Dear Editors,
Date: 09-01-2015
We hereby submit the manuscript entitled “Does marketing support help brand extension
success? A three-path mediation model from Indian perspective.” by Nithya Murugan and
Jayanth Jacob to be considered for publication as an empirical research article in the Asia Pacific
Journal Research.
This study extends the existing literature on brand extension, suggesting categorization theory as
the theoretical framework to understand how marketing support can enhance success of brand
extension through indirect relationships. The implications, limitations and the scope for further
research are also discussed.
We believe these findings will be of interest to your readers.
We declare that this manuscript is original, has not been published before and is not currently
being considered for publication elsewhere.
We hope that the manuscript will be suitable for publication.
Sincerely,
Nithya Murugan
Ph. D Scholar,
Department of Management Studies,
Anna University,
Chennai - 600 025,
Tamil Nadu,
India.
Dr. Jayanth Jacob
Assistant Professor (Sr. grade)
Department of Management Studies,
Anna University,
Chennai - 600 025,
India.
TITLE: Does marketing support help brand extension success? A three-path mediation model
from Indian perspective
AUTHORS’ NAMES & DEPARTMENTS:
Nithya Murugan (Corresponding author),
Department of Management Studies,
Anna University,
Chennai 600 025,
Tamil Nadu,
India.
drnithya.phd@gmail.com
Dr Jayanth Jacob,
Department of Management Studies,
Anna University,
Chennai 600025,
Tamil Nadu,
India.
Nithya Murugan is a senior research fellow of Management Studies Department, Anna
University, India. Her background is B Tech, MBA and she has cleared National Eligibility Test
(NET) for lectureship conducted by University Grants Commission, India. Her research interests
include consumer behaviour, brand management and Asian perspective of consumer decision
making.
Jayanth Jacob is a full time faculty in the Department of Management Studies at Anna
University. He is a Mechanical Engineer with a Master degree in Business Administration and a
Doctorate in Management Sciences. He is a corporate trainer and conducts training programs for
executives, research scholars and management faculty on topics which include but not limited to
Model Building, Leadership, Motivation, Stress Management, Quality Management and
Statistical Analysis using SPSS. He has published research articles in peer reviewed and indexed
national and international journals and presented papers in regional, national and international
conferences.
Does marketing support help brand extension success? A three-path
mediation model from Indian perspective
Abstract
Even though many studies on the potential determinants of brand extension success have been
conducted, previous works have failed to study the indirect relationships between the drivers or
have proposed models with direct effect only. Ignoring potential indirect effects might lead to
over or underestimation of success factors and thus faulty managerial decisions. Our study
contributes to the growing literature by examining the indirect relationship between marketing
support, perceived fit and retailer’s acceptance, and their effect on consumer evaluation of brand
extension using real extensions. The current study proposes a multi mediating model and tests
the mediation. In particular, we posit that the perceived fit and retailer’s acceptance play a
mediating role in the marketing support to consumer evaluation of extension relationship. A
variance based structural equation modeling (Partial Least Squares) has been applied to a sample
of 425 Indian housewives. Our analysis lends support to the importance of marketing support
and their influence on extension success. Moreover, mediation hypothesis posit how perceived fit
and retailer’s acceptance play a critical mediating role in the marketing support – consumer
evaluation relationship. Analysis of the data suggest that the variables are interrelated in such a
way that the perceived fit and retailer’s acceptance: (a) fully mediate the effect of marketing
support on the consumer evaluation of brand extension (b) exert significant influence on the
consumer attitude and purchase intention of the extension product.
Keywords
Brand extension, mediation analysis, perceived fit, retailer’s acceptance, partial least squares
Introduction
Brand extension is the use of well known brand names for new product introductions (Aaker,
1990). In India more than 80% of the new products in the market are extensions (Thamaraiselvan
and Raja, 2008). Firms are increasingly turning to extension strategy because of the belief that
they would build and communicate strong brand positioning, enhance awareness and quality
associations (Patro and Jaiswal, 2003) and increase the probability of trial (Swaminathan et al.,
2001) by lessening the new product risk for consumers (Chowdhury, 2007). Successful
extensions not only provide a new source of revenue, but also positively impact choice of the
parent brand (Swaminathan, 2003). However, success of brand extension is uncertain;
approximately 50% extensions are reported as failures in Fast Moving Consumer Good (FMCG)
product categories (AC Nielson India 2012 report). The success or failure of brand extensions is
vastly dependent on how the customers evaluate the brand extensions (Klink and Smith, 2001).
