Final Dissertation Copy

Business-to-Business Brand Extension into Consumer Market

Vivek Narayanan – MA Marketing Dissertation, Kingston University 2009/2010 Page 1

ACKNOWLEDGEMENTS

I owe thanks to several people who have played important roles in facilitating the progress of my

post graduate program at Kingston University and the completion of this dissertation. This

dissertation wouldn‟t have been possible without the expert guidance and support from my

supervisor Stavros P. Kalafatis. He has made available his support in a number of ways, right

from the initial to the final stages of this dissertation. I thank Stavros for all the prompt responses

and forever remain indebted for the valuable insights and motivation he has provided. Next I

would like to thank my course director (MA Marketing, Kingston University) Patricia Harris for

her endless support that began during the early stages of this post graduate course and continued

throughout the course of this dissertation. Next I would like to thank my beloved family for their

long distance support and their confidence in my abilities. Finally, I thank my friends and

colleagues for their scholarly interactions and camaraderie.



ABSTRACT

Leveraging a brand name into a new product category through brand extension facilitates the

success of the new brand extended and considerably reduces the cost involved in introducing a

new product. In the recent years several brand extension studies have been conducted, however

their application in the business-to-business context remains limited. This study attempted to

examine whether B2B brand equity can be leveraged in the consumer market through brand

extension. In-order to substantiate this aim, Phang et al. (2004) B2B to B2C brand extension

model was replicated which measured consumers‟ attitude towards the consumer brand

extension of a B2B parent brand. Besides testing the generalizability and reproducibility of

Phang et al. (2004) the current study also examined cross-sector brand extensions with the

selection of category based extensions. The overall attitude or the extension acceptance was

measured through a set of variables, namely, Brand Knowledge, Quality, CSR, Innovativeness,

Transfer and Difficult. Quality of the parent brand was found to be the only determinant factor

for all the consumer brand extensions. In contrast to Phang et al. (2004) findings skills and

resources of the parent B2B brand was not perceived as transferrable to the category extensions,

thus indicating the risk involved with extending a brand into a different category. As a result of

these findings it was concluded that companies must direct their marketing activities in-order to

enhance their reputation as being socially responsible and innovative which will facilitate the

success of their brand extensions. Furthermore category extensions for B2B brands must be

employed only if necessary.



TABLE OF CONTENTS

Chapter 1

Introduction __________________________________________________________________________ 7

1.1.Background __________________________________________________________________ 8

1.2.Aim and Objective ____________________________________________________________ 11

1.3. Organization of the Dissertation ________________________________________________ 11

Chapter 2

Literature Review ____________________________________________________________________ 13

2.1. Brand and branding __________________________________________________________ 14

2.1.1. Definition of Brand – Then and Now _______________________________________ 14

2.1.2. Business-to-Business Branding ____________________________________________ 15

2.1.3. B2B-Consumer Market Dimensions Continuum ______________________________ 18

2.1.3.1. Contextual Conditions _______________________________________________ 18

2.1.3.2. Psychological Conditions _____________________________________________ 18

2.1.3.3. Product Variables ___________________________________________________ 19

2.1.3.4. Marketing Communication variables ___________________________________ 20

2.2. Brand Extension _____________________________________________________________ 20

2.2.1. Definition of Brand Extension _____________________________________________ 21

2.2.2. Types of Brand Extensions ________________________________________________ 23

2.2.3. Benefits of Brand Extensions ______________________________________________ 24

2.2.4. Drawbacks of Brand Extension ____________________________________________ 25

2.2.5. Consumer Evaluation of Brand Extensions __________________________________ 26

2.2.5.1. Aaker and Keller’s (1990) Consumer Evaluation of Brand Extension _________ 27

2.2.5.2. Business-to-Business Brand Extension: Application of Aaker and Keller (1990) 28

2.3. Problem Statement ___________________________________________________________ 29



Chapter 3

Methodology ________________________________________________________________________ 30

