What Works Best When Combining
Teievision Sets, PCs, Tabiets, or
Mobiie Phones?
How Synergies Across Devices Result From
Cross-Device Effects and Cross-Format Synergies
DUANE VARAN
The Disney Media &
Advertising Lab/
Advertising research often confounds device effects (e.g., television sets, radios, and
personal computers) with communication format effects (e.g., respectively, video,
Audience Labs,
audio, and Web sites). Across four experiments, this study documents empirical
Murdoch University
patterns of cross-device effects among television sets, PCs, iPods, and mobile
varan@audiencel8bs.com
phones. In three experiments, the format was identical across devices, and the device '
JAMIE MURPHY
made no difference to advertising effectiveness. The fourth experiment—with differeni
Australian School of
formats and devices—showed sequential synergy effects. Synergy can strengthen or
Management/ Curtin
Graduate School of
weaken advertising campaigns that combine multiple communication devices. The
Business
combined results of four experiments suggest possible cross-format synergies but not
jamie.perth@gmail.com
cross-device synergies.
CHARLES F. HOFACKER
Florida State University
chofack@cob.fsu.edu
INTRODUCTION
JENNIFER A. ROBINSON
RMIT University
jenny.robinson@
rmit.edu.au
ROBERT F. POTTER
Indiana University
rfpotter@indiana.edu
STEVEN BELLMAN
Audience Labs, Murdoch
University
bellman@
audiencelabs.com
Not long ago, cross-media advertising was relatively easy: there was video on television sets;
sound coming from radios; print on something
extracted from wood or rags. The personal computer—with video, sound, and text, as well as
new platforms offering messaging, hypertext, and
rich interactivity—changed the rules of consumer
engagement. Now computers fit in a pocket and
double as a phone.
In the twenty-first century, devices rather than
media may be more appropriate to marketers. Two
dimensions that differentiated media in the past were
mode and pacing (Dijkstra, Buijtels, and Van Raaij,
2005). But video-mode content with uncontrollable
pacing—once available only on television sets—is
available today on personal computers (PCs), tablet computers (e.g., iPads), portable audio-video
devices (e.g., iPods), and mobile phones. Nielsen, in
fact, now has a panel to measure television ratings
across devices (Nielsen, 2013). Interactivity allows
2 1 2 JOURiL DF HDUERTISli RESEHRCH June 2 0 1 3
self-pacing of video-mode content. And interactivity has become across the full spectrum of devices...
including television sets.
In this context, empirical generalizations about
combining "media" now not only need to define
which devices they apply to, but also what modB
and pacing on each device. In this paper, th3
authors use "format" to describe combinations cf
mode and pacing, such as non-interactive video,
audio, and text.
The current study reports on four experiments
that looked for potential synergy effects across
devices and formats. In three experiments, the
same format—video—is shown on three or more
devices: television sets, PCs, iPods, or mobile
phones. In the fourth experiment, a different format is shown on each device.
SYNERGY
A combination of devices yields synergy when one
enhances or reduces the effectiveness of another
DOI: 10.2501/JAR-53-2-212-220
WHAT WORKS BEST WHEN COMBINING TELEVISION SETS, PCS, TABLETS, OR MOBILE PHONES?
EIVIPIRICAL GENERALIZATION
other things being equal, device makes^no difference to ad effectiveness. But format
differences can generate multiplicative sequential synergy effects.
(Belch and Belch, 2009). Sometimes, synergy is claimed when one device has a
steeper nonlinear response (Havlena,
Cardarelli, and de Montigny, 2007). Others
insist, however, that synergy is a multiplicative effect: a x b, not a + b (Assael, 2011;
Lubinski and Humphreys, 1990). Multiplicative synergy ignores exposure-order;
a x b = b 'X. a. Sequential S)mergy may
occur in one order but not another (Assael,
2011).
Synergy has clear strategic and financial implications for marketers, but it
remains under-researched and inconclusive (Assael, 2011). Lab experiments, for
example, have demonstrated positive
and negative spirals when combining
different devices (Edell and Keller, 1989).