Hence for the past 15 years, more than 50 researches on brand extension have shown a
substantial interest in identifying the conditions required for successful extensions (Völckner and
Sattler, 2007) to reduce the failure rates. Even though many studies have been conducted in this
context, as Völckner and Sattler (2006) claim, only direct relationships between the brand
extension success (dependent variable) and potential success factors have been tested
disregarding the fact that some success factors may constitute dependent variables in other
relationships.
Prior studies suggest that consumer acceptance of extension is greatly affected by the
perceived fit between the extension product and the parent brand (Broniarczyk and Alba, 1994,
Hem and Iversen, 2009, Keller and Aaker, 1992). The resulting managerial implication is that
brands should not be extended to perceptually distant categories. Yet, it is not difficult to find
brands that have been extended successfully into relatively distant categories (Tata steel and Tata
telecom services), also many extensions have failed in the market still perceptually close to the
parent brand. For example, Rasna is a famous soft drink company in India, but its extension
product Oranjolt fizzy fruit drink failed in the market.
The discrepancy between the research findings and real examples reveal that past
research has overstated the main effect of perceived fit and its relationship with other success
drivers that indirectly contribute to brand extension success have been mostly ignored. In
addition, previous studies have examined consumer attitude in controlled conditions using
hypothetical extensions (i.e. extensions not introduced in the market) and hence the external
validity of such studies have been questioned (Hem et al., 2003) The studies by the use of
fictitious extensions provide a single cue-brand name and extension product category for the
evaluation of stimulus (Klink and Smith, 2001). In a real marketplace situation, customers are
exposed to a lot of information about the extension product and consumer attitude is sensitive to
advertisements (Taylor and Bearden, 2003), retailer decisions (Collins-Dodd and Louviere,
1999) and competitor activity (Czellar, 2003). That is why advertisements and distribution
support plays a critical role in extensions success (Nijssen, 1999, Völckner and Sattler, 2006). In
a similar context, Reddy et al. (1994) argue extensions that have higher marketing support in
terms of advertising are more likely to be successful than extensions that have less support.
(Nijssen, 1999) discusses the power of the retailers (in terms of distribution) has greater
influence on the extension success. However, there has been limited research in this area.
Against this background, our paper seeks to fill a gap in the literature by taking a deeper
look at the structural (indirect) relationships among important success drivers: marketing
support, perceived fit and retailer’s acceptance on brand extension success through a multiple
mediation model. In particular, we posit that perceived fit and retailer’s acceptance play a
mediating role in the relationship between marketing support and consumer evaluation of brand
extension. Ignoring potential indirect effects might lead to over or underestimation of success
factors and thus faulty managerial decisions (Sattler et al., 2010). Thus the proposed model and
the use of real extensions as stimuli, may lead to a better understanding of direct and indirect
relationships of drivers on extension success, thus offering various managerial implications that
are helpful for launching brand extensions.
With these objectives in mind, this paper is organized as follows: We begin the review of
literature on marketing support, perceived fit and retailer’s acceptance as well as the impact of
each one on the consumer evaluation of brand extension. We propose a multiple mediating
model that shows the serial mediation among the success drivers. We then present our results
based on the analysis of data. This study concludes with a discussion of results, their
implications, the limitations of the study and suggested future research.