3.1. Research Hypotheses _________________________________________________________ 31

3.1.1. Brand Knowledge _______________________________________________________ 31

3.1.2. Attitude towards the parent brand _________________________________________ 32

3.1.3. Innovativeness __________________________________________________________ 32

3.1.4. Corporate Social Responsibility ___________________________________________ 33

3.1.5. Fit between the original brand and extension: Transfer ________________________ 33

3.1.6. Difficulty ______________________________________________________________ 34

3.1.7. Moderating Factors _____________________________________________________ 34

3.2. Research Design _____________________________________________________________ 35

3.2.1. The current model ______________________________________________________ 37

3.3. Purpose of study _____________________________________________________________ 38

3.4. Type of Investigation _________________________________________________________ 38

3.5. Extent of Interference _________________________________________________________ 38

3.6. Study Setting ________________________________________________________________ 39

3.7. Measures and Measurements ___________________________________________________ 39

3.8. Sampling Design _____________________________________________________________ 40

3.8.1. Definition of Population __________________________________________________ 41

3.8.2. Sampling Frame ________________________________________________________ 41

3.8.3. Sampling Procedure _____________________________________________________ 42

3.8.4. Sample Size ____________________________________________________________ 43

3.9. Data collection Method ________________________________________________________ 43

3.9.1. Quantitative Method ____________________________________________________ 44

3.10. Questionnaire Design ________________________________________________________ 44

3.10.1. Specifying the data required _____________________________________________ 45

3.10.2. Questionnaire Administration Method _____________________________________ 46

3.10.3. Questionnaire Content __________________________________________________ 46

3.10.4. Questionnaire Drafting __________________________________________________ 47

3.10.5. Piloting _______________________________________________________________ 48



Chapter 4

Analysis and Results __________________________________________________________________ 49

4.1. Reliability assessment _________________________________________________________ 50

4.1.1. Cronbach’s alpha _______________________________________________________ 50

4.2. Regression Analysis___________________________________________________________ 51

Chapter 5

Discussion and Conclusion _____________________________________________________________ 62

5.1. Results and Discussion ________________________________________________________ 63

5.2. Summary of Findings and Conclusion ___________________________________________ 68

5.2.1. Theoretical Implications __________________________________________________ 69

5.2.2. Managerial Implications _________________________________________________ 69

5.2.3. Limitations and Suggestions for Future Research _____________________________ 70

REFERENCES _________________________________________________________________ 71

APPENDIX

Appendix 1: Questionnaire Design __________________________________________________ 79



LIST OF TABLES

Table 1.1: Companies formerly operating in Business-to-Business markets only………………..9

Table 4.1: Reliability Assessment (Croncbach‟s Alpha)………………………………………...51

Table 4.2: Estimation of the model and overall fit - Initial Results……………………………...52

Table 4.3: ANOVA Results (Significance Value)……………………………………………….53

Table 4.4: Collinearity Statistics (VIF and Sig Value – Initial Results)…………………………55

Table 4.5: Statistical Significance of Independent Variables……………………………………56

Table 4.6: Estimation of the model and overall fit (R2 and Adjusted R

2 – Final Results)………57

Table 4.7: Independence of Error Terms (Durbin Watson Results)……………………………..59

Table 5.1: Beta Coefficient and Sig Value………………………………………………………63

Table 5.2: Beta Coefficient value for Business-to-Business Product and Service Brands………64

Table 5.3: Phang et al. (2004) Full Model……………………………………………………….64

Table 5.4: Tang et al. (2008) Regression Results for Industrial Brands…………………………65

Table 5.5: Summary of Hypotheses Testing……………………………………………………..68

LIST OF FIGURES

Figure 1: B2B-Consumer Market Dimensions Continuum……………………………………...17

Figure 2: Brand Equity and the Brand Extension………………………………………………..22

Figure 3: Schematic Diagram for the Theoretical Framework…………………………………..36

Figure 4: Steps in Questionnaire Design………………………………………………………...45

Figure 5: Scatterplot……………………………………………………………………………..58

Figure 6: Histogram……………………………………………………………………………...60

Figure 7: Normal P-P Plot of Regression Standardized Residual………………………………..61



This chapter introduces the first chapter by describing the academic background based on which

this study was conducted, followed by defining the aim and objective.