Recent field data has shown how interactive online content—viewed primarily on
PCs—can enhance the efficiency of noninteractive offline content—seen on televisions and other devices—^justifying an
increase in the media budget (Naik and
Peters, 2009).
But these results confound device and
format (e.g., video on televisions vs. Web
sites on PCs). When the advertising on a
PC closely matches the advertising shown
on a television, no synergy occurs (Dijkstra et al., 2005). This result suggests that
synergy may depend more on format than
the device.
For cross-device synergy, the devices
must differ in effectiveness. Studies have
foimd that the bigger the screen (e.g., television vs. mobile phone), the better the
effect (Reeves and Nass, 1996). Objects
seen on larger screens appear more natural (Kock, 2005), and generate greater
emotional response (Reeves, Lang, Kim,
and Tatar, 1999).
This screen-size effect, however, may be
counteracted by viewing intensity, such as
leaning forward to watch a PC (Barwise,
2001) or having a strong personal relationship with a mobile phone (Barwise and
Strong, 2002). Screen size may not matter if
viewers hold smaller screens so close that
they seem about the same size as a television screen (Bellman, Schweda, and Varan,
2009). Finally, viewer interactivity, which
adds self-pacing to the video-mode format, also may counter television's apparent big-screen superiority.
The current paper focuses on advertising effectiveness—awareness, likeability,
and persuasion—across devices when
each uses the same (and different) advertising formats. In doing so, this study augments knowledge on cross-device effects
and cross-device synergies by investigating three questions:
• Are video comniercials more effective
if seen on a television set, as compared
to viewings on PCs, small audio-visual
devices, and mobile phones?
• Are there positive (or negative) synergy
effects for video commercials seen across
combinations of devices, such as a television set, a PC, and a mobile phone?
• What happens if there are differences in
advertising format—i.e., interactive versus non-interactive video commercials?
METHODOLOGY
This article's "Many Sets of Data"
approach analyzed four data sets with different devices, commercials, advertising
formats, and measures (Ehrenberg, 1990;
Hammer, Riebe, and Kennedy, 2009).
Experimental methods controlled for
viewing-envirortment differences, such
as viewing televisions at home, PCs at
work, and mobile phones while commuting. Random assignment to devices
controlled individual differences, such as
age and gender. The data sets, collected in
Australia, were industry-sponsored and
used real brands, advertised in nationally
televised commercials from the United
States (See Table 1). The research team
was able to control brand-familiarity
and product-category effects by averaging across brands and counterbalancing
order-of-exposure.
Four representative measures of advertising effectiveness are:
•
•
•
•
awareness
advertising likeability
brand attitude
purchase intention.
The "awareness" measure, in the current
study, was day-after proven advertising recall (Brown, 1985) in Experiments 1
and 2, and unaided free recall after a
20-minute delay in Experiments 3 and 4.
In Experiments 1 and 2 advertising
"likeability" was the average of four
semantic-differential items (all reversecoded, a > 0.91): agreeable-disagreeable,
clear-imprecise, interesting-boring, and
well structured-badly structured (Perrien,
Dussart, and Paul, 1985). Experiments 3
and 4 used a validated single item measuring advertising-liking (Bergkvist and
Rossiter, 2007).
In Experiments 1 and 2, the authors
used a four-item scale (e.g., bad-good,
a > 0.94) to measure "brand attitude"
(Gardner, 1985). In Experiments 3 and 4,
the authors averaged three items (a = 0.74
in both experiments):
• brand preference (Bergvist and Rossiter,
2008);
• brand feeling (hate it-love it);
• brand fit (no fit-perfect fit).
