without major delays and buffering.
6
However, if Internet connection speeds rise signif-
icantly (as seems bound to happen eventually, if not yet imminently), then I expect sim-
ilar changes might occur in the television industry. However, in the presence of binding
video distribution constraints, it seems possible that online video will continue to exist as
a supplement to traditional television consumption, a channel for niche program
demand, user-generated content, delayed releases of major networks’ content, and a
means for incumbent programmers to identify high-value production inputs.
5.3. EFFECTS OF MEDIA MULTITASKING
A consumer who is watching television has two primary motivations to multitask:
(i) information search which has been prompted by something on the television screen
or (ii) seeking refuge from aversive television content (such as advertising or boring parts
of a program). I will refer to these as media complementarities and competition for atten-
tion, respectively.
Multitasking behavior has been studied in laboratory experiments and in-home
observational studies. For example,
Pearson and Barwise (2007) analyzed videotapes
recorded within 22 households. They found that viewers paid attention to 79% of com-
mercials presented during live programming, defined as “participants looking directly at
and listening to the TV while doing nothing else which required conscious attention.”
They also reported that usage of the digital video recorder is nearly always secondary to
live viewing, even among young viewers.
Jayasinghe and Ritson (2013) studied video-
tapes and interviews from eight Australian households, showing a variety of means by
which family members engaged with or ignored advertisements.
Brasel and Gips
(2011)
videotaped 42 college students and staff while they used television and Internet
simultaneously in a lab. Subjects switched their attention between television and Internet
four times per minute on average, and subsequently underestimated their own switching
behavior by a factor of 8. Although findings from such small samples might not represent
the broader population, they provide vivid depictions of viewer behavior in natural
settings.
5.3.1 Media Complementarities
Do firms achieve economies of scope by simultaneously advertising in multiple media?
These might be achieved by spreading the media budget across multiple media to reinforce
6
Waldfogel (2009) surveyed college students to understand how usage of Internet video affected their tele-
vision consumption. He found that the availability of unlicensed television content on youtube.com led
to slightly lower network television viewing but an offsetting increase in consumption on television
networks’ websites.
218
Handbook of Media Economics
the message with multitasking consumers in a way that single-medium advertising is unable
to do. Also, advertising in more media may reach single-tasking consumers who might oth-
erwise remain uncontacted. Numerous recent studies have found evidence of synergistic
effects between television advertising and Internet advertising on offline sales (
Kolsarici and
Vakratsas, 2011; Naik and Peters, 2009; Naik and Raman, 2003; Naik et al., 2005; Ohnishi
and Manchanda, 2012; Stephen and Galak, 2012
). However, these studies mostly used
aggregate data, which may have trouble disentangling multimedia synergies from other
unobserved variables that may correlate with both advertising expenditures and sales. Fur-
ther corroborating evidence has been found in investigations of individual-level data by
Bollinger et al. (2013) and Zantedeschi et al. (2014).
There now exists substantial evidence that television advertisements can prompt con-
sumer search.
Zigmond and Stipp (2010, 2011) offered several case studies showing that
search queries entered at google.com responded immediately to television advertisements
broadcast during the Winter Olympics.
Lewis and Reiley (2013) showed that search
queries at yahoo.com for particular brands spiked instantly during Super Bowl commer-
cial breaks when those brands advertised (and did not spike during commercial breaks
when the brands did not advertise).
Joo et al. (2014, 2015) investigated hourly advertising
and Google search data for a mature category (financial services) over a 3-month period,
showing that TV advertising generated new searches in the product category and also
increased the share of searches that included branded keywords.
There is also a substantial body of evidence that Internet behavior prompted by adver-
tising leads to online sales.
Wu et al. (2005) offered the first such evidence. They showed
that online-only firms’ use of magazine advertising can lead shoppers to a website, and
that subsequent conversion rates depend on website characteristics. They also found that
joint modeling of user acquisition and conversion was required for correct inference, as
unobserved characteristics in visit generation and sales leads may be correlated. More
recently,
Kim and Hanssens (2014) examined data on advertising, blog mentions, online
search, and revenue for motion pictures. They found that pre-launch advertising gener-
ated both search and blogging, and blogging generated further search.
Hu et al. (2014)
brought search data collected from Google Insights for Search into a sales/advertising
response model. Using aggregate data, they found that automotive advertising is associ-
ated with a positive search lift for automotive brands, as well as a heightened conversion
probability among interested consumers.
Liaukonyte et al. (2015) estimated how mea-
sures of online shopping behavior (traffic and sales) at 20 brand websites changed in nar-
row windows of time around the airing of television advertisements, and how those
effects depended on ad content. They found that direct response tactics increase both visit
probability and purchase probability. In contrast, informative or emotional branding tac-
tics reduce traffic while simultaneously increasing sales among those who do visit, con-
sistent with improving the efficiency of consumer search, as predicted by
Anderson and
Renault (2006)
.
219Recent Developments in Mass Media
Finally, there is substantial evidence supporting the converse effect: Internet content
can influence television viewing. Early work in this area focused on the effects of online
“buzz” on television viewing and book sales (
Chevalier and Mayzlin, 2006; Godes and
Mayzlin, 2004
). More recently, Gong et al. (2015) ran field experiments in China, show-
ing that television program ratings respond to promoted posts and content posted on a
microblogging service.
Hill and Benton (2012) developed a method by which con-
sumers’ Twitter accounts can be mined to generate television program recommenda-
tions. In summary, there is ample evidence that television content and advertising can
drive online behavior, and that online information can influence television viewing
choices.
5.3.2 Competition for Attention
Anderson and de Palma (2012) modeled how consumer attention constraints affect prod-
uct market competition and advertising. They predicted that the entry of additional clas-
ses of new products would raise advertising prices and clutter, but only up to a point. At
some point, so many ads are sent that product market competition intensifies and adver-
tising profitability falls.
7
Wallsten (2014) investigated ATUS data to determine how increasing attention paid to
one medium (Internet) affects the attention paid to other activities, such as watching TV.
He found that each additional minute of Internet usage is associated with 0.13 fewer
minutes watching television.
Woo et al. (2014) investigated similar survey data from South
Korea, replicating the negative correlation between television and Internet use, but finding
a much smaller negative correlation between television and Internet use on a mobile device
than between television and Internet use on a desktop computer.
Zentner (2012) quantified
how Internet adoption changed advertising revenue in a panel dataset of 80 countries. He
found negative correlations between Internet penetration and television and print adver-
tising revenues, but no correlation with radio advertising revenues.
Perhaps the best evidence comes from
Reis (2015). Reis analyzed data from a “triple-
play” television/phone/Internet provider and showed, using both an instrumental vari-
ables approach and a field experiment, that increased television consumption is associated
with smaller Internet download traffic. However, even this does not speak to how mul-
titasking is influenced by television consumption, as an increase in multitasking time may
be reflected as a decrease in download traffic. No study has yet presented solid evidence
on simultaneous usage of both television and Internet in a large-scale sample, perhaps due
to the difficulties inherent in acquiring passive measurements of individuals’ simultaneous
media behavior from multiple competing platforms.
7
See also Chapter 10.
220 Handbook of Media Economics
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.