Describing the Dynamics of Attention to TV Commercials: A Hierarchical Bayes Analysis of the Time to Zap an AdPaul Gustafson and S. Siddarth Journal of Applied Statistics, 2007, vol. 34, issue 5, pages 585-609 Abstract: This paper provides insights into the dynamics of attention to TV commercials via an analysis of the length of time that commercials are viewed before being 'zapped'. The model, which incorporates a flexible baseline hazard rate and captures unobserved heterogeneity across both consumers and commercials using a hierarchical Bayes approach, is estimated on two datasets in which commercial viewing is captured by a passive online device that continually monitors a household's TV viewing. Consistent with previous findings in psychology about the nature of attentional engagement in TV viewing, baseline hazard rates are found to be non-monotonic. In addition, the data show considerable ad-to-ad and household-to-household heterogeneity in zapping behavior. While one of the datasets contains some information on characteristics of the ads, these data do not reveal any firm links between the ad heterogeneity and the ad characteristics. A number of methodological and computational issues arise in the hierarchical Bayes analysis. Keywords: Heterogeneity; hierarchical Bayes; marketing (search for similar items in EconPapers) Downloads: (external link) Related works: Ordering information: This journal article can be ordered from Access Statistics for this article Journal of Applied Statistics is edited by Professor Gopal K. Kanji More articles in Journal of Applied Statistics from Taylor and Francis Journals |
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