The Short-and Long-Term Impact of Brand Placement in an Advertiser Funded TV Program on Viewers' Attitudes towards the Sponsor Brand and Its Main Competitor

Article (PDF Available)inInternational Journal of Advertising 35(6) · October 2015with 1,081 Reads
DOI: 10.1080/02650487.2015.1087089
Cite this publication
Abstract
The present research investigates how viewers' liking of an advertiser-funded television program (AFP) influences viewers' attitude toward the brand that sponsors the program and its main competitor through a field study at two points in time (Nwave1 = 529 and Nwave2 = 256). An AFP is a television program which is fully sponsored by and built around a sponsoring brand. We test how the perceived program-sponsor brand fit moderates the effect of program liking one week and one month after the program finale. Program liking positively impacts brand attitude for the sponsor, and this effect becomes weaker over time. Program-sponsor brand fit reinforces the positive effect of program liking on brand attitude, especially in the longer term. In the longer term, program liking of an AFP also positively impacts viewers' attitude toward the main competitor of the sponsor.
The Short- and Long-Term Impact of Brand Placement in an Advertiser Funded TV
Program on Viewers’ Attitudes towards the Sponsor Brand and Its Main Competitor
Authors:
Yann Verhellen,
University of Antwerp,
Faculty of Applied Economics, Marketing Department.
Prinsstraat 13, 2000 Antwerp, Belgium
Email: yann.verhellen@antenno.be
Jiska Eelen,
Vrije Universiteit Amsterdam,
Faculty of Economics and Business Administration, Department of Marketing.
De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands
Email: j.eelen@vu.nl
Nathalie Dens (corresponding author),
University of Antwerp,
Faculty of Applied Economics, Marketing Department.
Prinsstraat 13, 2000 Antwerp, Belgium
Email: nathalie.dens@uantwerpen.be
Patrick De Pelsmacker,
University of Antwerp,
Faculty of Applied Economics, Marketing Department.
Prinsstraat 13, 2000 Antwerp, Belgium
Email: patrick.depelsmacker@uantwerpen.be
Acknowledgement
The authors gratefully acknowledge financial support from the agency for Innovation by
Science and Technology (IWT Vlaanderen).
Please cite this article as:
Verhellen, Y., Eelen, J., Dens, N., De Pelsmacker, P. (2015). The short- and long-term impact
of brand placement in an advertiser-funded TV program on viewers' attitudes toward the
sponsor brand and its main competitor. International Journal of Advertising. Advance online
publication. doi: 10.1080/02650487.2015.1087089
1
The Short and Long Term Impact of Brand Placement in an Advertiser Funded TV
Program on Viewers’ Attitudes towards the Sponsor Brand and Its Main Competitor
Abstract
The present research investigates how viewers’ liking of an advertiser funded television
program (AFP) influences viewers’ attitude toward the brand that sponsors the program and
its main competitor through a field study at two points in time (Nwave1 = 529 and Nwave2 =
256). An AFP is a television program which is fully sponsored by and built around a
sponsoring brand. We test how the perceived program-sponsor brand fit moderates the effect
of program liking one week and one month after the program finale. Program liking positively
impacts brand attitude for the sponsor, and this effect becomes weaker over time. Program-
sponsor brand fit reinforces the positive effect of program liking on brand attitude, especially
in the longer term. In the longer term, program liking of an AFP also positively impacts
viewers’ attitude toward the main competitor of the sponsor.
1. Introduction
Digital Video Recording (DVR) systems (TiVo) are challenging the traditional
commercial television business model, as they allow viewers to fast-forward commercials. In
addition, online content providers of pay-per-view streaming services such as iTunes and
Netflix now allow viewers to watch their favorite content wherever and whenever they want,
completely ad-free. As ad breaks are under pressure of becoming ineffective (Bellman,
Schweda and Varan 2010), advertising formats that merge commercial content with media
content become increasingly popular (PQMedia 2012; Verhellen, Dens and De Pelsmacker
2013). One of the formats that have emerged is that of advertiser funded programming (AFP),
a (television) program that is completely funded by a specific brand. The program is usually
built around the brand so that the brand becomes the “star” of the show (Sheehan and Guo
2
2005). For example, Philips joined forces with Eurosport to launch a pan-European program
to leverage their Williams F1 sponsorship. “The Factory” is a 'docu-soap' on the AT&T
Williams F1 team, which brings motorsport enthusiasts a glimpse into the personalities and
lives of the people 'behind the scenes' at the Williams factory in their quest to put the best car
on the track and their driver on the podium. Other examples of AFPs include Channel 5’s
“Extraordinary dogs”, developed by Eukanuba, “Vodafone TBA” on Channel 4, in which
music artists are enlisted to play a one-off gig at a mystery location, and BBC’s “The
Restaurant” that had couples compete for the chance to set up a restaurant, sponsored by
American Express. AFPs will normally contain prominent and highly plot connected brand
placements of the sponsor brand.