June 2 0 1 3 JOURnilL DF RDDERTISIRG RESERRCR 2 1 3
WHAT WE KNOW ABOUT ADVERTISING II
TABLE 1
Descriptions of the Four ExperirTients
Experiment N
Design
Devices
Repetition? interactivity? Test Ads Content
1
131
3 groups
Television
PC
iPod
No
258
4 groups
No
Television
PC
i Pod
Mobile phone
336
3x3
Television
Yes
(9 groups) PC
Mobile phone
No
8
^ h o u r video sitcom + 20 video commercials
(4 breaks x 5 commercials/break)
No
video (2 x 15-minute edited sitcoms)
+ 6 video commercials
{2 breaks, 1 per sitcom: 1 x 5 commercials,
1 x 1 pre-roll or mid-roll [counterbalanced])
No
40-minute video (2 x 20-minute edited
programs) + 20 video commercials
(4 breaks [2 per program] x 5 commercials)
Participants saw each program in a different
room, on the same or a different device
274
3x3
Television
Yes
(9 groups) PC
Mobile phone
Yes:
PC
(Web sites
replace
programs and
commercials)
Mobile phone
(clickable
banners
superimposed
on video
commercials)
Finally, "purchase intention" was a subjective probability scale (Juster, 1966).
Checks using measures of brand familiarity (Machleit, Allen, and Madden, 1993,
a > 0.92) and product-category involvement (Mittal, 1995, a = 0.96) cor\firmed
that these are not alternative explanations
for the results of the current study.
Television & Mobile phone:
Same as Experiment 3, but the video commercials
were interactive on the mobile phone
PC:
Self-paced television program Web site
8 banner ads (4 pages x 2 ads per page)
One of the 2 on each page was a test
advertisement that linked to the test brand's
Web site. Exposure to brand Web sites was
forced but duration was not
Participants saw each program in a different
room, on the same or a different device
{p = 0.014). In Experiments 1-3, with the
same advertising format on each device,
there were no significant differences. A
single null result could have several explanations, such as low sample size or poor
methodology. Consistent non-significant
differences across the first three data sets
support the following empirical generalization (See Tables 2-6).
EiVIPIRICAL GENERALIZATIONS
In the current study of devices—as
opposed to advertising media—the only
difference was a marginally significant
effect on recall {p = 0.055), due entirely
to Experiment 4, which used a different advertising format on each device
2 1 4 JOUROIIL OF
BESEIIÍICH
June 2 0 1 3
EGl:
Other things (e;g., viewing environment) being equal, there are
no differences in advertising
effectiveness for non-interactive
video commercials seen across
television sets, PCs, portable
audio-video devices, and mobiie
phones.
The results of the first three experiments (See Table 2) showed that, under
laboratory-controiled viewing conditions
with each device showing the same noninteractive format (video commercials),
advertising awareness—brand-associated
advertising recall—was the same across
four devices that vary widely in screen
size (effect size [partial rj^] = 0.010, i.e.,
small [Cohen, 19881).
Given advertising recall was abnormally distributed, using non-parametric
Kruskal-Wallis tests showed the same
WHAT WORKS BEST WHEN COMBINING TELEVISION SETS, PCS, TABLETS, OR MOBILE PHONES?
TABLE 2
If the format is the same, then device
Unaided Recall for Television Commercials across Devices
""^^^^ ''° difference to advertising
(Percent of Ads Recalled)
^ ^''^
'-
. .
A • •
Experiment 1
Television
42
PC
42
iPod
36
JÜ
23
26
23
1
i^
?i
^
Experiment 2
39
46
33
39
gQ
4^
jg
25
40
involvement viewing on PCs or mobile
n
50
57
39
44
phones also would reduce the importance
.
,
, .
of peripheral influences such as advertis-
.!!'.P.^.'!i.T.?.".l.?
.??
SD
^
•
Phone
, •
The most important advertismgeffectiveness measure is persuasion.
which links directly to sales (Gibson,
1983). Advertising on television sets can
Average
40
have powerful persuasive effects without
recall (Heath, 2009), and also without lik40
ing (Bergkvist and Rossiter, 2008). High-
.S.
35
27
29
23
^c
^2
45
Experiment4
38-^
61''
olí-
^P,
20
31
29
enees on two persuasion measures (Tables
n
22
23
37
4 and 5). Brand attitude was the same (par-
Average
40
46
35
38
ing likeability (Petty, Cacioppo, and Schumann, 1983).
