When the algorithm feels like mine: personalisation depth, algorithmic transparency and psychological ownership in continued streaming engagement

Purpose This study examines whether artificial intelligence (AI) personalisation depth and algorithmic transparency relate to continued engagement with streaming platforms through consumers’ psychological ownership of the recommendation stream, and over what range of privacy concern the transparency route holds. Design/methodology/approach A 14-day, two-wave panel of streaming subscribers in Türkiye (N = 450) was analysed with Partial Least Squares Structural Equation Modeling (PLS-SEM) and re-estimated with covariance-based SEM. A 2 × 2 between-subjects experiment (N = 236) manipulated both features. Findings Personalisation depth showed an indirect-only mediation pattern through ownership in the estimated model, with a direct path practically equivalent to zero within a pre-specified bound; the pattern replicated under random assignment. Ownership carried 45 per cent of the association between transparency and engagement, and a direct path accounted for the rest. The transparency–ownership link was no longer significant above a privacy-concern level of about 4.5 (7-point scale), a region holding roughly two in five respondents. Platform involvement strengthened the personalisation route; no group difference was detected for transparency. Research limitations/implications Participants were subscribers aged 18–35 in three Turkish cities, engagement was self-reported and ownership and engagement were measured on the same occasion. Practical implications Ownership measures can complement viewing and churn metrics when personalisation is evaluated, and layered explanations let users choose how much detail they see. Originality/value For interactive marketing, the study recasts the AI feed as a possession consumers co-produce, not exposure firms deliver. It tests, and does not assume, whether design features keep a direct relationship with engagement once ownership is modelled.