Hulu.com or NBC? Streaming Video versus Traditional TV
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
Hulu.com or NBC?
Streaming Video versus Traditional TV
A Study of an Industry in Its Infancy
KELTY LOGAN The research employed online interviews among young adult viewers of online
University of Colorado-
streaming television and traditional television to determine how media differ in terms
Boulder
kelty.logan@colorado.edu of use and advertising perceptions and avoidance. Results indicated more similarities
than differences. Significant differences regarded the amount of use and viewer
attitudes toward advertising. Specifically, young adults watched 62 percent more
traditional television than online television and were significantly less tolerant of online
television advertising. These findings appeared to reflect the convenience-orientation
of online television viewers. Advertisers should note that advertising presence on
online streaming television will increase their message frequency among young adults.
INTRODUCTION AND REVIEW important advantages to advertisers seeking to dif-
Thirty years ago, television was the medium that ferentiate their media portfolio:
drove the creation of advertising. In 2011, adver-
tisers aggressively are seeking alternatives to tel- • The advertising environment is very similar
evision advertising in the wake of escalating costs to traditional television in that it provides epi-
and decelerating reach. Audience erosion has been sodic television programs interspersed with
attributed to the proliferation of television chan- commercials.
nels and the increasing popularity of media alter- • Online streaming video (OTV) appeals to a
natives such as video rentals, video games, and young audience that is difficult to reach on tra-
Internet use. Although the new media options ditional television owing to their light television
often provide advertisers with the ability to micro- viewership and heavy usage of technology to
target an advertising message, television remains avoid advertising.
a reliable—if expensive—medium for achieving • The current format of OTV does not provide
broad reach. This article investigates the relatively viewers with the opportunity to zip or zap
new phenomenon of online access to television commercials.
programming in the belief that advertisers can
use online streaming television to increase the effi- OTV episodic television has been available
ciency of television advertising. to consumers since 2008. At present, consumers
As of April 2010, Nielsen stopped reporting how can access first-run television shows on all of the
many channels the average television household major network sites including ABC.com, CBS.com,
receives because a television channel’s content is CWTV.com, Fox.com, and NBC.com. Current tel-
no longer accessed in a single, easily measurable evision programming also can be accessed on con-
manner (Mandese, 2010). Television viewers now tent aggregator sites such as Hulu.com, Fancast.
are able to time-shift content by recording shows com, and TV.com. These aggregator sites are the
or accessing content online. Online streaming result of partnerships between networks and
television programming, however, offers three production companies and, consequently, offer
276 JOURNAL OF ADVERTISING RESEARCH March 2011 DOI: 10.2501/JAR-51-1-276-287THE FUTURE: ONLINE STREAMING VIDEO
a broader range of programs than the net- intention to increase the advertising load The potential effectiveness of an adver-
work sites. on its online television episodes to repli- tisement depends upon consumers’ will-
Today approximately 85 percent of U.S. cate the television advertising load (Fried- ingness to view the advertising. In other
Internet users view online video. The man, 2010). words, the primary barrier to advertising
duration of the average online video is 4.3 To assess the attractiveness of the online effectiveness is advertising avoidance. It
minutes, reflecting the dominance of the television environment relative to tra- has been suggested that advertising avoid-
YouTube site. YouTube accounts for about ditional television, advertisers need to ance in a specific medium is related to
40 percent of all videos viewed online. understand more about consumers’ use of perceived advertising clutter (Elliott and
Hulu.com ranks second as a video destina- both media. This study will evaluate the Speck, 1998; Greyser, 1973) or advertising
tion with less than a 4-percent share (com- differences between the two media types intrusiveness in that medium (Li, Edwards,
score.com 2010). Approximately 30 percent in terms of both reception context and and Lee, 2002). Although advertising clut-
of 18- to 34-year-old U.S. Internet users potential advertising effectiveness among ter refers specifically to overexposure to
view complete television show episodes young adults. advertising, “advertising intrusiveness”
online (Knowledge Networks, 2009). “Reception context” refers to the degree refers to the target consumer’s perception
Although it is readily apparent to adver- of audience activity associated with a spe- of the negatives associated with advertis-
tisers that online access of episodic televi- cific medium. This notion describes why ing in a specific medium. Intrusion meas-
sion is increasingly popular, there is little and how a specific consumer target uses ures the extent that advertising interferes
information regarding how the reception a specific medium. Conceptually, it is a with the enjoyment of media content, or
context may affect advertising effective- composite of motives for use of a specific content utility. It reflects consumers’ per-
ness. A recent Nielsen IAG survey (2010) medium, usage patterns, and affinity for ceptions of advertising clutter and their
indicated that online video commercials the medium. perceived ability to avoid the advertising.
