Cast Demographics, Unobserved Segments, and Heterogeneous Switching Costs in a Television Viewing Choice Model

Abstract

An accurate television viewing choice model is an important tool for television executives and advertisers. The authors present a new viewing choice model, which differs from the traditional Rust-Alpert model in three ways: (1) It introduces a new show characteristic—the demographic characteristics of a show's cast; (2) it allows the preferences over the traditional show categories to be a function of both observable and unobservable individual characteristics; and (3) it allows the cost of switching among the viewing alternatives to vary across show types and individual characteristics. Cross-validated predictive testing shows that this model fits the data better than the Rust–Alpert model does. Furthermore, the authors demonstrate that network executives can improve ratings by using this model. The authors predict that by following their scheduling strategies (in particular, by broadcasting comedies after 10:00 P.M.), ABC, CBS, and NBC could have increased their average ratings by 12.9%, 7.5%, and 6.7%, respectively, on selected evenings.

The Asymmetric Information Model of State Dependence

“…The first six b parameters capture the effect of cast demographics on the utility. Shachar and Emerson (2000) demonstrate that viewers have a higher utility from shows whose cast demographics are similar to their own. Thus, we expect to find that:…”

“…The television networks almost always place a preview advertisement for a show in the show preceding it. These previews, which can be considered as a ''bit of the product'' are quite informative, as illustrated by Shachar and Anand (1998). Thus, viewers are relatively well informed about the coming show on the same network.…”

“…Rust and Alpert (1984) show that viewers differ in their preferences over show genre, and Shachar and Emerson (2000) demonstrate that the demographic match between the casts and the viewers is an important factor in viewers' utility. Thus, we formulate X j,t b i as X j;t b i ¼ b Gender Á Ifthe gender of i and show j, t is the sameg þ b Age0 Á Ifthe age group of i and show j, t is the sameg þ b Age1 Á Ifthe distance between the age group of i and show j, t is oneg þ b Age2 Á Ifthe distance between the age group of i and show j, t is twog þ b Family Á Ifi lives with her family and show j, t is about family mattersg þ b Race Á Income i Á Ifone of the main characters in show j, t…”

“…One of the most striking features of loyalty appears in the television network industry. Although almost every household in the United States has a remote control, 65% of the viewers continue to watch the same network when a show ends and a new show starts (Shachar and Emerson 2000). The strong persistence in television viewing choices is well known in the industry and is named ''the lead-in effect.''…”

Business Models for Media Firms: Does Competition Matter for How They Raise Revenue?

“…Several studies of the media industry focus on program scheduling and, in particular, on the well-known 'lead-in'e¤ect (see, for example, Rust and Eechambadi, 1989, and Shachar and Emerson, 2000). 4 Other studies are concerned with the choice of programming, i.e., what programs to produce (see, for example, Liu et al, 2004).…”