But in the first three experiments, when
all four devices showed the same adver^Í
u
j • J«
. tismg format, there were no device differ-
50
~41
41
"^^ "^^ = °°°^^' ' ' "^^^ P"'"''^'^ ^'^"*^°"
(partial Ti2 = 0.004).
¡f j^e format is the Same, then device
Note means with the same superscript letter are significantly different at p < 0.05.
makes no difference to persuasion,
non-significant results in the first three
studies (all p > 0.473).
TABLE 3
If the advertising format is the same,
then device makes no difference to adver- Ad Liking for Television Commercials across Devices
tisingawareness.
(1 = "Unfavorable" to 7 = "Favorable")
Advertising-liking has a gatekeeper
function, opening or closing access to fur,,
,
^ .
•
/TT ,
.
Television
PC
iPod
Phone
Experiment 1
3.9
3.9
3.7
ther adverhsmg processing (Haley and
Baldinger, 1991). Television sets might
^,P,
0-6
0.5
0.8
he better for advertising-liking because
n
44
43
44
of their association w i t h f i m a n d enter-
r - , . , - ,
Expenment 2
„ , ,
4.8
'
4.7
4.8
4.8
.'.
:.
t:^.
...:....
^]
Experiment 3
64
4.9
67
4.8
49
54
48
'
tainment; PCs are associated with work,
and advertisements might seem especially intrusive on a personal device like a
mobile phone (Barwise and Strong, 2002).
But, similar to advertising awareness,
3.9
the results for the first three experiments
showed no differences in advertising-
oU
.1.3
0.9
1.1
1
ÛË.
í£
f^
liking across televisions, PCs, portable
Experiment 4
5.0
5.3
4.9
audio-video devices, and mobile phones
showing the same advertising format
QQ
J^ Q
Qg
Qg
22
2"^
9^
.,..l^
.l^
(See Table 3). Advertising-likeability was
equally favorable (partial T|2 = 0.001).
n
^y®.'?.?®
•
.l^
Average
.I?
4.8
^ ^
4.8
5.0
4-6
June 2 0 1 3 JOURDRL OF HDUERTISIDG RESERRCH 2 1 5
WHAT WE KNOW ABOUT ADVERTISING II
TABLE 4
Attitude toward the Brand for Television Commercials across
Devices (1 = "Unfavorable" to 7 = "Favorable")
Experiment 1
Television
PC
¡Pod
Phone
5.2
5.1
5.3
•
Average
0.9
0.8
effectiveness
5.2
;:
SD
The most important
, ,
advertising-
is persuasion, which
0.8
"^
'
^
if
^3
^^
Experiment 2
4.9
4.9
4.9
4.9
iinks directiy to saies.
SD
1.0
1.0
1.1
1.1
[!.
^
^
ÍL
—
Experiments
3.9
3.9
en
Qg
n
45
42
Experiment 4
3.9
4.4
SD
1.1
1.1
1-0
EGl suggested that the device makes
n
oo
22
no
23
QÄ
JO
no difference to the effectiveness of same-
Average
.^
4.6
4.6
4.1
-iQ
4.9
EG2: Other things being equal, the
4.0
same advertising format makes
09
" ^ difference across combir\a.tions of television sets, PCs^
45
-
3.9
5.0
4.3
iPods, and mobile phones.
4.0
format ads. The current study's EG2
^ u £: ^
.
u J
extends that finding to combmed exposure
4.6
situations, where viewers see two devices,
rather than one.
Since
T«ni r ^
explanations
of
combined-
exposure effects (e.g., Edell and Keller,
TABLE 5
.
.
.
1989) rely on the superiority of one device.
Purchase Intention for Television Commercials across Devices
^^ cross-device synergy effects are likeiy
(0% t o 99%)
when none of the four devices is superior
' ° ^"°*^'-- ^"'^^'
'^^"^^^ ^'""^ "^"perLment 3 support EG2. Besides the data for
.
. .u
^ • ^c
repeat-exposure to the same device (bee
Tables 2-4), the third experiment meas-
•
Te,evj3,o„
^¡
^ ¿
Experiment 1
32
29
31
SD
19
16
14
f^
44
43
44
^
.