Theoretical background and hypothesis
Consumer attitude towards extension is conceptualized as the consumer’s perception of overall
quality of the extension product (Bottomley and Holden, 2001). Measuring consumer evaluation
(attitude) offers an important indicator to extension success (Czellar, 2003) because the attitude
based measure of extension success is positively related to purchasing behaviors (Ajzen and
Fishbein, 1980). In this study, purchase intention is also included as a measure of extension
evaluation (Bhat and Reddy, 2001) because it is an attitude based measure and it can be
interpreted as the conative component of attitude (Fazio, 1986). Therefore the study uses
consumer attitude and purchase intention as a measure to predict extension success since attitude
based measures generalize to economic success of brand extensions (Völckner and Sattler,
2007).
The brand extension research relies on categorization theory (Aaker and Keller, 1990,
Boush and Loken, 1991). According to this theory, when consumers are presented with a new
extension product, the evaluative task attempts to classify the object (extension product) within a
certain category i.e., the brand which offers the product (Fiske and Pavelchak, 1986). The
categorization facilitates the transfer of affect and beliefs associated with the category to the
product (Boush and Loken, 1991) leading to attitude formation towards the new product. This
transfer of positive associations is enhanced when there is greater similarity between the new
product and original brand category (Bottomley and Holden, 2001, Milberg et al., 1997). The
category brand name and the perceived fit act as the cues to stimulate the category based
processing. Based on this conceptual reasoning, the hypotheses are framed in this study. The
hypotheses vary in their level of detail depending on the extent of theoretical and empirical
evidence on the subject.
The relationship between marketing support and consumer evaluation of brand extension
Advertising effort is a signal to overall marketing support (Kirmani and Wright, 1989). Firms
that show high advertising efforts in terms of frequency and expenditure significantly influence
the consumer evaluation of extensions (Lane, 2000, Völckner and Sattler, 2006). The reason is
perceived advertising effort is interpreted as a sign of high product quality and consumers think
that the manufacturer is confident on the new product’s quality and hence the company has spent
a huge amount of money on advertising it (Kirmani, 1990). Also high frequency of advertising is
positively related to brand awareness and elicits brand related associations. This fosters greater
elaboration to make positive evaluation of extensions (Bridges et al., 2000, Lane, 2000).When
the quality of the product is not observable before trial and when repeat purchase is important,
firms use advertising as a cue to attitude formation and make them try the new product (Kirmani,
1997). Thus, higher marketing support in terms of advertising is expected to positively influence
consumer evaluation of brand extension.
H1: Marketing support has a positive effect on consumer evaluation of brand extension
The mediating role of perceived fit
In categorization research, typicality refers to the degree to which an object resembles a category
(Loken and Ward, 1990). When a product shares more attributes in common with the category,
the more typical is the product in that category. Research on typicality suggests that repeated
exposure to an extension may enhance the perception of fit (Klink and Smith, 2001). Greater
exposure to advertisements on extension helps the customers identify shared associations
between the extension product and the parent brand and thus enhances the similarity between
them (Lane, 2000, Milberg et al., 1997). To further explain in detail, higher frequency of
advertisements acts as an external stimulus and triggers the recall of parent brand attributes and
its association with the extension product, this activation of information improves the perceived
fit and leads to higher perceptions on the extension’s quality (Carter and Curry, 2013). Based on
these prevalent findings from previous studies, it is proposed that higher marketing support
positively relates to perceived fit, which in turn relates to positive evaluation of brand extension.
H2: The relationship between marketing support and consumer evaluation of brand
extension is mediated by perceived fit.
The mediating role of retailer’s acceptance
Particularly for new products, success with retailers is a necessary prerequisite for success with
the consumers, because retailers act as gatekeepers by selecting products and setting
merchandising policies (Messinger and Narasimhan, 1995). Collins-Dodd and Louviere (1999)
have found out that retailer’s acceptance decisions (in terms of distribution intensity) are
dominated by the manufacturer’s consumer advertising because it increases product awareness
and utility; thereby pre-sells the products and reduces retailer’s selling cost. They also warn
manufacturers that the success of extension does not depend on strong brands and advertising
efforts alone; instead retailer’s acceptance is even more important, else they will have problems
obtaining in-store listings. For frequently purchased products, mere distribution and shelf
visibility will generate awareness and product trial (Heeler, 1986). Völckner and Sattler (2006)
observed that strength of the relationship between marketing support and extension success
increased when retailer’s acceptance mediated the effect. Based on these propositions, it is
hypothesized that advertising effort increases the retailer’s acceptance of new extensions which
in turn leads to higher acceptance among consumers.
