What Type of Relationship Do We Have With Loved Brands?

Abstract

Purpose
– The purpose of this paper is to provide a discussion, testing and comparing two different relationship theories and their underlying scales as applied to brand love. Current brand love studies neglect a detailed discussion and analysis of the appropriate relationship theory and underlying measurement scale to be used.

Design/methodology/approach
– We use a 2 × 2 experimental design where we compare two relationship theories (interpersonal versus parasocial) across two samples (USA and Japan). Model testing were conducted using exploratory factor analysis, confirmatory factor analysis and multi-group structural equation modeling techniques assessing the type of relationship consumers have with loved brands.

Findings
– Our results show conceptualizing and measuring “brand love” as a parasocial relationship, as compared to interpersonal relationship, leads overall to equal and, in some instances, better results. For both samples, we get stronger relationships between brand love and purchase intention, as well as for brand love and positive word of mouth (WOM). We also get higher explanation power for dependent variables purchase indentation and WOM.

Originality/value
– This paper compares different relationship theories and underlying measurement scales and proposes an alternative relationship theory to conceptualize and measure brand love relationships. With the parasocial interaction scale, we provide researchers and practitioners an alternative and very suitable instrument to measure brand love relationships.

Full text

What type of relationship do we have with
loved brands?
Marc Fetscherin
Department of International Business, Rollins College, Winter Park, Florida, USA
Abstract
Purpose – The purpose of this paper is to provide a discussion, testing and comparing two different relationship theories and their underlying scales as
applied to brand love. Current brand love studies neglect a detailed discussion and analysis of the appropriate relationship theory and underlying
measurement scale to be used.
Design/methodology/approach –Weusea2⫻2 experimental design where we compare two relationship theories (interpersonal versus parasocial)
across two samples (USA and Japan). Model testing were conducted using exploratory factor analysis, confirmatory factor analysis and multi-group structural
equation modeling techniques assessing the type of relationship consumers have with loved brands.
Findings – Our results show conceptualizing and measuring “brand love” as a parasocial relationship, as compared to interpersonal relationship, leads
overall to equal and, in some instances, better results. For both samples, we get stronger relationships between brand love and purchase intention, as well
as for brand love and positive word of mouth (WOM). We also get higher explanation power for dependent variables purchase indentation and WOM.
Originality/value – This paper compares different relationship theories and underlying measurement scales and proposes an alternative
relationship theory to conceptualize and measure brand love relationships. With the parasocial interaction scale, we provide researchers and
practitioners an alternative and very suitable instrument to measure brand love relationships.
Keywords Brand loyalty, Brand love, Brand relationship, Consumer brand relationships, Relationship theory
Paper type Research paper
1. Introduction
In the past few decades, researchers have begun to assess the
relationships consumers have with brands (Blackstone, 1993).
Early discussions of the way people feel about brands center on
assigning human characteristics (Levy, 1985), personalities
(Aaker, 1997), and brands have been seen as relationship
partners (Fournier, 1998). In fact, a “variety of different
perspectives, concepts, models and various theories have been
developed and introduced to understand consumers’
relationships to their brands” (Fetscherin and Heinrich, 2014a,
p. 1). Examples are brand loyalty (Jacoby and Chestnut, 1978),
brand trust (Chaudhuri and Holbrook, 2001), brand attachment
(Belaid and Behi, 2011;Park et al., 2010), brand passion (Bauer
et al., 2004), brand romance (Patwardhan and
Balasubramanian, 2011), brand tribalism (Veloutsou and
Moutinho, 2009) and brand love (Ahuvia, 2005). These
studies distinguish various emotions consumers have for
brands (Batra et al., 2012) and illustrate that “consumer brand
relationships research is multi-disciplinary, multi-dimensional
and multi-conceptual”(Fetscherin and Heinrich, 2014b,p.1).
In the current “brand love” literature, the concept of “brand
love” is often used as a holistic term, including many of the
previously mentioned construct such as brand loyalty or brand
passion. Appendix 1 summarizes the dimensionality of the
brand love constructs studied so far. All these studies make an
important contribution to the understanding of the
conceptualization and dimensionalities of brand love, but
regrettably do not assess and discuss the appropriate
relationships theory behind the construct. This is important as
the “relationship” part of the “consumer brand relationships
equation” (Fournier, 2009, p. 19) is the one which explains
the emotional bond consumers have with brands. The
“equation” consists of three parts: the “consumer”, the
“brand” and the “relationship” in-between. The relationship
theory used to explain consumers’ relationships with brands
put forward which measurement scales to be used. So far,
brand love studies used, without any critical discussion, scales
originated from interpersonal relationship theories.
