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The impact of online word-of-mouth on television show viewership: An inverted U-shaped temporal dynamic

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Abstract

This article examines the dynamic impact of online word-of-mouth (WOM) on US television show viewership. With WOM data collected from the Internet Movie Database website, we find that the cumulative volume of online WOM has significant explanatory power for viewership over time. Consistent with the mere exposure effect theory, the dynamic impact of the volume of online WOM over time varies according to a curvilinear, inverted U-shaped curve. Due to an initial floor effect, the volume of WOM is not significant in the early episodes. The impact of volume increases over time, before peaking and starting to decrease in the latter part of a show’s life. This article demonstrates the differential effects of online WOM over time and thereby suggests that firms’ online marketing strategies, such as media planning, must adjust with the product life cycle.

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Notes

  1. Although consumers are more likely to access recent information, the importance of past information likely decreases; so, our model grants greater weight to recent than to older online WOM information.

  2. Our data collection thus might suffer from a selection bias, because we focused on successful products (De Bruyn and Lilien 2008). However, our data set includes a wide range of heterogeneous shows; including unsuccessful shows canceled after as few as 26 episodes. This heterogeneity in product popularity is consistent with the research recommendations formulated by Zhu and Zhang (2010).

  3. The data include five Super Bowl events. For example, the episode of Grey’s Anatomy broadcast on February 5, 2006, was watched by more than 37 million viewers, whereas the show’s average viewership for the season was less than 20 million, representing a 185 % increase.

  4. With few time periods and many panel participants, estimation of a fixed effect model with lagged dependent variables may be subject to finite-sample bias (Arellano and Bond 1991). However, the bias is unlikely to be substantial in our sample, because the number of observations per show is not low (M = 89) and the number of shows is not large (N = 41). We also ran regressions for a random effect model, but the Hausman test revealed that the group-specific term is correlated with the independent variables, which violates the hypothesis of a random effect model and could lead to biased estimates.

  5. We also ran a regression with daily online WOM instead of cumulative information. Consistent with Godes and Mayzlin (2004), both daily volume and valence were not significant in this alternative model.

  6. We start with τ = 5, or the shortest period that includes enough data to estimate the model.

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Acknowledgments

The author wishes to acknowledge the support of the AFNOR Chaire Performance des Organisations of the Foundation of Paris-Dauphine. The author would also like to thank Beatrice Parguel, Manuel Cartier and the participants in the Paris Dauphine ERMES seminar, the 2013 BPF Camp in HEC Paris, and the 2013 Marketing Science Conference.

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  1. Paris Dauphine University, DRM – UMR CNRS 7088, Paris, France

    Romain Cadario

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  1. Romain Cadario
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Correspondence to Romain Cadario.

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Cadario, R. The impact of online word-of-mouth on television show viewership: An inverted U-shaped temporal dynamic. Mark Lett 26, 411–422 (2015). https://doi.org/10.1007/s11002-013-9278-6

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