H3: The relationship between marketing support and consumer evaluation of brand
extension is
mediated by retailer’s acceptance.
Theory extension through serial mediation
As discussed above, both perceived fit and retailer’s acceptance are associated in the relationship
between marketing support and consumer evaluation of brand extensions. Surprisingly,
researches showing the interrelationship between these two factors are scant. Völckner and
Sattler (2006) substantiate the relationship between perceived fit and retailer’s acceptance as
retailers want to avoid poor assortments perception among consumers. Higher perceived fit
between extension and the parent brand symbolize closer association of the extension product
with the parent brand. A new extension product which is obviously affiliated with the parent
brand (in terms of similarity between extension product and parent brand) when not listed in the
store may create the perception of an incomplete assortment. Hence, high levels of fit lead to
higher retailer’s acceptance. The authors observed that the relative influence of marketing
support on the brand extension success increased from 9.35% to 22.51% when perceived fit and
retailer’s acceptance were included as mediators. However, the study has not explored the serial
mediation effect among the variables.
With the theory and empirical evidence mentioned above, it is hypothesized that
marketing support is related to consumer evaluation of brand extension through perceived fit first
and then retailer’s acceptance. Integrating the two models with mediation through perceived fit
and with mediation through retailer’s acceptance yields a three-path mediation model, depicted
in figure 1B (Hayes, 2009, Taylor et al., 2008). Whether perceived fit and retailer’s acceptance
serially mediate the relationships between marketing support and consumer evaluation of brand
extension is tested through the following hypothesis.
H4: The relationship between marketing support and consumer evaluation of brand
extension is sequentially mediated by perceived fit and retailer’s acceptance.
Methodology
Measurement
The operationalization of the proposed constructs was based on the existing scales from previous
brand extension studies. Consumer evaluation of brand extension was measured in terms of
attitude and intention to buy the extension product. Three items measuring overall attitude
towards the extension product (1 = dislike, 7 = like) from Broniarczyk and Alba (1994) were
used to measure attitude. Single item measured consumer’s intention to purchase the extension
product (1 = will certainly buy a competitor brand, 7 = will certainly buy the extension product)
assuming they had planned a purchase in the product category (Aaker and Keller, 1990).
To increase the robustness, all the independent variables were measured on two
dimensions. Perceived fit was measured as the fit between the parent brand and extension
product using two items, one from Park et al. (2002) and another from Barone et al. (2000).
Second dimension fit between the consumer and extension product using two items derived from
Hem and Iversen (2002). Retailer’s acceptance was measured in terms of perceived availability
using two items from Völckner and Sattler (2006) and distribution intensity using three items
from Smith and Park (1992). Völckner and Sattler (2006) two items for perceived advertising
intensity, Kirmani and Wright (1989) three items for perceived advertising spending were used
to measure the marketing support.
Data collection and analysis
Pretest was done to select the stimuli for the study (refer Table1). The study required real and
recent extension products from well known brands in the FMCG sector. Top 30 brands were
selected from the survey on most trusted brands in India, published in the Brand Equity column
of Economic Times on November 7, 2013. A convenience sample of 50 consumers, evaluated
the brands on familiarity, on a 7 point scale (1= not at all familiar to 7 = extremely familiar).
Based on the findings, 10 parent brands (3 food and 7 non-food categories) were chosen. The
parent brand helped in identifying new extension products launched in the market. Most recent
extensions were chosen for the parent brands with multiple extensions (according to AC Nielson,
India). The study identified 10 extension products, one for each brand.