Against this background, the contribution of this paper is to
close this gap by providing a discussion, testing and comparing
two different relationship theories and their underlying scales
as applied to brand love. On one hand, existing studies use the
interpersonal relationship metaphor and theories to
conceptualize and measure the brand love relationship. On the
other hand, we propose and discuss an alternative relationship
metaphor, the parasocial relationship theory, as another
relationship theory to use to construct and assess the love
relationship consumers have with brands[1]. Our finding
suggests that using the parasocial love scale is appropriate for
studying brand love relationships. In fact, we find that it leads
to better results compared to the results obtained when using
the interpersonal love attitude scale. For example, the
explanation power of the dependent variables purchase
intention and word of mouth (WOM) were higher for both
samples when using the parasocial love scale as compared to
the interpersonal love attitude scale. Our findings are helpful,
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Journal of Consumer Marketing
31/6/7 (2014) 430–440
© Emerald Group Publishing Limited [ISSN 0736-3761]
[DOI 10.1108/JCM-05-2014-0969]
430

as we provide researchers and managers an alternative scale
for their research projects related to brand love relationships.
2. Love relationship theories
Existing brand love studies use the interpersonal relationship
theory and their underlying measurement scales without
critically assessing whether these scales are the most suitable
ones. In that respect, and as Batra et al. (2012, p. 1) stated,
“there are compelling reasons these conceptualizations of
interpersonal love should not be applied to brand love”. In
fact, only a handful of papers have as a focal point a discussion
about the “relationship” part of the “consumer brand
relationship equation” (Fournier, 2009, p. 19). One such
study is by Hess et al. (2011) who focus on communality and
exchange relationships characteristics and how they impact
consumer brand relationships. More recently, the study by
Fetscherin and Conway Dato-on (2012) provides a first
attempt in discussing relationship theories and brand love
relationships. However, their study has some major limitations
such the use of one sample; they do not include brand
outcome variables such as purchase intention and WOM as
well as overall used a different conceptual model. Taking all
this into account, this section discusses first interpersonal
relationship theory, which is used in current brand love studies
and then we discuss the parasocial relationship theory.
2.1 Interpersonal relationship theory
Current brand love studies are based on Sternberg’s (1986)
triangular theory of love and apply his triangular love scale
(Sternberg, 1997) to the brand relationship context (Shimp and
Madden, 1988). As Aggarwal (2004, p. 87) states “when
consumers form relationships with brands they use norms of
interpersonal relationships as a guide in their brand
assessments”. However, there are many other interpersonal
relationship theories and underlying measurement scales in the
literature proposed in addition to Sternberg’s theory and
triangular love scale. For example, Masuda (2003, p. 30) states
in his meta-analyses of love theories, “in the realm of social
psychology research on love, there have been four major love
theories constructed”. Rubin (1970) is the first researcher who
measures love, suggesting the liking scales. Second, Hatfield and
Sprecher (1986) introduce the passionate love scale. Third,
Hendrick and Hendrick (1986) developed the love attitude scale
based on Lee’s (1977) early work on the color theory of love. The
fourth and last one is Sternberg’s (1997) triangular love scale.
In Masuda’s (2003, p. 31) “dichotomous classification of
love scales”, he argues all the above love relationship theories
“are based on the assumption that love comprises at least two
aspects, that is sexual attraction to romantic partners, and
non-sexual psychological closeness to partners”. His
dichotomy classifies the four scales into erotic love scales
(Hatfield and Sprecher, 1986;Sternberg, 1986) and
companionate love scales (Rubin, 1970;Hendrick and
Hendrick. 1986). As consumers do not really have a sexually
related (erotic) relationship with brands, we are left with
Rubin (1970) or Hendrick and Hendrick (1986) scale for our
interpersonal love scale. We chose Hendrick and Hendrick
(1986) scale, as it is subject of multiple validation studies
related to brands (Whang et al., 2004) as well as multiple
cross-cultural validating studies (Neto et al., 2000).
2.2 Parasocial relationship theory
Yoon et al. (2006) show consumers process brand relationships
in a different part of their brain than interpersonal relationships.
Furthermore, Whang et al. (2004, p. 320) argue “when the target
of love is replaced with an object, love becomes uni-directional”.
More recently, Batra et al. (2012) argue “there are compelling
reasons these conceptualizations of interpersonal love should not
be applied to brand love”. All these studies recommend to be
cautious when applying interpersonal love relationship theory to
brand love relationships and ask for an alternative relationship
theory.
Parasocial relationship has its origin from the early works on
parasocial interaction (PSI) by Horton and Wohl (1956) and the
development of the PSI scale by Perse and Rubin (1989).
Parasocial relationships describe a one-sided relationship where
one party knows greatly about the other, but the other knows
nothing. It is a perceived relationship of friendship or intimacy a
person has with a media person (Schmid and Klimmt, 2011).
