Consumer evaluation of brand extensions: can online brands be extended to offline products?

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MSc in INTERNATIONAL BUSINESS WITH MARKETING

2011

CONSUMER EVALUATIONS OF BRAND

EXTENSIONS: CAN ONLINE BRANDS BE EXTENDED

TO OFFLINE MARKETS?

By

ANTONIO MARTINEZ

H00023227

Presented for the award of MSc.

Heriot-Watt University

Can online brand be extended to offline products?

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ACKNOWLEDGEMNENT

I would like to thank my parents for their continual support throughout my

undergraduate and postgraduate years of study.

To my supervisor, Steve Clode, thank you for allowing me to learn from my own

mistakes, and for encouraging me to explore. Your faultless guidance and unwavering

trust will remain a standard of comparison for me in my future academic endeavours.

To Ana Martinez, for being there, and for providing an ever-sympathetic ear to my

grievances. Thank you for your succor and faith.

To my friend, Claudio Rider, without whom these academic year would have been

considerably less enriching. I also thank Dolores Rider for her assistance in providing

grammatical proof reading.

Lastly, I offer my regards and blessings to all of those who supported me in any

respect during the completion of the dissertation.

Declaration

I declare that the thesis embodies the results of my own work and has been

composed by myself and meets the University policies on plagiarism and ethical

research. Where appropriate within the thesis I have made full acknowledgement to

the work and ideas of others or have made reference to work carried out in

collaboration with other persons.

Signature of student ………………………… Date: …………….

Word count: 14,989

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ABSTRACT

Increasing competence within the marketplace has provoked that firms seek to

go beyond the boundaries of their actual businesses by offering products in totally

new markets. Companies attempt to reduce the risk associated with launching these

new products by using an existing brand name, which allows the companies to

leverage brand equity in the new product categories. Brand extension has become a

popular strategy not only within the limits of offline markets but, also in an online

context to the extent that numerous offline companies have extended their brands to

online markets. Nevertheless, a recent trend shows that the reverse is also possible,

and Internet brands can also benefit from entering in new offline product categories.

This study examines whether online brands can be successfully extended to offline

product categories from a consumer perspective. Specifically, this study develops an

explanatory model of consumer evaluation of brand extensions which combines

variables previously studied in the literature with other extracted from online branding

and applies them to the research context. Empirical survey data are analysed through a

regression analysis applied to different online brands and their offline extensions to

identify the most important factors influencing consumers´ attitude toward the brand

extensions. The main results indicate that the attitude towards the offline extensions

launched by online companies is determined by the degree of product similarity, the

transference of emotional associations with the parent brand to the new product, the

marketing support received by the extension and the extent to which the consumers

are involved with the new product category. As consequence of these findings, the

success of online brands going offline will depend on the capability of managers to

build a strong and positive brand personality and organisational relationships with

consumers as well as implementing marketing activities which reinforce product

similarity perceptions and foster consumer involvement with the brand extension.

Keywords: Brand extensions, Brand equity, Brand associations, Brand knowledge,

Brand loyalty, Brand image, online companies, perceived quality, similarity,

consumer innovativeness, consumer involvement.

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TABLE OF CONTENTS

ACKNOWLEDGEMNENT ...................................................................................................................... I

ABSTRACT .......................................................................................................................................... II

LIST OF FIGURES ................................................................................................................................ VI

LIST OF TABLES .................................................................................................................................. VI

CHAPTER 1.INTRODUCTION ...................................................................................................... 1

1.1 BACKGROUND..................................................................................................................................... 1

1.2 PROBLEM STATEMENT. ......................................................................................................................... 3

1.3 CONTRIBUTIONS .................................................................................................................................. 4

1.3.1 Theoretical Contributions ........................................................................................................ 4

1.3.2 Practical Contributions ............................................................................................................ 5

1.4 THESIS OUTLINE .................................................................................................................................. 5

CHAPTER 2.BRAND EXTENSIONS ............................................................................................. 6

2.1 INTRODUCTION ................................................................................................................................... 6

2.2 CONCEPTUALISATION. .......................................................................................................................... 6

2.3 PSYCHOLOGICAL PROCESSES INVOLVED IN BRAND EXTENSION EVALUATIONS .................................................. 9

2.4 CONSUMER EVALUATIONS OF BRAND EXTENSIONS .................................................................................. 10

2.4.1 Similarity ............................................................................................................................... 12

2.4.2 Characteristics of the parent brand ...................................................................................... 13

2.4.3 The extension´s marketing context ....................................................................................... 14

2.4.4 Consumer characteristics ...................................................................................................... 14

2.4.5 Limitations of the current research on brand extensions ...................................................... 15

2.5 BRAND EXTENSIONS OF ONLINE BRANDS ............................................................................................... 16

2.6 SUMMARY ....................................................................................................................................... 18

CHAPTER 3. HYPOTHESES........................................................................................................ 20

3.1 INTRODUCTION ................................................................................................................................. 20

3.2 BRAND EQUITY VARIABLES................................................................................................................... 20

3.2.1 Brand knowledge .................................................................................................................. 22

3.2.2 Perceived Quality .................................................................................................................. 23

3.2.3 Brand Associations. ............................................................................................................... 24

3.2.4 Brand Loyalty ........................................................................................................................ 27

3.3 MARKETING SUPPORT ........................................................................................................................ 28

3.4 PERCEIVED SIMILARITY ........................................................................................................................ 29

3.4.1 Product category similarity ................................................................................................... 29

3.4.2 Brand image Similarity .......................................................................................................... 30

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3.5 INVOLVEMENT IN THE EXTENSION PRODUCT CATEGORY ............................................................................. 31

3.6 CONSUMER INNOVATIVENESS .............................................................................................................. 32

3.7 THE HYPOTHESIZED MODEL ................................................................................................................ 34

3.8 SUMMARY ....................................................................................................................................... 35

CHAPTER 4. METHODOLOGY .................................................................................................. 36

4.1 INTRODUCTION ................................................................................................................................. 36

4.2 RESEARCH PHILOSOPHY ...................................................................................................................... 36

4.3 RESEARCH DESIGN ............................................................................................................................. 37

4.3.1 Research strategy ................................................................................................................. 38

4.3.1 Time horizon ......................................................................................................................... 39

4.4 SURVEY DEVELOPMENT ...................................................................................................................... 39

4.4.1 Selection of brands and extensions ....................................................................................... 40

4.4.2 Scaling and multi-item scales ................................................................................................ 41

4.5 SAMPLING........................................................................................................................................ 46

CHAPTER 5. DISCUSSION .......................................................................................................... 48

5.1 INTRODUCTION ................................................................................................................................. 48

5.2 RELIABILITY AND CORRELATION ANALYSES. ............................................................................................. 48

5.2.1 Reliability analysis ................................................................................................................. 48

5.2.2 Correlation analysis............................................................................................................... 49

5.3 REGRESSION ANALYSIS ........................................................................................................................ 50

5.4 HYPOTHESES TESTING ........................................................................................................................ 53

5.5 DISCUSSION ..................................................................................................................................... 55

5.6 SUMMARY ....................................................................................................................................... 57

CHAPTER 7. CONCLUSION ........................................................................................................ 59

7.1 CONCLUSION .................................................................................................................................... 59

7.2 IMPLICATIONS ................................................................................................................................... 59

7.2.1 Theoretical Implications ........................................................................................................ 59

7.2.2 Managerial Implications ....................................................................................................... 60

7.3 LIMITATIONS AND DIRECTIONS FOR FURTHER RESEARCH ........................................................................... 61

REFERENCES ..................................................................................................................................... 63

APPENDIX ........................................................................................................................................ 78

APPENDIX A – SPSS DATA ...................................................................................................................... 78

Appendix A.1: Reliability Analysis .................................................................................................. 78

Appendix A.2: Correlation analysis ................................................................................................ 80

Appendix A.3: Regression analysis ................................................................................................. 82

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APPENDIX B - QUESTIONNAIRES ........................................................................................................... 90

QUESTIONNAIRE 1: GOOGLE.......................................................................................................... 91

QUESTIONNAIRE 2: AMAZON ........................................................................................................ 95

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LIST OF FIGURES

FIGURE 2.1: TAUBER´S GROWTH MATRIX ......................................................................................................... 7

FIGURE 2.2: E-SERVICE PORTALS GRID ........................................................................................................... 17

FIGURE 3.1: HYPOTHESIZED MODEL .............................................................................................................. 35

LIST OF TABLES

TABLE 2.1: MAIN FACTORS OF BRAND EXTENSION EVALUATION ......................................................................... 11

TABLE 3.1: HYPOTHESES ............................................................................................................................. 33

TABLE 4.1: OVERVIEW OF ONLINE BRANDS AND OFFLINE EXTENSIONS .................................................................. 41

TABLE 4.2: SCALES USED IN THE QUESTIONNAIRES ............................................................................................ 44

TABLE 5.1: CRONBACH´S ALPHA COEFFICIENTS FOR MULTI-ITEMS CONSTRUCTS .................................................... 49

TABLE 5.2: CORRELATIONS .......................................................................................................................... 50

TABLE 5.3: REGRESSION I (AGGREGATED COMPONENTS OF SIMILARITY) ............................................................... 51

TABLE 5.4: REGRESSION II (SEPARATED COMPONENTS OF SIMILARITY) ................................................................. 52

TABLE 5.5: REGRESSION ANALYSIS BY TYPE OF COMPANY .................................................................................. 53

TABLE 5.6: REVIEW ON HYPOTHESES ............................................................................................................. 58

Can online brand be extended to offline products?

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CHAPTER 1.INTRODUCTION

1.1 Background.

Increasingly competitive forces in the global markets are forcing companies to

differentiate themselves from competitors in order to survive and take advantage of

the current opportunities of growth. One way to differentiate from competitors is the

establishment of strong brands that allow companies to increase the efficiency of their

marketing expenses (Keller, 1993) achieving thus benefits to the company such as a

more favourable perception of the products by the customers, greater loyalty, less

vulnerability to competitors´ marketing actions, high profits margins, less negative

reactions by consumers to price increases, higher support of middlemen, higher

marketing promotion effectiveness, increasing licensing and brand extensions

opportunities (Keller, 2008). In other words, while competitors can emulate financial

and physical assets, intangible assets, as brands, represent a more sustainable

competitive advantage (Hunt and Morgan 1995). The importance of brands is not only

measured in terms of the competitive advantages that they provide in their present

markets but also the future opportunities that they provide in untapped markets

(Srivastava and Shocker, 1991). This way, firms can enter new markets by using an

existing, well-known brand name in order to reduce both the cost of launching new

products and the risk of product failure. The strategy behind the leverage of the

company brand equity to new markets, products or sectors is known as brand

extension.

The acceptance of brand extension is principally due to the benefits that both

brand and extension provide (Keller, 2003). On the one hand, the product

commercialised under a well-known brand is more attractive to the consumers (Aaker

and Keller 1990) and suppliers, thus reducing the marketing costs and increasing the

chance of success (Morrin, 1999). On the other hand, brand extensions reinforce

brand image and notoriety, which make consumers purchase other products offered by

the brand (Chen and Liu, 2004). All this allows an increase of the market share and

efficiency of market efforts (Smith and Park, 1992). In other words, extensions benefit

the companies because they transfer intangible components of the brand such as brand

awareness, trust or other specific brand associations (Broniarczyk and Alba, 1994)

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stored in the consumers´ minds to the new products. For example, National

Geographic has been able to extend successfully its brand by transferring associations

of nature, adventure and multiculturalism from photography and documentaries to

travel products, furniture or outdoors clothing (shop.nationalgeographic.com).

Despite the positive effects of brand extensions, their inappropriate use may

harm the company´s brand image if the new products do not fit with the consumers´

brand associations. This does not mean that a high degree of similarity between the

parent brand product category and the new product has to be present; in fact, some

companies have stretched their brands to very dissimilar product classes. For instance,

Louis Vuitton successfully extended to luxury resorts although it is a different

business from fashion (Passariello, 2010).

The use of brand extensions as a strategy to achieve growth has drastically

increased in recent years. In fact, between 80 and 90% of new products are launched

under the name of an existing brand (Völckner and Sattler, 2004). This recent

proliferation of brand extensions has contributed to change market structures in many

sectors. For example, in the financial services sector the entry of new competitors

from the retailing sector (e.g., Tesco or Sainsbury´s) has intensified the competence

and divided even more the market among participants. On the other hand, extensions

have also gone through the borders of the offline markets to markets from the online

domain. Consequently, companies have stretched their brands within and towards the

online markets. Traditionally based offline companies, in addition to use the internet

as an alternative distribution channel (Levin et al. 2003) or mean of running

communication campaigns (Srisuwan and Barnes, 2008), have considered the online

domain as a valuable market to commercialise both their current products or services

and their extensions. For instance, Apple sells mobile applications and music on the

internet through its iTunes shop (Bravo et al., 2010). For offline brands, the expansion

into the online market increases the brand value for consumers by providing

additional availability and exposure through the internet (Rubinstein and Griffiths,

2001).

On the other hand, some online businesses, such as Google, Amazon, Yahoo

and eBay, have extended their brands within the Internet limits, becoming some of the

top 100 global brands according to the Interbrand report (Interbrand, 2010). Amazon,

for instance, started to sell electronic goods and music online in addition to books.It is

also possible to extend online brands to offline markets. Following this trend, Google

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has launched a new mobile phone which uses Google´s mobile operation system,

Android. Besides, Amazon has extended its name to a new device, Amazon Kindle,

which enables consumers to read eBooks, newspapers and magazines through an

Internet connection. Therefore, offline markets enable Internet brands to enhance

brand awareness by making them more tangible for consumers, which may create

stronger trust and consequently higher brand loyalty (Yoo and Donthu, 2001; Delgado

and Hernández, 2008). Furthermore, the adaptation of online brands´ competences

(communication, customer service, IT) to the commercialisation of offline products

and the absence of some of the costs originally attributed to brick and mortar

companies such as, costs linked to the establishment of stores, turn offline product

into attractive markets where online brands can be extended. Hence, it would be

interesting to investigate how online brands can leverage brand equity to new offline

products.

1.2 Problem Statement.

Customer evaluation of brand extensions plays a vital role in the success or

fail of new products launched into the markets (Klink and Smith, 2001). Numerous

academic studies have contributed to determinate the factors that shape customer

attitudes towards the extension. However, there is a lack of agreement regarding the

validity of these factors across sectors, brands and product categories. This study

investigates the applicability of the aforementioned factors in the context of online

brands that launch their products into offline markets. In other words, the study

attempts to answer the following statement:

Can online brands be extended to offline products?

Additionally, the purpose of this research is to: (1) determine the feasibility of

factors proposed by previous research within the context of online brands, (2) assess

the significance of the variables within the brand equity construct (Aaker, 1996) in

predicting consumer attitude towards extensions, (3) examine whether antecedents

from brand extension theory can be combined with those related to online brand

management in order to build a valid model to predict consumer acceptance of brand

extensions in the research context; and (4) establish managerial recommendations

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based on the research´s findings that may help online brand managers to develop

strategies oriented to enhance the acceptance of brand extensions.

1.3 Contributions

1.3.1 Theoretical Contributions

Extensive research on brand extension has added a considerable number of

potential determinants of brand extension success without achieving generally

accepted conclusions (Czellar, 2003; Völckner and Sattler, 2007). Indeed,

approximately 15 explicative factors of brand extension success have been found to

be significantly relevant in at least one empirical study (Völckner and Sattler, 2006).

However, the majority of these studies are focused on a limited number of variables

and they do not consider possible relationships among determinants (Buil et al.,

2008b).

The current study includes the determinants that have been mostly accepted by

scholars within a unique model with the objective of assessing the validity of these

factors when they are applied to a different scope (online brands). In other words, the

study will examine whether current research is extra-sectoral and thus, brand equity

can be leveraged beyond the online limits towards offline products.

Besides the above mentioned replication, the study contributes to the existing

theory on brand extension by measuring the similarities between the parent brand and

the extension as a multidimensional construct. Along with the product category

dimension suggested by Aaker and Keller, (1990), the proposed model includes the

perceive similarity between the new extension and brand image (Park et al., 1991).

On the other hand, an additional contribution of this study is the incorporation

of brand equity variables such as brand loyalty (Yoo and Donthu, 2001), brand

knowledge (Dawar, 1996) and brand associations (Aaker, 1996) as determinants

factors of the success of brand extensions. Specially, brand associations are

introduced within the model according to the differentiation made by Aaker, (1996)

who distinguished three types of associations: brand-as-product (value associations),

brand-as-person (brand personality) and brand-as-organisation (organisational

associations).