AFPs and all forms of brand placement are a booming business. The total spending on
brand placement surpassed $10 billion for the first time in 2014, and forecasts predict a
continued double-digit growth up until at least 2019 (PQMedia 2015). Academic research on
brand placement has surged accordingly (e.g., Charry 2014; Dens et al. 2012; Kamleitner and
Jyote 2013; Lin 2014). To our knowledge, only one study has focused on brand placement in
an AFP. Sheehan and Guo (2005) found that viewing a fictional show, “Airline”, centering
around Southwest Airlines, improved consumers’ attitude toward the airline, both
immediately after the show, as well as several weeks after. The present study contributes to
their research (and, by extension, to the brand placement literature in general) in a number
ways.
First, we try to explain the positive effects of viewing an AFP by program liking, and
study the moderating role of viewers’ perceived fit between the program and the brand as a
boundary condition for that effect. Program liking (Cowley and Barron 2008; Redker, Gibson
and Zimmerman 2013) and perceived program-sponsor brand fit (Balasubramanian, Karrh
and Patwardhan 2006; Balasubramanian et al. 2014) are two important factors identified in
3
current brand placement research. To our knowledge, however, there is no research that
studies how these two factors interact. Second, we investigate the impact of brand placement
in an AFP on viewers’ brand attitude not only towards the sponsor brand, but also towards its
main competitor. Traditional advertising research shows that the advertising efforts of one
brand may also benefit competing brands with a similar brand positioning (e.g., Kent and
Allen 1994; Pieters and Bijmolt 1997), but this has not yet been investigated for brand
placements.
Finally, this article makes a contribution by reporting on a field study, which measures
responses of actual viewers of an entire season of an actual AFP both one week and one
month after the season finale. Many brand placement studies report on experiments based
forced exposure to short program excerpts in laboratory settings, measuring only immediate
responses (e.g., Kamleitner and Jyote 2013; Russell and Stern 2006; Van Reijmersdal 2009;
Wilson and Till 2011). The present study in that way addresses the call for increasing the
ecological validity in studying brand placement effects (Dens et al. 2012; Wilson and Till
2011).
2. Affect transfer: The effect of program liking of an AFP on viewers’ attitude toward
the sponsor brand
As proposed by Russell (1998), integrating brands in TV media content induces a
transformational process in which content-related feelings and thoughts spill over to the
placed brands. This spillover or affect transfer is also a well-established principle in
advertising literature (Cauberghe, De Pelsmacker and Geuens 2011; Moorman, Neijens and
Smit 2006; Pham, Geuens and De Pelsmacker 2013). Ultimately, the mechanism of affect
transfer is nested in the workings of the human associative memory (Bower 1981). According
to Associative Network Theory (Anderson and Bower 1973; van Osselaer and Janiszewski
4
2001) human memory is a network of interconnected nodes that activate each other in
relevant contexts.
A brand’s associative network can be conceptualized as a series of nodes in memory, to
which various associations are linked (Dens and De Pelsmacker 2010). The context
(television program) in which a brand is encountered makes up part of that brand’s associative
network (Gawronski and Bodenhausen 2006). Therefore, a brand’s associative network
should contain more positive associations by being placed in a program which induces
positive affect. The more viewers like the program, the more they should like the brand.
Indeed, a number of studies on brand placement show that viewers’ attitude toward the
program positively impacts their attitude toward placed brands (e.g., Balasubramanian et al.
2014; Van Reijmersdal, Smit and Neijens 2010).
The more prominently and plot connectedly a brand appears in a program, the greater the
number of shared associations between the program and the brand, and thus the greater the
affect transfer should be (Dens et al. 2012; Russell 2002). Therefore, the spillover of program
liking to viewers’ attitudes toward the placed brand should a fortiori hold for an AFP, because
the brand placements in this type of program are almost per definition highly prominent and
highly plot connected.
H1: Program liking of an AFP has a positive effect on viewers’ attitude toward the sponsor
brand.
3. The moderating influence of program-sponsor brand fit on affect transfer
Program-sponsor brand fit refers to the degree of congruence between the program and
the sponsor brand (Balasubramanian et al. 2014). In turn, fit positively influences brand
attitudes: In general, placements that are (perceived as) more congruous or fitting with the
program generate more positive brand attitudes (Myers and Royne 2014; Verhellen, Dens and
5
De Pelsmacker 2015), because they are less likely to interrupt the viewing experience and
evoke resistance to persuasion (Balasubramanian, Karrh and Patwardhan 2006). The positive
effects of context-brand fit is also well documented in other marketing communication
formats, such as sponsorship (Han et al. 2013), online advertising (Janssens, De Pelsmacker
and Geuens 2012), banner ads in blogs (Segev, Wang and Fernandes 2014) and in-game
advertising (Chang et al. 2010).
In the present study, we do not focus on the main effect of the perceived fit between the
AFP and the brand, but consider it as a moderator which facilitates the affect transfer of
program liking to the attitude toward the sponsor brand. Attitude objects that fit well are
strongly connected through shared associations in their respective associative networks
(Gawronski and Bodenhausen 2006). Associative Network Theory prescribes that the more
associative links exist between two attitude objects, the easier it becomes to transfer affect
from one attitude object to another (Bower 1981). Therefore, we expect that the spillover of
program liking to the sponsor brand attitude will be greater with higher levels of perceived
program-sponsor brand fit. This proposition is also in line with the misattribution account of
evaluative conditioning, which suggests that affect transfer is the misattribution of positive
affect to the brand instead of to the editorial content, the original source of affect (Jones,
Fazio and Olson 2009). The chance that the audience misattributes positive program-related
affect to the brand increases as the brand and program are perceived as more congruous. We
expect:
H2: The positive effect of program liking on viewers’ attitude towards the sponsor brand is
moderated by program-sponsor brand fit, so that the effect is more positive with higher
levels of perceived fit.