Examples of such relationships are the celebrity–fan relationship
(Cohen, 1997) or the influence of TV personalities on audience
members’ teleshopping intentions and behavior (Curras-Perez
et al., 2011). The parasocial relationship also assesses the
relationship between viewers and non-personal or fictional
characters (e.g. Mikey Mouse, Hulk), which some of them are
brands themselves. The previously mentioned research in
combination with the anthropomorphism of brands such as
attributing human characteristics (Levy, 1985) or personalities to
brands (Aaker, 1997), both research streams suggest that it is a
reasonable assumption to apply parasocial relationship theory to
product or service brands. Note that:
[. . .] we do not mean to imply that brand love researchers should abstain from
citing interpersonal love research as sources of hypotheses or even citing
parallels between findings on brand love and interpersonal love (Batra et al.,
2012, p. 6), but this paper discusses, tests and compares two different
relationship theories and their underlying measurement scale as applied to
brand love.
3. Conceptual background
3.1 Brand love
Ha and Perks (2005) suggest the lowest intensity of a relationship
consumers have with brands is “brand satisfaction” which results
from the consumer’s positive experiences with the brand. As the
intensity of the relationship grows, brand satisfaction can lead to
brand trust and then brand loyalty (Horppu et al., 2008).
Extensive research confirms that brand satisfaction drives brand
trust, which in turn drives brand loyalty (Fournier and Yao,
1997). But researchers know much less about the relationship
between brand loyalty and brand love. The few brand love
studies (Thomson et al., 2005;Carroll and Ahuvia, 2006;Batra
et al., 2012) illustrate brand love precedes brand loyalty. In line
with previous research, we state the following hypothesis.
H1. Brand love positively influences brand loyalty.
As Miniard et al. (1983, p. 206) state, “the prediction of purchase
intention is a central concern in marketing”, arguing that
purchase intention is influenced by the attitude toward the
brand. Eagly and Chaiken (1993) confirm that consumer
satisfaction with a brand influences the willingness to buy the
brand. Several studies demonstrate the positive relationship
between brand loyalty and purchase intention (Jacoby and
What type of relationship we have with loved brands?
Marc Fetscherin
Journal of Consumer Marketing
Volume 31 · Number 6/7 · 2014 · 430 –440
431

Chestnut, 1978;Srinivasan et al., 2002). As brand love precedes
brand loyalty (Carroll and Ahuvia, 2006), we test the following
hypothesis:
H2. Brand love positively influences purchase intention.
Many studies focus on the antecedents and consequences of
WOM, including extreme (dis)satisfaction (Maxham and
Netemeyer, 2002), commitment to products (Dick and Basu,
1994) and length of the relationship with brands
(Wangenheim and Bayón, 2004). Bowman and Narayandas
(2001) show that self-described loyal consumers are
significantly more likely to engage in positive WOM. Most
recently, Batra et al. (2012, p. 1) confirm that brand love is
“associated with positive word of mouth”. We therefore test
the following hypothesis:
H3. Brand love positively influences word of mouth.
3.2 Brand loyalty
Bloemer and Kasper (1995) outline the difference between
brand loyalty and purchase intention, suggesting that purchase
intention refers to buying a brand where actual behavior prevails.
Many researchers explore the positive relationship between
brand loyalty and purchase intention (Jacoby and Chestnut,
1978;Srinivasan et al., 2002). Therefore, we test the following
hypothesis:
H4. Brand loyalty positively influences purchase intention.
There has been less research on the relationship between brand
loyalty and WOM. Dick and Basu (1994) or Srinivasan et al.
(2002) find that brand loyalty can add to positive WOM. The
positive and direct relationship between brand loyalty and
(positive) WOM finds further support by Walsh and Beatty
(2007). We test the following hypothesis:
H5. Brand loyalty positively influences word of mouth.
Current brand love studies examine the above relationships
individually but no study incorporates them collectively and
more importantly, tests and compares different relationship
theories and their underlying measurement scales. The objective
of this study is to address this gap as mentioned in the
introduction section.
4. Research method
4.1 Measurement items
4.1.1 Dependent variables
●Purchase intention. We considered two aspects, purchase
intention and purchase probability. Market research uses
purchase intention scales extensively, and we employ two
items from Kumar et al. (2009) to ascertain purchase
intention. Purchase probability captures another aspect of
purchase intention. Like many other studies, we use the
popular Juster (1966) scale, a 11-point probability scale,
which is subject to multiple validation studies (Clawson,
1971).
●Positive WOM. The literature proposes different WOM
scales, from single-item (Swan and Oliver, 1989)to
multi-item scales by Bone (1992) and Carroll and Ahuvia
(2006). In this study, we use the four items proposed by
Carroll and Ahuvia (2006) in their brand love study.