Table 1 Parent brand and extension products
Parent Brand
Parent Brand’s Original Category
Extension Product’s Category
Aashirvaad
Aata
Sambar Powder
Cinthol
Bath Soap
Talcum Powder
Colgate
Tooth paste
Mouth Wash
Dettol
Antiseptic Lotion
Dish Wash Gel
Hamam
Bath Soap
Hand Sanitizer
Horlicks
Health Drink
Masala Oats
Lifebuoy
Bath Soap
Hand Sanitizer
Medimix
Bath Soap
Hand Wash
Sunfeast
Biscuits
Noodles
Surf Excel
Washing Powder
Liquid Detergent
A total of 517 housewives in Tamilnadu, the southern region of India participated in the
study. . A systematic sampling was used by approaching every fifth female purchaser coming out
of three chosen department stores. The sample was directed at female purchasers only, as in an
emerging economy like India women are the primary decision makers in the food and grocery
departments (The Nielson Company, 2011). They were first asked to read the brief information
about the extension product in the questionnaire, for example, ‘Horlicks is known for its health
drinks, the brand has recently introduced Horlicks masala oats in the market’. The questionnaire
for the current study had screening questions that checked the awareness and purchase interest of
the participants in the category, based on which valid responses were chosen. Out of 517
subjects, 22 were not aware of the product and 70 were not interested in purchase of the
category. So 92 responses were removed and the sample (n=425) contained consumers who were
aware and interested in the purchase of the extension product category. The total time for
completing the entire questionnaire was approximately 10 minutes.
Partial Least Square (PLS), a variance based Structural Equation Modeling technique was
used to estimate the research model using the software application Smart PLS 2.0 M3 version
(Ringle et al., 2005). PLS was deemed an appropriate tool for this study, because of the
following reasons (Roldán and Sánchez-Franco, 2012): (i) the study focuses on prediction of the
dependent variable through the role of critical success drivers (ii) incremental nature of the
research, which implies earlier models form the basis of the study, while the current model adds
new measures and structural paths (iii) the model is complex in terms of the number of
relationships. A PLS model is analyzed and interpreted in two phases: (1) the assessment of the
measurement model (outer model), and (2) the evaluation of the structural model (inner model).
Results
Demographic characteristics
The mean age of the respondents was calculated to be 36.24 years, their age ranged from 26 to
57 years. Undergraduates accounted for 43.76%, postgraduates (194 or 45.74%) and other
educational qualifications for about 10.58% of the entire sample. The number of household
members included, three members family (21.41%), four (52.47%) and more than four family
members (23.05%). In terms of decision making, 313 respondents were self-decision makers in
the family (73.65%), spouses were the decision makers (26.35%) in 112 families.
Measurement model
The evaluation of the measurement model examines its reliability and validity (Henseler et al.,
2009). Internal consistency reliability and construct validity were tested and presented as per the
guidelines of Straub et al. (2004). Construct reliability is assessed using Cronbach’s alpha and
composite reliability. For both indices, 0.7 is the cut-off value (Nunnally and Bernstein, 1994).
All the constructs used in this research are reliable (Table 3). Construct validity was examined
through convergent and discriminant validity. The estimation of standard loadings, Average
Variance Extracted (AVE) and composite reliability gauges convergent validity. Standard factor
loading lied within the range of 0.61 to 0.83 (Hair et al., 2010). AVE of each measure extracted
more than 50% of the variance (Bagozzi and Yi, 1988). The square roots of AVE were greater
than the correlation values across the row and column. Hence discriminant validity was
warranted according to Fornell and Larcker (1981) criterion.
Because these measures are self reported, the impact of common method bias was also
checked. Harman single factor test was conducted and it was found that the items did not
significantly load on to a single factor (Podsakoff et al., 2003); hence common method bias was
not a major concern in the analysis.