6
4. Effects of program liking and program-sponsor brand fit on the attitude toward the
sponsor brand over time
Time should impact the extent to which program-induced affect for an AFP transfers to
the attitude toward the sponsor brand. Academic research on the role of associative networks
in the formation of attitudes has emphasized the volatile nature of human memory, and the
tendency to forget learned associations when these are no longer activated (for further
discussion, see Anderson and Bower 1973). Sujan and Bettman (1989) indeed show that
specific brand associations that exist in consumers’ mind fade over time. In computer games,
Nelson (2002) asserted that, while players identified several brands directly after game-play,
the numbers were severely reduced after a five-month time delay. These studies indicate that
the associations between a program and a brand will indeed fade over time, reducing the
potential for affect transfer.
Based on a literature review, Van Reijmersdal, Neijens and Smit (2009) suggest that affect
transfer for brand placements relies on activating the link between the program and the brand.
Sweldens, Van Osselaer and Janiszewski (2010) have demonstrated that when a brand gains
its positive affect from the repeated connection with one stimulus (in this case, the AFP),
instead of with many different stimuli, affect transfer is likely to rely on the reactivation of the
connection with that stimulus and decreases over time when no reactivation occurs. As such,
the positive effect of program-induced liking on viewers’ attitudes toward the sponsor brand
should be smaller as some time has passed.
H3: The positive effect of program liking on viewers’ attitude towards the sponsor brand
weakens over time.
Further, we posit that program-sponsor brand fit will moderate the weakening of affect
transfer over time. We have argued that affect transfer relies on the association between the
7
AFP and the brand. A high degree of perceived fit benefits both the number and strength of
associations between the brand and the program. As the AFP and the brand are more directly
related, it is more likely that affect transfer will still occur as time goes by. Sheehan and Guo
(2005), for example, even found that participants had a more positive brand attitude toward
the brand in an AFP-like setting one month after viewing the show than immediately after
viewing it, and before viewing it. In contrast, under conditions of low perceived program-
sponsor brand fit, the brand is only weakly associated with the program to begin with. These
weak associations are much more likely to erode over time (Finn and Roediger 2013). In line
with this logic, we posit that:
H4: There is a three-way-interaction between program liking, program-sponsor brand fit
and time on the sponsor brand attitude: The positive effect of program liking on viewers’
attitude towards the sponsor brand weakens over time, but slower with increasing program-
sponsor brand fit.
5. The impact of an AFP on viewers’ attitude toward a competing brand
Finally, marketers should consider the impact of brand placement in an AFP on
competing brands. The sponsor brand not only shares associations with the AFP, but also
shares certain associations with its competitors. At the very least, brands in the same product
category share associations that are related to that product category (e.g., all cigarette brands
will share the association of being unhealthy). Brands with a similar positioning within that
product category, will share even more associations (e.g., both can be “high-end”).
In advertising, it is well established that consumers have difficulties recalling advertised
information that is idiosyncratic to each brand (competitive interference) and are likely to
wrongly attribute claims to a competitor when two brands use a similar positioning or make
similar claims (Keller 1987; Kent and Kellaris 2001; Loken, Ross and Hinkle 1986). While
8
competitive interference literature has mainly looked at cognitive outcomes, focusing on
recall, brand attitude is also part of consumers’ associative network in memory (Keller 1993).
Competitive interference has been shown to affect brand attitude and sales as well (Dahlén
and Rosengren 2005; Danaher, Bonfrer and Dhar 2008).
Based on the idea of competitive interference, brand misattribution with an AFP should
also lead to changes in brand attitude for a competing brand. Program liking would also spill
over to viewers’ attitudes toward competing brands, especially when this brand has a similar
positioning to that of the sponsor. This expectation is also in line with Associative Network
Theory (Gawronski and Bodenhausen 2007). The more associations a brand and its
competitor share through positioning, the more likely it is that adding new associations
(program liking) to one brand would also affect the other.
While the AFP is running (the time of encoding), or immediately after, the chance of
brand misattribution is relatively small, as the brand is the central focus of the program.
However, as time goes by, brand misattribution becomes more likely. As we have argued with
H3, associative networks are affected by temporal deterioration and learned links in a brand’s
associative network may be forgotten. Consumers have greater knowledge of common rather
than distinct properties of brands in a category, which facilitates stronger category-program
links than brand-program links (Kent and Kellaris 2001). This means that the spreading
activation of an AFP may result in the retrieval of a number of brands within the product
category (Dahlén and Rosengren 2005). Thus, while it is mainly the sponsor brand that
benefits from affect transfer at encoding (i.e., during or immediately after the program), the
program may be linked to another brand at a later stage (Dahlén and Rosengren 2005). As the
strength of the associative network between the program and the sponsor brand diminishes
over time, the chance for brand misattribution increases. As a result, so does the chance for an
affect transfer of program liking to a competing brand.