1.1. Background

The ever increasing competition and the constant change in market dynamics has made „brands‟

the center of attention today. The origin of brand development can be traced back to the era of

industrial revolution, where, building a strong brand meant creating quality perceptions as an

assurance for customers (Kotler and Pfoertsch, 2006). In recent years much has been spoken

about brand related quality perceptions, albeit brands deliver other benefits than just providing

quality assurances. Managers today strategically use brands to create value-associations and

launch new products under the same brand name (Kotler and Pfoertsch, 2006). According to

Aaker (2004, pg. 193) the recipe for strategic success is to “create, enhance and leverage assets”

and the most powerful asset to a firm is its brand. A popular trend therefore has been to take a

brand to a new market in order to leverage the equity of an existing brand – brand extensions.

However, marketers have to be careful about achieving growth by reducing the cost of a new

product introduction and the risk of a new product failure.

According to Kapferer (1991), brand extensions can prove advantageous in reducing the cost of a

new product introduction and at the same time increase its chances of success. The rationale why

brand managers employ brand extensions is clear – a well-established brand delivers more than

just a functional utility to the consumer. It gets transformed into a realm of values (Mortimer,

2003). Hence, economically, it makes sense to provide the same emotional benefits, however in a

new market. Since the brand is already well-known, a new product introduction under the same

brand name will be an economically viable option. As functional benefits can be imitated or

substituted, brand extensions is a way of leveraging the intangible attributes of a brand (Urde,

1999).

According to Keller (2003), the issue is not, whether the brand must be extended; it is, when,

where and how to extend a brand. In simple terms, a brand must be extended, if it is possible.



However this does not imply that brand extension is a risk free course of action. It is crucial for

brand managers to have a clear understanding of the brands‟ potential and limitations; extensions

can prove erroneous otherwise (Aaker, 2004).

Most of the research conducted on branding has been in the consumer branding context (Van

Riel et al., 2005; Low and Blois, 2002; Walley et al., 2007; Roberts and Merrilees, 2007;

Morgan et al., 2007; Chaves de Melo, 2009). While the power of branding has been widely

acknowledged in the consumer markets, the nature and importance of branding in industrial

markets, remains under-researched (Brown et al., 2007). The concept of brand management

chain originates from research on consumer market (business-to-consumer). Researchers realized

the importance of branding relatively early in the consumer market, however understanding of its

nature and relevance in the business-to-business (B2B) context remains limited (Mudambi et al.,

2002). Today, there are many successful brands that cater to both industrial as well as consumer

markets. For instance Nokia, now a reputed mobile phone brand first ventured into forestry in

1865, then moved on to selling rubber boots in the 1960‟s (Company website - Nokia). Other

instances include globally recognized companies like Microsoft, IBM and Phillips, who now also

cater to consumer markets, were once B2B centric companies. This suggests that a stretch from

business-to-business to consumer markets is not uncommon (Refer table 1.1).

Many authors in the past have attempted to study the effects of a brand extension (e.g., Aaker

and Keller, 1990; Sunde and Brodie, 1993; Nijssen and Hartman, 1994; Bottomley and Holden,



1996; Van Riel et al., 2002), however their research was limited only to consumer markets. To

the knowledge of the author only two available studies conducted by Phang et al. (2004) and

Tang et al. (2008) provide insights into business-to-business brand extensions. The two studies

examined the reciprocal effects of brand extensions on brand equity based on random choice of

B2B brands and their respective B2C extensions, by replicating the original Aaker and Keller

(1990) model – „consumer evaluations of brand extensions‟. Besides empirically replicating the

Aaker and Keller‟s (1990) study, they examined whether concepts of evaluating brand

extensions could be successfully combined to form an effective model for predicting extension

acceptance within the research context. The basis of the current study is derived from Phang et

al. (2004). This study besides analyzing the generalizability of Phang et al. (2004) model also

examines cross-sector brand extensions with the selection of one „product‟ B2B brand and one

„service‟ B2B brand; and each parent brand will be evaluated on the basis of two B2C

extensions, (a) product offering and (b) service offering.