Table 2 Parameter estimates of measurement model
Loadingsa
t-valueb
MS1
0.78**
31.21
MS2
0.82**
30.01
MS3
0.70**
18.31
MS4
0.76**
29.90
MS5
0.65**
16.92
PF1
0.76**
20.00
PF2
0.75**
21.29
PF3
0.82**
37.21
PF4
0.79**
28.56
RA1
0.61**
13.37
RA2
0.71**
22.39
RA3
0.83**
25.39
RA4
0.81**
30.67
RA5
0.82**
37.01
CEB1
0.78**
28.58
CEB2
0.74**
22.91
CEB3
0.78**
29.83
CEB4
0.73**
19.06
Constructs and items
Marketing support
Perceived fit
Retailer’s acceptance
Consumer evaluation of BE
Descriptive statistics
Mean
SD
4.33
1.03
4.12
4.51
4.79
1.04
1.05
0.93
BE, Brand Extension; a Standardized loadings; b All t-values are highly significant(**p < 0.001)
Table 3 Construct reliability, convergent and discriminant validity of constructs
Variables
CR
α
AVE
1
1 Marketing support
0.86
0.80
0.56
0.75
2 Perceived fit
0.86
0.79
0.61
3 Retailer’s acceptance
0.87
0.81
0.58
4 Consumer evaluation of BE
0.84
0.75
0.58
2
0.36
0.78
3
4
0.36
0.42
0.61
0.38
0.76
0.33
0.76
CR, composite reliability; AVE, average variance extracted; Diagonal elements (in bold)
represents square root of AVE while off diagonals represent the correlation among the
constructs. For discriminant validity, diagonal elements should be larger than off diagonal
elements.
Structural model
To test the structural model, two types of relationships are required: the direct and the
indirect effect of Marketing Support (MS), Perceived Fit (PF) and Retailer’s Acceptance (RA) on
Consumer evaluation of Brand Extension (CBE). The structural path is evaluated from the
algebraic sign, magnitude and significance of the structural path coefficients, the R 2 values, the
Q2 test for predictive relevance and the effect size (f2). A non-parametric bootstrapping (5000
resamples) was used to generate standard errors and t-statistics (Henseler et al., 2009). From the
values, the statistical significance of the path coefficients was assessed. Results of the direct
effects described in Table 4 show that five of six direct effects are significant. The direct effect
of marketing support on consumer evaluation of brand extension (c’) is not significant, and
hence H1 is not supported. In addition, the research model has an appropriate predictive power
(R2) for all the dependent variables. The retailer’s acceptance attains the largest explained
variance (0.398) while the entire serial mediation model explains 24% of variance from its
antecedents and mediators. In PLS, R2 results of 0.20 are considered high in a discipline such as
consumer behavior (Hair et al., 2011). To examine the predictive relevance of the structural
model, the cross validated redundancy index (Q2) for endogenous constructs is assessed (Chin,
1998). The Q2 value can be obtained using the blindfolding procedure. Q2 > 0 implies that the
model has predictive relevance, whereas Q2 < 0 suggests lack of predictive relevance (Chin,
2010). The model has satisfactory predictive relevance for the three dependent variables:
perceived fit (Q2 = 0.07), perceived availability (Q2 = 0.21) and attitude towards extension
product (Q2 = 0.13). The effect size of the PLS model can be measured by means of Cohen’s f2
(Cohen, 1988). Effect size, f2 is computed based on the change in the predictive power (R2)
whether an independent latent variable has a substantial influence on the dependent latent
variable. Thus the change in the dependent variable’s predictive power is calculated by
estimating the structural model twice, that is one with and another without the independent
variable. Following the thumb rule by Chin (1998), f2 values of 0.02, 0.15 and 0.35 indicate
small, medium and large level of impact accordingly. Thus from Table 4 it can be concluded that
marketing support has a large influence on retailer’s acceptance (f2 = 0.44) and a medium
influence on perceived fit (f2 = 0.15).
