Modelling viewing patterns of serial TV dramas considering live viewing and time shifting

In this study, we focus on the segmentation of viewing behavior for serial TV dramas at the individual level, considering both live and time-shift viewing. In particular, many consumers have recently engaged in time shifting after a program is broadcast, in addition to live viewing. Time-shift viewing is prominent in drama viewing because drama viewing may be less urgent. However, few studies that focus on individual-level viewing choice models have considered time shifting and no studies have utilized segmentation to analyze heterogeneous viewing patterns that consider live viewing and time-shifts. We use a multinomial probit (MNP) model to capture viewing or not viewing and viewing method (live or time shifting). Furthermore, a latent growth curve model and a latent class model are included in the MNP model to represent heterogeneous patterns of viewer retention and dropout as episodes progressed. We analyze six individual dramas and a simultaneous analysis of multiple dramas broadcast in 2019. The results show that segments are affected by popularity and growth curve models, as well as differences in viewing rate trends by episode and segment. The findings provide information that can support marketing research and media strategies.