had better recall than television com- “Motives for media use” are defined Advertising avoidance—the bane of
mercials. The report suggested, however, as “… general dispositions that influence all advertisers—has been made easy for
that the positive results may have been people’s actions taken to fulfill a need or those who record television shows. They
attributable to the inability to fast-forward want” (Papacharissi and Rubin, 2000). In can simply fast-forward through com-
through the online videos coupled with 1984, Rubin determined that two kinds mercials during the replay. There are other
the reduced clutter offered by the online- of media use—ritual and instrumental— advertising-avoidance methods, however,
video environment. reflected significantly different motives, that can be utilized when viewing televi-
Both of these advantages may be short- content preferences, usage levels, affin- sion programming in real time or online.
lived. On May 7, 2010, the FCC granted ity for a specific medium, and degree of Demographic characteristics are strong
“selectable output control” to content involvement in the medium. predictors of media avoidance (Speck and
producers (Bond, 2010). The ruling is Rubin defined “ritual media use” as Elliott, 1997); younger consumers are most
intended to prevent the recording, shar- “ritualized use of a medium to gratify likely to avoid advertising. When evaluat-
ing, and piracy of movies that are aired on diversionary needs or motives” (p. 69). ing online advertising, for example, young
television prior to release on DVD or Blu- Ritual use is related to enjoyment and, to adults (18 to 34) are very likely to ignore
ray. The ruling establishes a precedent for a certain extent, occupation of time. Rubin pop-up windows, banner ads, and click-
content providers to disable set-top boxes determined that ritual use is associated through ads (Mintel, 2007). Among young
remotely—a capability that could lead to with low levels of viewer involvement. adults (18 to 34), more than 40 percent
further efforts to stop viewers from time- “Instrumental use,” conversely, Rubin reported that they avoid watching televi-
shifting programming. If this practice were wrote, is “goal-directed use of media sion commercials, and nearly 50 percent of
widely adopted, viewers could lose the content to gratify informational needs or them changed the channel when commer-
ability to fast-forward through television motives.” Such media usage is driven by cials air (Mintel, 2005).
commercials. Although the threat of losing the need to know something such as a
control of the fast-forward button looms news update, a baseball score, or even the RESEARCH QUESTIONS
in the future, increased commercial clutter winner of “American Idol.” Rubin deter- The purpose of the current research is to
on Internet television soon may be a real- mined that instrumental usage is a more determine whether the advertising context
ity. In 2010, the CW network announced its involving experience than ritual usage. and potential advertising effectiveness
March 2011 JOURNAL OF ADVERTISING RESEARCH 277THE FUTURE: ONLINE STREAMING VIDEO
vary significantly between viewers of • RQ5: Does the perception of advertis- television programs viewed in “real time”
traditional, non-recorded television pro- ing intrusiveness vary between viewers and programs that were recorded for later
gramming, and OTV programming. Spe- of traditional broadcast television and viewing. Only participants who watched
cifically, this research seeks OTV? television in “real time” during the past
• RQ6: Do methods of advertising avoid- 3 months were included in the sample,
• to determine whether the degree of ance vary between viewers of tradi- and the questionnaire specified that all
involvement with the medium differs tional broadcast television and OTV? responses pertain only to “real time”
between television viewers and OTV viewership.
viewers; METHODOLOGY The unusually specific requirements
• to determine whether the amount of A 75-item online questionnaire was for participation resulted in a high rate of
viewer involvement is related to the ten- developed and modified for users of tel- disqualification. Only 27.9 percent of all
dency to avoid advertising; and evision and OTV. The questionnaire was respondents qualified for participation in
• to determine whether the tendency to pre-tested on a small sample of students the research and completed the question-
avoid advertising differs significantly to ensure clarity. The questionnaire con- naire (See Table 1). It should be noted,
between television and OTV viewers. sisted of six major sections focusing on however, that viewership of complete tel-
motives for media use; level of media use; evision episodes via streaming video has
Because no prior research has inves- media content; affinity for the medium; more than doubled among young adults
tigated OTV use in terms of motives for perceived advertising intrusiveness; and during the past 3 years (Knowledge Net-
use, types of programs viewed, amount advertising avoidance. All measures were works, 2009), indicating the increased
of usage, and affinity for the medium, established, five-point Likert-type scales likelihood of this participant profile in the
the following research questions will be (See Appendix A). future.
addressed. This information will provide A professional online-research ser-
an understanding regarding whether the vice collected the data. A national sample SUMMARY OF RESULTS
viewing context differs between television of approximately 380 participants was Comparison of Reception Context for
and OTV. recruited for each media type (television Television and OTV
and OTV) between the ages of 18 and 34. Motives for Media Use. The primary
• RQ1: Do viewers of traditional televi- Participants were screened to reflect the motive for media use—entertainment—
sion broadcasts have different motives gender, race, ethnicity, education, and did not vary significantly between users of
for media use compared to viewers of income of the U.S. adult Internet users television and OTV. Nearly 60 percent of
OTV? (See Appendix B). Participants also were television viewers and 70 percent of OTV
• RQ2: How does viewership of tradi- screened for media usage. viewers reported that they had used the
tional television differ from viewership Specifically, all participants had viewed medium for entertainment (See Table 2).
of OTV in terms of types of program- episodic television programs on tradi- Confirmatory use of exploratory factor
ming viewed? tional television and OTV during the past analysis—employing television and OTV
• RQ3: How does viewership of tradi- 3 months. Regarding traditional television data—determined that the loadings of
tional television differ from viewership viewership, the screener and question- items for Motivations for Media Use cor-
of OTV in terms of hours of usage? naire explicitly differentiated between responded to the two patterns of media
• RQ4: How does viewership of tradi-
tional television differ from viewership TABLE 1
of OTV in terms of media affinity?