Collins (1985, p.19) opines that, “replicability…is the supreme court of the scientific system”.

According to Hubbard and Armstrong (1994), other things being equal, a replication study that

observes contrasting results from the original study indicates the need for further research in that

area. On the other hand successful replications (similar observations) instill confidence and

reliability of the results yielded. They further suggest the necessity to examine whether

generalizations can be made across geographical boundaries, populations, products and so on.

Hubbard and Armstrong (1994) further state that “replications with extension serve this function

of assessing whether outcomes can be generalized beyond the original context. They help to

determine the scope and limits of the findings” (p.1). Thus, with a view to contribute to the

extant business-to-business branding literature the current study attempts to replicate Phang et al.

(2004) study in-order to investigate business-to-business brand extensions into consumer market.



1.2. Aim and Objective

The study aims to investigate „business-to-business brand extensions into consumer markets‟.

The following objective is defined in-order,

To predict „overall attitude‟ of consumers‟ towards business-to-consumer brand

extensions through a set of B2B parent brand specific factors and B2C brand extension

specific factors. They are as follows;

B2B parent brand specific factors

1. Brand Knowledge – the level of familiarity with the parent brand.

2. Overall Quality – the perceived quality of the parent brand.

3. Innovativeness – the perceived innovativeness of the parent brand.

4. Corporate Social Responsibility – the perceived corporate social responsibility of the

parent brand.

B2C brand extension specific factors

5. Transfer – transfer of parent brand resources to the brand extension

6. Difficult – the perceived difficulty of making the extension.

1.3. Organization of the Dissertation

Chapter two is dedicated to a review of the literature related to the emergence and importance of

branding in both business-to-business and consumer marketing contexts, followed by a review of

the academic literature on the types, benefits and drawbacks of brand extensions. The third

chapter deals with the methodology employed in the current research, where a discussion about

the research hypotheses and the model used in the current study along with other critical

decisions involved in the research design is presented. The analysis and results of the research



undertaken are discussed in chapter four. The study is concluded in chapter five which is further

divided into two parts; the first part is dedicated to a discussion of the results related to the

research hypotheses and the second part is a discussion on theoretical and managerial

implications of the current study followed by closing perspectives on limitations and directions

for future research. Apart from appendices, the academic journals and books that were referred

to, during the course of this study are also enlisted at the end of this document.



2.1. Brand and branding

Since the purpose of this study is to investigate business-to-business brand extension into

consumer markets, this section is presented in order to develop a preliminary understanding of

the concept of branding in a B2B setting followed by a review of the brand extension literature.

The decision to visit the following literature is based on the necessity to understand the

importance of branding in B2B markets and therefore engage in a discussion on the concept and

emergence of branding from the academic literature (Brown et al., 2007).

2.1.1. Definition of Brand – Then and Now

A dramatic shift was witnessed in the last decade with respect to branding and the role of brands.

Traditionally a brand was viewed as “a name associated with one or more items in the product

line that it used to identify the source of character of the item(s)” (Kotler, 2000, p.396; Guzman,

2005, p.1). In view of the above definition Keller (2003) states, whatever a marketer created

then, a new name, symbol, logo, was considered a brand. The above definition suggests that

previously brands played a simple role of that of identifiers; today however, a brand provides

much more than that (Kotler, 2000).