9
H5: The positive effect of program liking on viewers’ attitude toward a competing brand
increases over time.
Building on the reasoning for H3 and H5, we also expect that the temporal effect of time
on the relationship between program liking and attitude toward a competing brand is
moderated by the perceived fit between the program and the original sponsor. As theorized
above, program-sponsor brand fit will strengthen program-related links in the brand’s
associative network, making them more resistant to the influence of time and decreasing the
likelihood of brand interference (Keller 1987). In contrast, under conditions of low program-
sponsor brand fit, the course of time may weaken or erase idiosyncratic associations between
the program and the sponsor brand. The weaker the links between the brand and the
associations that were added by the program, the more likely it becomes that these
associations are misattributed to a similar competing brand. As such, the positive longer-term
effect of program liking on viewers’ attitudes toward the sponsor’s main competitor is
expected to be stronger when the perceived fit between the program and the sponsor brand is
low.
H6: There is a three-way-interaction between program liking, program-sponsor fit and time
on viewers’ attitude toward a competing brand: A higher perceived fit between the program
and the sponsor brand weakens the positive long term effect of program liking on viewers’
attitude toward a competing brand.
.
6. Method
6.1. Research setting
The study was conducted in Belgium, a small open economy, centrally located within
Western Europe, whose viewer market in many ways represents an average European Union
10
profile (De Pelsmacker and Janssens 2007; Verhellen, Dens and de Pelsmacker 2014).
Popular television (sitcoms, reality shows, game show formulas, etc.), movies (all major
blockbusters) and music (charts and video clips) are dominated by American productions
(e.g., De Bens and de Smaele 2001). On average, Belgian television viewers are exposed to a
brand placement every 12 minutes (Wouters and De Pelsmacker 2011). The average amount
of placements in domestic television programs does not differ significantly from that in U.S.
programs (Wouters and De Pelsmacker 2011).
The program under study is ‘De Designers’, the local version of ‘Project Runway’. De
Designers’ is a 10-episode advertiser funded fashion designer competition, sponsored by a
well-known Belgian fashion retailer, and broadcast on the largest Belgian commercial
television station. Each episode lasted 50 minutes. The winner of the competition got to
design his/her own clothes collection, which would be sold in the retailer’s stores. As such,
the brand was an omnipresent and essential part of the competition and the program. The
program contained several brand placements in the form of verbal mentions, brand logos in
the designers’ workshop, and visits by the participants to the retailer’s current designers and
stores. The sponsor brand was also shown and mentioned in the program’s end credits by
means of a sponsorship disclaimer.
6.2. Procedure and sample
The study represents a two-wave posttest-only cross-sectional field study. Short-term and
long-term program effects were measured through an online questionnaire one week (N =
529) and, as in previous research (Sheehan and Guo 2005), one month (N = 256) after the
program finale was broadcast, respectively. Both samples were collected by a Belgian market
research agency to be broadly representative of the program’s viewer profile (mostly young
women). Both samples were unique; meaning that wave 2 did not contain respondents from
11
wave 1 and vice versa. As can be seen in Table 1, the sample in wave 1 was slightly younger
than that in wave 2. We control for the potential confound of age by adding it as a covariate in
the analyses. Only viewers who had viewed at least 10 minutes of the program were
considered so that we could assume that they would have encountered at least one brand
placement. Table 1 provides a socio-demographic description of the two samples.
Table 1: Sample characteristics
Gender
Male
Female
Total
Wave 1
Age category
-20 years
11 (14.5%)
118 (16.4%)
129 (24.4%)
21 – 30 years
34 (44.7%)
185 (41.0%)
219 (41.5%)
31 – 40 years
12 (15.8%)
78 (17.2%)
90 (16.9%)
41 – 50 years
13 (17.1%)
54 (11.9%)
67 (12.6%)
51 – 60 years
4 (5.3%)
14 (3.1%)
18 (3.4%)
+ 60 years
2 (2.6%)
4 (.9%)
6 (1.1%)
Total
76
453
529 (100%)
Wave 2
Age category
-20 years
1 (2.3%)
23 (10.8%)
24 (9.3%)
21 – 30 years
15 (34.1%)
66 (31.0%)
81 (31.5%)
31 – 40 years
10 (22.7%)
55 (26.3%)
65 (25.7%)
41 – 50 years
10 (22.7%)
48 (22.5%)
58 (22.6%)
51 – 60 years
6 (13.6%)
19 (8.9%)
25 (9.7%)
+ 60 years
2 (4.5%)
1 (.5%)
3 (1.2%)
Total
44
212
256 (100%)
6.3. Measures
First, respondents were asked to indicate their age category and gender, which served as
quota in order to match the program’s viewer profile. Next, in order to build in a control for
exposure frequency, the online questionnaire measured ‘viewing frequency’ (how many
episodes of the program respondents had seen, between 1 and 10; M = 5.86 SD = 3.96).