^
Expenment2
^^
32
._
27
^28
__
28
ar)
._T..
n
Experiment 3
OQ
t°.
67
40
25
^.
67
37
26
21
57^
SD
19
20
56
41
;""
23
2
_£
Experiment 4
29
34
23
2¿
^g
21
15
n
22
23
36
Average
34
31
2 1 6 JDUHnHL OF RDÜERTISIOG
HESEHHCH
Phone
Average
31
ured
advertising effectiveness
for aD
-29
possible two-device combinations of tel^
evision, PC, and mobile phone. There was
40
no significant synergy effect on any of the
four advertising effectiveness measures
(device 1 x device 2 interaction: partial
ri2< 0.009; Table 6).
'
'
// the format is the same, then devicecombination makes no difference.
June 2 0 1 3
30
31
28
DIFFERENT ADVERTISING FORMATS
•
32
These two empirical eeneraUzations may
, when
,
, devices
^ • show
..
jdînèrent
. « '.
not apply
the
advertising formats.
WHAT WORKS BEST WHEN COMBINING TELEVISION SETS, PCS, TABLETS, OR MOBILE PHONES?
TABLE 6
the shallow interactivity on the mobile
Results for Various Combinations of Devices (Experiments 3
P ^ ° " ' ^ ' " " " advertisements superim-
dllU ^ j
^
posed over video commercials) and the
non-interactive video commercials on the
Second Device
television.
Experiment
iVIeasure
First Device
Teievision
PC
Phone "
^ ' ''^'^^*' °^ Experiment 4 show a sig-
nificant synergy effect on recall (p = 0.004),
3
Recall (%)
. . , . , . ^ ,. ^,
Ad Liking (1-7)
Television
39
35
34
u- c
• c
.
i • i- •
resultmg from a sigmficant multiplicative
PC
Phone
34
41
35
PC X mobile phone effect (p = 0.026). There
39
46
35
^^^° ^^^ ^ main effect of format: recall
-r , • •
Television
. ^
4.9
^^
5.0
48
was significantly higher for both the PC
J a
:
."Ü?.
Brand Attitude (1-7)
Purchase Intention (%)
(p = 0.005) and mobile phone {p = 0.043)
.1.?
.1.?.
.1-.?
compared to the television (Table 2).
4.7
3.9
4.7
4.0
4.8
4.0
PC
3.8
3.9
3.8
.^.*^.°!?.^.
.?;.?
.?;.?
.1.^
The difference in recall between the two
interactive formats, PC and mobile phone,
w^as not significant. There were no sienifi^
cant mam or mteractive (synergy) effects
on any of the other three ad-effectiveness
Television
40
40
42
measures (Tables 2-6).
PC
36
37
36
P*^""?
^8
40
41
ADVERTISING SYNERGIES
.1'!.'.^!)?.'.°';'.
PC
??!^^1
50"
.?.^.'.
61"
5^'*
SI"«"*'
Experiment 4 showed that different advertising formats can generate multiplica-
Phone
52i
55='>
5P
"^^ synergy. Retrieval Practice Theory
(RPT) provides one explanation for how
Television
5.0
5.0
5.0
5.1
4.9
.„..„
5.3
49
..:^.
5.4
49
sequential exposures to different formats
interact to improve or impede advertis^ 8 effectiveness. Difficulty remember-
3.9
4.2
3.8
irig a previous exposure during a current
°
..?.
Phone
.^;.?
3.6
I'.l
3.6
.I'.I
3.9
exposure increases processing activity,
which enables or strengthens a pathway
for later recall, unless retrieval of the prior
Television
29
25
23
Phone
' Television
THEORETICAL EXPLANATIONS OF
4
Recall (%)
Ad Liking (1-7)
"
PC
Phone
r,
J «....Lx - , , . . - , >
Brand Attitude (1-7)
Purchase Intention (%)
-••...
Television
PC
•
37
34
39
.„!^.?.".?.
??.
Note: means with the same superscript letter are significantli/ different atp< 0.05.
.?.?
^.^.