This study also contributes to extend the current research on online brand

extensions (van Riel and Ouwersloot, 2005) by incorporating new factors, relative to

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consumer characteristics such as innovativeness and involvement with the extension,

to the explanatory model of brand extension evaluations.

Finally, the theoretical findings of this study contribute and complement the

current understanding within the online branding theory.

1.3.2 Practical Contributions

This study may help managers identify and monitor the factors that stimulate

the acceptance of offline products launched under online brand names as well as to

detect harmful factors to the parent brand image. Moreover, the findings of this

research may determine whether the explicative factors affect in the same manner to

different kinds of online brands which have a virtual origin (e-portals and e-tailers)

and thus, brand extension strategies for each of these types of online brands should be

adapted accordingly.

1.4 Thesis Outline

The thesis is structured as follows: the first part reviews the existing literature

on brand extension concepts and antecedents as well as the studies that have

considered brand extensions in the context of online brands. Thereafter, the second

part introduces a conceptual framework and, establishes a set of hypotheses based on

the theories provided in the preceding chapters and presents the hypothesized

theoretical model applied to online companies. This is followed by a research design

section where the applied methodology is described. The third part presents the

research findings, where the proposed hypotheses and model are tested by analysing

and interpreting the empirical data. Finally, the last section is related to the

conclusions and provides a summary of the main findings, obtained conclusions,

theoretical and managerial implications, as well as, limitations and directions for

future research.

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CHAPTER 2.BRAND EXTENSIONS

2.1 Introduction

Brand extensions represent an important growth strategy for companies facing

a fierce competence within the marketplace. The use of an already existing brand

when launching new products into the market increases the likelihood of success

because consumers perceive a lower risk in their purchasing process (Montgomery

and Wernerfelt, 1992) and transfer positive consumer associations to the new product

(Aaker and Keller, 1990). Therefore, the way in which consumers evaluate the new

extensions and the determinants involved in this process will determine the success or

fail of brand extensions and, consequently, the image of the parent brand may be

reinforced or harmed (Keller, 2003)

In order to investigate how consumers evaluate brand extensions, scholars

have proposed numerous explicative factors of consumers´ attitude towards the new

products and they have applied them to different types of products, companies and

markets. Following this idea, this chapter reviews the existing literature regarding

consumer evaluation of brand extensions. The chapter begins with a conceptualisation

of the different strategies in which a company can make use of its band in order to

launch new products. Afterwards, the psychological processes involved in consumers´

evaluations of new products are described. Thirdly, a review of the main explicative

factors of brand extensions evaluation is provided along with the limitations on brand

extension research. Finally, the chapter concludes with a review of the studies that

have been applied to the context of online companies in which this research work

takes place.

2.2 Conceptualisation.

Intense competition forces companies to adopt strategies that allow them to

remain in the market while taking advantage of the opportunities of growth that are

present across sectors. Tauber (1981) categorised the opportunities of growth for a

firm by using two dimensions: product category and firm´s brand name as shown in

the matrix in Figure 1.

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FIGURE 2.1: Tauber´s growth matrix

New Existing

Bra

nd

nam

e

New New product Flanker brand

Existing Franchise extension Line extension

Product category

Source: Tauber, (1981)

Tauber made a difference between four possible strategies that utilise a new or

existing brand name in order to commercialise products within a new or existing

product category for the company (new product, flanker brand, franchise extension

and line extension). Regarding the strategies where the company adopts an existing

brand name to take advantage of market opportunities by leveraging the benefits

linked with the brand such as customer awareness, goodwill and impressions

conveyed by its brand name, Tauber identified two ways to extent an existing brand,

termed as line extension and franchise extension. Whereas line extension represents

new sizes, flavours, and the like where items use an existing brand name in a firm´s

present category, franchise extensions refers to taking a brand name familiar to the

consumer and apply it to products that are in a new category to the parent brand.

Following Tauber´s definition of extension strategies, scholars have also identified

two extension strategies: line extensions and brand extensions. Keller and Aaker

(1992) defined line extension as the fact of extending a current brand name into a new

market segment in its product category. In contrast, Brand extensions are those that

use a current brand name to enter a completely different product class or category

(Aaker and Keller, 1990). According to Ambler and Styles (1997) the definition of

brand extension proposed by Aaker and Keller (1990) acknowledges to the Tauber´s

concept of franchise extension.

The different attempts to define brand extension by academics show

noticeable variations in the literature. Kotler (1991) defined brand extensions using a

holistic approach as “any effort to extend a successful brand name to launch new or

modified products or lines”. On the other hand, Choi (1998) supported that brand

extensions are explained as the use of an existing brand name in a category to

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introduce products in a totally different category. A more general definition of brand

extension was given by Keller (2003, p. 577) who held that “a brand extension is

when a firm uses an established brand name to introduce a new product”.

Extension strategies have not only been classified according to differences in

product category but also regarding quality of the extension and similarity among

categories. In this line, Randall et al. (1998) distinguished between horizontal and

vertical brand extensions. The former is regarded as dissimilar brand extensions

which apply an available brand name to enter a new product category. Vertical brand

extensions involve products with similar or modified features within the same product

category, although at a different price or quality level (Reddy et al., 1994). Therefore,

according to Buil et al. (2008b) the definition of vertical brand extension adds

differences in quality and price to the definitions of line extension proposed by Tauber

(1981) and Keller and Aaker (1992), but represent the same concept.

The differences in quality and price within vertical brand extensions can be

categorized in upscale and downscale brand extensions (Pitta and Katsanis, 1995).

The first one is related to extension with higher quality and price than the parent brand

products. On the other hand, downscale extensions involve products in the same

category of the parent brand products but at a lower price and quality. The category of

vertical extension, upscale or downscale, depends on the type of product offered by

the company. Whereas downscale vertical extensions allow consumers try and learn

about the new functional product based on brand awareness and parent brand

company prestige (Xie, 2008), upscale extensions are more effective for luxury

products where consumers are more likely to transfer perceptions about quality and

consequently high price to the new products (Pitta and Katsanis, 1995)

All these definitions agree with the fact that an existing or established brand

can be used as ways of commercialising products which are, in certain degree, new to

the firm. Nevertheless, the degree to which scholars define the product category has

caused that the terms of brand and line extensions are used interchangeably depending

on how broad the product category is defined (Ambler and Styles, 1997). For

example, Sony´s range of mobile phones could not be considered as brand extension

if Sony´s product category was defined more broadly as “consumer electronics” and

thus mobile phones would represent a line extension in this case (Ambler and Styles,

1997). Regardless, the existence of variations in defining brand extension, researchers

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(Volckner and Sattler, 2007) have mostly adopted the definition proposed by Aaker

and Keller (1990) who defined brand extension as:

“Brand Extensions involve the use of an established brand name to enter a

new product category”

However, whether the existing brand name is used to a new or existing

product category; the company pursues the objective of transferring positive

consumers´ associations towards the brand to the new products (Aaker and Keller,

1990) and thus, the psychological processes by which customers assign certain

products to one category rather than another (Kapferer, 1997), create impressions of

brand extensions as well as of the factors involved in these processes, which will

determinate whether a brand can be successfully extended to a given category (Klink

and Smith, 2001).

2.3 Psychological Processes Involved in Brand Extension

Evaluations

Consumers play a significant role within brand extension strategy because

their judgements regarding the new extensions will be one of the principal

determinants of successful brand extensions (Klink and Smith, 2001). Therefore,

understanding how consumers evaluate brand extensions and the subjacent

psychological processes involved is crucial in order to elaborate and implement

efficient branding strategies for new products.

Two main psychological processes have been used in order to explain how

consumers evaluate the new products: categorical and piecemeal evaluation process.

The former suggests that individuals evaluate the new instances by comparing them

with previous acquired information stored in form of categorical structures within

memory (Fiske, 1982). In contrast, “piecemeal” information processes (Fiske, 1982),

“analytical” (Cohen, 1982) or “computational” (Brooks, 1978) stated that evaluations

of a new instance are based on its specific attributes rather than on initial beliefs

(Bristol, 1996).

Related to the evaluation of brand extensions, Boush and Loken (1991)

maintained that a categorical evaluation process is developed when the brand

extension is perceived by consumers as belonging to an already existing category

(brand). Therefore, beliefs and attitudes associated with the parent brand are

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transferred to the new product (Romeo, 1991). However, if consumers do not

identified congruence with the mental category associated to the brand, a piecemeal

process is activated in which consumers evaluate the new product by making

inferences over the extension individual attributes (Fiske and Pavelchack, 1986).

Thus, both theories are not exclusive and result on a two-stage process where brand

extensions are evaluated according to previous affect associations towards the brand

in the first place and a second stage where consumers elicit an analytical evaluation of

the extension (Fiske and Pavelchack, 1986).

2.4 Consumer Evaluations of Brand Extensions

Ever since the first relevant article on customer evaluations of brand

extensions was published by Boush et al. (1987), researchers have focused their

researches on investigating the antecedents, processes, and consequences of brand

extension evaluation (Hem et al. 2003), as well as achieving a generalisation of these

factors across product categories and parent brands (Volckner and Sattler, 2007;

Czellar, 2003).

Boush et al. (1987) identified perceived similarity and parent brand reputation

as explicative factors of positive customer evaluations of extensions. They concluded

that similarities between product categories, original product and extension, enable

the transfer of positive affection to the new product. On the other hand, the study

suggested that a brand´s good reputation in one product area cannot be transferred in

the same way to a dissimilar product category, since it would produce negative

evaluations from consumers.

Following the research line supported by Boush et al., (1987), Aaker and

Keller´s (1990) seminal article assessed not only the role of similarity between

original and extension product classes but also proposed that customers´ quality

perceptions about the parent brand and the difficulty of producing the extension

determined the consumer acceptance of brand extensions. Despite of the fact this

article stated the base of subsequent research on brand extensions and it has been

applied to different contexts such as services (Hem et al. 2003) or online extensions

(van Riel and Ouwersloot, 2005), replications have emerged about the validity and

generalisation of its conclusions (e.g., Broniarczyk and Alba, 1994; Bottomley and

Doyle, 1996; Bottomley and Holoden, 2001). Moreover, additional factors such as

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consumer innovativeness (Klink and Smith, 2001), familiarity (Dawar et al., 1996) or

marketing support (Reddy et al. 1994) were subsequently tested in brand extension

literature with mixed conclusions. These factors can be classified, as shown in Table

1, in four groups: (1) parent brand characteristics, (2) perceived similarity, (3) the

extension´s marketing context (Völckner and Sattler, 2006), and (4) consumer

characteristics (Czellar, 2003).

TABLE 2.1: Main factors of brand extension evaluation

Factors related to the parent brand

Factor Consumers evaluate positively the extension if… Source

Perceived quality The perceived quality of the parent brand is high Bottomley and Holden, (2001);

Gronhaug et al., (2002)

Brand associations They transfer positive brand associations to the

extension

Park et al., (1991); Hem et al.,

(2003); De Ruyter and Wetzels,

(2000)

Brand Loyalty They are loyal to the parent brand Hem et al, (2003), Buil and Pina,

(2008)

Familiarity The familiarity with the parent brand is high Swaminathan, (2003)

Similarity

Product category similarity There is congruence between product categories Aaker and Keller, (1990)

Brand concept consistency Parent brand and extension share the same image Park et al., (1991)

The extension´s marketing context

Marketing support The extension receives appropriate marketing support Reddy et al.,(1994)

Völckner and Sattler, (2006) Advertising The extension is well supported in terms of advertising

Consumer characteristics

Innovativeness They are highly innovative (early adopters) Klink and Smith, (2001); Hem et al.,

(2003)

Motivation They have a high motivation for purchasing the

extension Gürhan-Canli and Maheswaran, (1998)

Involvement There is an involvement in the brand extension

category

Hansen and Hem, (2004); Steenkamp

and Baumgartner, (1992).

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2.4.1 Similarity

One of the most important contributions of Aaker and Keller´s (1990) study

was the role of similarity in consumer attitude towards brand extensions. Aaker and

Keller (1990) included three dimensions of similarity: complementarity, substitution

and transfer. Whereas the two first concepts allude to how consumers view two

products classes as complement or substitutes respectively, transfer shows how

consumers evaluate whether the skills, competences and resources owned by the

parent brand can be employed in producing the extension. The authors concluded that

only the transfer dimension presented a direct association with attitude towards the

extension.

Boush and Loken (1991) defined similarity by evaluating how typical brand

extensions are for consumers in terms of product features shared by the brand´s

current products and the extension. Whereas typical or atypical extensions are

evaluated by categorisation, moderately typical extensions are likely to be assessed

through piecemeal process. Furthermore, they suggested that the direct relationship

between similarity and consumer evaluations of brand extensions can also produce

negative effects to the parent brand, in the case of atypical brand extensions.

Unlike the aforementioned studies that explain similarity by using a product-

category approach, Park et al. (1991) suggested that extensions are more favourably

evaluated when they are consistent to the consumers´ brand-concept associations such

as reliability or status. Consequently, they concluded that similarity is explained by

two factors, product feature similarity and brand-concept consistency. The importance

of brand concept consistence has been supported by subsequent studies (Broniarczyk

and Alba, 1994; Volcker and Sattler, 2006; Hem and Iversen 2009)

In this line, Broniarczyk and Alba (1994) indicated the existence of specific

brand associations (e.g., friendliness or reliability) that moderate the influence of

product category similarity in extension evaluations because of the fact that these

associations are strong, so they enable a brand to extend to dissimilar product

categories. Thus, the existence of a high degree of congruence between the consumer

brand specific associations and extension product concept has positive effects on

consumer appraisal. (Czellar, 2003)

Regardless of the fact that positive outcomes of similarity have been

recognised, scholars have found moderating conditions which affect similarity when it

13

comes to explaining consumers´ attitude towards the extensions. Smith and Park

(1992) considered that when a greater amount of product related information is

available, consumers do not use similarity between the brand and the extension

categories as a major cue in their evaluations and, hence, more analytical evaluation

processes take place. Supporting these findings, Klink and Smith, (2001) argued that

the limited extension attribute information provided in prior research has provoked an

overestimation of similarity as evaluation factor.

Most recent studies have included other moderating variables of similarity

such as the number of products associated with the brand (Del Vecchio, 2000), the

exposure to the extension (Klink and Smith, 2001); and the price and perceived

quality of the extension (Taylor and Bearden, 2002). Despite of the aforementioned

moderating variables, there is an agreement among academics regarding the

importance of similarity on brand extension evaluation (Völckner and Sattler, 2006).

2.4.2 Characteristics of the parent brand

The research on factors related to the parent brand has principally focused on

different elements of the brand equity construct (Aaker, 1996) such as perceive

quality, brand familiarity, brand associations and brand loyalty. In Aaker and Keller´s,

(1990) study, perceived quality of the parent brand did not present any positive direct

effect on brand extension evaluation. Nevertheless, further empirical research

(Bottomley and Holden, 2001; Gronhaug et al., 2002) demonstrated a positive

relationship between perceived quality and brand extension success. Supporting these

finding, Rao et al., (1999) suggested that quality perceptions of parent brands are

transferred to new products. In a recent article, Völckner et al., (2010) went even

further by stating that perceived quality is the principal driver of brand extensions

success rather than similarity in the case of services. On the other hand, brand

familiarity has proved to have a positive direct effect on brand extension evaluation

because consumers are more inclined to buy products of brands they have previously

consumed (Swaminathan, 2003). Dawar, (1996) studied familiarity in relation to

perceived fit and found contrasting results depending on the different associations

between the extension and the brand. Brand associations represent another important

feature of the parent brand. These associations have been investigated in terms of

perceptions of credibility (De Ruyter and Wetzels, 2000), reputation (Hem et al.,

14

2003), prestige (Park et al., 1991) and the consumers’ affection for the brand (Sheinin

and Schmitt, 1994). Regardless of the fact that brand associations have proved to

produce positive effect on quality, similarity and, consequently, attitude towards the

extension (Martinez and Pina, 2005); there is a lack of agreement in the way in which

they are measured. Finally, brand loyalty has been incorporated by recent studies

(Hem and Iversen, 2003, Build and Pina, 2008) as an important driver of brand

extension success. However, the implications of brand loyalty in brand extension

evaluation have not been replicated and tested in different contexts.

