Algorithmic Personalization Impact on Streaming Service Continuance

The escalating dynamics of information technology profoundly shape consumer adaptation to digital products, particularly streaming video services. In the competitive Video on Demand (VoD) market, platforms like Netflix leverage extensive content libraries and personalized recommendations as critical competitive advantages. This study investigated the impact of algorithmic personalization on user cord-cutting and continuance intention, mediated by perceived advantage and perceived value. Employing a quantitative approach, data were collected via a national survey from 150 Indonesian Netflix subscribers. Analysis using Structural Equation Modeling-Partial Least Squares (SEMPLS) revealed that personalization significantly influences users’ continuance intention for VoD services. However, personalization was found to have no significant direct or mediated effect on cord-cutting intention. These findings provide valuable insights for VoD platform providers, emphasizing the need to develop strategies that bolster user engagement and retention through effective personalization, rather than solely focusing on cord-cutting prevention.