4.1.2 Independent variables
●Parasocial Love. We used eight items from the original PSI
or parasocial love scale (Perse and Rubin, 1989).
●Interpersonal Love. We used seven items from the love
attitude scale by Hendrick and Hendrick (1986) which is
subject to multiple brand-related (Whang et al., 2004) and
cross-cultural validation studies (Neto et al., 2000).
●Brand loyalty. Jacoby and Kyner (1973) suggest
incorporating behavioral and attitudinal dimensions in any
measurement for brand loyalty.
We use three items developed by Quester and Lim (2003) to
measure attitudinal brand loyalty and two items for behavioral
brand loyalty. Appendix 2 summarizes the measurement items
used in this study. If not mentioned otherwise, all items are
measured along a 5-point Likert scale where respondents express
their agreement or disagreement (1 ⫽strongly disagree; to 5 ⫽
strongly agree). We calculate and compare the mean scores for all
variables to prevent ecological fallacy (i.e. drawing conclusions
for individual behavior based on group behavior) and atomistic
fallacy (i.e. drawing conclusions between groups based on
individual behavior).
4.2. Product category
Albert et al. (2008) suggest that brand love studies should investigate
product categories with heavily branded products such as shoes,
cars, lingerie, watches or perfumes. However, a more recent study
(Fetscherin et al., 2014) shows that brand love relationship can be
applied to different product categories as long as respondents can
choose their favorite brand. With this in mind, we selected cars as
the product category for this study. Using the product category and
brands for cars, category equivalence was assured, as both product
categories and brands are widely available to our samples (Bensaou
et al., 1999;Hayes et al., 2006).
4.3 Samples
We use two samples, one from the USA and one from Japan. From
a theoretical viewpoint, using an American and a Japanese sample is
appropriate according to the method Sivakumar and Nakata (2001)
suggest for suitable country combinations to strengthen the
hypothesis testing. From a practical viewpoint, it is a relevant
country combination as the USA is the largest and Japan the third
largest economy. Both also have a very high percentage of car
ownership and are major car producing countries. Erdem et al.
(2006, p. 37) suggest two ways to get sample comparability, by
either “drawing nationally representative samples or selecting
matched samples on the basis of some set of characteristics of
interest”. As we have undergraduate and graduate student samples
from private Universities in both countries, we have “matched”
homogenous samples. Also student samples have limitations, one
justification is that our study focuses on testing hypotheses rather
than analyzing population projections. In that respect, Sternthal
et al. (1994, p. 208) state:
[. . .] when the researcher is interested in theoretical explanation, a
homogeneous sample is the preferred option [. . .] lowering inter-subject
variance in this way enhances the likelihood of finding support for the theory
is true. In such instances, student samples are preferred.
Similarly, Erdem et al. (2006, p. 38) argue that the smaller
“differences in age, socio-demographics, relative income and
What type of relationship we have with loved brands?
Marc Fetscherin
Journal of Consumer Marketing
Volume 31 · Number 6/7 · 2014 · 430 –440
432

so forth [. . .] making possible a clearer attribution of
substantive theoretical differences”. Finally, numerous brand
relationship (Swaminathan et al., 2007) and brand love studies
also use students samples (Batra et al., 2012). Finally, note
that for the survey in Japan, we used a translation
back-translation method by two independent translators to
establish translation equivalence, implying the translation
does not alter the item’s meaning (Bensaou et al., 1999).
4.4 Data collection
For both countries, local trained field workers conducted
pre-tests with 20 respondents to uncover any potential
question-based issues. For the survey, we randomly selected
students on campus. Trained field workers were present to help
if needed and to overlook the process. Through unaided brand
recall, respondents were asked to mention three car brands and
then indicating their favorite one. This was important in the
study design to give respondents the choice to pick their favorite
brand (Fetscherin et al., 2014) and also suggests they have some
brand awareness. Each respondent then filled out the survey
which consistent of all items as described in Appendix 2. In that
respect, each participant responded to both brand love scales.
The data collection efforts yielded 196 completed questionnaires
in the USA and 248 in Japan. Missing data and list-wise deletion
reduced the sample to 180 and 225, respectively. For both
samples, the absolute number is above the suggested threshold of
100 per (Hatcher, 1994). The item to sample ratio is 6.6 for the
USA and 8.3 for the Japanese sample, respectively. Again, both
are above the suggested minimum of 5:1 (Hatcher, 1994;Bryant
and Yarnold, 1995). We also calculated the sampling adequacy
by means of Kaiser–Mayer–Olkin (KMO) and Bartlett’s test of
sphericity. The KMO for American sample was 0.881 and 0.877
for the Japanese sample and the Bartlett’s test of sphericity was
significant for both sample indicating sample adequacy.