In Experiment 4, the advertising formats on the PC, mobile phone, and television differed in the presence and depth of
interacdvity. Interactivity can have negative or positive effects. Its effects generally
are positive when consumers personalize their information flow (Ariely, 2000),
which increases information processing
^. ,
,
,.„
<•
exposure is so difficult it fails (Appleton-
and favorable evaluations of the advertised product (Sicilia, Ruiz, and Munuera,
2005).
The interactive content on PCs in Experiment 4 allowed highly personalized information flow, as it was the actual Web sites
for the advertised brands. These interactive PC advertisements contrasted with
Knapp, Bjork, and Wickens, 2005).
rr 1
RPT contrasts with another popular
explanation for repeat-exposure effects.
Encoding Variability Theory (EVT; Yaveroglu and Donthu, 2008). According to EVT,
exposure to different content formats,
such as visual versus verbal, yields two
independent retrieval routes rather than
amplifying one memory by another (Costley. Das, and Brucks, 1997; Paivio, 1971).
EVT effects occur regardless of which format was seen first. In contrast, order-ofexposure matters for RPT effects.
June 2 0 1 3 JOÖflOflL OFflOOERTISIIlGRESEflflCR 2 1 7
WHAT WE KNOW ABOUT ADVERTISING II
Interactivity is more than a cosmetic
difference in exposure variability (Schumann, Petty, and demons, 1990), and
so its effects more likely are explained
by RPT than EVT. But the two interactive devices also differed in their input
capability for interaction: the push-button
mobile phone was less ergonomie than
the PC. Other potential explanations for
synergy effects include exposure duration, forward encoding, and multiple
source perceptions {van Reijmersdal,
2011). Unlike RPT, however, these alternative explanations struggle to explain
the sequential synergy effects in the fourth
experiment.
The significant interaction effect on
recall was due to an asymmetric deviceorder effect (See Table 6). Exposure to
interactive content on the PC, first, and
the mobile phone, second, yielded significantly superior recall compared to the
same content in the reverse order (81 percent vs. 55 percent, p = 0.002). The RFT
explanation for this effect is that recalling
a previous PC exposure during a mobile
phone exposure was so difficult that their
combined effect was enhanced. In contrast, exposures to interactive content on
the mobile phone, first, and the PC, second, acted independently, because their
combined effect was not significantly different from two repeat exposures on either
device (PC-PC 61 percent, mobile phonemobile phone 51 percent).
CONCLUSION
Across four data sets, the results were
consistent.
As the start of a generalization on crossdevice effects, this paper documents that
when the format is the same (video commercials) and all else is equal:
• device makes no difference to advertising effectiveness, measured by
awareness, advertising likeability, or
persuasion (brand attitude and purchase intention)...
• ... and so, under those conditions,
any combination of devices is equally
effective.
• But, if the format is not the same on
each device (e.g., interactive vs. noninteractive), there can be sequential synergy effects.
In short, these findings suggest possible
cross-format synergies, but not crossdevice synergies. In many instances,
advertisers have little control over which
device consumers will use to view their
content.. But if devices show the same
advertising format (e.g., video), under the
same viewing conditions, all exposures are
equally effective.
Alternatively, advertisers can use different devices to reach certain demographics,
without sacrificing advertising effectiveness. For example, video viewing on
mobile phones skews younger, male, and
non-white (Nielsen, 2012). Outside the lab,
however, viewing conditions can vary, so
this default recommendation to use the
same ads across devices may not apply to
every campaign.
When devices show different advertising formats (e.g., interactivity), sequential
synergy effects can result. Retrieval difficulty can enhance memory for certain
orders of exposure, as retrieval practice
theory explains (Appleton-Knapp et al.,
2005). The pattern of results in the current study suggests that managers should
focus on message format and sequencing
rather than the devices consumers use. For
example, where interaction differs across
devices (e.g., push-button vs. mouse vs.
touch-screen), format will differ as well.
If order of exposure matters, ads could be
run at different times on different devices,
or linked in the most effective order (e.g.,
in the results of this study, PC -> mobile
phone rather than mobile phone —> PC).
