does marketing support help brand extension
TRANSCRIPT
Asia Pacific Journal of Research Vol: I. Issue XXI, January 2015
ISSN: 2320-5504, E-ISSN-2347-4793
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DOES MARKETING SUPPORT HELP BRAND EXTENSION SUCCESS? A THREE-PATH
MEDIATION MODEL FROM INDIAN PERSPECTIVE
Nithya Murugan,
Department of Management Studies,
Anna University,, Chennai 600 025,
Tamil Nadu,India.
Dr Jayanth Jacob,
Department of Management Studies,
Anna University,Chennai 600025,
Tamil Nadu,India.
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
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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
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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,
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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
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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.
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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.
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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
Constructs and items Descriptive statistics Loadingsa t-value
b
Mean SD
Marketing support 4.33 1.03
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
Perceived fit 4.12 1.04
PF1 0.76** 20.00
PF2 0.75** 21.29
PF3 0.82** 37.21
PF4 0.79** 28.56
Retailer’s acceptance 4.51 1.05
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
Consumer evaluation of BE 4.79 0.93
CEB1 0.78** 28.58
CEB2 0.74** 22.91
CEB3 0.78** 29.83
CEB4 0.73** 19.06
BE, Brand Extension; a Standardized loadings;
b All t-values are highly significant(**p < 0.001)
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Table 3 Construct reliability, convergent and discriminant validity of constructs
Variables CR α AVE 1 2 3 4
1 Marketing support 0.86 0.80 0.56 0.75 0.36 0.36 0.42
2 Perceived fit 0.86 0.79 0.61 0.78 0.61 0.38
3 Retailer’s acceptance 0.87 0.81 0.58 0.76 0.33
4 Consumer evaluation of BE 0.84 0.75 0.58 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 R2 values, the Q
2 test for predictive relevance and the effect size (f
2). 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, f
2 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
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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).
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Figure 1 Structural model: three-path mediation model
Marketing
support
Consumer
evaluation of BE c = 0.329**
R2 = 0.11
Marketing support
Retailer’s
acceptance
Perceived fit
Consumer
evaluation of BE
a1 = 0.36**
c’ = 0.08ns
a3 = 0.16**
a2 = 0.55**
b1 = 0.31**
b2 = 0.22**
R2 = 0.13 R2 = 0.40
R2 = 0.24
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
A. Model with total effect
B. Model with a three-path mediated effect
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Table 4 Direct effects
Effects on endogenous
variables
Direct effect
(Beta)
t-value (bootstrap) Decision000000 Effect size(f2)
Perceived fit
(R2 = 0.13/Q
2 = 0.07)
Marketing support (a1) 0.36** 9.01 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)
Consumer evaluation
(R2 = 0.24/Q
2 = 0.13)
H1: Marketing support (c’) 0.08ns
1.37 Not supported 0.003 (none)
Perceived fit (b1) 0.31** 5.84 Supported 0.11 (small)
Retailer’s acceptance (b2) 0.22** 3.88 Supported 0.04 (small)
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; Q
2 represent the cross
validated redundancy; f2 = (R
2incl-R
2excl) / (1-R
2incl).R
2incl.; **p < 0.001;
ns not significant.
Table 5 Mediation effects
Total effect of MS
on CBE (c)
Direct effect of MS on
CBE …..
Indirect effect of MS on CBE
Beta t value ……………. Beta t
value
Point
estimate
Percentile bootstrap 95%
confidence interval
Lower Upper
0.33** 7.55 H1 = c’ 0.08ns
1.37 H2 = a1b1
(via PF)
0.112 0.082 0.179
H2 = a2b2
(via RA)
0.121 0.068 0.202
H3 = a1a3b2
(via PF +
RA)
0.013 0.005 0.026
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:
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(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.
Asia Pacific Journal of Research Vol: I. Issue XXI, January 2015
ISSN: 2320-5504, E-ISSN-2347-4793
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Authors:
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.