Rachele Ciulli, PhD Candidate, The Wharton School; Cait Lamberton, Marketing, The Wharton School
Abstract: Every day, millions of people engage in the popular behavior called “binge-watching”, a type of media consumption where multiple episodes of the same TV show are seen in a row (Schweidel and Moe, 2016). Given how popular “binge-watching” is and how much streaming platforms are relying on it to recommend and create new content to stream, it is very important to understand whether consumers are satisfied by their binging sessions and whether recommendation systems are well calibrated in suggesting binge-worthy content that will maximize this satisfaction. What type of content is best to binge both for consumers’ satisfaction and for companies returns on investment? In this project, we propose a physics-inspired model capturing how consumers are more satisfied when they binge content they perceive as high in momentum; a content that streaming platforms’ algorithm would often classify as non-binge worthy. We test our theory through experiments and secondary data.