2.4.3 The extension´s marketing context

A third group of brand extension factors has emerged in order to explain the

marketing context in which extensions are developed. Therefore, scholars have

proposed variables such as the marketing support of the brand towards the new

products and the role of advertising in brand extension evaluation. Reddy et al.,

(1994) studied the effects of marketing competences and advertising support on brand

extension evaluations. The author concluded that extensions which receive greater

marketing support in terms of advertising and promotional effort are more favourably

evaluated by consumers. However, this relationship was studied regarding line

extensions rather than brand extension. In order to test these findings, Völckner and

Sattler, (2006) applied Reddy et al´s, (1994) measures of marketing support to the

context of fast moving consumer goods, supporting the positive effect of marketing

support on consumers´ attitude towards extensions .

2.4.4 Consumer characteristics

Certain consumer characteristics such as innovativeness, motivation or

involvement with the extension category, have been introduced within the explicative

factors of consumer attitude towards brand extensions. Klink and Smith, (2001)

suggested that highly innovative consumers (early adopters) perceive a lower risk

from the new products and consequently, they do not base their evaluations on

similarity. Hem et al., (2003) demonstrated a direct relationship between

innovativeness and consumer acceptance of brand extensions and suggested that this

is even stronger in the case of service brand extensions. A second factor is the

consumers´ motivation towards the extension. Gürhan-Canli and Maheswaran, (1998)

15

found that whereas highly motivated consumers tend to evaluate the new products in a

piecemeal manner, under low motivation conditions, consumers are more likely to

transfer affect and prior beliefs from the parent brand to the new extension. On the

other hand, consumer´s involvement with the extension product category has been

found to increase the purchase intention of brand extensions (Hansen and Hem, 2004).

In this way, highly involved consumers tend to be less risk averse than other

consumers and therefore, they are believed to evaluate extensions more positively

(Steenkamp and Baumgartner, 1992).

The review of brand extension factors presented above only explains those

factors that have been proved to be significantly relevant, as they are significant in at

least one empirical study, following the line proposed by Völckner and Sattler,

(2006). However, literature on brand extension has not achieved a generalisation

which is applicable across sectors, brands and extensions. In addition, it still presents

a series of limitations which have prevented scholars from elaborating an explanatory

empirical model of consumer evaluation of brand extensions. These limitations are

outlined in the following section.

2.4.5 Limitations of the current research on brand

extensions

According to the previous review of the drivers of brand extension success, the

limitations of the current research on brand extension are explained by: (1) the use of

hypothetical brand extensions rather than real extensions already introduced in the

market, (2) the scarce number of studies dedicated to obtain general conclusions

(Völcker and Sattler, 2007) and (3) lack of studies in the online context.

There is a preponderance of studies that have evaluated consumer attitude

towards brand extensions by making use of hypothetical brand extensions associated

to real brands (Aaker and Keller, 1990; Bottomley and Holden, 2001; Broniarczyk

and Alba, 1994). These extensions do not provide additional information from the

marketplace as it is the case of extensions already introduced into the markets. As

mentioned, Klink and Smith, (1992) suggested that additional product information

moderates the significance of perceived quality and similarity. Nevertheless, Völckner

and Sattler, (2007) argued that similarity and perceived quality are the two more

significant drivers of both real and fictitious brand extensions.

16

According to Buil et al., (2008) the majority of explanatory models proposed

by scholars are centred on a limited number of factors rather than seeking

generalisation. Only three studies have been addressed to achieve general results

(Klink and Smith, 2001; Bottomley and Holden, 2001; Völckner and Sattler, 2007).

Whereas Klink and Smith, (2001) considered that the positive effects of perceived

similarity were generally applicable across brands and extensions, Bottomley and

Holden, (2001) suggested that, along with similarity, perceived quality and the

difficulty of producing the extension (Aaker and Keller, 1990) were common factors

of consumers´ evaluations of brand extensions. However, the pointed out that cultural

differences may affect the intensity of these variables. Finally, Völckner and Sattler´s,

(2007) findings reinforced the empirical generalizability of similarity and perceived

quality across product categories, parent brands, samples, success measures and both

real and hypothetical extensions. Notwithstanding, these generalizations did not test

other significant determinants of brand extension success (e.g., brand loyalty) and are

focused on fast moving consumer goods extensions and offline brands without

making any consideration for online brands and extensions.

Numerous empirical studies have been conducted in order to establish the

predictive factors of consumer attitude towards extensions in the cases of fast moving

consumer goods, durable goods and services within an offline context (Aaker and

Keller, 1990; Martínez and De Chernatony, 2004; Völckner and Sattler, 2006;

Martinez et al. 2008; Salinas and Perez 2009). However, scholars have not dedicated

much research to the study of the effects of these factors on online brands which

stretch their products or services (van Riel and Ouwersloot, 2005). The following

section is dedicated to review the brand extension research in the case of online

companies.

2.5 Brand Extensions of Online Brands

As mentioned, to the date, only a limited number of studies have investigated

the explicative factors of brand extension success in the online context. Van Riel and

Ouwersloot, (2005) introduced the first study on brand extension applied to online

services. They categorised online services in four groups depending on the origin of

the company (online or physical) and the type of product that provide (tangible goods

17

and traditional services or virtual products). These four types of online companies are

shown in Figure 2.

FIGURE 2.2: e-service portals grid

ORIGIN

Virtual Physical

PR

OD

UC

T

Virtual

E-portals (Click & bits)

Google

Yahoo

Company portals (Bricks & bits)

MSN

CNN

Physical

E-tailers (Click & mortar)

Amazon

Dell

E-sellers (Bricks & mortar)

EasyJet

Source: van Riel and Ouwersloot, (2005)

Van Riel and Ouwersloot, (2005) tested the model proposed by Aaker and

Keller, (1990) for each of the aforementioned types of e-service providers, mentioned

in the grid. They found that the variables of similarity, perceived quality and difficulty

of producing the extension help explain consumer attitude towards online services

extensions. Therefore, they concluded that consumers perceive online extensions in a

similar way to other product categories. Despite these affirmations, the authors

maintained that online services are subject to a more complex evaluation mechanism

than offline goods or services. Moreover, the research presented the limitation of

considering only factors previously proposed by Aaker and Keller, (1990) neglecting

other important determinants of brand extension success such as brand image,

consumers innovativeness or involvement in the extension.

Following the line of van Riel and Ouwersloot, (2005), Song et al., (2010)

proposed an explanatory model of brand extensions success in the online context. In

addition to perceived quality and fit between the parent brand and the extension, they

noted that the existence of hyperlinks in the online environment enables interactions

between different online products and fosters the perceived tie between the current

products and the extension. For example, Google search engine provides access to

other services such as Google Earth, Google News or Gmail with one click.

Therefore, Song et al., (2010) suggested perceived tie as a significant factor of online

brand extension evaluation. The two aforementioned studies were only focused on

18

extensions launched by online brands within the Internet limits. However, they did not

consider potential offline extensions.

Bravo et al., (2010) covered this research gap by examining potential offline

extensions of online brands. In their study, they incorporated, along with perceived fit,

brand image variables such as emotional, commitment or functional associations in

order to explain consumers´ evaluation of offline extensions. Their findings regarding

similarity or fit are in line with the previous research (van Riel and Ouwersloot,

2005), considering similarity as a key determinant of brand extensions. Moreover,

they found that whereas emotional and commitment associations with the parent

brand are more likely to be transferred in the case of internet brands, more functional

associations (e.g., perceived quality) are transferred from offline companies to brand

extensions. Even though these findings contributed significantly to the current

research the authors recognised that this study did not test the moderating effects of

consumer characteristics. Therefore, they recommended further research in order to

build an updated model in the online context.

2.6 Summary

Consumer evaluation of brand extension is explained by means of two

psychological processes: a categorical evaluation process and a piecemeal or

analytical process. In the first one, consumer previous beliefs are transferred to the

new product. The analytical process is based on product attributes rather than

memories in order to evaluate the new product. In addition to these psychological

processes, scholars have identified a series of factors which explain consumer attitude

towards extensions. These factors have been classified in: factors of similarity,

consumer characteristics, factor related to the parent brand and factors related to the

extension´s marketing context.

The current research shows an agreement regarding the generalizability of two

explicative factors: similarity and perceived quality of the parent brand. However,

scholars have proposed a broad variety of additional factors which call for further

research in order to prove their significance as predictors of attitude towards

extensions across sectors and extensions. On the other hand, the literature review

revealed that scarce brand extension research has been addressed to the online

environment and these research efforts have only considered a limited number of

19

factors. Therefore, the following chapters of this study are oriented to build and test

an empirical model applied to online brands which bridges these research gaps with

the aim of contributing to a better knowledge of brand extension evaluations.

20

CHAPTER 3. HYPOTHESES

3.1 Introduction

Chapter 2 has reviewed the most relevant studies in the field of brand

extension. It has also suggested the existence of a series of limitations in brand

extension research such as the utilisation of a reduced number of factors in

consecutive research and the scarce investigation in the field of online companies,

specifically in those online companies that utilise a brand extension strategy in order

to stretch their brands away from the internet world.

In addition to address these research gaps in the literature, this chapter

contributes to fulfil the research objectives of contrasting the conclusions obtained by

scholars regarding the implication of the explicative factors of consumer evaluations

of brand extensions in the area of online companies and particularly when extensions

are produced in an offline context, and examining whether antecedents from brand

extension theory can be combined with those related to brand equity and online brand

management in order to build a valid model to predict consumer acceptance of brand

extensions. In order to do so, hypotheses based on previous research in brand

extension and online brand management are proposed by selecting those factors that

have generated major research and acceptance among scholars but have never been

investigated simultaneously in the context of online companies.

Finally, the chapter concludes by describing the hypothesized model, based on

the formulated hypotheses, in which the overall attitude toward the extension

performs as the dependent variable that is explained by the effects either positive or

negative of the independent variables or explicative factors included in the model.

3.2 Brand Equity variables

Brand equity has been the subject of increased interest in marketing in recent

years. The current research has identified benefits from achieving high brand equity

such as consumer preference and purchase intention (Cobb-Walgren et al., 1995);

consumer perceptions of quality (Dodds, Monroe and Grewal 1991) and consumer

evaluations of brand extensions (Aaker and Keller 1990; Bottomley and Doyle 1996).

Even though scholars agree on the positive effects of strong brands that have high

brand equity, the conceptualisation of the brand equity construct lacks of a general

21

agreement that has provoked that numerous definitions and dimensions arise from the

literature (Christodoulides et al., 2006)

Brand equity can be measured either from a consume level or a firm level.

Whereas the firm-based brand equity is defined in terms of the financial market value

of a company and the cash flows generated from a product as a consequence of having

a brand name (Simon and Sullivan 1990), the consumer-based approach measures

brand equity in terms of consumer behaviour which can be object of actionable brand

strategies (Keller 1993).

Brand equity from a consumer perspective has been defined by two main

frameworks. On the one hand, Keller (1993) defined brand equity as “the differential

effect of brand knowledge on consumer response to the marketing of the brand.”

Therefore, he considered brand knowledge as the main determinant of brand equity

and measured it in terms of two components, brand awareness and brand image. On

the other hand, Aaker (1996) defined the concept of brand equity as “a set of assets

and liabilities linked to a brand, its name and symbol that adds to or subtracts from

the value provided by its product or service to a firm and/or to that firm’s customers”

and identified five dimensions of brand equity: brand awareness, perceived quality,

brand associations, brand loyalty and proprietary brand. Although this last dimension,

proprietary brand assets, is normally omitted in brand equity research since it is not

directly related to consumers (Buil et al., 2008a)

Both Keller´s and Aaker´s definitions of brand equity have been applied to the

context of online companies. Page and Lepkowska-White, (2002) adopted Keller´s

definition and stated that web equity (brand equity) for online companies can be made

similar to offline companies´ brand equity by enhancing brand awareness and brand

Image. They also suggested that Aaker´s dimension of brand loyalty was an outcome

rather than a determinant to create high brand equity. In contrast, Rios and Riquelme

(2008) used the conceptual framework from Aaker (1996) and considered brand

Loyalty as an important source of online brand equity.

Recent studies have introduced Aaker´s (1996) brand equity variables with the

aim of evaluating consumer attitude towards brand extensions (Lassar et al. 1995; De

Chernatony et al., 2004; Pappu et al., 2005; Buil et al. 2008b), However, these studies

have investigated a small group of these dimensions rather than them as if they were a

unique construct in which the relationships between dimensions can be tested in order

to predict attitudes towards the extensions.

22

The following sections develop the conceptual framework supported by Aaker

(1996) in the context of online companies by establishing the hypotheses

corresponding to the dimensions of brand awareness, perceived quality, brand

associations and brand loyalty.

3.2.1 Brand knowledge

Aaker (1996) defined brand awareness as the salience of the brand in the

customers´ mind and identified six levels of awareness: recognition, recall, top-of-

mind, brand dominance, brand knowledge and brand opinion. The brand extension

research has focused its attention on brand knowledge in order to explain extension

evaluations. According to Aaker (1996), the concept of consumer brand knowledge is

concerned with the consumer awareness of what the brand stands for. Brucks (1985)

identified three types of consumer knowledge, named subjective knowledge, objective

knowledge and usage experience. Whereas subjective knowledge refers to what

customers believe they know about the brand, objective knowledge is related to what

is actually stored in consumer’s memory. The third type of knowledge, usage

experience, is related to the purchased amount or experience with the brand. Brucks

also stated that objective and experience-based measures are less directly linked to

purchase behaviour than subjective knowledge measures and therefore customer

behaviour research has mostly utilised subjective consumer knowledge to measure

brand knowledge.

Subjective knowledge has been applied within the brand extension domain to

different variables (original product category, parent brand and extension category)

with mixed results. Keller and Aaker (1992) examined the effects of high subjective

knowledge about the original product category without finding any direct

relationships with the way in which customers evaluate extensions. However, they

concluded that a high perceived knowledge of the extension product category presents

positive effects on extensions assessments. In contrast, Smith and Park (1992)

supported that if the knowledge of the extension category is low, consumers evaluate

extensions more favourably. On the other hand, studies that researched the subjective

knowledge or familiarity with the parent brand (Herr et al., 1996; Dawar, 1996) found

positive effects on consumer attitude toward extensions. Finally, in a most recent

study, Hem and Iversen (2009) discovered that a high subjective knowledge about the

23

current product category of the parent brand correlates negatively to consumer

evaluations, while knowledge about the parent brand and extensions favours how

extensions are assessed. Hem and Iversen (2009) suggested that the conflicting results

regarding brand knowledge are produced by the use of fictitious parent brand in the

research (Keller and Aaker, 1992), the limited number of parent brands involved in

the studies (Dawar, 1996) and the diverse number of products associated with the

parents brands.

In the case of online companies which offer offline products, the role of

subjective knowledge has not been investigated and therefore, in order to replicate the

aforementioned conclusions, this research proposes the following hypothesis:

H1. A high consumer subjective knowledge of the online brand, original

product category and offline extension category has positive effects on the extension

evaluation.

3.2.2 Perceived Quality

According to Zeithaml (1988), Perceive quality designates a global assessment

of a consumer´s judgement about the superiority or excellence of a product. The

perceived quality construct has been included in diverse brand extension articles.

Aaker and Keller (1990) suggested that when consumers have a high overall

perception about the quality of the brand, the extension should be assessed more

positively than when they infer a low overall quality. Nevertheless, they found that

quality only affected the attitude towards the extension favourably when it was

accompanied by a high degree of similarity. In contrast, Bottomley and Holden,

(2001) concluded that there is a direct relationship between the quality of the parent

brand per se and consumer evaluations of the brand extension. Subsequent studies

have supported the positive effects of quality on consumers´ attitudes towards

extensions (van Riel et al., 2001), suggesting that if the brand is associated with a high

level of quality, this perception is transferred to the extension products. However, if

there is a perceived low quality of the parent brand, the extension is harmed as a

result. Völckner et al., (2010) measured the implications of parent brand quality in

service brand extension evaluation by distinguishing three different dimensions of

quality: outcome quality, interaction with service employee quality and psychical

24

environment quality. They concluded that, in the case of extensions from service

brands, quality represented the most significant factor of consumer evaluation rather

than perceived fit or similarity. The implications of perceived quality have been tested

in numerous contexts (Völckner and Sattler, 2006). For online brands, Danaher et al.,

(2003) suggested that consumers base their quality inferences on the brand name

rather than in more tangible product attributes due to the fact that products acquired

online cannot be usually assessed prior to purchase. Therefore, only the dimension

suggested by Völckner et al., (2010) regarding outcome quality is applicable to online

brands. Finally, van Riel and Ouwersloot, (2005), in their pioneer study about online

brand extensions, suggested that the quality of the parent brand helps explain positive

evaluations of extensions but its weight is relatively low compared to similarity.