According to our research model (Fig 1B), H2-H4 represent the mediation hypothesis,
which posit how, or by what means, an independent variable (MS) affects a dependent variable
(CBE) through mediating variables PF and RA (Preacher and Hayes, 2008). Fig.1A describes the
total effect of the marketing support on the consumer evaluation of brand extension without the
presence of mediators. The analytical approach described by Preacher and Hayes (2008) and
Taylor et al. (2008) was applied to test the mediation hypothesis (H2 – H4). The advantage of
this approach is that it is able to isolate the indirect effect of both mediating variables, that is,
perceived fit (H2: a1b1) and retailer’s acceptance (H3: a2b2). In addition, this approach allows the
analysis of indirect effects passing through both of these mediators in a series (H4: a1a3b2). The
results of indirect effects are specified in Table 5. Following Williams and MacKinnon (2008)
suggestions, bootstrapping procedure was used to test the indirect effects, because it does not
impose distributional assumptions and is a better alternative to Sobel test. (Chin, 2010) proposed
a two step procedure for testing mediation in PLS: (1) Use the model with both direct and
indirect paths and perform N bootstrap resampling and calculate the product of the direct path
that forms the indirect path estimate (2) Assess the significance using percentile bootstrap
(Williams and MacKinnon, 2008). This generates 95% confidence interval for mediators:
perceived fit (H2), retailer’s support (H3), perceived fit and retailer’s acceptance (H4). When the
interval for the entire mediation hypothesis does not contain zero, then the indirect effects are
significantly different from zero with 95% confidence. The results show all the indirect effects
listed in Table 5 are significant.
The total (c) and the direct (c’) effects of independent variable (MS) on dependent
variable (CBE) were also examined. Marketing support has a significant total effect on consumer
evaluation of brand extension as shown in Fig. 1A. When mediators are introduced (see Fig 1B),
MS no longer has effect on CBE (H1: c’). This means perceived fit and retailer’s acceptance
fully mediate the influence of marketing support on consumer evaluation of brand extension
(Baron and Kenny, 1986). As previously mentioned, H1 is not supported. However, support is
found for H2 –H4, the three indirect effects of MS on CBE are significant. The analyses show
that perceived fit mediates the relationship between Marketing Support and consumer evaluation
of brand extension (H2: a2b2). The results also show that retailer’s acceptance mediates the path
between MS and CBE (H3: a2b2). Finally, the marketing support is positively associated with
higher fit and retailer’s acceptance which relates to higher level of consumer evaluation of brand
extension (H3: a1a3b2).
Figure 1 Structural model: three-path mediation model
A. Model with total effect
R2 = 0.11
Marketing
support
Consumer
evaluation of BE
c = 0.329**
B. Model with a three-path mediated effect
R2 = 0.13
Perceived fit
R2 = 0.40
Retailer’s
acceptance
a3 = 0.16**
a1 = 0.36**
b2 = 0.22**
a2 = 0.55**
b1 = 0.31**
Marketing
support
R2 = 0.24
Consumer
evaluation of BE
c’ = 0.08ns
BE, brand extension; **p < 0.00; ns not significant.
H1 = Marketing support → Consumer evaluation of BE = c’
H2 = Marketing support → Perceived fit → Consumer evaluation of BE = a1b1
H3 = Marketing support → Retailer’s acceptance → Consumer evaluation of BE = a2b2
H4 = Marketing support → Perceived fit → Retailer’s acceptance → Consumer evaluation of BE = a1a3b2
Table 4 Direct effects
Effects on endogenous
Direct effect
t-value
variables
(Beta)
(bootstrap)
0.36**
9.01
Decision000000 Effect
size(f2)
Perceived fit
(R2 = 0.13/Q2 = 0.07)
Marketing support (a1)
Supported
0.15
(medium)
Retailer’s acceptance
(R2 = 0.40/Q2 = 0.21)
Marketing support (a2)
0.55**
13.82
Supported
0.44 (large)
Perceived fit (a3)
0.16**
3.49
Supported
0.04 (small)
0.08ns
1.37
Not supported
0.003
Consumer evaluation
(R2 = 0.24/Q2 = 0.13)
H1: Marketing support
(c’)
(none)
Perceived fit (b1)
0.31**
5.84
Supported
0.11 (small)
Retailer’s acceptance
0.22**
3.88
Supported
0.04 (small)
(b2)
Beta, regression weight for the direct effect; t-value are computed through bootstrapping
procedure with 425 cases and 5000 samples; R2, predictive power of the dependent latent
variable; Q2 represent the cross validated redundancy; f2 = (R2incl-R2excl) / (1-R2incl).R2incl.;
**p < 0.001; ns not significant.
Table 5 Mediation effects
Total effect of
Direct effect of MS on
MS on CBE (c)
CBE …..