Participant Screening Results
TV Group % OTV Group % Total %
Furthermore, no prior research has inves-
tigated attitudes and behaviors regarding Total Screened 1,346 100.0 1,360 100.0 2,706 100.0
online advertising. This information will Screen Outs 934 69.4 953 70.1 1,887 69.7
provide an understanding regarding the
Partials 33 2.5 30 2.2 63 2.3
relative receptivity to advertising among
viewers of television and OTV. Completes 379 28.2 377 27.7 756 27.9
278 JOURNAL OF ADVERTISING RESEARCH March 2011THE FUTURE: ONLINE STREAMING VIDEO
TABLE 2 TABLE 3
Motivations for Media Use Factor Matrix: Motives for
TV (n = 379) OTV (n = 377) Television Viewership
% Agree/ % Agree/ Factor 1 Factor 2
Mean SD Strongly Agree Mean SD Strongly Agree Motivation (Ritual) (Instrumental)
Entertainment 3.76 0.74 57.6 3.90 0.66 67.6 Arousal/Excitement –0.07 –0.96
Pass Time 3.72 0.74 53.8 3.64 0.79 48.0 Companionship 0.06 –0.74
Habit 3.65 0.72 48.3 3.51 0.69 33.4 Entertainment 0.77 –0.01
Relaxation 3.57 0.82 46.1 3.57 0.77 49.2 Economics/ 0.52 –0.00
Inexpensive
Economics/Inexpensive 3.45 0.92 41.2 3.87 0.79 59.9
Escape/Forget 0.39 –0.45
Convenience 3.16 1.04 40.7 3.48 0.98 53.8
Habit 0.93 0.09
Social Interaction 3.48 0.79 36.3 3.03 0.86 19.1
Information/ –0.03 –0.79
Escape/Forget 3.26 0.85 26.1 3.16 0.87 24.0 Learning
Information/Learning 3.02 0.91 20.3 2.85 0.99 17.5 Pass Time 0.78 0.06
Companionship 2.90 0.99 20.0 2.74 0.96 13.6 Relaxation 0.63 –0.06
Arousal/Excitement 3.02 0.83 15.8 3.25 0.81 24.9 Social Interaction 0.43 –0.37
Convenience 0.26 –0.48
use (ritual and instrumental) identified Independent groups’ t-tests also
by Rubin (1984). Entertainment, the pri- revealed that motives for media use var-
TABLE 4
mary motive for both television and OTV ied by gender. Specifically, men were more
groups, is classified as ritual usage. likely than women to use television and
Factor Matrix: Motives for
For each group, two factors were pro- OTV for information, arousal, and excite- Online Streaming Television
duced by the oblique-rotated, principal ment than women (Tables 6 and 7). Viewership
axis factoring method employed by Rubin.
Factor 1 Factor 2
For the television group, the first factor Media Content. Both television and OTV
Motivation (Ritual) (Instrumental)
had an Eigenvalue of 6.33 and explained users were more likely to watch enter-
Arousal/Excitement 0.34 –0.53
57.5 percent of the total variance. The sec- tainment types of programming than
ond factor was less substantial with an informational programming (See Table Companionship –0.08 –0.84
Eigenvalue of 1.04, explaining 9.4 percent 8). Canonical correlation analysis deter- Entertainment 0.88 0.17
of the total variance (see Table 3). For the mined that certain program types were Economics/ 0.72 0.09
OTV group, the first factor had an Eigen- associated with ritual or instrumental for Inexpensive
value of 5.76 and explained 52.4 percent of television use, but there was no association
Escape/Forget 0.32 –0.57
the total variance. The second factor was between program types and motivation for
Habit 0.62 –0.22
less substantial with an Eigenvalue of 1.47, OTV use (See Appendices C and D).
explaining 13.4 percent of the total vari- Information/ –0.07 –0.88
Learning
ance (see Table 4). Level of Media Use. Respondents indi-
Independent groups’ t-tests revealed cated the number of hours and minutes Pass Time 0.64 –0.14
that television users were more likely to they spent with each medium (televi- Relaxation 0.64 –0.24
use the medium for social interaction than sion and OTV) during the previous day
Social Interaction 0.11 –0.73
OTV users. OTV users, conversely, were for each of six, 3-hour time periods. The
Convenience 0.47 –0.25
more likely to use the medium for conven- methodology assumed that respondents’
ience and economics (See Table 5). recall regarding their own actions was
March 2011 JOURNAL OF ADVERTISING RESEARCH 279THE FUTURE: ONLINE STREAMING VIDEO
TABLE 5 basis of gender. Television and OTV levels
of usage did not vary significantly on the
Independent Groups’ t-Tests: Comparison of Television and
basis of age (18–24 versus 25–34 years).