Hence:

H.2 Higher quality perceptions toward the original online brand are

associated with more favourable attitudes toward the offline extension.

3.2.3 Brand Associations.

Keller (1998) defines brand associations as “informational nodes linked to the

brand nodes in memory that contain the meaning of the brand for consumers”. Aaker,

(1991, pp. 109-13) highlighted the importance of brand associations for both

marketers and consumers. Consumers use their previous beliefs and attitudes towards

the brand to help their purchase decision making process. On the other hand,

marketers seek to differentiate the brand by creating positive attitudes and feeling

towards the brand.

Brand associations have been considered as a multidimensional construct. In

this line, Keller (1998) used the concept of brand image in order to explain

consumers´ perceptions about the brand. He suggested that brand image consists of

associations of brand quality and attitude toward the brand. On the other hand, Aaker

(1996) considered that brand associations can be categorised in value associations,

organisational associations and brand personality. The first group of associations,

value associations, is linked to functional benefits that the brand represents under the

perspective of brand as a product. The value proposition is considered as a

multidimensional concept (Anckar et al., 2002) which is formed by variables such as

shopping convenience, customer service, broad product assortment and after sale-

25

care. The organisational associations represent the brand-as-organisation perspective

and consider facts such as concern for customers, being innovative, being successful,

having visibility, being oriented towards the community, providing trust and being a

global player. Finally, brand personality follows the brand-as-person approach which

might transfer emotional and self-expressive benefits to consumers as well as being a

basis for customer/brand relationships and differentiation.

3.2.3.1 Value associations

In previous brand extension research (Bravo et al., 2010); value associations have not

been separated from the concept of perceived quality. However, Aaker (1996)

suggested that value associations represent a different dimension from perceived

quality. Whereas perceived quality makes reference to a more overall construct

related to a higher level of abstraction (Zeithaml, 1988), perceived value reflect more

specific functional benefits and practical utility of the brand. Therefore, Zeithaml

(1988) defines brand value as the consumer's overall assessment of the utility of a

product based on perceptions of what is received and what is given. These specific

functional benefits have been measured in terms of convenience, value for money,

accuracy and quality of product information (Burke, 2002).

In the case of online brands, functional benefits can be measured in terms of

online experience (Christodoulides et al., 2006), value for money (Anckar et al.,

2002), shopping convenience, product breadth, and compensation (Rios and

Riquelme, 2008). According to Aaker (1996, p.81), value associations also add the

price component to perceived quality. In addition, (Burke, 2002) noted the importance

of price availability and price comparison as required characteristics in online

shopping. Hence, hypothesis 3 is proposed as follows:

H.3 The offline extension will be more positively evaluated, if consumers

perceive brand value in the online business

3.2.3.2 Brand personality

The brand-as-person approach is represented in the concept of brand

personality. Aaker, (1997, p.347) defined bran personality as “a set of human

characteristics associated with a brand”. In this line, Keller (1993) suggested that

brand personality consists of symbolic values which shape and maintain consumers´

26

social identity (Fiske, 1989). According to Aaker, (1996), brand personality provides

self-expressive benefits to consumers. Thus, consumers can express their actual self,

ideal self or social self through their relationships with the brand (Malhotra, 1988).

Aaker (1997) also noticed that the formation of brand personality can be produce

directly or indirectly. Direct sources of brand personality are those related to the

human characteristics of people associated with the brand such as customers, users,

employees or managers. Indirect sources include decisions made by the company in

terms of marketing-mix variables such as advertising, promotion or brand symbol

(Plummer, 1985).

Freling and Forbes (2005) found that strong and positive brand personality has

positive effects on product evaluations. Moreover, Wang and Yang, (2008) suggested

that brand personality also influences positively the consumers´ purchase intention. In

the case of brand extensions, Czellar, (2003) suggested that consumers who give more

importance to self-expressive associations with the parent brands are also more likely

to evaluate positively the new extensions. Hence:

H.4 The offline extension will be more positively evaluated if consumers

perceive a positive brand personality of the online brand.

3.2.3.3 Organisational associations

Aaker (1996) identified a third category of brand associations which reflect the

brand as an organisation rather than as a product or a person. These organisational

associations are related to consumer perceptions and attitudes of the brand in terms of

people, values and programs that lie behind the brand. In this line, Keller and Aaker,

(1992) identified corporate credibility within these associations and noted its

importance in consumer evaluation of new products. They distinguished three

dimensions of credibility: expertise, trust and likability. Expertise refers to the

capability of the parent brand to produce or provide its products. Trust reflects the

extent to which the brand is considered honest and sensitive to consumers´ needs.

Finally, likability is the degree of interest and prestige that consumers perceive in the

organisation. On the other hand, Keller (1998) suggested that marketing campaigns

addressed to reinforce organisational associations such as innovativeness,

environmental concern and community involvement favour brand extension

27

evaluations even in presence of product-specific advertisement. Therefore, the

following hypothesis is suggested:

H.5 The offline extension will be more positively evaluated if consumers

perceive positive organisational associations in the online brand.

3.2.4 Brand Loyalty

As mentioned before, Aaker (1991; 1996) introduced the concept of brand

loyalty within the brand equity construct. Aaker (1991, p. 39) defines brand loyalty as

“the attachment that a customer has to a brand”. This attachment involves a

behavioural and attitudinal component (Keller, 1993). The customer behaviour linked

to loyalty is measured in terms of repeat purchase, whilst the attitudinal component

reflects the positive disposition towards the brand, which includes a commitment in

terms of some unique values associated with the brand (Chaudhuri and Holbrook,

2001). Depending on the level of commitment with the brand, Oliver, (1997)

identified four stages in which loyalty moves: First, cognitive loyalty, where the

consumer makes a cost-benefit evaluation of the product and act in consequence.

Second, an affective loyalty in which consumers create positive feelings towards the

product as a result of satisfactory usage occasions. Then, a conative loyalty is

developed by means of repeated affective situations which generate a behavioural

intention of repurchasing the product. Finally, an action loyalty in which behavioural

intention turns into a routine and positive word-of-mouth behaviour. Therefore,

Oliver´s phases suggest how loyalty is created from attitude to behaviour (Kabiraj,

2010). In this way, customers who are loyal to the brand present an action loyalty,

which benefits the brand in terms of reduced customer acquisition costs, increased

base revenues, positive word-of-mouth, and the ability to impose price premiums

(Edvardsson et al., 2000).

Brand loyalty has also had a significant relevance in studies focused on the

online context. Srinivasan et al., (2002), defined e-loyalty as a customer’s favourable

attitude toward the e-retailer that results in repeat buying behaviour. Clarke, (2001)

highlighted the difficulty of earning and maintaining customer loyalty for Internet

companies where the cost of switching between online services is extremely low, and

thus online companies often face constant competition with numerous others

28

companies which are just one click away. In this line, van Riel and Ouwersloot,

(2005) pointed that the lower heterogeneity among Internet services makes it more

difficult to create consumer loyalty. Regardless loyalty is more challenging for online

companies, Srinivasan et al., (2002) coincided with previous offline brand loyalty

studies (Edvardsson et al., 2000) in the positive outcomes of online brand loyalty (e-

loyalty): positive word-of-mouth and willingness to pay more for products or services.

However, the majority of studies on online brand loyalty focus their research on e-

retailers rather than other types of online companies such as e-portals in which there is

not a transactional component.

The concept of brand loyalty has been scarcely studied in the context of brand

extensions. Hem and Iversen, (2003) found that loyal behavioural intention towards

the parent brand affects significantly the evaluation of brand extensions. Moreover,

Buil and Pina, (2008) supported these findings by stating that grater consumer loyalty

increases the probability of brand extension success. However, this relationship has

not been investigated in the case of brand extensions from online companies.

Therefore, the following hypothesis is proposed:

H.6 Online brand loyalty has a positive effect on consumer attitude

towards the offline brand extension launched by online companies.

3.3 Marketing Support

As commented in chapter 2, the marketing support of brand extensions has

been found by previous literature as a crucial success factor (Klink and Smith, 1992;

Reddy et al., 1994, Völckner and Sattler, 2006). Within these marketing activities,

Sattler et al., (2010) studied the impact of advertising support and product availability

in the distribution channel on consumers´ attitudes towards brand extensions. They

concluded that both advertising and product availability increase the probability of the

new extensions being purchased. In the case of online brands going offline,

advertising and appropriate availability of the new offline product are necessary to

create consumer awareness and perceptions of similarity on consumers´ minds.

Hence:

H.7 Offline brand extensions that received competent marketing support

from the online parent brand are more favourably evaluated by consumers.

29

3.4 Perceived similarity

As mentioned in chapter 2, perceived similarity has been found to be a major

determinant of brand extension evaluations (Aaker and Keller, 1990; Volckner and

Sattler, 2006). According to Gierl and Huettl, (2011), the rationale behind the effects

of similarity on attitude towards extensions is explained by the application of the

categorisation theory (see chapter two, section 2.4.1.2) to the brand extension domain.

In this line, consumers compare their knowledge category related to the parent brand

to the characteristics presented by the extension product (Park et al., 1991) and, if

there is a sufficient level of similarity, this information about the brand, stored in

consumers’ memories, is transferred to the extension product (Boush and Loken,

1991). Therefore, consumers evaluate more favourably those extensions that present a

high degree of similarity or fit with the parent brand (Aaker & Keller, 1990; Czellar

2003; Hem et al. 2003; Völckner & Sattler 2006, Hem and Iversen, 2009). This

overall dimension of similarity leads to the following hypothesis:

H8. The overall perceived similarity between the online parent brand and

the extension has a positive effect on consumer attitude toward the offline extension.

The provided definition of similarity mentions the congruence between the

parent brand and extension in general terms. However, scholars have identified

different levels within the similarity construct. Park et al., (1991) suggested that the

degree of consistency between the brand concept or image and the extension product,

along with the product category similarity (Aaker and Keller, 1990), form the overall

similarity perception in consumers´ minds so that consumers can establish attribute-

based (features, or benefits) and non-attribute-based (image, or context) associations

that link the parent brand and the extension.

3.4.1 Product category similarity

Product category similarity is the degree to which consumers perceive the

extension as similar to other products affiliated with the brand in terms of the needs

they satisfy, situations in which they are used, physical features or component parts,

and skills necessary to manufacture them (Smith and Park, 1992).

30

In the case of online brands going offline, the lack of practical examples may

produce that consumers perceive a low overall degree of similarity between the brand

and the extension, and thus consider offline extensions as incoherent with the image

of online brands (Bravo et al., 2010). However, product category fit can be explained

by the transference of competences or resources required to produce online products

to the new offline extensions. For example, the IT knowledge acquired by online

brands creating web applications may be applied to the development operating

systems for electronic devices such as computers, mobile phones or GPS as Google

did by launching its operating system Android (Gandhewar and Sheikh, 2010).

Moreover, the extensions to devices with connection to the internet enable the

complementarity and adaptability between the parent brand original products (e.g.,

search engines, web applications or ecommerce portals) and the new devices.

Therefore, consumers may perceive these offline extensions as coherent with the

online parent brand. Hence:

H8a. Offline brand extensions in to categories perceived as more similar to

the original product category of the online parent brand are more likely to be

evaluated favourably by consumers.

3.4.2 Brand image Similarity

Although a product class similarity may determine a positive attitude towards

the extensions, the existence of successful brand extensions in dissimilar product

categories from those of the parent brand as for example, Tesco moving its brand into

financial services (Alexander and Colgate, 2005), highlights the need to go beyond

the dimension of product category similarity (Hem and Iversen, 2009).

Consumers also perceive similarity between the extension and the parent

brand image formed in their minds (Bhat and Reddy, 2001). This way, brand image is

made up of specific associations that set the brand apart from other competing brands.

Park et al., (1991) suggested that whereas product features can vary from concrete

levels to other more abstract ones, brand concepts are brand-unique abstract meanings

that typically originate from a particular configuration of product features and a firm's

efforts to create meanings from these arrangements. Hence, consumers evaluate the

31

extensions more positively when there is a match between these associations towards

the brand and the new product (Broniarczyk and Alba, 1994).

In the case of online companies, associations linked to the brand image must

be coherent with perceptions of the new product in order to achieve consumer

acceptance. For example, if users consider Google as an innovative brand that

incorporate the latest technology to their products, they will expect that both online

and offline extensions share the same degree of innovativeness. Hence:

H8b. The match between the specific image of the online brand and the

extension product has a positive effect on the attitude towards the offline extension.

3.5 Involvement in the extension product category

The relevance of consumer involvement in consumer behaviour has been

explained by its influence in consumers´ decision making and communication

behaviour (Hansen and Hem, 2004). Involvement concerns to “a person’s perceived

relevance of the object based on inherent needs, values, and interests” (Antil, 1984;

Zaichkowsky, 1985). The concept of consumer involvement has been categorised by

Houston and Rothschild, (1978) as a multidimensional construct. The authors

differentiated between three types of involvement: enduring, situational and response.

Enduring involvement is related to the long-term attachment of a consumer to a

specific product category. This type of involvement is characterised as an extensive

information search, brand knowledge and, eventually brand loyalty. (Mittal, 1989)

considered that consumers who became involved with a specific situation, generally a

purchase decision, present a situational involvement. Finally, a response involvement

refers to a behavioural orientation characterised as information acquisition and

decision processes (Leavitt et al., 1981).

The study of involvement in brand extension evaluation has been focused on

the first type of involvement (enduring) which was measured by two dimensions:

consumers' knowledge of the product class of the extension (Smith and Park, 1992)

and the importance of purchase decisions in the extension's product category (Nijssen

and Bucklin, 1998). Therefore, high consumer´s knowledge of the extension product

class reduces the perceived risk of purchasing the new product and fosters the positive

evaluation of the extension (Smith and Park, 1992). Hence:

32

H.9 High involved consumers in the extension category will positively

evaluate the brand extension.

3.6 Consumer innovativeness

Rogers and Shoemaker, (1971, p. 27) defined consumer innovativeness as “the

degree to which an individual is relatively earlier in adopting an innovation than

other members of his system”. Roehrich, (2004) identified four explicative causes of

this early adoption from consumers: (1) new products help satisfy consumers´ need of

stimulation, (2) consumers seek novelty in the new products in terms of information,

adoption or use; (3) consumers make innovative decisions independently from the

communicated experience of others (Midgley and Dowling, 1978), and (4) the need of

uniqueness which differentiates the consumer from others. Therefore, consumers who

present a high degree of innovativeness, also known as early adopters, play a very

important role in the success of new products (Goldsmith and Flynn, 1992), since they

are more willing to try new products and brands (Steenkamp and Baumgartner 1992),

are less price sensitive, but more knowledgeable about new products and less risk

averse (Rogers, 1983). Therefore, these characteristic of early adopters affect their

purchase and learning processes within the marketplace.

In evaluating brand extensions, consumer innovativeness has been considered

as an antecedent of positive consumer attitude towards extensions. Klink and Smith,

(2001) concluded that early adopters react positively to a new extension in the case of

durable goods. Furthermore, the authors found consumer innovativeness as a

moderating factor of similarity, stating that consumers with high degree of

innovativeness do not base their extension evaluation on perceived similarity. Hem et

al., (2003) extended the Klink and Smith´s (2001) study to fast moving consumer

goods and services finding positive effects of consumer innovativeness on consumers’

evaluation of brand extensions. Xie (2008) studied consumer innovativeness with

regard to different types of extensions, product information and interpersonal

communication. The study found that innovative consumers evaluate extensions in

different categories more favourably than those of the parent brand (horizontal

extensions) and than those which present a lower degree of similarity with the parent

brand. In addition, the availability of product information and interpersonal

33

communication moderate the effects of consumer innovativeness and the evaluation

of extensions. Despite the research on consumer innovativeness for different kinds of

product and extensions, there is no study regarding the positive role of consumer

innovativeness in the evaluation of extensions from online companies. Therefore, the

following hypothesis is suggested:

H.10 Consumers with a high degree of innovativeness will evaluate more

positively offline brand extensions from Internet brands.

The hypotheses proposed by this research are summarised in the following

table:

TABLE 3.1: Hypotheses

H.1 A high consumer subjective knowledge of the online brand, original product category and offline

extension category has positive effects on the extension evaluation.