Beta
…………….
Beta
t value
Indirect effect of MS on CBE
t
Point
Percentile bootstrap
value
estimate
95% confidence
interval
0.33**
7.55
H1 = c’
0.08ns
1.37
H2 = a1b1 0.112
Lower
Upper
0.082
0.179
0.068
0.202
0.005
0.026
(via PF)
H2 = a2b2 0.121
(via RA)
H3 =
0.013
a1a3b2
(via PF +
RA)
MS, Marketing Support; PF, Perceived Fit; RA, Retailer’s Acceptance; CBE, Consumer
evaluation of Brand Extension; indirect effects were tested using the bootstrap procedure with
5000 samples; ***p < 0.001; ns not significant.
Discussion
The present study contributes to the extant of brand extension literature by testing the
sequential mediation effect of perceived fit and retailer’s acceptance on the relationship between
marketing support and consumer evaluation of brand extension. When the total effect model is
considered, the results indicate that greater exposure to advertisements led to greater acceptance
of extension products among customers. However the importance of the direct effect of the
marketing support decreases considerably in favor of perceived fit and retailer’s support when
the full model is analyzed. Though not direct, the hypotheses test clarifies its contribution is high
in three indirect ways:
(1) Perceived marketing support in terms of advertising increases the salience of crucial brand
associations and helps the customers understand how the extension fits with the brand. The
results show marketing support leads to positive evaluation of extensions by indirectly enhancing
the perceived similarity to the parent brand (Park et al., 1991, Pryor and Brodie, 1998).
(2) Mere distribution and product availability in the store leads to trial and repeat purchase of the
extension product which is a result of retailer’s acceptance. Repetitive advertising increases the
retailer’s acceptance for the new extension product because it creates awareness and demand for
the product among consumers (Collins-Dodd and Louviere, 1999).
(3) Frequent exposure to advertising reminds the parent brand associations and its consistency
with the extension product thus improves the extension fit with the parent brand. Non availability
of an extension product which is closely associated with the parent brand may signal poor
assortments in the store. To maintain the store selection and to prevent the customers from
delaying the purchase or going to another store if the product was unavailable, retailers increase
the listing of extension products. The availability of extension product in a large number of
stores enhances the product’s image and improves the consumer evaluation of the brand
extensions. Therefore, marketing support improves the perception of fit which increases the
retailer’s acceptance of the extensions which in turn indirectly affect the success of brand
extension in the market. From the results, it is evident that, perceived fit and retailer’s acceptance
completely mediate the relationship between marketing support and consumer evaluation of
extensions.
In terms of managerial contribution, marketing support is important for the success of the
extension product in the FMCG sector. Managers show a great interest on this factor because it is
under the direct control of the company. The general belief about brand extensions is that they
require lesser advertisements and promotions as they come from strong parents. Our model
might help managers understand the importance of marketing support (in terms of advertising
frequency and expenditure) and how Indian consumers evaluate the brand extensions. The
advertisements can be used as a tool to improve the similarity perceptions of a moderate fit
extension. For example, advertisements can illustrate how the parent brand attributes improve the
extension’s ability to provide core benefits. Certainly, in such situations, Eastern consumers
(specifically Indians) may perceive higher brand extension fit and evaluate the extensions more
favorably as they are holistic thinkers (Monga and John, 2007). Added to this, our results on
effect size reveals when an extension product is well supported in terms of advertising, it can
strengthen the distribution channel besides creating demand for the product. Brand extension
strategy can be used more successfully in India, provided the power of advertising is utilized
appropriately in enhancing the fit and retailer’s acceptance of the extensions.
In terms of its limitations, the current study focuses solely on FMCG sector. Future
research might investigate the generalizability of the findings across various sectors (consumer
durables or services). Further research could extend the model by exploring possible structural
relationships among other important success drivers of extensions which can improve the
predictive power of the model. Our respondents are from a single country (India) and may raise
the question of generalizability of our results to other countries. Additional studies can
investigate the impact of culture on the consumer evaluation of extensions.
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