According to Urde (1999) the importance of a brand was only as much as the functional and

practical utility of a product- “For a long time, the brand has been treated in an off-hand fashion

as a part of the product” (p.119). Kotler (2000) suggests that branding was a major issue in

product strategy. Since a brand was only seen as a part of a product, the communication strategy

was focused solely on creation of the brand image- a tactical element that impetuses short-term

results (Aaker and Joachimsthaler, 2000; Guzman, 2005). Aaker and Joachimsthaler (2000)

further state that prior to realization of the strategic importance of a brand, the branding model

was more tactical and reactive.



Kapferer (1997) mentions that, after the 1980‟s brands were viewed differently; marketers now

saw brands as differentiators rather than just identifiers. One of the most widely used definition

given by the American Marketing Association (AMA) (p.404; cited in Keller et al, 2008, p.2) is,

“a brand is a name, sign, symbol, or design, or a combination of them, intended to identify the

goods or services of one seller or group of sellers and to differentiate from those of competitors”.

Scott Bed-bury (2002), author of the book „A New Brand World‟ puts forward the concept of

„branding‟ as follows, “branding is about taking something common and improving upon it in

ways that make it more valuable and meaningful”. Brands not only help facilitate the

identification of products, services and businesses; they distinguish them from competition

(Kotler, 2000). Heding et al. (2009) state that, “the aim of a brand strategy, is to enhance the

internal and external opportunities of the brand and hence the brand strategy must be strategic,

visionary and proactive, rather than tactical and reactive” (p.15).

Webster and Keller (2004) opine that a brand can be thought of as a “psychological

phenomenon” (p.211). Adding to this Brown et al. (2007) state that the psychological meaning

of a brand is best denoted by two attributes, namely, brand image and brand awareness-

“Customers must know what products and services are associated with a brand (brand

awareness), what attributes and benefits the brand offers (brand value), and what makes the

brand better and distinctive (brand image)” (p.211). Hence Brown et al. (2007) suggest that

much of the branding literature is considered from a consumers‟ perspective and that brand

strategy is superseded by the dynamics of organizational settings.

2.1.2. Business-to-Business Branding

Researchers turned their attention to branding in B2B in the mid-nineties (de Chernatony, 1999;

Hatch and Schultz, 2003). A pronounced distinction between product and corporate brands was

first instituted by King (1991) when he observed the necessity to follow a multidisciplinary

approach to manage brands in a corporate setting. He foresaw the necessity for corporate

branding after observing, that, consumers‟ choices were determined by the associations of the



company behind the product, than the evaluation of the functional utility of it. Urde (2003)

emphasizes the role of a corporate brand when he opines that in a corporate setting, the values of

an organization must reflect through the corporate brand. He further states that the core values of

an organization must facilitate both internal and external opportunities of the brand. In sum,

“corporate brands must communicate the brand‟s values (often seen as a promise), they must

afford a means of differentiation from their competitors, and they must enhance the esteem and

loyalty in which the organisation is held by its stakeholder groups” (Balmer and Gray, 2003,

p.974).

Brown et al. (2007) state that “although branding in consumer contexts has a rich literature, with

a few exceptions, it had been ignored as a significant area of focus by B2B academics” (p.210).

They further opine that there exists an assumption that both markets are too similar and hence

there is a lack of dedicated exploration in business settings. Baumgarth (2010) provides a

different perspective; according to him academic studies have implied that branding has limited

relevance in the business-to-business context. Some empirical studies however (e.g., Abratt et

al., 2004; Cantone et al., 1993; Mudambi et al., 1997) have supported that branding plays a

crucial role in the industrial settings too. To substantiate the difference in the business-to-

business and consumer markets‟, Gilliland and Johnston (1997) proposed the “B2B-Consumer

Market Dimensions Continuum” as a tool to compare both the contexts. They implied that both

differ in terms of their general tendencies (Brown et al., 2007) with respect to contextual

conditions, psychological conditions, product variable and marketing communication variables.

The B2B-Consumer Market Dimensions Continuum is illustrated in figure 1.



