9 – Session 2 – 12:15-1:45 pm
Impact of Personal Involvement, Ad Avoidance, and Goal Systems on Viewer’s
Willingness to Watch Advertisements during Online Streaming Shows
Jae Jung, Christian Lindke, California State Polytechnic University, Pomona,
In the past two decades, American media have witnessed significant changes in the way
audiences consume entertainment media. Historically, the advertising-based revenue model
has been highly profitable for the television industry, but the model is changing radically as new
media technologies emerge (Berman, Battino, and Feldman 2011). The advertising-based
model has been undermined by the “phenomenon of the free” (Berman, 2011) and the
introduction of substitutes such as the DVR, DVDs, video-on-demand (VOD), and mobile video
(Klopfenstein, 2011). Viewers can increasingly watch content at a time of their own choosing
and shift their viewing behavior from traditional TV to various formats (Bondad-Brown, Rice, and
Pearce, 2012). Further, consumers can minimize or eliminate their exposure to advertising
through zipping or zapping (Cronin and Menelly, 1992; Wilbur 2008; Chen, Shang, and Lin,
2008).
Leading this transformation in digitization are Millennials, who differ significantly from earlier
generations in attitudes and behaviors (Pinzaru, Savulescu, and Miltan, 2013). Millennials are
more likely to get their entertainment from digital means than from traditional media (Tanyel,
Stuart, and Griffin, 2013). They are also more critical of internet-based advertising than they are
of traditional advertising (Tanyel, Stuart, and Griffin, 2013). According to a study conducted by
Motorola, over 80 percent of Millennials influence their parents in selection of broadband choice
or TV services, even if they do not live with their parents (Motorola, 2008).
Hence, understanding Millennials is important. Research shows that personal involvement is a
strong predictor of Millennial’s willingness to interact with digital content (Botha and Reyneke,
2013), showing potential for the appropriateness of traditional models in predicting Millennial’s
behaviors. Other research also tried to understand motivations of Millennials to share usershared video (e.g., Bondad-Brown, Rice, and Pearce, 2012), but unclear to date is what
influences Millennials’ willingness to watch online streaming video programs that contain
advertising or their willingness to watch advertising during online streaming viewing experience.
To fill this gap, we draw on extant literature on advertising as well as consumer psychology to
identify key factors that influence willingness to watch online program and advertising. Our
research examines three factors—personal involvement, ad avoidance, and viewers’ goal
systems (equifinality vs. multifinality; Kruglanski et al. 2002). This research expects that viewers’
equifinality set, the number of means a viewer uses to watch programming (Orehek et al., 2012)
and viewer’s multifinality set, the number of goals that a viewer pursues with a means, influence
Millennials’ willingness to watch differently. This study expects also that these goals systems
moderate the impact of involvement and ad avoidance on their willingness to watch online
programing that contains the ad. In addition to these hypotheses, this study will also compare
Millennials with other age cohort groups (e.g., Gen X) to explore generational differences. To
test the research hypothesis and address the research question, this study takes a sample of
700 Millenials and other generation groups from consumer panel using a questionnaire that
includes all the key measures necessary for hypothesis testing. Structural Equation Modeling
will be used to test the hypothesis.
Our study contributes to the theory about television viewer behavior with regard to the personal
involvement and ad avoidance by updating it to current technologies and an initial examination
of the role that goal systems play in viewing behavior. Further, our findings will provide
practitioners with important information as they adapt their business models to address these
changing technologies. Since digital management capabilities will likely become a core
competency and differentiator (Berman 2004), looking at those techniques that have been most
successful in responding to the changing marketplace may help television networks remain
profitable in a changing marketplace.
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