12
Second, respondents’ liking of the program was measured on a 6-item, 5-point Likert scale
based on Cowley and Barron (2008) from strongly disagree to strongly agree (i.e., ‘I really
enjoyed watching De Designers’, ‘I looked forward to seeing the next episode of De
Designers’, ‘Watching De Designers is more pleasant than watching other shows’, ‘If they
would make another season of De Designers, I would definitely watch it’, ‘De Designers is a
good program’ and ‘De Designers was vivacious to me’; αwave1 = .912, M = 3.50, SD = .98;
αwave2 = .922, M = 3.058 , SD = 93). Third, involvement with the product category (i.e.,
fashion) was measured by means of a 4-item 5-point semantic differential scale based on
Zaichkowsky (1985) (i.e., ‘Unimportant/Important’, ‘Meaningless/Meaningful’, ‘Does not
matter to me/Matters to me’ and ‘Insignificant/Significant’; αwave1 = .811, M = 4.33, SD = .73;
αwave2 = .818, M = 4.11, SD = .87). This variable was included as a covariate in subsequent
analyses to account for biasing effects of a special interest in fashion. Afterwards, respondents
had to indicate their attitude toward the sponsor brand on a 6-item, 5-point semantic
differential scale based on Sengupta and Johar (2002) (i.e., ‘Bad/Good’,
‘Unfavorable/Favorable’, ‘Unpleasant/Pleasant’, ‘Unfriendly/Friendly’, ‘Negative/Positive’
and ‘Don’t like it/Like it’; αwave1 = .968, M = 3.54, SD = .861; αwave2 = .964, M = 3.58, SD =
.79). The same scale was used to measure viewers’ attitude toward the sponsor’s main
competitor (αwave1 = .978, M = 3.23, SD = .97, αwave2 = .977, M = 3.53, SD = .95). Finally,
respondents indicated their perceived fit between the sponsor brand and the program on a 4-
item, 5-point Likert scale (i.e., ‘[Sponsor brand] matches De Designers’, ‘[Sponsor brand] and
De Designers are logically connected’, ‘[Sponsor brand] and De Designers have a similar
image’ and ‘There is a clear link between [Sponsor brand] and De Designers’; αwave1 = .944,
M = 2.94, SD = 1.11; αwave2 = .941, M =3.03, SD = .97).
7. Results
7.1. Analyses
13
To test our hypotheses, we estimated two OLS regression models using ‘Model 3’ of
Hayes’ (2008) PROCESS macro for SPSS, one with the attitude toward the sponsor brand as
the dependent variable, and one with the attitude toward the sponsor’s main competitor. The
independent variable was program liking. Perceived program-sponsor brand fit and wave (0 =
‘wave 1’ and 1 = ‘wave 2’) were modeled as moderators. Exploratory analyses revealed a
moderate, yet significant correlation (r = .221, p <.001) between program liking and program-
sponsor brand fit. This indicates that respondents who liked the advertiser funded program
better, were also more likely to see a closer fit between the program and the sponsor. As noted
by Hayes (2008), a correlation between the independent variable (program liking) and a
moderator (program-sponsor brand fit) may result in estimation problems. In order to remedy
potential confounding effects caused by this correlation we first partialled out the influence of
program liking on program-sponsor brand fit by running a linear regression model with
perceived brand-program fit as the dependent variable and program liking as the independent
variable, and saving the standardized residuals into a new variable (“Residual fit”). The
residual program-sponsor brand fit variable was used in our final model instead of the
measured program-sponsor brand fit. In what follows, “program-sponsor brand fit” thus
always refers to the residual fit. However, the conclusions with respect to the hypotheses are
the same if we would use the original measure. Program liking and program-sponsor brand fit
were both mean-centered (see discussion in Hayes 2008). Gender (0 = ‘male’ and 1 =
‘female’), age category, viewing frequency (mean-centered) and product category
involvement (mean-centered) were entered as control variables. Gender was included as a
dummy variable. Age category was indicator coded into 5 dummy variables, according to the
procedure prescribed by Aguinis (2003), using the youngest age group as a reference
category.
14
The results of the analyses are summarized in Table 3 (sponsor brand) and Table 4
(competing brand). Both models explain a significant amount of variance in the dependent
variable (Sponsor brand: R² = .341, F(15, 769) = 26.567, p < .001; Competing brand: R² =
.129, F(15, 769) = 7.597, p < .001). Variance Inflation Factor scores demonstrate good
discriminant validity (range: 1.040 – 1.918 across both models) between the independent
variables. As shown in Tables 3 and 4, the covariates gender and age exerted a (marginally)
significant effect on the attitude toward the sponsor and competing brand. Viewing frequency
did not impact viewers’ brand attitude for either the sponsor brand (b = -.021, p = .141) or its
main competitor (b = -.007, p = .724). Product category (fashion) involvement did not
significantly influence viewers’ brand attitude toward the sponsor brand (b = .053, p = .111),
but had a significant effect on the attitude toward the competitor (b = -.124, p = .005).
Table 3: Results - attitude toward the sponsor brand
Unstandardized coefficients
B
Std. Error
Sig.
Constant
3.049
.148
< .001
Program liking
.248
.040
< .001
Brand-program fit
.395
.032
< .001
Wave
-.036
.087
.677
Program liking x Fit
.106
.032
.001
Program liking x Wave
-.136
.060
.024
Fit x Wave
-.073
.055
.185
Program liking x Fit x Wave
.079
.055
.156
Gender
.200
.072
.006
Age [21-30]
.044
.071
.537
Age [31-40]
.226
.083
.007
Age [41-50]
.322
.086
< .001
Age [51-60]
.306
.124
.014
Age [+60]
.238
.238
.318
Viewing frequency
-.021
.014
.141
Fashion involvement
.053
.033
.111
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Table 4: Results - attitude toward the competitor brand (H5 and H6).
