Algorithmic Experience: Exploring User Perception of OTT Recommender Systems (RS)
(A2025-126034)

AUTHORS

Tushita Chadha, International Management Institute (IMI), New Delhi; Himanshu Joshi, International Management Institute (IMI), New Delhi; Neena Sondhi, International Management Institute- New Delhi

ABSTRACT

Globally, media consumption on OTT platforms is profoundly shaped by algorithms, particularly through recommender systems that provide users with diverse content choices. As a result, users save considerable time scrolling and selecting content that matches their preferences, leading to delightful encounters with choices. Despite the relevance of algorithms in shaping human-computer interactions, only a few studies have examined the Algorithmic Experience (AX) in shaping end-user experiences. The current study, rooted in Algorithmic Experience design framework, seeks to investigate user interactions with entertainment-centred recommender systems. A qualitative approach, utilizing semi-structured interviews with active OTT subscribers, delved into exploring user AX as a function of movie recommender systems. The findings reveal that users are susceptible to availability bias and are willing to compromise their privacy for the sake of delightful user experience. These insights shed light on users’ demand for convenience in their leisure activities, offering valuable guidance for further algorithm design.