OTV Motives for Use
Group N M SD t df p Affinity for the Medium. Though there
Social Interaction TV 379 3.48 0.79 7.56 754 0.001 was no significant difference between
the OTV and television groups in terms
OTV 377 3.03 0.86
of media affinity, among OTV users,
Convenience TV 379 3.16 1.04 4.28 754 0.001 men had significantly more affinity for
OTV 377 3.48 0.98 the medium (M = 2.74, SD = 0.89) than
Economics TV 379 3.45 0.92 6.74 754 0.001 women (M = 2.53, SD = 0.89), t(375) = 2.23,
p < 0.05.
OTV 377 3.87 0.79
Comparison of Perceived Advertising
TABLE 6 Intrusiveness and Avoidance for
Television and OTV
Independent Groups’ t-Tests: Comparison of Motives for
Advertising Intrusiveness. An independ-
Television Use by Gender ent group’s t-test indicated a significant
Group N M SD t df p difference between the means, t(754) = 2.82,
p < 0.01, suggesting that users of online
Arousal/Excitement Men 207 3.12 0.83 2.61 377 0.010
television regarded advertising as more
Women 172 2.89 0.81
intrusive than television users. Nearly 60
Information/Learning Men 207 3.14 0.91 2.01 377 0.001 percent of OTV users agreed that advertis-
Women 172 2.87 0.89 ing was distracting, whereas fewer than
half of the television users agreed with the
same statement (See Table 10).
TABLE 7
Independent Groups’ t-Tests: Comparison of Motives for OTV Advertising Avoidance. An independent
Use by Gender group’s t-test indicated a significant differ-
Group N M SD t df p ence between the means, t(754) = 2.34, p <
0.05. This suggested that television view-
Arousal/Excitement Men 206 3.37 0.78 3.03 375 0.001
ers were more likely to avoid ads than OTV
Women 171 3.11 0.83 viewers. The responses indicated that tel-
Information/Learning Men 206 2.98 0.99 2.85 375 0.001 evision viewers had different alternatives
versus OTV viewers. For example, 47 per-
Women 171 2.70 0.95
cent of the television group indicated they
were most likely to switch channels dur-
extremely reliable for a 24-hour period average of 2.9 hours of OTV usage during ing commercials, whereas the OTV group
but diminished significantly beyond that the prior day, nearly 2 hours less media was most likely to mentally tune out the
scope. usage per day compared to the television commercials (See Table 11).
Television users reported an average of group (See Table 9).
4.7 hours of television usage during the An independent t-test revealed that men DISCUSSION
prior day, which was consistent with the watched more hours of television (M =
4.8 hours estimated by the U.S. Census 338.09 hours, SD = 277.62) than women RQ1: Do viewers of traditional televi-
(2009). Compared to the television group, (M = 236.94 hours, SD = 236.94), t(377) = sion broadcasts have different
the OTV users reported far less media 1.99, p < 0.05 whereas the level of OTV motives for media use compared
usage. Specifically, OTV users reported an usage did not vary significantly on the to viewers of OTV?
280 JOURNAL OF ADVERTISING RESEARCH March 2011THE FUTURE: ONLINE STREAMING VIDEO
TABLE 8 rather than instrumental motivations and
evoked similar, relatively low levels of
Programming Preferences viewer involvement.
TV (n = 379) OTV (n = 377) OTV satisfies an economic need, how-
Every Every ever, that television does not address.
Program Type Mean SD Week (%) Mean SD Week (%) Specifically, a key differentiating motive
Movies 4.05 1.20 50.4 3.37 1.52 35.2 for OTV use is the ability to access televi-
sion content without paying for cable-tel-
Drama 3.80 1.42 47.8 3.17 1.58 31.7
evision access. There also were indications
Sitcoms 3.52 1.52 40.4 2.93 1.53 24.9 that men were more likely than women
Sports 3.27 1.58 35.6 2.45 1.57 18.3 to use both television and OTV for infor-
mational needs and, therefore, exhibited
Action 3.12 1.60 30.9 2.93 1.53 21.4
higher levels of involvement with the
Talk 2.96 1.56 27.2 2.26 1.47 13.5
media. Finally, it appeared that viewer-
Reality 3.00 1.60 26.4 2.46 1.56 17.2 ship of OTV more likely was a solo activity
Variety 2.80 1.60 23.5 2.39 1.58 17.5 that may have been conducted in an out-
of-home environment. Out-of-home usage
News 2.79 1.59 23.0 2.20 1.48 13.0
may have explained the fact that OTV
Humor 3.09 1.41 22.2 2.74 1.54 18.5 usage—compared to television usage—
Children’s 2.54 1.64 21.6 2.30 1.58 15.3 was less likely to be motivated by social
Fake News 2.68 1.55 19.3 2.31 1.52 13.5 interaction.