Unstandardized coefficients
B
Std. Error
Sig.
Constant
2.837
.198
.000
Program liking
.020
.054
.754
Brand-program fit
.258
.043
.000
Wave
.243
.117
.038
Program liking x Fit
.084
.043
.051
Program liking x Wave
.146
.080
.070
Fit x Wave
-.174
.073
.017
Program liking x Fit x Wave
-.176
.074
.018
Gender
.171
.097
.078
Age [21-30]
.026
.094
.781
Age [31-40]
.227
.111
.041
Age [41-50]
.254
.115
.028
Age [51-60]
.235
.166
.156
Age [+60]
.245
.317
.441
Viewing frequency
-.007
.019
.724
Fashion involvement
-.124
.044
.005
7.2. Effects on the attitude toward the sponsor brand (H1 – H4)
We first report the results of the hypotheses tests for viewers’ attitude toward the AFP’s
sponsor brand. The results show that program liking has a significant positive effect on
viewers’ attitude toward the sponsor brand (b = .248, p < .001), confirming H1. H2 predicted
that the effect of program liking on sponsor brand attitude would be reinforced by the
program-sponsor brand fit (H2). The two-way interaction between program liking and
program-sponsor brand fit is indeed positive and significant (b = .106, t = 3.307, p = .001), in
support of H2.
H3 posits that the effect of program liking on brand attitude would be larger in the short-
term than in the long-term. As shown in Table 3, the program liking x wave interaction is
negative and significant (b = -.136, p = .024), indicating that the effect of program liking on
brand attitude is significantly smaller in wave 2 than in wave 1, which supports H3.
16
The three-way-interaction between program liking, program-sponsor brand fit and
wave is insignificant (b = .079, p = .156). We did expect, though, in H4, that in the longer
term, higher levels of perceived fit would be required to retain the effect of program liking.
We therefore further inspected the results using conditional effects analyses (Figure 1). These
analyses show that, within wave 1, the positive impact of program liking on brand attitude
becomes stronger with increasing perceived program-sponsor brand fit (low fit: b = .143, t =
2.824, p = .005; moderate fit: b = .248, t = 6.155, p < .001, strong fit: b = .354, t = 6.745, p <
.001, effects estimated at the mean value of program-sponsor brand fit, and one standard
deviation below and above the mean of program-sponsor brand fit). In wave 2, however,
program liking did not affect brand attitude when program-sponsor brand fit was low, b = -
.072, t = -1.059, p = .290, but did affect brand attitude for moderate fit, b = .113, t = 2.383, p
= .017, and even more when program-sponsor brand fit was high, b = .297, t = 4.693, p < .001
(effects estimated at the mean value of fit, and one standard deviation below and above the
mean of fit). These results show that in the longer term, the effect of program liking increases
with higher levels of program-sponsor brand fit, whereas the effect was always significant in
the short term. These results provide support for H4.
17
Figure 1: Interaction between program liking and perceived program-sponsor brand fit on
the attitude toward the sponsor brand
7.3. Effects on the attitude toward the sponsor’s main competitor (H5 – H6)
H5 posits that program liking would impact viewers’ attitude toward a competing brand
more strongly in the longer term. In accordance with this prediction, the observed two-way
interaction effect of program liking and wave on the attitude toward the competitor brand (b =
.146, p = .070) does show that the effect of program liking on the attitude toward the
competitor brand is higher in the second period, but the difference is only marginally
2"
3"
4"
5"
Low"(*1"SD)" Moderate" High"(+1"SD)"
A"tude'toward'sponsor'brand'
Program'liking'
WAVE'1'
"""Low"fit"(*1"SD)"
"""High"fit"(+1"SD)"
2"
3"
4"
5"
Low"(*1"SD)" Moderate" High"(+1"SD)"
A"tude'toward'sponsor'brand'
Program'liking'
WAVE'2'
"""Low"fit"(*1"SD)"
"""High"fit"(+1"
SD)"
18
significant. Although the data do show a clear increasing trend in the effect of program liking
on attitude toward the competitor brand, H5 is not confirmed.
H6 posits that the perceived program-sponsor brand fit would weaken the long term effect
of program liking on viewers’ attitudes toward the competitor brand. As displayed in Table 4,
the three-way interaction term between program liking, program-sponsor brand fit and wave
and viewers’ attitude toward the competitor is negative and significant (b = -.176, p = .017).
The conditional effects demonstrate that, in wave 2, program liking exerts a significant
positive impact on attitude toward a competing brand at low (one standard deviation below
the mean) (b = .254, p = .005) and moderate (mean value) (b = .162, p = .011) levels of
perceived fit between a program and its sponsor, but not at high levels of perceived sponsor
brand-program fit (b = .070, p = .408) (Figure 2). This confirms H6.
