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 MuruganPh. D Scholar,Department of Management Studies,Anna University,Chennai - 600 025,Tamil Nadu,India.

Dr. Jayanth JacobAssistant 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

Constructs and items Descriptive statistics Loadingsa t-valueb

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)

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

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

Marketing support Consumer evaluation of BE

c = 0.329**

R2 = 0.11

Marketing support

Retailer’s acceptancePerceived 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 = a1b1H3 = Marketing support → Retailer’s acceptance → Consumer evaluation of BE = a2b2H4 = 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

Table 4 Direct effects

Effects on endogenous

variables

Direct effect

(Beta)

t-value

(bootstrap)

Decisio

n000000

Effect

size(f2)

Perceived fit

(R2 = 0.13/Q2 = 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/Q2 = 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; Q2 represent the cross validated redundancy; f2 = (R2

incl-R2excl) / (1-R2

incl).R2incl.; **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:

(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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