Game 2.91 1.46 19.0 2.17 1.48 11.9
RQ2: How does viewership of tra-
Magazines/Documentaries 2.60 1.45 14.2 2.21 1.44 11.9 ditional television differ from
Soaps 1.84 1.39 10.3 1.75 1.34 8.5 viewership of OTV in terms of
types of programming viewed?
Religious 1.66 1.25 6.9 1.62 1.24 7.4
TABLE 9 The results indicated that, overall, the
television and OTV groups did not differ
Media Usage by Daypart (Prior Day) in terms of program content preference.
Time Periods TV (n = 379) OTV (n = 377) Index Vs. TV Users of television and OTV were more
5:00 AM–7:59 AM 8.7% 9.0% 103 likely to view entertainment content (e.g.,
comedy and drama) rather than informa-
8:00 AM–10:59 PM 11.0% 12.5% 114
tional content (e.g., news and sports).
11:00 AM–1:59 PM 14.2% 14.5% 102
2:00 PM–4:59 PM 17.0% 16.5% 97 RQ3: How does viewership of tra-
5:00 PM–7:59 PM 21.3% 19.6% 92 ditional television differ from
viewership of OTV in terms of
8:00 PM–11:00 PM 27.7% 28.0% 101
hours of usage?
100.0% 100.0%
Average Hours of Use 4.7 2.9 62 Television viewership was significantly
higher than OTV viewership among young
adults. These findings were consistent
The findings suggested that there were primarily were used for entertainment regardless of whether participants were
no significant differences between users rather than information. This suggested younger (18–24), older (25–34), male, or
of television and OTV in terms of motives that both television and OTV were used female. Specifically, participants reported
for media use. Both television and OTV to satisfy primarily ritual motivations an average of 4.7 hours of television usage
March 2011 JOURNAL OF ADVERTISING RESEARCH 281THE FUTURE: ONLINE STREAMING VIDEO
TABLE 10 television group. Nearly 60 percent of
OTV users agreed that advertising was
Perceived Advertising Intrusiveness
distracting; fewer than half of the televi-
TV (n = 379) OTV (n = 377) sion users agreed with the same statement.
% %
When I watch % Neither % Neither % RQ6: Do methods of advertising
television in Strongly Agree % Disagree/ Strongly Agree Disagree/ avoidance vary between view-
real time, the Agree/ nor Strongly Agree/ nor Strongly ers of traditional broadcast tel-
advertising is … Agree Disagree Disagree Agree Disagree Disagree evision and OTV?
Distracting 48.3 31.1 20.6 57.0 27.6 15.4
Disturbing 33.3 37.2 29.6 39.3 31.8 28.9 The findings suggested that television
viewers were more likely to avoid adver-
Forced 51.2 33.5 15.3 56.7 30.8 12.5
tisements than OTV viewers, reflecting
Interfering 51.5 34.3 14.2 56.0 29.7 14.4 the greater number of avoidance options
Intrusive 48.1 37.2 14.7 53.6 31.6 14.9 available to television viewers. For exam-
ple, 47 percent of the television group
Invasive 36.7 43.5 19.8 43.2 36.6 20.1
indicated they were most likely to switch
Obtrusive 35.9 43.0 21.2 42.0 39.0 19.0
channels during commercials. OTV view-
ers were most likely to mentally tune out
TABLE 11 the commercials.
Advertising Avoidance
CONCLUSIONS
TV (n = 379) OTV (n = 377)
The research suggested that young adults
% Never/ % % Almost % Never/ % % Almost (ages 18–34) used online episodic televi-
During commercials Almost Some- Always/ Almost Some- Always/ sion to augment their traditional television
I… Never times Always Never times Always use. Young adults appeared to watch the
Leave the room 8.7 63.9 27.5 17.3 47.7 25.0 same types of programs for the same ritu-
Mentally tune out 9.0 45.9 45.1 8.8 38.2 53.1 alistic motives regardless of the medium.
the commercials The disparate amount of viewing time
attributed to the two media suggested,
Switch programs 10.8 42.0 47.3 27.0 35.5 27.4
however, that television was the primary
during commercials
medium, accounting for more than 60 per-
Lower the volume 34.3 39.6 26.1 25.2 41.1 33.7 cent of the total viewing time.
during commercials
Online episodic television (OTV)
appeared to provide an economical, addi-
versus 2.9 hours of OTV usage. Interest- terms of affinity for the specific medium. tional usage occasion. Young men (ages
ingly, although men watched more tel- Among the OTV group, however, men 18–34) appeared to be an attractive target
evision than women, men and women indicated significantly more affinity for for advertising within OTV programming.