Figure 2: Interaction between program liking and perceived program-sponsor brand fit
on the attitude toward the sponsor’s main competitor (wave 2)
2"
3"
4"
5"
Low"(*1"SD)" Moderate" High"(+1"SD)"
A"tude'toward'main'compe<tor'
Program'liking'
WAVE'2'
"""Low"fit"(*1"SD)"
"""High"fit"(+1"SD)"
19
8. Discussion
We investigated attitudinal brand placement effects among viewers of an advertising
funded program (AFP) for the sponsor brand and its main competitor, one week and week
month after the show had been broadcast. The present study finds evidence for the existence
of attitudinal brand placement effects in a real life setting with viewers that voluntarily
watched a program at home and in their own time. In accordance with prior brand placement
research (e.g., Van Reijmersdal, Smit and Neijens 2010), we found that program liking spills
over to viewers’ attitudes for the integrated sponsor brand. The present research adds more
depth to academic understanding of this affect transfer process by demonstrating that the
effect of program liking is strengthened by a higher degree of perceived fit between the
sponsor brand and the program. Thereby, the findings support the notion that the perceived fit
or convergence between the associative networks of the integrated brand and the AFP makes
it easier to make an impact on the brand through the AFP (Gawronski and Bodenhausen 2006;
Till and Busler 2000).
Another contribution to existing academic work on the effects of brand placement is the
long-term angle of the present research. Brand placement effects are often studied
immediately after exposure (for a review, see Van Reijmersdal, Neijens and Smit 2009).
However, in practice marketers hope to establish effects for longer periods of time. Our
findings show that the impact of program liking on the attitude towards the sponsor brand
diminishes over time, but that a high degree of program-sponsor brand fit helps to retain a
more positive effect. In that sense, the results are at least partly in line with those by Sheehan
and Guo (2005), which is the only other study we are aware of on the effects of an AFP on
brand attitude. They found that exposure to an AFP even increased viewers’ brand attitude
toward the “star” brand a few weeks after watching, compared to immediately after. While
they do not report on fit perceptions in their study, they were likely very high (the AFP was
20
“Airline”, focused on Southwest Airlines). Our study therefore contributes to the debate by
showing that long-term effects are not necessarily always positive, but dependent upon the
perceived fit between the program and the brand. When the perceived program-sponsor brand
fit is low, the results of our study indicate that the program’s effect on brand attitude is
completely wiped out one month after the AFP stops being broadcast. The stronger linkage
between the brand and the program makes the affect transfer of program related associations
to the brand more robust to temporal deterioration. This means that creating a high perceived
fit between the brand and the program is crucial to warrant longer term effects of program
liking on brand attitude.
A last contribution of the present research is that it considers how investing in an AFP
affects viewers’ attitudes toward a sponsor’s competitor in both the short and the longer term.
Our results indicate that liking of an AFP does not immediately (positively or negatively)
affect viewers’ brand attitude toward a competing brand, but can boost their attitude toward
the competitor in the longer term. Established brands possess clear associative networks with
strong links between the brand’s node and certain associations, which make it easier to
distinguish (an AFP of) the target brand from similar competitor brands (Keller 1987).
Therefore, immediately after the program, viewers are likely to associate the AFP very
strongly to the actual sponsor, and competitors are not likely to benefit from this. In the longer
term, however, time may weaken the links between the sponsor brand and the program
induced associations. The weaker these links become, the more likely it becomes that these
associations are misattributed to a similar competing brand. When this happens, viewers’
liking of the program is (also) transferred to the competitor brand. Indeed, our results indicate
that, in the longer term, program liking positively affects viewers’ attitudes toward the main
competitor of the brand that is sponsoring the AFP. These findings are in line with the idea of
brand misattribution based on competitive interference effects in advertising (e.g., Dahlén and
21
Rosengren 2005; Danaher, Bonfrer and Dhar 2008). However, it is important to highlight that
a high perceived fit between the sponsor brand and the AFP prevents the misattribution of
AFP-induced brand associations to another brand, which again underlines the importance of
program-sponsor brand fit and creating unique connections between the program and the
sponsor brand in memory.
9. Managerial implications
The present study offers several managerial implications for practitioners involved in the
production or management of branded entertainment content. Although building entertaining
and well-liked content around a brand is beneficial in itself, a good match between the brand
and the content reinforces the attitudinal benefits the brand draws from the entertaining
character of the content. Therefore, managers should pay close attention to matching their
products to the right type of content before investing in a branded entertainment campaign. If
the associations between the brand and program are not entirely clear to viewers, within the
program or accompanying commercials efforts can be made to emphasize and improve the
perceived fit. One way to improve the perceived program-brand fit is to better build the brand
into the storyline, as prior research indicates that plot connection contributes to perceived fit
(e.g., Verhellen, Dens and De Pelsmacker 2015).
The importance of perceived fit between the program and the sponsor brand becomes
particularly clear when looking at the longer-term impact of the AFP. In the longer run, the
beneficial effect of program-induced liking on sponsor brand attitude disappears, unless
viewers perceive the brand as a very good fit with the program. Under these conditions, the
program makes a long-term impact on viewers’ attitudes toward the sponsor brand. Moreover,
our findings suggest that by increasing the fit between the brand and the AFP, advertisers may
prevent similarly positioned competitors to profit from their advertising efforts. In time,
22
viewers may forget learned idiosyncratic links between the program and the sponsor brand
and misattribute positive program associations to a competing brand with a similar
positioning. When there is an excellent program-sponsor brand fit, however, the
misattribution of program induced affect is less likely to occur and liking of the AFP does not
improve viewers’ brand attitudes toward competing brands. This offers advertising managers
an additional incentive to invest time, effort and funds in matching their brand with
appropriate content.