Figure 1.The B2B-Conusmer Market Dimensions Continuum

Brown. P. B., Bellenger. N. D., Johnston. J. W. (2007, p.214) „The implications of Business-

to-Business and Consumer Market differences for B2B Branding Strategy‟, Journal of Brand

Management, (1) 3, p.209-229.



2.1.3. B2B-Consumer Market Dimensions Continuum

The following discussion illustrates the difference between business-to-business and consumer

market setting with reference to importance of branding in purchasing decisions.

2.1.3.1. Contextual Conditions

Brown et al. (2007) suggest that the risk involved differs both in magnitude and nature in the

organizational buyers as compared to consumers. McQuiston (1989) observed that the

complexity involved with respect to a purchase decision is more in business setting as compared

to consumer markets. Heilman, Bowman and Wright‟s (2000) theory of “dynamic brand choice”

suggests that, since the level of risk involved in a purchase decision is lower in the consumer

context, buyers are more likely to purchase a less-known brand as compared to organizational

buyers. In consumer markets, central areas like emotions and perceptions play a major role in

determining buyer behaviour. On the other hand in a business setting the buyer is more

concerned with functionality and performance of the vendor (Anderson & Narus, 2004).

According to Aaker (2004) brands provide an aspirational value to consumers whereas in a

business setting, brands are means of strategic alliance.

The distinctions in each context suggest unique marketing approaches and, thus, unique branding

approaches.

2.1.3.2. Psychological Conditions

The role of a brand as a risk reducing agent is likely to differ in both settings. The level of

anxiety experienced by a buyer also differs. This anxiety affects their purchase decisions and

their choice of goods in terms of the product‟s price, quality, performance, services and usability

(Brown et al., 2007). Organizational purchases may force the buyers to consult informal or

personal sources for information (De Chernatony and Mc Donald, 1998), even contacting with



sales representatives. Consumers on the other hand seek information from peers or reference

groups or observe their behavior which influences their purchase decisions (Fiegenbaum and

Thomas, 1995). Adding to the nature of buyer behavior in both contexts Minett (2002) suggests

that a purchase decision in the consumer context is most often impulsive whereas organizational

purchases are carefully planned actions. Brown et al. (2007) states that, “in business settings,

buyers are more likely to be influenced by objective and expert testimonials or the actual

performance of referent firms”.

2.1.3.3. Product Variables

According to Gilliland and Johnston (1997) and Brown et al. (2007) when discussing brand‟s

effect on a buyer, in organizational marketing (e.g., IBM, Du Pont, BASF, and CISCO) brands

are often treated as vendors. They suggest that there exists a “continuum of corporate branding

endorsement levels”, (p.219) where one end of the continuum is referred to as umbrella

branding, corporate branding, or a branded house strategy and the other end is referred to as the

product brand or a “house-of-brands” where a brand name for individual line of products is

different from the company name. Corporate branding is “a systematically planned and

implemented process of creating and maintaining a favourable reputation of an organization and

its constituent elements, by sending signals to stakeholders using the corporate brand” (Van Riel

and Van Bruggen, 2002, p.242; also cited in Brown et al., 2007, p.219). Michell et al. (2001) and

Shipley and Howard (1993) opine that in any purchase within a corporate setting, the suppliers‟

corporate image plays a pivotal role. More than the individual product brands, company‟s name

and reputation come first. In the same context Michell et al. (2001) further suggest that the buyer

will not only evaluate the functional benefits of a product, but will also critically assess the

company‟s personnel, their skills and resources.



2.1.3.4. Marketing Communication variables

Gilliland and Johnston (1997, p.16; also cited in Brown et al., 2007, p.223) argue that “the

inherent differences between B2B marketing and consumer marketing results in important

differences in how marketing communication tools are processed and acted on by their targets”.

Supporting the above view, Brown et al. (2007) view that both the settings, with respect to their

communication strategies, differ in terms of the content communicated and the mediums

employed. They further suggest that, in contrast to traditional consumer marketing

communication techniques, which are normally interactive, personal and iconic messages, B2B

communication is more personal and interactive.

