, passing time),”“algorithm recommendation cognition,” and “social influence”—impact thedelay of OTT content selection. Additionally, we test whether users' “expected benefits” from content mediate relationships among thesevariables and whether content genre preferences moderate theserelationships. This study employed an online questionnaire targeting Chinese users aged18 to 59 with OTT service experience, ultimately collecting 416validresponses. Through correlation analysis, multicollinearity analysis, andregression analysis of the collected data, combined with variable relationshipanalysis, mediation effect analysis, and moderation effect analysis, thefollowing conclusions were drawn: First, stronger usage motivations, algorithmic recommendation cognition, and social influence among OTTuserscorrelate with easier content selection. Notably, among usage motivations, only when “killing time” dominates does content selection become easier. Second, usage motivation, algorithmic recommendation cognition, and social
influence all positively (+) influence perceived benefits. However, amongusage motivations, only the “alleviating loneliness” motivation significantlyand positively influences expected benefits. Expected benefits, in turn, positively influence ease of selection. Third, expected benefits exhibit apartial mediating effect between usage motivation, perception of algorithmicrecommendations, social influence, and selection delay. Fourth, preferencesfor five major program categories—TV dramas, movies, documentaries, variety shows, and sports—exhibit distinct moderating effects ontherelationship between usage motivation, perception of algorithmicrecommendations, social influence, and selection delay. Across all five content
preferences, no moderating effects were observed between time-killingand
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selection delay, or between algorithm recommendation cognition and selectiondelay. However, preferences for variety shows, documentaries, and moviessignificantly moderated the relationship between social influence and selectiondelay. These findings indicate that among the five motivations, users experiencethe least delay within choices only when using OTT for time-killing purposes. When users hold positive perceptions of OTT algorithmic recommendationtechnology, this technology effectively replaces users in content selection. Simultaneously, it was found that OTT content consumption carries social
attributes. That is, influences from others can reduce users' content selectiondelay. Unlike traditional TV content selection, stronger user cognition of OTTalgorithmic recommendation systems facilitates content choice. Even whenusers have genre preferences, no moderating effect occurs between thesefactors. Furthermore, from a psychological perspective, when users developcertain expectations about content based on past experiences, this alsoreduces their selection difficulty. Overall, the findings of this study have positive implications for content
production and promotion on Chinese OTT platforms, while also providingnewempirical evidence for OTT platform marketing strategies. Moving forward, OTT platforms can leverage these research results to enhance users' content
selection efficiency, thereby boosting commercial value and market
competitiveness.