Abstract
The increased time-shifted TV viewing practice undermines the role of traditional viewer ratings in gauging consumer interests in primetime TV drama. This paper introduces Google Trends data as a supplementary measure of popularity and proposes a lifecycle model for describing the pattern of search activity related to the TV drama shows. This is accomplished by developing three separate models that deal with three different phases (i.e., prerelease period, on-season period, and post-season period) that a TV drama series goes through. In our empirical analysis, we demonstrate that the proposed model provides an apt description of the diffusion pattern of consumer search activity related to a primetime TV drama series. We also show that the search volume cumulated during the pre-season period has the predictive power to expect the level of consumer interest in the upcoming season premiere. Furthermore, we find that the release of following seasons of a drama series accompanies the search for its previous seasons due to reciprocal spillover effects. Our findings indicate the importance of monitoring online search activity of consumers in the TV drama industry.
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