4.4 Measurement and model testing
The model testing comprised of three steps as suggested by
Anderson and Gerbing (1988) recommendations:
1 We conducted an exploratory factor analysis (EFA). For the
EFA, we used the principle component analysis[2] with
varimax rotation. We excluded items with either a factor load
of less than 0.5 or those with significant cross-loadings (⬎
0.5). Of the 27 items, we retained 18 for the confirmatory
factor analysis (CFA). The results confirm that the research
framework in Figure 1 is well-specified, as we got the same
number of factors and underlying items loading on those
factors for both samples.
2 we performed a CFA where we used again the principle
component analysis with variamax rotation. We got the same
number of factors and items loadings, except one item which
we excluded, and we retained 17 items for our structure
equation models (SEM). Appendix 3 provides the details of
our CFA for both samples.
3 Finally, we run a series of validity and reliability tests,
including content validity; internal consistency, stability and
reliability of the scales; and construct validity including
convergent and discriminant validity tests. Content validity –
we used valid and reliable measurement scales. Internal
consistency, stability and reliability of the scales – We calculated
Cronbach Alpha where we obtained for both samples values
which exceed the recommended minimum of 0.7 as show in
the Appendix 4. Finally, we also assessed construct validity.
This included assessing convergent and discriminant validity.
“Convergent validity refers to the degree of agreement in two
or more measures of the same construct” (Sin, 2005,
p. 189). The convergent validity of the scale was examined by
calculating the Average Variance Extracted (AVE) and the
construct reliability (CR). Both, the AVE needs to be above
the threshold of 0.50 (Fornell and Larcker, 1981) and the CR
of 0.60 (Bagozzi and Yi, 1988), respectively. Of the 16 AVE
and 16 CR values, all exceeded the corresponding thresholds
except two for AVE and one for CR, respectively. To test this
further, we tested our scales for discriminant validity by
comparing the AVE with the squared inter-construct
correlation estimates (SIC). As a rule of thumb, if all AVE
estimates are higher than the corresponding SIC, this
indicates discriminant validity. We used the Kendall’s tau-b
correlations, a measure of correlation between ordinal scales
(as we used Likert scale), to test common method bias. We got
all satisfactory results as Appendix 4 displays.
5. Analysis and results
5.1 Descriptive statistics
US respondents mentioned a total of 35 different brands,
whereas Japanese respondents mentioned 19 different brands.
The following Table I provides some basic descriptive
statistics for the two samples:
Figure 1 Research framework
Table I Descriptive statistics
United States (
n
ⴝ180) Japan (
n
ⴝ225)
Gender
Male (%) 54 58
Female (%) 46 42
Marital status
Single (%) 87 81
Married (%) 12 17
Divorced/other (%) 12
Age
Minimum years 18 18
Maximum years 47 53
Mean years 25 24
Mode years 22 21
What type of relationship we have with loved brands?
Marc Fetscherin
Journal of Consumer Marketing
Volume 31 · Number 6/7 · 2014 · 430 –440
433

Both data sets consist of student samples and are fairly similar
in terms of gender, marital status and age distribution, all
suggesting sampling equivalence (Erdem et al., 2006).
5.2 Hypotheses testing
To investigate the differences in inter-construct relationships, we
performed multi group structural equation models (MGSEM).
Table II provides the results of the model fit indexes for the two
samples (USA and Japan) and two scales tested (interpersonal
and parasocial). Our chi-square/df for the US (Model I ⫽1.89;
Model II ⫽2.46) and Japanese sample (Model I ⫽1.95; Model
II ⫽1.88) are below the threshold of 3.0. The goodness of fit
criteria with the Tucker–Lewis Index (TLI), the Comparative Fit
Index (CFI), the Normed Fit Index (NFI) and Incremental Fit
Index (IFI) are all higher than the threshold of 0.9. The Root Mean
Square Error of Approximation (RMSEA) for both samples and
models are also below or equal to the threshold of 0.09.
Table III provides the summary results of the explanation
power for the two dependent variables as well as the results of
our hypotheses testing.
We can draw at least five main observations from the results
of Table II and III:
1 Looking at Table II and the various fit indexes, we can
conclude that for both samples and models, our research
framework is well specified and theoretically robust and
sound.
2 Looking at the explanation power of the dependent variables
purchase intention and positive WOM in Table III,wecan
conclude that the values are higher for the model using the
parasocial love scale compared to model using the
interpersonal love scale. This suggests conceptualizing and
measuring the brand love relationship as a parasocial
relationship leads to superior results in terms of explanation
power for purchase intention and WOM. With our samples,
we are able to explain in Model II between 53-62 per cent of
the variance of purchase intention and 50-60 per cent for
WOM compared to Model I with 23-32 per cent for
purchase intention and 41-49 per cent for WOM,
respectively.