Finally, our findings suggest that positive affect transfer relies on the reactivation of the
link between the TV program and the sponsor brand, which diminishes over time when the
program is no longer broadcast. In other words, the positive feelings are not definitively
acquired by the brand (i.e., direct affect transfer), but borrowed from the program (i.e.,
indirect affect transfer) (Sweldens, Van Osselaer and Janiszewski 2010).
To prolong brand placement effects, we suggest advertisers to use reminders of the TV
program in the brand communication in the months that follow broadcasting (e.g., in store, on
a product package, on the brand website, “making of” videos on a Facebook page).
10. Limitations and suggestions for further research
The present research has a number of limitations that can be investigated in future
research. Whereas the field study we conducted has a number of strengths, such as its high
ecological validity, it also poses challenges. A field study is limited in the amount of control it
has over external variables. For instance, we had no way of controlling for exposure to other
brand communications for the sponsor brand or its competitors, outside of the program.
Although we control for other external variables, such as viewing frequency and product
category involvement, we encourage researchers pursuing similar field experiments to
incorporate additional marketing communication investments into their research design.
23
In general, a field study is unable to establish causality. We found a positive relationship
between program liking and brand attitude and chose to interpret that relationship as a causal
effect of program liking on brand attitude, consistent with theory on affect transfer and
existing research in brand placement (e.g., Russell 1998). The direction is also consistent with
the single existing paper on AFPs (Sheehan and Guo 2005), which found that viewers’
exposure to an AFP increased their attitude toward and beliefs about the sponsor brand
(explicitly compared to before exposure). In theory, one could also imagine that the feelings
towards highly liked brands spill over to the program content. In the present study, the
sponsor brand was a mid-range fashion retailer that did not have a particularly strong brand
image at the start of the program. In fact, the retailer sponsored the program to boost its image
and link it more to design. Therefore, we believe it is unlikely that people viewed and liked
the program because of their interest in the brand. Nevertheless the causality of the relation
between program liking and brand attitude is an interesting avenue for further research.
Second, only one specific form of branded entertainment, namely brand integration
through an advertiser funded fashion design contest, and only one product category (i.e.,
fashion) are explored. Branded entertainment and content marketing incorporate a large
diversity of content types with their own idiosyncratic characteristics and contextual
background, e.g., company videos, exclusive online content for customers, etc. (Rose 2013).
Although we have demonstrated that time after exposure and the (absence) of fit have an
important influence on whether (positive) affect spillover from the program to the sponsor
brand occurs, it would be highly interesting to find out whether the same mechanisms apply to
other forms of branded entertainment.
Finally, the study uses only one outcome variable, i.e., brand attitude. Although this
metric is valuable from both an academic and practical viewpoint, it is not the only outcome
researchers could consider in order to gain insight into the workings of branded entertainment.
24
To attain a more comprehensive picture of how branded entertainment influences viewers,
explicit and implicit cognitive, attitudinal and behavioral outcomes should be studied.
Especially given the fact that previous research on brand placement has shown that it may
have a different impact on different outcome variables (Cowley and Barron 2008; Dens et al.
2012; Van Reijmersdal 2009).
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    The purpose of this investigation was to explore the persuasive effect of product placement on mobile phone games. An experiment was conducted with a 2 (type of game: high level of attention vs low level of attention) x 2 (placement location: focal vs peripheral) x 2 (type of brand: high-familiarity brand vs low-familiarity brand) between-subjects design to examine whether the type of game, type of brand and product placement of mobile phone games affect garners' (N = 324) memories, attitudes towards product placement and purchase intentions. The results showed that: (1) garners have higher recall of brands embedded in the focal area than those in the peripheral areas of the game, (2) garners' product-related recall improves when high-familiarity brands rather than low-familiarity brands are embedded within games; and (3) garners who exhibit more positive attitudes towards product placement are more likely to exhibit stronger purchase intentions.
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    Using the case study data of the South Korea 2002 and 2006 World Cup sponsorship campaigns, this study examined (1) whether more favourable sponsorship response occurs as image congruence between a sponsor and the World Cup increases, and whether (2) consumer attributions of a sponsor's motives in sponsoring the World Cup and (3) a sponsor's perceived fit in aiding World Cup cheering events, namely cheering event fit, moderate image congruence's effects on sponsorship response. Consistent with prior research, results suggest that high vs low image congruence sponsorships generate more favourable responses to the sponsorship, as measured by attitudes and intentions at three different levels of the hierarchy of effects. Results also show that high cheering event fit leads to more favourable sponsorship response. Furthermore, a negative interaction between image congruence and cheering event fit indicates that, albeit still significant and positive, the effect of image congruence on sponsorship response becomes significantly weaker at higher levels of cheering event fit than at lower levels of cheering event fit. A moderating role of a sponsor's sponsoring motive has not been supported. Overall, the findings underscore the significance of image congruence as well as the utility of cheering event fit as a particular type of 'created fit' that can be used to reduce the perception of low fit and its associated risks.
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