H.2 Higher quality perceptions toward the original online brand are associated with more favourable

attitudes toward the offline extension.

H.3 The offline extension will be more positively evaluated, if consumers perceive brand value in the

online business

H.4 The offline extension will be more positively evaluated if consumers perceive a positive brand

personality of the online brand.

H.5 The offline extension will be more positively evaluated if consumers perceive positive organisational

associations in the online brand.

H.6 Online brand loyalty has a positive effect on consumer attitude towards the offline brand extension

launched by online companies.

H.7 Offline brand extensions that received competent marketing support from the online parent brand

are more favourably evaluated by consumers.

H.8 The overall perceived similarity between the online parent brand and the extension has a positive

effect on consumer attitude toward the offline extension.

H.8a Offline brand extensions into categories perceived as more similar to the original product category

of the online parent brand are more likely to be evaluated favourably by consumers.

H.8b The match between the specific image of the online brand and the extension product has a positive

effect on the attitude towards the offline extension.

H.9 High involved consumers in the extension category will positively evaluate the brand extension.

H.10 Consumers with a high degree of innovativeness will evaluate more positively offline brand

extensions from Internet brands.

34

3.7 The Hypothesized Model

Following the procedures of the previous research (Aaker and Keller, 1990),

the hypotheses proposed above are studied within a linear regression model, where the

dependent variable, the attitude towards the extension, is explained by ten explicative

factors that represent the independent variables of the regression. The linear

regression model is as follows:

Where the dependent variable:

ATT= Overall attitude towards the brand extension, and where the independent variables are:

FAM= Brand knowledge or familiarity

PQ= Perceived quality of the parent brand

BAV= Value associations

BAP= Brand personality

BAO= Organisational associations

BLO= Brand loyalty

SIMP= Product category similarity

SIMI= Brand image similarity

MS= Marketing support

INE= Consumer involvement in the extension product category

CIN= Consumer innovativeness

35

The hypothesized model is summarised in Figure 3.1:

3.8 Summary

This chapter has reviewed the factors that build an explanatory model of consumer

attitude towards brad extensions which is applied to online brands that extend the brand name

to the offline context. A set of hypotheses related to the principal factors involved in the

model was proposed in order to demonstrate their implications on consumer evaluations of

brand extensions. The next chapter will describe the research methodology which was used in

order to gather the required information to test the aforementioned hypotheses.

36

CHAPTER 4. METHODOLOGY

4.1 Introduction

Chapters 2 and 3 have introduced the general theory about consumer

evaluations of brand extensions. They have also stated the principal hypotheses that

configure a model applicable to offline brand extensions produced by online

companies. Therefore, with the aims of determining the feasibility of the factors

proposed by previous research within the context of online brands as well as

responding to the main research question of whether online companies can leverage

the brand equity to offline products, this chapter justifies the research methods utilised

in this study by which the data has been gathered in order to test the suggested

hypotheses and validate the proposed model in chapter three (see Figure 3.1)

The chapter begins by making a general description of the philosophy

underpinning the research project. The research design then justifies the adoption of

quantitative research in the field of brand extensions as well as the utilisation of the

method of survey as the most suitable to gather the required information to this study.

The following section describes the different types of data, primary and secondary,

that have been used in the research. Thereafter, a description of how the survey has

been built is provided by explaining the reasons that support the election of online

brands (Google and Amazon) and the extensions linked to them (Smartphone and

eBook reader). This section also describes the typology and scaling of the items or

questions which have been introduced in the questionnaires to be answered by the

respondents. Finally, the section related to the sampling describes the characteristics

of the used sample.

4.2 Research philosophy

The selection of an appropriate methodology which fits the research purpose and

focus, has to be underpinned by a philosophical framework within which the research

project is situated (Quinlan, 2011). In this line, two philosophical positions can be

adopted by researchers: ontology and epistemology. Blaikie (1993) define ontology as

“the science or study of being”, therefore, ontology describes the nature of being and

our ways of being in the world (Crotty, 2005). On the other hand, epistemology

considers what knowledge is and what the sources and limits of knowledge are

37

(Eriksson and Kovalainen, 2008). According to Easterby-Smith et al., (2008),

epistemology also considers views of the most appropriate ways of enquiring into the

nature of the world. Hatch and Cunliffe (2006) stated that there is an inter-dependent

relationship between ontology and epistemology so that the way in which they are

related to each other determines different research philosophies (Saunders et al.,

2009).

Within the context of epistemology, the methodology of this study adopts a

positivist approach which holds that an objective reality is out there to be found.

Epistemologically this can be done with knowable degrees of certainty using

objectively-correct scientific methods (Carson et al., 2001). The rationale behind the

choice of positivism for this study is derived from the additional research objective of

testing hypothesis developed from the existing theory through measuring the

observable social reality within the context of online brands. Thus, the study uses a

deductive approach where the proposed hypotheses introduced in chapter 3 represent

the theoretical considerations to which a quantitative research is addressed in order to

develop further theory in the context of this study (Saunders, 2009). Therefore, the

research must be designed in order to contrast the formulated hypothesis and

consequently, answer the research questions. In the next section, the research design is

explained by developing the research strategy and the time horizon of the research.

4.3 Research Design

Once that the research has been positioned within a philosophical framework,

it needs to be designed in order to collect the needed data that will lead to answer the

following research question: can online brands extend the brand name to offline

products successfully?. In order to do so, there are two different research designs to

collect the required data: the qualitative and quantitative research approach. Whereas

qualitative research is oriented toward understanding of a natural world, and is highly

interpretive in nature without depending on numerical measurements (Gall et al.,

1996), quantitative research is addressed to investigate the relationship between

certain variables and is based on statistical and numerical analysis of proposed

hypothesis from previous theory (White, 2000).

The utilisation of quantitative research in this study has a twofold objective: first,

quantitative research design enables to measure the multiple factors involved in the

38

model (e.g., brand knowledge, similarity, consumer innovativeness) and the potential

relationships among factors (Easterby-Smith et al., 2008) and secondly, this study

attempts to replicate previous quantitative research on determinants of brand

extension success. Therefore, the analysis of the obtained quantitative data will allow

comparing the results with those of previous studies. In order to fulfil these objectives

the research must adopt a research strategy which is addressed to obtain the

qualitative data to be analysed.

4.3.1 Research strategy

This study makes use of a survey as a strategy by which the quantitative data

is collected and subsequently analyzed by means of descriptive and inferential

statistical methods. According to Saunders, (2009), the method of survey presents the

following advantages: it allows the collection of a large amount of data from a

measurable sample in an inexpensive way, allows comparison by providing

standardised data and it is easy to explain and understand. Despite these benefits,

surveys require time to design and pilot data collection instruments, and to ensure that

the sample is representative and there is a good rate of response (Saunders, 2009).

These drawbacks are bridged in this study by the use of an internet survey which

permits real time data capture and analysis, greater accuracy and respondent

anonymity (Zikmund et al., 2011).The advantages of the survey fit with the research

objectives of this study due to the need of a large amount of information regarding

explicative factors of brand extension success as well as a representative sample of

potential consumers of the brand extensions. The method of survey has been used in

previous research by studies such as “Effects on market share and advertising

efficiency” (Smith and Park, 1992) or “Effects of different types of perceived

similarity and subjective knowledge in evaluations of brand extensions” (Hem and

Iversen, 2009), therefore, the use of a survey for this study allows comparing results

with those of previous research.

Within the survey strategy, the questionnaire represents the most suitable

method to gather the necessary data for this study. A questionnaire is a technique of

data collection in which each respondent is asked to answer the same questions in a

certain order (deVaus, 2002 cited in Saunders, 2009). Hence, the questionnaire

permits to this research makes use of standardised questions from previous literature

39

regarding the determinants of consumer attitude towards brand extensions and applies

them to a different context (offline extensions from online brands). Consequently, the

study follows an explanatory approach in order to test and explain the relationships

between the factors of band extension success and the consumer evaluation of brand

extensions in the purposed context. This study uses self-administered questionnaires

(respondents complete them on their own) which are administered online. This type of

questionnaire benefits the study by gaining greater interactivity, control and faster

data collection (Zikmund et al., 2011).

4.3.1 Time horizon

This study is considered as a cross-sectional study or snapshot which studies

the consumer attitude towards brand extensions at a particular time. The reason

supporting the use of a cross-sectional study for this research is that cross-sectional

studies are carried out to investigate associations between risk factors (brand

extension success factors) and the outcome of interest (attitude towards brand

extensions) at a single period of time (Levin, 2006). This characteristic benefits the

research because less time is needed to gather and analyse the data. In addition, the

majority of previous studies on brand extension are based on cross-sectional studies

which allow findings of these studies to be compared with the conclusion obtained in

this study.

4.4 Survey Development

In order to test the proposed model (Figure 3.1), an empirical study was

constructed. Firstly, two online brands were selected, Amazon and Google,

distinguishing them in terms of type of online company, degree of familiarity, ability

to elicit unique associations and to be associated with multiple products. Secondly,

real offline extensions of the selected brands were utilised (eBook reader and mobile

phone) in contrast to the usual procedures from previous research (Aaker and Keller,

1990; van Riel and Ouwersloot, 2005; Martinez and Pina, 2010). Afterwards,

antecedents of consumer evaluations of brand extensions where measured by means

of multi-items rating scales based on previous research and adapted to a five-point

Likert scale in order to standardize the different scales used by researchers. Finally,

two internet-mediated questionnaires were developed, one for each brand and its

40

corresponding extension, in order to avoid bias produced by the comparison between

brands and extensions within the same questionnaire. The questionnaires were

administered electronically through the Internet which allowed the interaction of

respondents by providing the logos of Amazon and Google and real pictures of the

extensions (mobile phone and e-reader).

4.4.1 Selection of brands and extensions

Google and Amazon belong to different types of online brands or e-services

according to the categorisation made by van Riel and Ouwersloot (2005). Google is

considered an e-portal which was originated in the e-world and offers virtual products

within the online limits, for instance web searching, video streaming or blogging, to

name but a few. In contrast, Amazon is categorised as an e-tailer which offers more

tangible products, such as books, apparel or electronic products through its website

which is used as a distribution channel, in spite of being equally originated in the e-

world. Additionally, the two brands present differences in their experience

commercialising their products. Whereas Google delivers fundamentally intangible

online services through the web, Amazon manages tangible items from computerized

warehouses and fulfilment centres where they are shipped direct to customers

(Veverka, 2009). Therefore, these differences may arise contrasting perceptions of

similarity.

Following the line of previous research (Aaker and Keller, 1990; Hem et al.,

2003), the selected brands present a high degree of consumer familiarity according to

their unique audience or total number of visitors who visit their websites or use their

applications at least once in a given period. Following this, Google and Amazon are in

first and eighth positions respectively as reported on the list of top 10 internet

companies elaborated by Nielsen, (2010). Moreover, familiar brands have the

advantage of holding clear brand images on consumers´ minds (Van Heerden and

Puth, 1995) and provoke more brand associations (Low and Lamb, 2000).

The selected brands are also characterised by being associated to multiple

products. According to Dawar et al., (1996), broad brands present different brand

associations that may influence consumers’ brand judgments. For instance, a

consumer may be familiar with Google Android (mobile software platform) but the

41

product associations may be weak, with Google being more strongly associated with

web search services.

Real offline extensions were chosen in order to test the influence of marketing

communications on consumer evaluations of brand extensions. In the case of Google,

the selected extension was its mobile phone also known as Nexus One, which became

available on January 5, 2010 and utilises Google´s own operating system, Android.

The device was sold through Google online store until May 2010 when Google

announced the closing of the web store, with the intention of distributing the phone

through partners around the world (Official Google Blog, 2010). On the other hand,

Amazon´s brand extension was its eBook reader, Kindle, which uses wireless

connectivity to enable users to shop for, download, browse, and read e-books,

newspapers, magazines, blogs, and other digital media (Loeffler, 2010). Real brand

extensions already commercialised into the market have the advantage of providing

additional information to consumers in terms of marketing communications or word

of mouth which is employed to evaluate extensions. In contrast, hypothetical

extensions previously utilised in the literature only provide brand name and similarity

as only stimulus to be evaluated and therefore, they may fail to reflect the processes

consumers use to evaluate a real-world, available extension (Völckner and Sattler,

2007).

Table 4.1: Overview of online brands and offline extensions

Brand Original Category Brand Extension Extension Category

Google e-portal Google Nexus One Mobile phone

Amazon e-tailer Amazon Kindle eBook reader

4.4.2 Scaling and multi-item scales

The items in the questionnaire were measured by means of five-point Likert

scales. Respondents were requested to state their level of agreement with the specific

statement (e.g., 1= strongly disagree, 5 = strongly agree) or directly assess the

variable (e.g., 1 = One of the worst, 5 = One of the best). Likert-type scales are

suitable to be used on internet surveys because they are easy to build and administer

to the sample and the respondents are familiar with the use of these scales. However,

42

they require more time from respondents to read and consider each statement

(Malhotra and Birks, 2003).

The study uses multi-item measures for the overall evaluation of brand

extension and for explicative factors. Traditionally, multi-item scales are used to

represent complex psychological constructs that cannot be summarized in a single

question: attitudes, stress levels, personality, loyalty and satisfaction, among others.

The rationale behind the use of multi-items rating scales rather than single scales is

that by having several items that measure the same construct, the problem of having a

single representation variable is solved (Aaker, 1998). For example, if a respondent

misunderstands one part of the question, it will affect part of the measure rather than

all of the measure (Bearden and Netemeyer, 1999).

Table 4.1 shows the items used to measured each variable. The overall attitude

towards the brand extension (ATT) was based on the studies of Aaker and Keller,

(1990) and Broniarczyk and Alba (1994) and measured with three questions that

ascertained (1) positive attitude towards the extension (1 = strongly disagree, 5 =

strongly agree), (2) likelihood of trying the extension (1 = not at all likely, 5 = very

likely) and; (3) overall evaluation of the extension relating to the existing brands in

the extension category (1 = one of the worst, 5 = one of the best).

In regards to the explicative factors linked to the parent brand, items of brand

familiarity (FAM) were adapted from Dawar´s scale (Dawar, 1996). Participants were

asked to rate the following items: familiarity with the brand and its original product

category (1 = not familiar, 5 = very familiar) and the purchase frequency of the

brand’s products (1 = not at all frequently, 5 = very frequently). Perceived quality

(PQ) was measured with three items, previously used by Pappu et al., (2005). These

are: (1) the brand offers good quality products, (2) the brand offers consistent quality

and (3) the brand offers products with excellent features (1 = strongly disagree, 5 =

strongly agree). Brand associations items were divided, according to Aaker (1996), in

three categories: value associations (BAV), brand personality (BAP) and

organisational associations (BAO). As commented in chapter three, value associations

are related to brand-as-product associations, therefore, are linked to functional

benefits provided by the brand (Aaker, 1996). In the questionnaire, value associations

were measured in terms of the online experience provided by the brand´s website and

the perceived value for money of the brand´s products (Christodoulides et al., 2006).

The items adapted from Aaker (1996) to measure brand personality were: The brand

43

has personality, the brand is interesting and I have a clear image of the type of person

who would use the brand. On the other hand, organisational associations were

measured in terms of online trust which includes consumer perceptions of privacy,

security and overall consumer confidence in the online business (Bart et al., 2005).

All brand associations items were measured by means of a five-point Likert scale

anchored at 1 = “strongly disagree”, 5 = “strongly agree”. Finally, brand loyalty was

estimated through three items adapted from Rios and Riquelme, (2008) and anchored

at 1 = “strongly disagree”, 5 = “strongly agree”.

Factors related to the extension were measured as follows: First, the subjective

knowledge of the extension product category (FAM4) was asked through the

question: overall, how much do you know about products in the extension category?

(Hem and Iversen, 2009) where 1 = very little 5 = very much. Then, two types of

similarity were studied, product category similarity and brand image similarity.

Product category similarity was estimated by using the following three items: how

similar is the typical usage situation of the brand´s products with the usage of the

extension? (Hem and Iversen, 2009), how similar is the competence required to

produce the brand´s products and the extension? (Aaker and Keller, 1990) where 1 =

“not at all similar”, 5 = “very similar”; and there is complementarity of the brand´s

products and services and the extension (1 = strongly disagree, 5 = strongly agree).

Brand image similarity was measured with a single item which estimated the overall

similarity between brand and extension regarding image (1 = not at all similar, 5 =

very similar). Two variables were adapted from the literature in order to measure

marketing support: whether the extension is well supported in terms of advertising

(Nijssen, 1999) and whether the extension receives competent marketing support

(Reddy et al., (1994) where (1 = strongly disagree, 5 = strongly agree).