reported similar levels of OTV use. the medium. They demonstrate higher levels of affin-
ity for the medium compared to women
RQ4: How does viewership of tra- RQ5: Does the perception of advertis- viewers and were more likely than women
ditional television differ from ing intrusiveness vary between to use the medium for informational
viewership of OTV in terms of viewers of traditional broadcast use, indicating greater levels of viewer
media affinity? television and OTV? involvement. Furthermore, although OTV
advertising was viewed as intrusive, it
There was no significant difference The online television group regarded was more likely to be viewed than televi-
between the television and OTV group in advertising as more intrusive than the sion advertising because the OTV viewer
282 JOURNAL OF ADVERTISING RESEARCH March 2011THE FUTURE: ONLINE STREAMING VIDEO
was less likely to be distracted by compan- media including income, education, DR. KELTY LOGAN is a member of the advertising faculty
ions and had fewer options to avoid the geographic location, and innumerable at the University of Colorado at Boulder. She earned
advertising. other, unknown covariates. As a conse- her Ph.D. at The University of Texas at Austin. She has
Online television may be in an early quence, the sample screening process over 20 years of experience as a marketing executive
adoption phase. Though young adults generated a unique participant profile. in the advertising, broadcast network, and product
already have formed viewing habits By requiring the same usage experience marketing industries. She worked for multinational
that are difficult to break, teenage view- from all participants, the design gained advertising agencies in New York and Europe,
ers may be more inclined to incorporate certainty at the risk of generalizability. managed program promotion for NBC, and directed
online viewing into their television view- • The research design relied on self- brand management for Mars, Inc. As an academic
ing routine. Therefore, the percentage of reporting. It is possible, for example, she focuses on the challenges of the new media
total viewing attributed to online viewing that research responses reflected how environment for advertisers.
among young adults may expand over the participants feel they should respond
next few years. rather than their actual opinions.
Advertisers should note that advertising This especially may be true regarding
presence on OTV will increase their mes- the attitudes and perceptions about APPENDIX A
sage frequency among the young adult advertising. Measures
media target and, in particular, the young
adult male target. Advertising viewed in Future research should address the • Motives for Media Use were measured
an online television context also appeared limitations posed by the sample. By con- using an established 30-item, five-
to have a greater chance to be seen by the ducting research among respondents who point Likert-type scale (1 = “strongly
young adult target than ads viewed in a were not screened on the basis of recent disagree” and 5 = “strongly agree”) to
traditional television context. exposure to both types of media, it will be assess a variety of gratifications sought
OTV, however, does not provide suf- possible to compare results with those of from media use such as “Because it
ficient advertising reach as a stand-alone the present study and determine the effect relaxes me,” “Because it entertains me,”
medium owing to the relatively low usage of the sample composition. and “So I can get away from what I’m
levels among the young adult target. In addition, more should be learned doing” (Rubin, 1981; Papacharissi and
The combination of low usage levels and about how the young-adult target defines Rubin, 2000).
broad programming choices will make it their media environment. Do they, in fact, • Level of Media Use was measured using
difficult for advertisers to achieve effective distinguish between television and OTV an established self-reporting process
reach solely through OTV presence. Given when discussing television viewership? (Rubin, 1984). Respondents indicated
the similarities between the television Do they regard online television viewer- for each of six, 3-hour-long time periods
and OTV groups regarding programming ship as an extension of television usage or the number of hours and minutes they
type, it would make sense for advertisers as another aspect of online entertainment? spent using television or OTV during
to extend their network buys to include It would appear that the era of media the previous day.
the online versions of all appropriately tar- convergence is underway. When facing • Media Content was measured using an
geted programs. a paradigm shift in response to techni- established 16-item, five-point Likert-
The research design generated two limi- cal innovation, the challenge is to define type scale (1 = “Never watch” and 5 =
tations regarding the results: the category and determine the segments “Regularly watch”) to report how often
based on the consumer needs. Future participants watched various catego-
• The sample screening process generated research regarding comparison of media ries of television programs (Rubin 1981,
a unique participant profile. Specifically, in this period of rapid media evolution 1984). The program categories included
all participants had used television should help define both the category and areas such as “Situation Comedies,”
and online television within the past 3 segments. “News,” “Game Shows,” and “Reality
months. The screening process was an Programs.”
effort to avoid obtaining results that are • Affinity for the Medium was measured
confounded by individual differences using an established five-item, five-
between the users of different types of point Likert-type scale (1 = “Strongly
March 2011 JOURNAL OF ADVERTISING RESEARCH 283THE FUTURE: ONLINE STREAMING VIDEO
disagree” and 5 = “Strongly agree”) to APPENDIX B
assess the importance of each medium Sample Composition
importance in the context of the
participants’ daily lives (Rubin, 1984). U.S. Internet Users* (%) TV Group (%) OTV Group (%)
Statements reflected sentiments such
Gender
as “If the television wasn’t working, I
would really miss it.” The five items Male 50.0 55.0 55.0
were summed to calculate a mean score Female 50.0 45.0 45.0
for television (α = 0.85, M = 2.64, SD = Age
0.93) and OTV (α = 0.85, M = 2.65, SD
18–24 51.0 49.0
= 0.90).