3 Looking at the directionality, signs and significance level of
the path coefficients of our models, except in two cases, all
were positive and significant. For the relationship between
brand love and brand loyalty (H1), we got between 0.31 (p⬍
0.01) and 0.52 (p⬍0.01); for brand love and purchase
intention (H2), we got 0.32 (p⬍0.01) and 0.73 (p⬍0.01);
for brand love and word of mouth (H3), they were 0.32 (p⬍
0.01) and 0.60 (p⬍0.01); for brand loyalty and purchase
intention (H4), they were 0.14 (p⬍0.01) and 0.58 (p⬍
0.01), and finally for brand loyalty and word of mouth (H5),
they were 0.33 (p⬍0.01) and 0.65 (p⬍0.01).
4 Interestingly, the two hypotheses which are not significant
are with our US sample when brand love was conceptualized
as an interpersonal relationship (Model I). The two
non-significant relationships were between brand love and
purchase intention ⫺0.03 (p⬎0.10) and brand love and
WOM 0.09 (p⬎0.10). One could argue that this is in line
with what Batra et al. (2012, p. 1) stated, “there are
compelling reasons these conceptualizations of interpersonal
love should not be [. . .and . . .] cannot be applied directly to
brand love”. In fact, we showed in Point 1 above that we can
use interpersonal relationship theory to explain the love
relationship with brands, but Point 2 above also shows that
using parasocial relationship theories leads to higher
explanation power of the dependent variables studied. The
non-significance of the two hypotheses in Model I further
point out that parasocial relationship scale leads to superior
and stronger results. This brings us to the next discussion
point.
5 Despite the similarities of the results between the two
samples, there are also some differences. One explanation for
these differences could be cultural. Numerous studies
confirm cultural differences, as they relate to the orientation
toward love (Sprecher et al., 1994), their attitudes toward
love (Simmons et al., 2001) and their love relationships (Kim
and Hatfield, 2004) between people. However, the
interpersonal love relationship literature is not conclusive.
While the above studies show differences, there are also
studies showing there are no differences. For example, Cho
and Cross (1995) found American students’ beliefs about
love to be similar to those of Taiwanese students or Gao
(2001) shows with an American and Chinese samples that
there were no cultural differences between intimacy and
commitment. This all suggests that further studies should
investigate to what extend culture influences brand love
relationships and which relationship theory and underlying
scale is more suitable in one or the other culture.
6. Discussion and conclusion
This paper seeks to advance research about relationship
theories as applied to brands by discussing, testing and
comparing two different relationship theories and their
underlying scales as applied to loved brands. We used a 2 ⫻2
experimental design with two competing models based on
different love relationship theories (interpersonal versus
parasocial) and across two samples (USA versus Japan). We
Table II Summary model fit
United States Japan
Model I Model II Model I Model II Threshold
x
2
/df 1.89 2.46 1.95 1.88 ⱕ3.0
TLI 0.94 0.91 0.94 0.95 ⱖ0.9
CFI 0.96 0.94 0.96 0.97 ⱖ0.9
NFI 0.92 0.91 0.92 0.94 ⱖ0.9
IFI 0.96 0.94 0.96 0.97 ⱖ0.9
RMSEA 0.07 0.09 0.06 0.06 ⱕ0.09
What type of relationship we have with loved brands?
Marc Fetscherin
Journal of Consumer Marketing
Volume 31 · Number 6/7 · 2014 · 430 –440
434

offer an alternative perspective and theoretical explanation of
the relationship consumers have with their loved brands.
6.1 Theoretical contributions
From a theoretical point of view, this paper discusses and
presents an alternative relationship theory for testing brand love
relationships. Our results show that conceptualizing “brand love”
as a parasocial relationship leads to superior and stronger results
compared to interpersonal relationship. This suggests that the
brand love construct should be theorized and modeled as a
one-sided (parasocial) rather than a two-sided (interpersonal)
relationship, and using the parasocial love scale is more suitable
than using the interpersonal love attitude scale. For both
samples, we get stronger relationships between brand love and
purchase intention as well as positive WOM. We also get higher
explanation power for the both dependent variables when we
measured this relationship with the parasocial love scale.