Regarding consumer characteristics, the involvement in the extension product

category was measured with two items which stated the importance of the extension

product category in consumers purchase intentions and the knowledge of the products

offered within the extension category. Consumer innovativeness was measured with

items extracted from Hem et al., (2003): Overall, I enjoy buying the latest products; I

like to purchase the latest products before others do and; overall, it is exciting to buy

the latest products. Both involvement and consumer innovativeness items were

anchored at (1 = strongly disagree, 5 = strongly agree).

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Table. 4.2: Scales used in the questionnaires

Scale Measured Concept

Overall Attitude towards the brand extension

(ATT).

Aaker and Keller (1990) and Broniarczyk and Alba

(1994)

ATT1: Positive attitude towards the extension

ATT2: Likelihood of trying the extension

ATT3: Overall evaluation of the extension relative

to the existing brand in the extension category

Familiarity (FAM).

Dawar, (1996); Hem and Iversen (2009)

FAM1: Familiarity with the brand

FAM2: Familiarity with the brand´s products

FAM3: Purchase frequency of the brand’s products

FAM4: Subjective knowledge of the extension

product category

Perceived quality (PQ).

Pappu et al., (2005)

PQ1: Perceived quality of the brand´s products

PQ2: Quality consistence of the brand´s products

PQ3:Quality of the brand´s products features

Brand associations (BA)

Value associations (BAV).

Christodoulides et al., (2006)

BAV1: The brand´s website provides easy-to-

follow search paths

BAV2: I never feel lost when navigating through

the brand’s website

BAV3: Ability to obtain information without delay

BAV4: Value for money of the brand´s product

Brand Personality (BAP).

Aaker, (1996)

BAP1: The brand has personality

BAP2: The brand is interesting

BAP3: Image the type of person who would use

the brand

45

Organisational associations (BAO).

Aaker, (1996); Bart et al., (2005); Rios and

Riquelme, (2008)

BAO1: Overall trust in the brand

BAO2: Safety to disclosure personal information to

the brand

BAO3: Safety to conduct transactions with the

brand

BAO4: Attitude towards the organisation behind

the brand

BAO5: Credibility of the organisation behind the

brand

Brand Loyalty (BLO).

Yoo and Donthu, (2001)

BLO1: It makes sense to use the brand´s products

or services instead of other competing companies,

even if they are the same

BLO2: Even if other company has the same

features as the brand´s products or services, I

would prefer use the brand´s ones

BLO3: I would definitely recommend the brand to

friends, neighbors and relatives

Similarity (SIM)

Product category similarity (SIMP).

Hem and Iversen (2009), Aaker and Keller (1990)

SIMP1:Similarity of usage situations between the

brand and extension

SIMP2: Transfer of competences between the

brand´s products and the extension

SIMP3: Complementarity between the extension

and the brand´s products

Band image similarity (SIMI)

Hem and Iversen (2009)

SIMI: Similarity between the parent brand and the

extension product category

Marketing Support (MS).

Reddy et al. (1994); Nijssen (1999)

MS1: Advertising support

MS2: Marketing support

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Consumer involvement in the extension product

category (INE).

Smith and Park (1992); Nijssen and Bucklin (1998)

INE1: Importance of the extension product

category

INE2: Knowledge about the products in the

extension category

Consumer innovativeness (CIN).

Hem et al.,(2003)

CIN1: I enjoy buying the latest products

CIN2: I like to purchase the latest products before

others do

CIN3: Overall, it is exciting to buy the latest

products

4.5 Sampling

The difficulty of obtaining data corresponding to the entire population makes

necessary to limit the total population to a more suitable number of respondents or

sample (Schiffman and Kanuk, 2007). This sample has to be as representative of the

entire population as possible. Therefore, sampling techniques have to be configured in

order to reach the appropriate sample for the research (Saunders, 2009). There are two

different kinds of sample: probability sample and non-probability sample. The former

is adequate for studies where the researcher needs to make inferences from the sample

about the population to answer the research questions. On the other hand, in non-

probability samples statistical inferences about the characteristic of the population

cannot be made due to the probability of each case to be selected from the population

is not known (Saunders, 2009).

This study adopts a probabilistic sample, since total population for this study

would be all the potential consumers of the suggested offline brand extensions. In

addition, there is not any suitable sampling frame available to which, probabilistic

sampling can be applied. However, it is possible to obtain a representative sample by

configuring a quota sampling. Quota sampling is considered a type of stratified

sample, where the selection of categories is not made randomly by the researcher

(Barnet, 1991 cited in Saunders et al., 2007). This study has stratified potential

consumers according to demographic characteristics by using quotas regarding age,

gender and level of studies in order to capture the influence of these variables in the

evaluation of brand extensions.

47

A total of 160 respondents were sampled which varied in age between 18 to 55

years old, 51.3% were male and 47.5% were female. In terms of level of education,

the most important groups were graduate school 50.6% and college 28.1%. Finally the

two most important groups regarding nationality were Spanish 27.5% and British

26.3%

48

CHAPTER 5. DISCUSSION

5.1 Introduction

This chapter presents the analysis and discussion of the collected data in the

survey. The chapter begins with a reliability analysis where the internal validity of the

variables introduced in the model is tested. After that, the relationships among the

variables are discussed by means of a correlation analysis. Then, a regression analysis

is provided for both an aggregated model and for each brand (Google and Amazon),

with the aim of testing the proposed hypotheses in chapter 3. Afterwards, the

regression results are discussed. Finally, the chapter concludes with a review of the

findings and their implications in the proposed model.

5.2 Reliability and Correlation analyses.

5.2.1 Reliability analysis

A reliability analysis was performed in order to test the internal validity of the

variables within the model. First, the attitude towards the extension (ATT) was

operationalized as the average of overall attitude, likelihood of trial and overall

evaluation of the extension relating to the existing brands in the extension category.

Secondly, the independent variables were operationalized by aggregating the values of

their multi-item scales.

Reliability was assessed by measuring the values of the reliability coefficient,

Cronbach´s alpha (α). As Table 5.1 exhibits, the coefficients revealed that all

measures presented an alpha coefficient exceeding the recommended value of 0.7

(Hair et al., 1998), except for the variable brand personality (α = 0.585). Further

analysis indicated that by removing the item related to the image of the person who

uses the brand (BAP3), the coefficient (α) increased to 0.657. Consequently, this item

was removed from further analyses.

In the light of the results, all items appeared to gel really well together.

Therefore, the model has a good internal consistency.

49

TABLE 5.1: Cronbach´s Alpha Coefficients for Multi-Items Constructs

Dependent variable Α No. items

Attitude toward extension (ATT) 0.845 3

Independent variables Α No. items

Brand knowledge (FAM) 0.828 3

Perceived quality (PQ) 0.846 3

Value associations (BAV) 0.743 4

Organisational associations (BAO) 0.853 5

Brand personality (BAP) 0.657 2

Brand Loyalty (BLO) 0.840 3

Marketing support (MS) 0.806 2

Consumer innovativeness (CIN) 0.900 3

Involvement with the extension (INE) 0.825 2

Product Similarity (SIMP) 0.733 3

5.2.2 Correlation analysis

A correlation Analyses identifies how variables in the conceptual model relate

to each other. The correlation coefficients which are shown in Table 5.2 (Appendix

A.2.1) prove that all variables have a positive relationship to attitude towards the

extension, particular BAO (0.57), BLO (0.415), BAP (0.454), SIMP (0.597), SIMI

(0.443) and MS (0.445). Furthermore, a strong relationship is shown in the case of

perceived quality and value associations (0.687**), which is in accordance with

previous research on perceived quality (Aaker, 1996). On the other hand, Brand

loyalty is also strongly related to perceived quality (0.631**) and organisational

associations (0.662**) which supports the idea that perceive quality and trust in the

online brand help increase consumer e-loyalty (Reinartz & Kumar, 2000).

50

TABLE 5.2: Correlations

ATT FAM PQ BAV BAO BLO SIMP MS INE CIN BAP SIMI

ATT 1 .191* .313

** .268

** .570

** .415

** .597

** .445

** .330

** .358

** .454

** .443

**

FAM .191* 1 .574

** .439

** .322

** .459

** .220

** .021 .396

** .232

** .350

** .145

PQ .313**

.574**

1 .687**

.498**

.631**

.294**

.117 .216**

.221**

.440**

.354**

BAV .268**

.439**

.687**

1 .459**

.553**

.230**

.130 .297**

.180* .454

** .327

**

BAO .570**

.322**

.498**

.459**

1 .662**

.443**

.261**

.194* .399

** .547

** .350

**

BLO .415**

.459**

.631**

.553**

.662**

1 .341**

.043 .372**

.323**

.578**

.272**

SIMP .597**

.220**

.294**

.230**

.443**

.341**

1 .329**

.301**

.330**

.331**

.588**

MS .445**

.021 .117 .130 .261**

.043 .329**

1 .158* .113 .043 .232

**

INE .330**

.396**

.216**

.297**

.194* .372

** .301

** .158

* 1 .439

** .185

* .172

*

CIN .358**

.232**

.221**

.180* .399

** .323

** .330

** .113 .439

** 1 .208

** .192

*

BAP .454**

.350**

.440**

.454**

.547**

.578**

.331**

.043 .185* .208

** 1 .234

**

SIMI .443**

.145 .354**

.327**

.350**

.272**

.588**

.232**

.172* .192

* .234

** 1

*. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

5.3 Regression analysis

The study employed multiple regression analysis in order to test the

hypotheses proposed in chapter 3. Two different regressions were conducted with the

aim of testing the role of the two dimensions of similarity. In the first model shown in

Table 5.3, the two components of similarity, product category similarity (SIMP) and

brand image similarity (SIMI) were aggregated in the variable similarity (SIM) which

measures the overall similarity construct. The second regression (Table 5.4) separated

these two components in order to assess their individual effects on attitude towards

the extension (ATT).

As it is logical, both models explain the same percentage of the dependent

variable´s variance (Adjusted R2

= 0.57) because they represent the same model being

only differentiated by its level of aggregation. The computed F-statistic is 17.87 for

the first regression, and 16.13 for the second regression which are significant at

p=0.000. It means that at least one variable within the model is relevant and its

regression coefficient is different from zero (Thomas, 1997).

51

TABLE 5.3: Regression I (Aggregated components of similarity)

Independent variables Full model

Predicted

direction B

Std.

error Beta T-value

Constant -0.70 0.42 -1.64

H.1: Subjective knowledge (FAM) + -0.07 0.08 -0.07 -0.92

H.2: Perceived quality (PQ) + -0.04 0.13 -0.03 -0.31

H.3: Value associations (BAV) + -0.18 0.11 -0.31 -1.61

H.4: Organisational associations (BAO) + 0.32 0.12 0.25*** 2.62

H.5: Brand personality (BAP) + 0.23 0.11 0.18** 2.20

H.6: Brand loyalty (BLO) + 0.05 0.12 0.05 0.48

H.7 Marketing Support (MS) + 0.22 0.06 0.25**** 3.87

H.8 Similarity (SIM) + 0.43 0.09 0.34**** 4.77

H.9: Involvement (INE) + 0.14 0.07 0.17** 2.19

H.10: Consumer innovativeness (CIN) + 0.06 0.06 0.08 1.06

F statistic 17.87****

R squared 0.60

Adjusted R squared 0.57

Significant at ****p<.000;***p<.01;**p<.05;*p<.10

52

TABLE 5.4: Regression II (Separated components of Similarity)

Independent variables Full model

Predicted

direction

B Std.

error

Beta T-value

Constant -0.72 0.43 -1.67

H.1: Subjective knowledge (FAM) + -0.08 0.08 -0.07 -0.95

H.2: Perceived quality (PQ) + -0.04 0.14 -0.03 -0.27

H.3: Value associations (BAV) + -0.18 0.12 -0.13 -1.53

H.4: Organisational associations (BAO) + .033 0.12 0.25*** 2.62

H.5: Brand personality (BAP) + 0.23 0.11 0.17** 2.10

H.6: Brand loyalty (BLO) + 0.06 0.11 0.05 0.47

H.7 Marketing Support (MS) + 0.24 0.06 0.25**** 3.86

H.8a: Product similarity (SIMP) + 0.35 0.10 0.28*** 3.50

H.8b: Brand Image Similarity (SIMI) + .09 0.07 0.10 1.26

H.9: Involvement (INE) + .14 0.06 0.17** 2.19

H.10: Consumer innovativeness (CIN) + .06 0.06 0.07 1.02

F statistic 16.13****

R squared 0.60

Adjusted R squared 0.57

Significant at ****p<.000;***p<.01;**p<.05;*p<.10

Regression was also conducted at a brand level in order to assess the effects of

the independent variables on attitude towards extension when different types of online

brands are involved. The proposed model explains 73% and 53% of the attitude

towards the extension for Amazon and Google respectively. The findings from the

analysis are shown in Table 5.5.

53

TABLE 5.5: Regression analysis by type of company

Full model Amazon Google

Variable Beta T-value Beta T-value Beta T-value

Constant -1.67 -.360 -1.848

FAM -.072 -.94 -.117 -.996 .073 .742

PQ -.025 -.27 -.250* -1.848 .067 .494

BAV -.126 -1.53 .043 .385 -.045 -.368

BAO .249*** 2.62 .228* 1.677 .081 .643

BAP .170** 2.10 .107 1.109 .325*** 2.633

BLO .047 .47 .124 1.007 .021 .144

SIMP .282*** 3.50 .124 1.027 .255** 2.162

SIMI .095 1.26 .105 1.153 .099 .885

MS .250**** 3.86 .268*** 3.011 .175* 1.750

INE .166** 2.19 .503**** 4.924 -.072 -.574

CIN .073 1.02 -.002 -.020 .220** 1.999

R squared 0.60 0.86 0.73

Adjusted R2 0.57 0.73 0.53

Significant at ****p<.000;***p<.01;**p<.05;*p<.10

5.4 Hypotheses Testing

Surprisingly, the results for the regression analysis for the full model (Table

5.5) showed that both brand knowledge (FAM) and perceived quality of the parent

brand (PQ) had no significant effect on attitude towards the extension (ATT). The

beta coefficient related to brand knowledge (FAM) appeared to be no significant at

any level of significance (p>0.1) and negative (0.72), therefore the first hypothesis

(H1) is rejected. Moreover, brand knowledge was not significant on a brand level,

which supports the declination of H1. The variable also presents a negative sign in the

case of Amazon which differs from the predicted direction of this hypothesis.

Perceived quality (PQ) appeared to be no significant on an aggregated level

(p> 0.1) and its beta coefficient presented a negative sign for the full model (β= -

0.02). Therefore, the second hypothesis has to be rejected. On a brand level, perceive

quality of the parent brand (PQ) was significant (p<0.1) and substantial (β= -0.25) in

the case of Amazon but no significant for Google. However, the negative sign of PQ

54

is opposed to the proposed direction and therefore H2 was rejected for Amazon. In the

same line, value associations towards the brand (BAV) are not significant at any level.

Thus the third hypothesis (H3) is also rejected.

The results also suggested that five variables present significant beta

coefficients: organisational associations (BAO), brand personality (BAP), product

category similarity (SIMP), marketing support (MS) and involvement in the extension

category (INE). Organisational associations (BAO) presented a considerable and

positive beta coefficient of 0.25 which was significant at p<0.01. Thus, the hypothesis

4 is accepted at an aggregated level. On a brand level, organisational associations

were only found significant for Amazon (β=0.228; p<0.1). Thus, H4 is also accepted

in the case of Amazon but rejected for Google.

Brand personality (BOP) was found also significant and positive (β=0.17;

p<0.05) supporting the acceptance of H5 for the aggregated model. The impact of

brand personality is also relevant in the case of Google (p<0.01), which showed a beta

coefficient of 0.325. The fifth hypothesis (H5) is therefore accepted on a brand level

for Google but rejected for Amazon. On the other hand, brand loyalty (BLO) was

found no significant at any level p>0.1 and H6 was therefore rejected.

The impact of overall similarity (SIM) on attitude towards the extension was

found significant and positive, see Table 5.4, on an aggregated level (β=0.25;

p<0.000). However, when the dimensions of similarity, product category similarity

(SIMP) and brand image similarity (SIMI), were introduced in the regression

separately, only product similarity appeared to be significant (β=0.282; p<0.01).