• Intrusiveness was measured using an 25–34 49.0 51.0
established index that summed a seven- Race/Ethnicity
item, five-point Likert-type scale (1 =
Caucasian 78.1 73.0 67.0
“Strongly disagree” and 5 = “Strongly
African American 10.7 8.0 8.0
agree”) regarding their perception of
advertising intrusiveness (Li et al., 2002). Asian 11.3 6.0 12.0
Scale items included “distracting,” “dis- Hispanic 8.0 9.0
turbing,” “forced,” “interfering,” “intru-
Other 5.0 4.0
sive,” “invasive,” and “obtrusive.” The
Region
seven items were summed to calculate a
mean Intrusiveness Score for television South 36.8 27.0 32.0
(α = 0.89, M = 3.33, SD = 0.76) and OTV Northeast 18.1 26.0 27.0
(α = 0.88, M = 3.45, SD = 0.80).
Midwest 24.9 25.0 22.0
• Advertising Avoidance was measured
using a four-item, five-point Likert-type West 23.3 22.0 20.0
scale (1 = “Never” and 5 = “Always”) Income
to assess the respondent’s likelihood to Less than $35,000 32.9 34.0 34.0
engage in specific advertising avoid-
$35,000–49,999 22.0 24.0 24.0
ance behaviors such as “Leave the room
during television commercials” (Speck $50,000–74,999 23.4 21.0 23.0
and Elliott, 1998). The five items were $75,000+ 21.6 21.0 19.0
summed to calculate a mean Ad Avoid-
Education
ance Score for television (α = 67, M =
High school or less 39.2 16.0 15.0
3.24, SD = 0.65) and OTV (α = 0.68, M =
3.12, SD = 0.77). Some college 23.0 45.0 45.0
College+ 37.7 39.0 40.0
*Pew Internet Project, February, 2009
284 JOURNAL OF ADVERTISING RESEARCH March 2011THE FUTURE: ONLINE STREAMING VIDEO
APPENDIX C
Canonical Correlation Matrix for TV Viewing Motives and Programs (n = 379)
Root 1 (Instrumental) Root 2 (Ritual)
Canonical Correlation 0.63 0.48
Eigenvalue 0.66 0.30
Wilks’ lambda 0.33 0.33
Significance p < 0.001 p < 0.001
Canonical coefficients Structure correlations Canonical coefficients Structure correlations
Viewing Motives
Arousal/excitement –0.41 –0.89 0.08 –0.10
Companionship –0.03 –0.72 0.52 0.06
Entertainment –0.01 –0.50 –0.23 –0.62
Economy/inexpensive –0.05 –0.53 0.45 –0.10
Escape/to forget –0.36 –0.76 –0.14 –0.30
Habit 0.06 –0.44 –0.53 –0.65
Information –0.50 –0.89 0.23 –0.02
Pass time 0.17 –0.31 –0.25 –0.55
Relaxation 0.05 –0.52 –0.35 –0.58
Social interaction 0.00 –0.60 –0.34 –0.48
Convenience 0.04 –0.57 0.06 –0.16
Program Type
Sitcom –0.02 –0.31 –0.37 –0.58
Talk –0.09 –0.53 0.00 –0.15
News –0.06 –0.58 –0.11 –0.08
Magazine/documentary –0.28 –0.75 0.33 0.08
Sports 0.00 –0.26 –0.08 –0.09
Movies –0.28 –0.47 –0.35 –0.56
Drama 0.08 –0.31 –0.52 –0.66
Humor 0.00 –0.50 0.01 –0.26
Variety –0.02 –0.46 0.19 0.00
Action –0.15 –0.41 0.11 –0.25
Game –0.14 –0.58 –0.15 –0.19
Children’s 0.10 –0.41 –0.16 –0.10
Daytime serials –0.07 –0.66 0.02 0.08
Religious –0.49 –0.79 0.42 0.33
Fake news –0.11 –0.46 0.03 –0.06
Reality 0.02 –0.38 –0.18 –0.23
March 2011 JOURNAL OF ADVERTISING RESEARCH 285THE FUTURE: ONLINE STREAMING VIDEO
APPENDIX D
Canonical Correlation Matrix for OTV Viewing Motives and Programs (n = 377)
Root 1 (Instrumental) Root 2 (Ritual)
Canonical Correlation 0.71 0.44
Eigenvalue 1.00 0.24
Wilks’ lambda 0.26 0.52
Significance p < 0.001 p < 0.001
Canonical coefficients Structure correlations Canonical coefficients Structure correlations
Viewing Motives
Arousal/excitement 0.63 0.70 –0.54 –0.46
Companionship –0.53 0.82 –0.50 –0.03
Entertainment –1.53 0.12 0.11 –0.77
Economy/inexpensive –0.04 0.18 0.16 –0.79
Escape/to forget –0.51 0.64 0.56 –0.39
Habit –0.37 0.51 –0.37 –0.51
Information –0.13 0.88 1.16 –0.03
Pass time 1.28 0.24 0.71 –0.56
Relaxation 0.10 0.42 –0.09 –0.74
Social interaction 0.53 0.77 –0.87 –0.31
Convenience 0.27 0.34 –0.15 –0.44
Program Type
Sitcom –0.01 0.56 –0.42 –0.55