In conclusion, the above discussed B2B-Consumer Market Dimensions Continuum highlights

the role of a brand in a business setting, suggesting that it is likely to be sufficiently different in a

consumer setting.

2.2. Brand Extension

As mentioned previously the importance of branding in business-to-business context remains

under-researched [Refer section 2.1.2]. Thus, knowledge on the application of a brand extension

strategy in the B2B context also remains limited. However, in-order to develop a preliminary

understanding of the concept of brand extension, this section is dedicated to a discussion on

consumer brand extension from the academic literature. This section will furthermore provide

information on the types, benefits and drawbacks of brand extensions.

In-order comprehend the meaning of a brand extension better, selected definitions of „brand

extension‟ are enlisted in the following section from the academic literature followed by a

discussion on the same.



2.2.1. Definition of Brand Extension

One of the widely used definitions given by Keller (2003, pg. 577) of brand extension is “when a

firm uses an established brand name to introduce a new product”. Tauber (1981) defines brand

extension as “using the leverage of a well-known brand name in one category to launch a new

product in a different category”.

Given that a new product failure, financially affects a firm, marketing academics and

practitioners have been working towards developing methods and strategies in-order to enhance

the likelihood of a new product success (Sirdeshmukh, 1995; Urban and Hauser, 1980). Aaker

(2004) suggests, a firm can achieve and maintain its competitive advantage by targeting

untapped markets. Entering into new markets implies introduction of a new brand, which is risky

and expensive (Kapferer, 1991). Hence Aaker (2004) suggests that leveraging an existing brand

through brand extension, must be the preferred option. Introducing new products through market

innovation and by extending them as new brands can help to continue the desired growth (Keller,

2003).

The strategy of a brand extension is based on the notion that the positive-image of the parent

brand, that has been established through previous marketing efforts; will stimulate favourable

consumer perceptions towards the extension (Sirdeshmukh, 1995; Aaker, 2004). Lattin and

Bucklin (1989) and Kalwani and Yim (1992) state that there is a certain perception of risk

involved when making a purchase decision. A brand name helps to minimize the perceived risk

in consumers. Consumers use a brand name as proxy for quality assurance; as a result the

assurances are reinstated towards the newly extended brand, given that it bears the same parent

brand name (Maheswaran et al., 1992), thus, facilitating the consumer decision making process

(Sirdeshmukh, 1995).



Figure 2.Brand Equity and the Brand Extension

Aaker, D. A. (2004, p.201) Brand portfolio strategy, New York: The Free Press, p.13–14.

Brown (2007) suggests that everything that a brand stands for is captured in the concept of brand

equity. Aaker (2004) in his book „Brand portfolio strategy‟ opines that brand equity can have

both negative and positive effect on the extension. The illustration above [See Figure 2] also

indicates that an extension can equally affect the equity of a brand negatively (ugly) and

positively (good). Aaker (2004) opines that most often the effect of an extension on the parent

brand equity is not acknowledged, although the impact of an extension will only be visible in the

long run. Aaker (2004) states that the intensity of the effect in both directions depends in the

strength of the brand equity and brand fit.



2.2.2. Types of Brand Extensions

In this section we will review the two basic forms of brand extensions,

1. Line extension: They are the simplest form of brand extension. The idea is to make some

innovation or addition to the existing line of product for a new market within the same

category (Nijssen, 1999).

An established brand becomes stale overtime hence it becomes necessary to revitalize the

existing brand by introducing some newness; this is called product development-

introducing a new product in an existing market. Morgan and Hunt (1999) opine that

product features are those intangible resources that a firm possesses which can be easily

substituted and imitated by competitors, hence in-order to maintain the competitive

advantage, it becomes essential for a firm to constantly keep innovating. Firms

continuously cater to line extension strategy in-order to maintain their competitive

position in the market (Aaker and McLoughlin, 2007).