These findings support the acceptance of H8 and H8a but reject H8b. On a brand level,

product similarity is significant for Google at p< 0.01, (β=0.255). In the case of

Amazon, H8a and H8b have to be rejected.

The variable marketing support (MS) appeared to predict 5.06%

[(0.225*0.225)*100] (β=0.25) of variation in attitude towards the extension (see

appendix A.3.3.3). The impact of Marketing support is significant at p<0.000.

Therefore, the seventh hypothesis (H7) has to be accepted. Marketing support is also

significant for Amazon (β=0.268; p<0.01) and Google (β=0.175; p<0.1). Therefore,

H7 is also accepted for both brands.

Regarding the variables related to consumer characteristics, only involvement

in the extension category was found significant (p<0.05) and presented a positive and

considerable beta coefficient of 0.166. Hence, the ninth hypothesis (H9) was accepted

55

for the aggregated model. Consumer involvement in the extension product category

also presented a significant value of its beta coefficient (β=0.503; p<0.00) in the case

of Amazon, which support the acceptance of H9 for Amazon. This hypothesis was

rejected for Google. On the other hand, consumer innovativeness was found no

significant at any level, rejecting H10 except in the case of Google in which it was

found significant (β=0.22; p<0.05) and therefore, H10 is accepted on a brand level for

Google.

5.5 Discussion

In the light of the results presented in the regressions, certain interpretations

can be suggested. First, in contrast with previous studies (Herr et al., 1996; Dawar,

1996), brand knowledge does not present a significant effect on attitude towards the

extension. It may be explained by the existence of piecemeal evaluation processes

(Fiske and Pavelchak, 1986) in which consumers evaluate the new extension

according to their features and attributes rather than by transfer of their previous

beliefs or attitudes towards the brand. The extension from an online environment to an

offline product may explain the negative sign of the brand knowledge beta coefficient

(-0.072), due to the fact that consumers may perceive these extensions as atypical or

unrealistic.

The absence of significance in the case of perceived quality (PQ) may suggest

that, according to Bravo et al., (2010), functional associations, such as quality

perceptions, do not impact attitude towards the extension when an online brand is

extended to offline products. Therefore, the impact of perceived quality is diluted by

the existence of emotional and self-expressive associations towards the extension.

Supporting this theory, the values presented by the three different categories of

brand associations suggest that whereas value associations related to more specific

functional attributes are not found significant, both organisational associations and

brand personality, which reflect more self-expressive and emotional perceptions of the

brand, appeared to have a significant impact on attitude towards the extension.

The no significance of brand loyalty within the model may be explained by the

fact that the lower heterogeneity in the online environment and the facility to change

from one brand to another (Clarke, 2001) provoke that relationships of loyalty are

harder to develop in the offline context (van Riel and Ouwersloot, 2005).

56

The importance of overall similarity within the model is in line with previous

studies (Aaker and Keller, 1990) which considered it as the most important predicting

factor of attitude towards extensions. However, this study showed that only product

similarity is considered significant within the model which contrasts with Park et al.,

(1991) who suggested that consumers evaluate extensions more favourably when they

find congruence between the parent brand image and the extension.

In the line of Reddy et al., (1994) and Völckner and Sattler, (2007), the

marketing support of the extension was found significant. This result suggests that

marketing strategies have an important impact in consumer evaluation of offline

extensions launched by online companies. As mentioned in chapter 4, this study used

real brand extensions with the objective of testing the impact of existing marketing

efforts on consumers´ attitude towards the extension. Finally, the involvement with

the extension product category appeared to have a significant effect on attitude

towards the extension. Therefore, when consumers feel that the extension product

category is important when it comes to their purchase decisions and they are familiar

with the existing products in this category, their will have a more positive attitude

towards the new product.

The regression results also have implications on a brand level. The relative

little weight of perceived quality in the cases of Amazon and Google may suggest that

consumers expect online brands to explore the boundaries of technical possibilities in

the new offline product categories. Therefore, quality perceptions are not transferred

to the new extensions (van Riel and Ouwersloot, 2005).

The relationships between brand associations and attitude towards the

extension presented differences on a brand level. Whereas Amazon´s consumers were

more likely to transfer organisational associations based on trust and credibility, more

emotional associations regarding Google´s brand personality were transferred to the

new product.

Product similarity was a significant determinant of brand extension success for

Google. This suggests that consumers evaluate more favourably those offline

extensions which present complementarity with the product of the parent brand and

use the same competences. In the case of Amazon, none of the categories of

similarity, product similarity and brand image similarity, was found to be relevant.

This result can be explained by the broad variety of products provided by Amazon,

57

which does not provide a clear basis for categorizing subsequent extensions.

Therefore, the transfer of similarity perceptions is reduced (Smith and Park, 1992).

Marketing support of the extensions seemed to have a considerable weight on

consumer evaluations in both brands. Thus, extensions that receive strong advertising,

distribution or promotion are more accepted among consumers (Reddy et al, 1994).

Finally, consumer characteristics presented variations across brands. The

involvement in the extension has an important weight in the case of Amazon but it is

not relevant for Google. It may be explained by the extension product category and its

lifecycle. EBook readers are considered as a relatively new product in a growth phase

where marketing efforts are more intensive and consumers are gathering information

about the product. On the other hand, mobile phones are more mature products in

which consumers´ motivation is reduced progressively. Thus, companies seek to

differentiate and gain consumer interest by adding new product features. These new

features will be better evaluated by highly innovative consumers, early adopters,

which reflect the importance of consumer innovativeness in the case of Google.

5.6 Summary

The principal findings of the analysis of the research data have been presented

and discussed in this chapter. These findings seemed to have significant implications

on consumers´ attitude towards offline extensions launched by online companies. The

following table (Table 5.6) presents the obtained conclusions from the analysis and

contrasting of the hypotheses in chapter 3.

58

TABLE 5.6: Review on hypotheses

Hypothesis Variable Full Model Amazon Google

H1 FAM Not Supported Not Supported Not Supported

H2 PQ Not Supported Not Supported Not Supported

H3 BAV Not Supported Not Supported Not Supported

H4 BAO Supported Supported Not Supported

H5 BAP Supported Not Supported Supported

H6 BLO Not Supported Not Supported Not Supported

H7 MS Supported Supported Supported

H8 SIM Supported Not Supported Supported

H8a SIMP Supported Not Supported Supported

H8b SIMI Not Supported Not Supported Not Supported

H9 INE Supported Supported Not Supported

H10 CIN Not Supported Not Supported Supported

The most interesting research findings are: First, organisational and brand

personality associations which transfer emotional and self-expressive benefits to the

consumers are used in order to evaluate the new extensions. Second, in the same line

as previous research, similarity appeared to be a significant factor within consumer

evaluation of brand extensions. However, consumers did not consider brand image

similarity in their evaluation process. Finally, marketing support and consumer

involvement in the extension were significant explicative factors of attitude towards

the extension. The theoretical and managerial implications of the findings will be

presented in the next chapter.

59

CHAPTER 7. CONCLUSION

7.1 Conclusion

This study attempts to provide a better understanding of the factors that

influence consumers´ evaluations of brand extensions in the context of online brands

and, in particular, when these extensions are launched away from the Internet limits

towards offline markets. The findings of this study suggested that the launching of

offline brand extensions by online companies is indeed possible. More specifically,

this study showed that consumers employ brand personality and organisational

associations rather than perceptions of quality and value in order to evaluate the new

offline extensions. Furthermore, this study seems to follow the line of previous

research by supporting the role of product similarity as predictor of brand extension

success. On the other hand, the marketing support provided by the parent brand to the

offline extension creates more positive consumer attitudes towards the extension as it

is demonstrated in this study. Finally, consumer involvement in the extension product

category appears to have a considerable weight in consumer evaluation of brand

extensions.

7.2 Implications

7.2.1 Theoretical Implications

The theoretical implications of this study are multifold. First, this study

extends the research on consumer evaluations of brand extensions in the online

environment by including new factors which have not been yet studied in the existing

research. In general terms, the acceptance of offline extensions launched by online

companies depends on the degree of product similarity perceived by consumers and

their relationships with the organisation behind the brand in terms of trust and

credibility. Additionally, consumers´ self-expressive feelings linked to the brand

personality are more likely to be transferred to the new extensions in the case of

online companies. Although overlooked in previous online brand extension research,

this study shows that marketing support of the extension and consumer involvement

in the extension product category play a significant role in predicting consumer

attitude towards the extensions. Secondly, this study also introduces differences with

60

regard to the type of online brand which is extended to offline products. The study

suggests that organisational associations are more likely to be transferred in the

evaluation of extensions launched by e-tailers (Amazon). In the case of e-portals

(Google) which are less accustomed to carry out online transactions with customers,

perceptions of trust, credibility and online safety are less significant. However, e-

portals are capable to transfer its band personality to the offline extensions. On the

other hand, similarity perceptions are better transferred from e-portals, in terms of

complementarity and transference of competences, than in the case of e-tailers. This is

provoked by the broader variety of tangible products that are provided by e-tailers

which blur consumers´ perceptions of similarity. Finally, the product category of the

extensions seems to play an important role regarding factors related to consumer

characteristics. Whereas consumer innovativeness is more linked to mature products

such as mobile phones, the relevance of consumer involvement in the extension

category seems to be more related to products in the growth phase (ebook readers)

which require a greater effort and motivation from consumers in order to gather

information about the new product.

7.2.2 Managerial Implications

The findings of this study also provide some implications for business

practice. Firstly, according to the significant role of product similarity on consumers´

evaluations of the extensions, managers of online brands have to decide the type of

product that is to be extended. This new product must be perceived as similar to the

current products of the parent brand. Therefore, managers must select offline

extensions which enable the Internet access and can be used together with the

products of the brand. Secondly, the study confirms that consumers´ emotional and

self-expressive associations toward the parent brand are also used to evaluate the

offline extensions. Thus, managers have to develop marketing campaigns addressed to

create a stronger brand personality as well as to reinforce relationships of trust and

credibility. Furthermore, managers have to invest highly in implementing marketing

techniques which support the new extensions with the aim of gaining greater perceive

product similarity and consumer involvement, which should as well be directed to the

correct segments (early adopters or late adopters). To summarize, such support will

help achieve two objectives: (1) it will facilitate a very aggressive push and pull

61

demand for the brand extension and (2) it will help create positive perceptions about

the company in the minds of the consumers.

7.3 Limitations and Directions for Further Research

Regardless of the importance of the implications mentioned above, this study

presents several ways in which it can be extended. Firstly, this study only assessed the

direct relationships between the determinants of brand extension success and

consumer attitude toward the extension. Possible interactions between explicative

variables may help improve the understanding of consumers´ evaluations of the

extensions. In this way, variables such as brand loyalty or brand knowledge that

appeared to be not significant within the model may play an important role when they

interact with other explicative variables. More specifically, it would be interesting to

investigate the interaction effects between brand loyalty and brand associations as

well as perceived quality and value associations, because these factors presented a

considerable correlation as commented in chapter 5. Therefore, further research

should investigate the existence of relationships between the proposed determinants of

brand extension success.

Secondly, this study only examined one brand within each of the two studied

categories of online brands (e-tailers and e-portals) which stops results from being

generalised. Therefore, further research should extend this research to the study of a

broader number of companies in each category in order to generalize the findings to

other e-tailers and e-portals. Moreover, only one offline extension was investigated

for each company. Therefore, additional product categories can be useful to test

whether the proposed model is applicable across different types of offline products.

Another substantial limitation is that this study is only focused in two

categories of online brands (e-tailers and e-portals) which were initially originated in

the online environment. However, van Riel and Ouwersloot, (2005) proposed two

additional categories of online brands (e-sellers and company portals) which have a

traditionally physical origin. Differences in origin may change the way in which

consumer evaluated the offline brand extensions, since they may perceive more

tangible relationships with these kinds of Internet companies.

Finally, this study consists in a cross-sectional analysis of the collected data.

However, the utilised variables were not statics. Moreover, given the importance of

62

marketing activities in the evaluation of brand extensions, which may have

progressive effects on the suggested explicative variables, this study may not fully

capture consumers´ attitudes toward the extension across time. Therefore, further

research should employ longitudinal studies to examine the dynamic effects of brand

extension evaluation.

63

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APPENDIX

Appendix A – SPSS DATA

Appendix A.1: Reliability Analysis

A.1.1 Attitude towards the extension

Reliability Statistics

Cronbach's

Alpha N of Items

.845 3

A.1.2 Brand knowledge

Reliability Statistics

Cronbach's

Alpha N of Items

.828 3

A.1.3 Perceived quality

Reliability Statistics

Cronbach's

Alpha N of Items

.846 3

A.1.4 Value associations

Reliability Statistics

Cronbach's

Alpha N of Items

.743 4

A.1.5 Organisational organisation

79

Reliability Statistics

Cronbach's

Alpha N of Items

.853 5

A.1.6 Brand personality

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if Item

Deleted

The brand has a personality 6.87 2.358 .420 .254 .456

I have a clear image of the type

of person who would use the

brand

7.56 1.706 .338 .122 .657

The brand is interesting 6.65 2.447 .498 .288 .390

A.1.7 Brand loyalty

Reliability Statistics

Cronbach's

Alpha N of Items

.840 3

A.1.8 Marketing support

Reliability Statistics

Cronbach's

Alpha N of Items

.806 2

Reliability Statistics

Cronbach's

Alpha N of Items

.585 3

80

A.1.9 Consumer innovativeness

Reliability Statistics

Cronbach's

Alpha N of Items

.900 3

A.1.10 Involvement with the extension

Reliability Statistics

Cronbach's

Alpha N of Items

.825 2

A.1.11 Product Similarity

Reliability Statistics

Cronbach's

Alpha N of Items

.733 3

Appendix A.2: Correlation analysis

A.2.1 Correlations between the conceptual model aggregates

Correlations

ATT FAM PQ BAV BAO BLO SIMP MS INE CIN BAP SIMI

ATT Pearson

Correlation

1 .191* .313

** .268

** .570

** .415

** .597

** .445

** .330

** .358

** .454

** .443

**

Sig. (2-

tailed)

.017 .000 .001 .000 .000 .000 .000 .000 .000 .000 .000

FAM Pearson

Correlation

.191* 1 .574

** .439

** .322

** .459

** .220

** .021 .396

** .232

** .350

** .145

Sig. (2-

tailed)

.017

.000 .000 .000 .000 .006 .791 .000 .004 .000 .070

PQ Pearson

Correlation

.313** .574

** 1 .687

** .498

** .631

** .294

** .117 .216

** .221

** .440

** .354

**

Sig. (2-

tailed)

.000 .000

.000 .000 .000 .000 .150 .007 .006 .000 .000

81

BAV Pearson

Correlation

.268** .439

** .687

** 1 .459

** .553

** .230

** .130 .297

** .180

* .454

** .327

**

Sig. (2-

tailed)

.001 .000 .000

.000 .000 .005 .111 .000 .027 .000 .000

BAO Pearson

Correlation

.570** .322

** .498

** .459

** 1 .662

** .443

** .261

** .194

* .399

** .547

** .350

**

Sig. (2-

tailed)

.000 .000 .000 .000

.000 .000 .001 .017 .000 .000 .000

BLO Pearson

Correlation

.415** .459

** .631

** .553

** .662

** 1 .341

** .043 .372

** .323

** .578

** .272

**

Sig. (2-

tailed)

.000 .000 .000 .000 .000

.000 .595 .000 .000 .000 .001

SIMP Pearson

Correlation

.597** .220

** .294

** .230

** .443

** .341

** 1 .329

** .301

** .330

** .331

** .588

**

Sig. (2-

tailed)

.000 .006 .000 .005 .000 .000

.000 .000 .000 .000 .000

MS Pearson

Correlation

.445** .021 .117 .130 .261

** .043 .329

** 1 .158

* .113 .043 .232

**

Sig. (2-

tailed)

.000 .791 .150 .111 .001 .595 .000

.049 .158 .593 .003

INE Pearson

Correlation

.330** .396

** .216

** .297

** .194

* .372

** .301

** .158

* 1 .439

** .185

* .172

*

Sig. (2-

tailed)

.000 .000 .007 .000 .017 .000 .000 .049

.000 .021 .031

CIN Pearson

Correlation

.358** .232

** .221

** .180

* .399

** .323

** .330

** .113 .439

** 1 .208

** .192

*

Sig. (2-

tailed)

.000 .004 .006 .027 .000 .000 .000 .158 .000

.009 .016

BAP Pearson

Correlation

.454** .350

** .440

** .454

** .547

** .578

** .331

** .043 .185

* .208

** 1 .234

**

Sig. (2-

tailed)