Talk 0.23 0.76 0.13 –0.01
News 0.05 0.71 0.16 0.18
Magazine/documentary 0.09 0.77 0.18 0.17
Sports 0.03 0.61 0.26 0.11
Movies 0.17 0.63 –0.52 –0.51
Drama 0.14 0.59 –0.21 –0.32
Humor 0.07 0.61 –0.15 –0.36
Variety 0.03 0.70 0.27 0.09
Action –0.00 0.52 –0.12 –0.30
Game 0.30 0.84 –0.01 0.05
Children’s 0.02 0.61 –0.08 –0.00
Daytime serials 0.05 0.71 0.06 0.25
Religious 0.22 0.75 0.37 0.34
Fake news –0.08 0.55 –0.38 –0.26
Reality 0.03 0.64 0.06 –0.02
286 JOURNAL OF ADVERTISING RESEARCH March 2011THE FUTURE: ONLINE STREAMING VIDEO
REFERENCES GREYSER, S. A. “Irritation in Advertising.” Jour- www.marketingcharts.com/television/online-
nal of Advertising Research 13, 1 (1973): 3–10. video-ads-beat-regular-tv-ads-12655/nielsen-
ABERNATHY, A. M. “Differences between Adver- online-vs-tv-ad-performance-apr-2010jpg/]
tising and Program Exposure for Car Radio KNOWLEDGE NETWORKS. “Use of Internet to
accessed on May 15, 2010.
Listening.” Journal of Advertising Research 31, 2 Watch Full TV Episodes Has Tripled since 2006
(1991): 33–42. among 13–54 Online Audience.” March 18, 2009
PAPACHARISSI, Z., and A. M. RUBIN. “Predictors
[URL: http://www.knowledgenetworks.com/
of Internet Use.” Journal of Broadcasting & Elec-
BOND, P. “FCC Backs Studios’ VOD Plan.”The Hol- news/releases/2010/031810_tv-web.html]
tronic Media 44, 2 (2000): 175.
lywood Reporter, May 7, 2010 [URL: http://www. accessed on May 15, 2010.
hollywoodreporter.com/hr/content_display/
RUBIN, A. M. “The Interactions of Television
news/e3ieedb56d6b7d31495515d322a83bdd347], LI, H., S. M. EDWARDS, and J.-H. LEE. “Measur-
Uses and Gratifications.” Paper presented at the
accessed on May 15, 2010. ing the Intrusiveness of Advertisements: Scale
Development and Validation.” Journal of Adver- Annual Meeting of the Association for Educa-
COM S CORE . “comscore releases March 2010 U.S. tising 31, 2 (2002): 37–47. tion in Journalism, East Lansing, MI, 1981.
Online Video Rankings.” April 29, 2010 [URL:
http://www.comscore.com/Press_Events/ MANDESE, J. “Nielsen Turns the ‘Channel’ RUBIN, A. M. “Ritualized and Instrumental
Press_Releases/2010/4/comScore_Releases_ Off, Permanently.” MediaPost News, April 29, Television Viewing.” Journal of Communication
March_2010_U.S._Online_Video_Rankings] 2010 [URL: http://www.mediapost.com/ 34, 3 (1984): 67.
accessed on May 15, 2010. publications/?fa=Articles.showArticle&art_
aid=127158] accessed on May 5, 2010. SPECK, P. S., and M. T. ELLIOTT. “Predictors of
ELLIOTT, M. T., and P. S. SPECK. “Consumer Per-
Advertising Avoidance in Print and Broadcast
ceptions of Advertising Clutter and Its Impact MINTEL GROUP. Attitudes towards Advertising in
Media.” Journal of Advertising 26, 3 (1997): 61–76.
across Various Media.” Journal of Advertising Digital and Broadcast Media – US. Chicago, IL:
Research 38, 1 (1998): 29–41. Mintel Group, 2005.
U.S. CENSUS BUREAU. “Statistical Abstract of
the United States: Information and Commu-
FRIEDMAN, W. “Net Gains: Nielsen Sizes up MINTEL GROUP. Attitudes towards Media – US.
nications.” 2009 [URL: http://www.census.
TV Hits Online.” Media Daily News, February Chicago, IL: Mintel Group, 2007.
12, 2009 [URL: http://www.mediapost.com/ gov/compendia/statab/cats/information_
publications/?fa=Articles.showArticle&art_ NIELSEN IAG. “Premium Online Video Meas- communications.html] accessed on January 20,
aid=100220] accessed on March 2, 2009. urement 2008–09.” April 21, 2010 [URL: http:// 2009.
March 2011 JOURNAL OF ADVERTISING RESEARCH 287Copyright of Journal of Advertising Research is the property of World Advertising Research Center Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
You can also read