6.2 Managerial implications
From a practitioner viewpoint, Harley-Davidson
®
,
Starbucks
®
and Apple
®
exemplify brands where consumers
have very strong emotional bonds with. Professionals try to
create emotional bonds with consumers such as by using the
concept of love in advertising (Batra et al., 2012), using the
word “love” in their slogans (e.g. McDonald’s I’m lovin’ it)or
using the symbol or word “love” in the brand name (e.g.,
; ). Roberts (2004, p. 57), the CEO of
Worldwide of Saatchi and Saatchi, argued in his Lovemarks
book, “I knew that love was the missing link, the only way to
strengthen the emotional and to create the new kinds of brand
relationship needed”. In that respect, for marketing and brand
managers, this study confirms the importance of the
consumer’s feeling of love for brands and validates previous
studies that brand love positive impacts brand loyalty,
purchase intention and WOM. This study specifically
contributions to the discussion about the appropriate
relationship theory and underlying scale to be used for the
study of brand love relationships. The study shows that using
the parasocial love scale leads to equally good and, in some
instance, even better results compared to the interpersonal
love attitude scale. Our findings are helpful for managers in
the research design of marketing research projects related to
brand relationships. We present managers with an alternative
and more suitable scale to measure brand love relationships.
The parasocial love scale seems also to provide more
consistent results across culture; also, this needs to be
validated with future studies.
6.3 Limitations and future research
Like any study, there are some limitations. First, surveying a
larger, more diverse pool of respondents would allow further
generalizability of the findings and could confirm the external
validity of our results. Nevertheless, the advantage of having
homogenous respondent samples is to test theoretical
hypotheses. Second, future studies should incorporate and
compare other interpersonal love scales as discussed in section
2.1 such as Rubin’s (1970) liking scale or Hatfield and
Sprecher’s (1986) passionate love scale, also Hendrick and
Hendrick’s (1986) love attitude scale is subject to multiple
validation studies related to brands as well as cross-cultural.
Third, our study assesses and compares two relationship
theories and their underlying measurement scale. In the case
of Model I (interpersonal relationship), we got some
differences between the US and Japanese sample. Future
research should assess whether these differences are due to
the methodology or due to culture. As Albert et al. (2008)
state, love and its expression are culturally grounded. By either
validating our results with non-student samples from the USA
and Japan, or extending our research beyond these two
samples, researchers could examine the brand love construct
among different cultures or sub-cultures (e.g.
African-American, Asian-American, Indian-American). In
that respect, this study is exploratory in nature. Fourth, other
models could be tested by incorporating other brand
relationship constructs such as brand experience (Brakus
et al., 2009) or brand meaning (Strizhakova et al., 2008). For
example, we know that personality and love are widely
associated (White et al., 2004) and future research could
investigate this. Fifth, future research could assess other
product categories. For example, most consumer brand
relationship studies focus on tangible products (Carroll and
Ahuvia, 2006), but more recent research investigates
consumer service brand relationships or consumer firm
relationships (Yim et al., 2008).
Notes
1 The Latin origin of the word “alternative” is “alternare”,
which means interchange. In that respect, we used the
Table III Summary results and hypotheses testing
United States Japan
Model I Model II Model I Model II
Summary results
Purchase intention (%)
R
2
⫽32
R
2
⫽53
R
2
⫽23
R
2
⫽62
Positive word of mouth (%)
R
2
⫽49
R
2
⫽50
R
2
⫽41
R
2
⫽60
Hypotheses testing
H1
. Brand Love ¡Brand Loyalty (ⴙ)0.49
ⴱⴱⴱ
0.51
ⴱⴱⴱ
0.52
ⴱⴱⴱ
0.31
ⴱⴱⴱ
H2
. Brand Love ¡Purchase Intention (ⴙ)⫺0.03 0.61
ⴱⴱⴱ
0.32
ⴱⴱⴱ
0.73
ⴱⴱⴱ
H3
. Brand Love ¡Word of mouth (ⴙ)0.09 0.32
ⴱⴱⴱ
0.41
ⴱⴱⴱ
0.60
ⴱⴱⴱ
H4
. Brand Loyalty ¡Purchase Intention (ⴙ)0.58
ⴱⴱⴱ
0.20
ⴱⴱ
0.23
ⴱⴱ
0.14
ⴱⴱ
H5
. Brand Loyalty ¡Word of mouth (ⴙ)0.65
ⴱⴱⴱ
0.49
ⴱⴱⴱ
0.33
ⴱⴱⴱ
0.34
ⴱⴱⴱ
Notes:
***
Significant at the 0.01 level;
**
significant at the 0.05 level;
ⴱ
significant at the 0.10 level
What type of relationship we have with loved brands?
Marc Fetscherin
Journal of Consumer Marketing
Volume 31 · Number 6/7 · 2014 · 430 –440
435

word “alternative” in this paper as we provide researchers
and managers a choice between two possibilities
(interpersonal relationship theory versus parasocial
relationship theory). They are different in their
conceptualization and their scale items
2 We used in this study principle component analysis as
for both samples, the Kolmogorov–Smirnov and Shapiro–
Wilk “test of normality” were significant.
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Appendix 1
Table AI Dimensionality of brand love construct
Author(s) Dimension(s)
Thomson
et al.
(2005) passion
connection
affection
Caroll and Ahuvia (2006) brand love (with 10 items)
Heinrich
et al.