2 1 8 JDUROIIL or HDUERTISinS RESORCH June 2 0 1 3
There is a clear need
for more research into
what causes synergy,
beyond differences
in interactivity.
There is a clear need for more research
into what causes synergy, beyond differences in interactivity (Assael, 2011; Naik
and Peters, 2009). Since synergistic interactions between exposures occur inside consumers, rather than between expenditures,
laboratory research is essential for increasing understanding of these processes.
The limitations of these results suggest other avenues for future research.
First, these findings may apply only to
Australia. Replication could extend these
empirical laws on cross-device effects to
different countries, different formats (e.g.,
small-text) and devices (e.g., radio), and
additional measures such as sales.
Future research also should focus en
conditions that introduce cross-device
differences, such as differences between
viewers or viewing environments, or create cross-format differences, such as visual
versus verbal content.
DuANE VARAN is the director of the Audience Labs
and holds the inaugural chair in new media at
Murdoch University. He also oversees Beyond :30, a
collaborative industry project expioring the changing
media landscape, and is the executive director
and chief research officer for The Disney Media &
Advertising Lab in Austin, Texas. He has a Ph.D. from
the University of Texas at Austin, and has published in
the Journal of Communication, Journal of Advertising
Research, and the Journal of Business Research.
JAMIE MURPHY is Professor at the Austraiian School of
Management and Adjunct Professor with the Curtin
WHAT WORKS BEST WHEN COMBINING TELEVISION SETS, PCS, TABLETS, OR MOBILE PHONES?
Graduate School of Business. His background includes
Measurement & Meaning: Cognitive and Emotional
BELCH, G . E., and M. A. BELCH. Advertising and
European marketing manager for PowerBar and Greg
Processing of Media (Routledge).
Promotion: An Integrated Marketing Communica-
Lemond Bicycles, and a Ph.D. from Florida State
University. Professor Murphy's industry and academic
experience spans continents and inciudes hundreds of
academic publications and presentations, as well as
New York Times and Wall Street Journal stories. His
research focus is on the effective use of the Internet
for citizens, businesses, and governments. His passion
is motivating and mentoring great students.
tions Perspective, 8th ed. New York, NY: Irwin/
McGraw-Hül, 2009.
STEVEN BEOMAN is Associate Professor and deputy
director of the Audience Labs at Murdoch University.
BELLMAN, S., A. SCHWEDA, and D. VARAN "View-
His research focuses on viewer responses to media
content and advertising. Much of this work is funded
ing Angle Matters—Screen Type Does Not."
by the sponsors of the Beyond :30 project, who
Journal of Communication 59, 3 (2009): 609-634.
include many of the world's leading TV networks
and advertisers. He has a Ph.D. from the University
BERGKVIST, L., and J. R. ROSSITER. "The Pre-
of New South Waies, and has pubiished in Journal
dictive Validity of Multiple-Item Versus Single-
CHARLES F. HOFACKER has a Ph.D. in Mathematical
of Marketing, Journal of the Academy of Marketing
Item Measures of the Same Constructs." Journal
Psychology from UCLA. He is Carl DeSantis Professor
Science, and Management Science. He is on the
of Marketing Research 44, 2 (2007): 175-184.
of Business Administration and Professor of Marketing
editoriai boards of Journal of Advertising, Journal of
at Florida State University. He was Visiting Professor
Interactive Marketing, and Communication Methods
at Université Bocconi in Milan, Italy, in 2001 and
and Measures. He is the co-author, with John R.
2007. His research is at the intersection of marketing
Rossiter, of the book Marketing Communications
and information technology. His work in that and
(Pearson Prentice Hall).
BERGKVIST, L., and J. R. ROSSITHR. "The Role of
Ad Likabüity in Predicting an Ad's Campaign
Performance." Journal of Advertising 37,2 (2008):
85-97.
other areas has appeared in the Journal of Marketing
Research, Journal of the Academy of Marketing
Science, Psychometrika, Management Science, and
BROWN, G . "Tracking Studies and Sales Effects:
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2 2 0 JDURnHL or HDÜEñTISIOG RESEHfiCH June 2 0 1 3
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