.000 .000 .000 .000 .000 .000 .000 .593 .021 .009

.003

SIMI Pearson

Correlation

.443** .145 .354

** .327

** .350

** .272

** .588

** .232

** .172

* .192

* .234

** 1

Sig. (2-

tailed)

.000 .070 .000 .000 .000 .001 .000 .003 .031 .016 .003

*. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

82

Appendix A.3: Regression analysis

A.3.1 Amazon

Variables Entered/Removedb

Model Variables Entered Variables Removed Method

1 CIN, MS, SIMI, BLO, INE,

BAV, BAP, FAM, SIMP, PQ,

BAO

. Enter

a. All requested variables entered.

b. Dependent Variable: ATT

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .856a .733 .678 .50314

a. Predictors: (Constant), CIN, MS, SIMI, BLO, INE, BAV, BAP, FAM,

SIMP, PQ, BAO

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) -.195 .542 -.360 .720

FAM -.105 .105 -.117 -.996 .324

PQ -.374 .202 -.250 -1.848 .070

BAV .062 .160 .043 .385 .701

BAO .315 .188 .228 1.677 .099

BAP .164 .148 .107 1.109 .272

BLO .140 .139 .124 1.007 .319

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 37.434 11 3.403 13.443 .000a

Residual 13.670 54 .253

Total 51.104 65

a. Predictors: (Constant), CIN, MS, SIMI, BLO, INE, BAV, BAP, FAM, SIMP, PQ, BAO

Dependent Variable: ATT

b. Dependent Variable: ATT

83

SIMP .160 .156 .124 1.027 .309

SIMI .094 .082 .105 1.153 .254

MS .260 .086 .268 3.011 .004

INE .454 .092 .503 4.924 .000

CIN -.001 .074 -.002 -.020 .984

a. Dependent Variable: ATT

A.3.2 Google

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 CIN, MS, BAV,

FAM, SIMI,

BAP, INE,

SIMP, BAO,

PQ, BLO

. Enter

a. All requested variables entered.

b. Dependent Variable: ATT

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .726a .528 .451 .65650

a. Predictors: (Constant), CIN, MS, BAV, FAM, SIMI, BAP, INE, SIMP,

BAO, PQ, BLO

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 32.736 11 2.976 6.905 .000a

Residual 29.307 68 .431

Total 62.043 79

a. Predictors: (Constant), CIN, MS, BAV, FAM, SMI, BAP, INE, SIMP, BAO, PQ, BLO

Dependent Variable: ATT

b. Dependent Variable: ATT

84

85

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

Collinearity

Statistics

B Std. Error Beta Tolerance VIF

1 (Constant) -1.597 .864 -1.848 .069

FAM .128 .173 .073 .742 .461 .710 1.409

PQ .089 .180 .067 .494 .623 .375 2.666

BAV -.061 .165 -.045 -.368 .714 .456 2.195

BAO .105 .164 .081 .643 .522 .438 2.285

BAP .392 .149 .325 2.633 .010 .456 2.194

BLO .025 .170 .021 .144 .886 .333 3.004

SIMP .271 .126 .255 2.162 .034 .500 2.001

SIMI .083 .093 .099 .885 .379 .556 1.799

MS .175 .100 .175 1.750 .085 .697 1.434

INE -.059 .103 -.072 -.574 .568 .445 2.247

CIN .195 .098 .220 1.999 .050 .572 1.747

a. Dependent Variable: ATT

86

A.3.3 Aggregated model

A.3.3.1 Model with aggregated Similarity

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 BAP, MS, INE,

CIN, PQ, SIM,

FAM, BAV,

BAO, BLO

. Enter

a. All requested variables entered.

b. Dependent Variable: ATT

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .776a .602 .569 .60508

a. Predictors: (Constant), BAP, MS, INE, CIN, PQ, SIM, FAM, BAV,

BAO, BLO

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 65.420 10 6.542 17.869 .000a

Residual 43.202 118 .366

Total 108.622 128

a. Predictors: (Constant), BAP, MS, INE, CIN, PQ, SIM, FAM, BAV, BAO, BLO

b. Dependent Variable: ATT

87

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) -.692 .422 -1.641 .103

FAM -.074 .081 -.069 -.915 .362

PQ -.042 .134 -.029 -.310 .757

BAV -.183 .113 -.130 -1.611 .110

BAO .325 .124 .248 2.622 .010

BLO .056 .116 .048 .482 .630

SIM .431 .090 .344 4.770 .000

MS .244 .063 .250 3.874 .000

INE .143 .065 .166 2.192 .030

CIN .064 .061 .075 1.062 .290

BAP .237 .108 .175 2.191 .030

a. Dependent Variable: ATT

A.3.3.2 Model contrasting two dimensions of similarity

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 CIN, MS, BAV,

FAM, SIMI,

BAP, INE,

SIMP, BLO,

PQ, BAO

. Enter

a. All requested variables entered.

b. Dependent Variable: ATT

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .776a .603 .565 .60733

a. Predictors: (Constant), CIN, MS, BAV, FAM,SIMI, BAP, INE, SIMP,

BLO, PQ, BAO

88

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 65.467 11 5.952 16.135 .000a

Residual 43.155 117 .369

Total 108.622 128

a. Predictors: (Constant), CIN, MS, BAV, FAM, SIMI, BAP, INE, SIMP, BLO, PQ, BAO

Dependent Variable: ATT

b. Dependent Variable: ATT

Coefficients

Model

Unstandardized

Coefficients

Standardized

Coefficients

T Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF

1 (Constant) -.715 .428 -1.669 .098

FAM -.077 .081 -.072 -.946 .346 .588 1.700

PQ -.037 .136 -.025 -.272 .786 .395 2.531

BAV -.176 .115 -.126 -1.529 .129 .502 1.991

BAO .326 .124 .249 2.622 .010 .376 2.662

BAP .231 .110 .170 2.102 .038 .517 1.936

BLO .055 .116 .047 .474 .637 .343 2.914

SIMP .349 .099 .282 3.504 .001 .525 1.903

SIMI .085 .068 .095 1.260 .210 .597 1.676

MS .244 .063 .250 3.855 .000 .809 1.236

INE .143 .065 .166 2.186 .031 .590 1.696

CIN .062 .061 .073 1.022 .309 .670 1.493

a. Dependent Variable: ATT

89

A.3.3.3 Correlations

Model

Correlations

Zero-

order Partial Part

1 (Constant)

FAM .217 -.087 -.055

PQ .300 -.025 -.016

BAV .251 -.140 -.089

BAO .582 .236 .153

BLO .409 .044 .028

SIMP .620 .308 .204

MS .442 .336 .225

INE .365 .198 .127

CIN .388 .094 .060

BAP .448 .191 .122

SIMI .452 .116 .073

90

Appendix B - QUESTIONNAIRES

Heriot Watt University

SURVEY ON BRAND EXTENSION

Dear participant,

My name is Antonio Martinez, and I am conducting a survey for my final dissertation

on branding.

I am interested in your opinion about different online brands and the brand extensions

linked to them.

I would be glad if you could help me to do this survey by taking the time to complete

this questionnaire. All information will be treated in the strictest confidence and

results will be produced in form of aggregated data only.

Thank you for your time and collaboration.

INSTRUCTIONS

As mentioned, this questionnaire is about online brands and their real and

hypothetical brand extensions. A brand extension is a new product which uses an

already existing band name. You will be asked about your opinion about one online

brand and its brand extensions. The questionnaire requires some time and effort to fill

out, therefore please try to do your best and make both your and my time worthwhile.

91

QUESTIONNAIRE 1: GOOGLE

Consider the following brand:

Google Inc.

For the next several questions, please choose a number from 1-5 to each statement to

indicate how much you agree with that statement.

NON

FAMILIAR VERY

FAMILIAR

1. Are you familiar to the brand Google? 1 2 3 4 5

2. Are you familiar with the products offered by Google? 1 2 3 4 5

NOT AT ALL

FREQUENTLY VERY

FREQUENTLY

3. I use frequently Google products or services 1 2 3 4 5

STRONGLY

DISAGREE STRONGLY

AGREE

4. Google offers very good quality products 1 2 3 4 5

5. Google offers products of consistent quality 1 2 3 4 5

6. Google offers products with excellent features 1 2 3 4 5

STRONGLY

DISAGREE STRONGLY

AGREE

7. Google’s website provides easy-to-follow search paths 1 2 3 4 5

8. I never feel lost when navigating through Google’s website 1 2 3 4 5

9. I was able to obtain the information I wanted without any delay 1 2 3 4 5

10. Considering what I would pay for Google, I would get much more than

my money’s worth 1 2 3 4 5

92

11. Google has a personality 1 2 3 4 5

12. Google is interesting 1 2 3 4 5

13. I have a clear image of the type of person who would use Google 1 2 3 4 5

14. I trust the company which makes Google 1 2 3 4 5

15. It feels safe to disclose personal information in Google 1 2 3 4 5

16. It feels safe to conduct transactions in Google 1 2 3 4 5

17. I like the company which makes Google 1 2 3 4 5

18. The company which makes Google has credibility 1 2 3 4 5

STRONGLY

DISAGREE STRONGLY

AGREE

19. It makes sense use Google´s products or services instead of other

competing companies, even if they are the same 1 2 3 4 5

20. Even if other company has the same features as Google´s products or

services, I would prefer use Google 1 2 3 4 5

21. I would definitely recommend Google to friends, neighbours and

relatives 1 2 3 4 5

Consider the following extension:

a) Google smartphone

93

VERY

LITTLE VERY MUCH

22. Overall, how much do you know about products in the smartphone

category? 1 2 3 4 5

NOT AT ALL

SIMILAR HIGHLY

SIMILAR

23. Think of Google. How similar is the typical usage situation of

Google´s products with the usage of mobile phones? 1 2 3 4 5

24. Think of Google. How similar is Google compared with mobile

phones regarding image? 1 2 3 4 5

25. Think of Google. How similar is the competence required to

produce Google products and mobile phones? 1 2 3 4 5

TOTALLY

DISAGREE TOTALLY

AGREE

26. There is complementarity of Google´s products and services and

mobile phones 1 2 3 4 5

STRONGLY

DISAGREE STRONGLY

AGREE

27. Google smartphone is well supported in terms of advertising 1 2 3 4 5

28.Google smartphone receives competent marketing support 1 2 3 4 5

STRONGLY

DISAGREE STRONGLY

AGREE

29. Buying a smartphone is important to me 1 2 3 4 5

30. I know the products offered by the smartphone category 1 2 3 4 5

STRONGLY

DISAGREE STRONGLY

AGREE

31. Overall, I enjoy buying the latest products 1 2 3 4 5

32. I like to purchase the latest products before others do 1 2 3 4 5

33. Overall, it is exciting to buy the latest products 1 2 3 4 5

94

STRONGLY

DISAGREE STRONGLY

AGREE

34. Overall, I am very positive to Google mobile phone 1 2 3 4 5

NOT AT ALL

LIKELY VERY LIKELY

35. I am likely to try Google smartphone 1 2 3 4 5

ONE OF THE

WORST ONE OF THE

BEST

36. Overall evaluation of Google smartphone relative to existing brands in

mobile phones category 1 2 3 4 5

Finally, answer the following questions about you

What is your age?

( ) 18-24 ( ) 25-34 ( ) 35-45 ( ) 45-55 ( ) 55+

What is your gender?

( ) Male ( ) Female

What is your marital status?

( ) Single ( ) Married ( ) Divorced ( ) Separated

What is your employment status?

( ) Full time employed ( ) Part time employed ( ) Self-employed ( ) Housewife/husband ( ) Unemployed ( ) Retired

What is your highest level of education?

( ) Elementary school ( ) High school ( ) College ( ) Graduate school

What is your degree level?

( ) High school diploma ( ) Bachelor's Degree ( ) Masters ( ) PhD ( ) None

What is your nationality?

95

QUESTIONNAIRE 2: AMAZON

Consider the following brand:

Amazon.com

For the next several questions, please choose a number from 1-5 to each

statement to indicate how much you agree with that statement.

NON

FAMILIAR VERY

FAMILIAR

1. Are you familiar to the brand Amazon? 1 2 3 4 5

2. Are you familiar with the products offered by Amazon? 1 2 3 4 5

NOT AT ALL

FREQUENTLY VERY

FREQUENTLY

3. I use frequently Amazon products or services 1 2 3 4 5

STRONGLY

DISAGREE STRONGLY

AGREE

4. Amazon offers very good quality products 1 2 3 4 5

5. Amazon offers products of consistent quality 1 2 3 4 5

6. Amazon offers products with excellent features 1 2 3 4 5

STRONGLY

DISAGREE STRONGLY

AGREE

7. Amazon’s website provides easy-to-follow search paths 1 2 3 4 5

8. I never feel lost when navigating through Amazon’s website 1 2 3 4 5

9. I was able to obtain the information I wanted without any delay 1 2 3 4 5

96

10. Considering what I would pay for Amazon, I would get much more than

my money’s worth 1 2 3 4 5

11. Amazon has a personality 1 2 3 4 5

12. Amazon is interesting 1 2 3 4 5

13. I have a clear image of the type of person who would use Amazon 1 2 3 4 5

14. I trust the company which makes Amazon 1 2 3 4 5

15. It feels safe to disclose personal information in Amazon 1 2 3 4 5

16. It feels safe to conduct transactions in Amazon 1 2 3 4 5

17. I like the company which makes Amazon 1 2 3 4 5

18. The company which makes Amazon has credibility 1 2 3 4 5

STRONGLY

DISAGREE STRONGLY

AGREE

19. It makes sense use Amazon´s products or services instead of other

competing companies, even if they are the same 1 2 3 4 5

20. Even if other company has the same features as Amazon´s products or

services, I would prefer use Amazon 1 2 3 4 5

21. I would definitely recommend Amazon to friends, neighbours and

relatives 1 2 3 4 5

Consider the following extension:

a) Amazon ebook reader (Kindle)

97

VERY

LITTLE VERY MUCH

22. Overall, how much do you know about products in the ebook reader

category? 1 2 3 4 5

NOT AT ALL

SIMILAR HIGHLY

SIMILAR

23. Think of Amazon. How similar is the typical usage situation of

Amazon´s products with the usage of ebook reader? 1 2 3 4 5

24. Think of Amazon. How similar is Amazon compared with ebook

readers regarding image? 1 2 3 4 5

25. Think of Amazon. How similar is the competence required to

produce Amazon products and ebook readers? 1 2 3 4 5

TOTALLY

DISAGREE TOTALLY

AGREE

26. There is complementarity of Amazon´s products and services and

ebook readers 1 2 3 4 5

STRONGLY

DISAGREE STRONGLY

AGREE

27. Amazon ebook reader is well supported in terms of advertising 1 2 3 4 5

28.Amazon ebook reader receives competent marketing support 1 2 3 4 5

98

STRONGLY

DISAGREE STRONGLY

AGREE

29. Buying an ebook reader is important to me 1 2 3 4 5

30. I know the products offered by the ebook reader category 1 2 3 4 5

STRONGLY

DISAGREE STRONGLY

AGREE

31. Overall, I enjoy buying the latest products 1 2 3 4 5

32. I like to purchase the latest products before others do 1 2 3 4 5

33. Overall, it is exciting to buy the latest products 1 2 3 4 5

STRONGLY

DISAGREE STRONGLY

AGREE

34. Overall, I am very positive to Amazon ebook reader 1 2 3 4 5

NOT AT ALL

LIKELY VERY LIKELY

35. I am likely to try Amazon ebook reader 1 2 3 4 5

ONE OF THE

WORST ONE OF THE

BEST

36. Overall evaluation of Amazon ebook reader relative to existing brands in

mobile phones category 1 2 3 4 5

Finally, answer the following questions about you

What is your age?

( ) 18-24 ( ) 25-34 ( ) 35-45 ( ) 45-55 ( ) 55+

What is your gender?

( ) Male ( ) Female

What is your marital status?

( ) Single ( ) Married ( ) Divorced ( ) Separated

What is your employment status?

( ) Full time employed ( ) Part time employed ( ) Self-employed ( ) Housewife/husband ( ) Unemployed ( ) Retired

What is your highest level of education?

99

( ) Elementary school ( ) High school ( ) College ( ) Graduate school

What is your degree level?

( ) High school diploma ( ) Bachelor's Degree ( ) Masters ( ) PhD ( ) None

What is your nationality?