(2008) commitment
Intimacy
Passion
Batra
et al.
(2008) perceived functional quality
self-related cognitions
positive affect
negative affect
satisfaction
attitude strength
loyalty
Albert
et al.
(2008) First order:
idealization
intimacy
pleasure
dream
memories
unicity
Second order:
passion
affection
Albert and Valette-Florence (2010) Affection
Passion
Batra
et al.
(2012) self-brand integration
passion-driven behaviors
positive emotional connection
long-term relationship
positive overall attitude valence
attitude valence
confidence
What type of relationship we have with loved brands?
Marc Fetscherin
Journal of Consumer Marketing
Volume 31 · Number 6/7 · 2014 · 430 –440
438

Appendix 2
Table AII Construct measurement
Dimensions Items Source
Interpersonal
love
When I think of this car brand, it is hard for me to say exactly when the
friendship
turned into love for this brand
In truth, the love I have for this car brand required friendship first
I expect to always be friends with this car brand
The love I have for the car brand is the best kind because it grew out of a long
friendship
The friendship with the car brand merged gradually into love over time
The love relationship is really a deep friendship, not a mysterious, mystical emotion
The love relationship is the most satisfying because it developed from a good
friendship
Hendrick and Hendrick
(1986);Lee (1977)
Parasocial
love
I feel sorry for this car brand when there is negative news
This car brand makes me feel comfortable, as if I’m with friends
I see this car brand as a natural, down-to-earth person
I’m looking forward to using this car brand
I miss seeing this car brand when it’s not available at a rent-a-car agency
This car brand seems to understand the kind of things I want
I find this car brand attractive
If there were a story about this car brand in a newspaper or magazine, I would read it
Perse and Rubin (1989)
Brand loyalty I am committed to this car brand
I pay more attention to this car brand than to other car brands
I am more interested in this particular car brand than in other car brands
a
It is very important for me to buy this car brand rather than another car brand
I always buy the same car brand because I really like it
Quester and Lim (2003)
Purchase
intention
I intend to buy this car brand
I plan to buy this car brand
Taking everything into account, what are the chances of you personally buying this car
brand in the next 5 years?
a
Juster (1966);Kumar
et al.
(2009)
WOM I have recommended this car brand to lots of people
I “talk up” this car brand to my friends
I try to spread the good word about this car brand
I give this car brand tons of positive word of mouth advertising
Carroll and Ahuvia (2006)
Note:
a
Item removed from confirmatory factor analysis (CFA) due to either low factor loads or high cross loadings
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Appendix 3
Appendix 4
Corresponding author
Marc Fetscherin can be contacted at: mfetscherin@
rollins.edu
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Table AIII Results confirmatory factor analysis
Item
United States Japan
1234512345
BLa1 0.746 0.841
BLb4 0.757 0.802
BLb5 0.829 0.799
IPL1 0.769 0.465
IPL2 0.771 0.799
IPL4 0.808 0.795
IPL5 0.847 0.741
IPL7 0.853 0.782
PAR4 0.605 0.738
PAR6 0.756 0.516
PAR7 0.809 0.614
WOM1 0.765 0.725
WOM2 0.842 0.808
WOM3 0.864 0.803
WOM4 0.790 0.742
PIa1 0.847 0.795
PIa2 0.854 0.766
Table AIV Reliability and validity results
Cronbach’alpha
Model I Model II SIC
AVE CR AVE CR IL PL BL PI WOM
US sample
Interpersonal love (IL) 0.89 0.64 0.83 0.05 0.09 0.03 0.08
Parasocial love (PL) 0.72 0.53 0.70 0.05 0.09 0.17 0.13
Brand loyalty (BL) 0.83 0.61 0.79 0.61 0.79 0.09 0.09 0.11 0.18
Purchase intention (PI) 0.93 0.72 0.90 0.72 0.90 0.03 0.17 0.11 0.25
Word of mouth (WOM) 0.91 0.67 0.86 0.67 0.86 0.08 0.13 0.18 0.25
Japan Sample
Interpersonal love (IL) 0.81 0.48 0.62 0.07 0.03 0.06 0.11
Parasocial love (PL) 0.75 0.40 0.51 0.07 0.06 0.05 0.07
Brand loyalty (BL) 0.84 0.66 0.85 0.66 0.85 0.03 0.06 0.21 0.21
Purchase intention (PI) 0.82 0.61 0.80 0.61 0.80 0.06 0.05 0.21 0.15
Word of mouth (WOM) 0.90 0.59 0.78 0.59 0.78 0.11 0.07 0.21 0.15
Notes: SIC calculation ⫽Kendall’s tau-b correlations coefficient in the square
What type of relationship we have with loved brands?
Marc Fetscherin
Journal of Consumer Marketing
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