does marketing support help brand extension

Asia Pacific Journal of Research Vol: I. Issue XXI, January 2015

ISSN: 2320-5504, E-ISSN-2347-4793

www.apjor.com 11

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.


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.


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.


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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.

does marketing support help brand extension

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