2. Category extension: When the parent brand is applied to a new category from the one it

currently serves (Aaker and Keller, 1990). The idea is to capitalize on a firms‟ perceived

expertise (Kim et al., 2001).

Aaker and Mcloughlin (2007) suggest that firms employ diversification strategy when

they want to enter a different product market than the one that they currently serve.

Diversification provides an opportunity for growth and revitalization as firms venture

into new markets with new products. Firms generally diversify by leveraging their parent

brand equity into a new market through category extension, although it is subject to

substantial risk if done erroneously (Aaker and McLoughlin, 2007).

Farquhar et al. (1990) in their study on „relational model for category extensions of

brands‟, suggest that leveraging a brands‟ equity through extensions to new categories



carries both opportunities and risks. Category extensions facilitate immediate name

recognition and the transfer of benefits associated with a familiar brand. On the other

hand contending the use of a category extension strategy Ries and Trout (1986) suggest

that a brand may be harmed due to over extension of the brand name. They further state

that an entire brand franchise may be diluted due to an extension into a new category.

Since consumers perceive a brand to only cater to specific class offerings, an extension to

a different category may not be accepted (Ries and Trout, 1986).

The following section will review the positive and negative effects of a brand extension,

2.2.3. Benefits of Brand Extensions

Aaker (2004) suggests that a brand can be extended for various other strategic reasons; they are

enlisted as follows;

To enhance the new brands visibility and image: Consumers form expectations and

draw conclusions about a new product on the basis of its association with the existing

brand (Keller, 2003). Consumers carry an image of the existing parent brand and this

knowledge reduces their anxiety about the potential performance of the new product

(Keller, 2003). The positive associations of consumers with the parent brand, also

enhances the likelihood of trial of an extension compared to new products that bear

relatively a non-established brand name (Winters, 1993; Aaker, 1992).

To create communication efficiencies: The distribution costs and other related direct

and in-direct costs for promoting the new brand extension also reduces to a great extent

on account of the associations with the parent brand image. A well-established brand will

always rank high on its awareness with consumers; this awareness in turn facilitates the

extension, hence expenses towards promotion of the new product (introduction/follow-up

ads and marketing programmes) are also greatly reduced (Aaker, 2004). This effect was



demonstrated by Smith (1992) when he compared new brand introductions and brand

extensions; he found that the advertising to sales ratio was significantly lower for brand

extensions.

To enhance parent brand image: As a strategic initiative, in-case a brand needs to shift

from its existing image in the market, the desired associations can be facilitated through a

brand extension (Aaker, 2004). As parent brand image propels the acceptance of the new

brand extended [See point 1]; a brand extension contributes equally to enhance the image

of the parent brand (Keller, 2003). An extension also helps to re-instill the „brand

meaning‟ and define the boundaries of the domain in which it competes (Phang et al.,

2004; Keller, 2003). Morrin (1999) further suggests that the exposure of an extension will

facilitate parent brand awareness with respect to its recall and recognition.

Provide a source of energy: Kapferer (1991) and Aaker (2004) opine that a new brand

can renew interest and improve attitude towards the parent brand; especially a brand that

is established and tired.

2.2.4. Drawbacks of Brand Extension

According to Aaker (2004) and Keller (2003) the „brand name‟ is the most important asset to a

firm. A faulty extension can have an adverse effect on the parent brand name; hence an extension

strategy must be carefully executed.

Diluting existing associations with the parent brand: According to Aaker (2004) just

like an extension can enable re-installation of the brand meaning, it can also reduce a

brands‟ credibility in the market. Keller (2003) mentions the direct relationship between

the parent brand and its extensions. According to Keller the image of a parent brand is

affected irrespective of whether the extension is a success or failure. Brand extensions if

unsuccessful erode the existing parent brand image and reduce the brand awareness



considerably creating ambiguity in the brand meaning (Morrin, 1999).

Aaker and Keller (1992) observe that a negative evaluation of an extension sometimes

leads to negative evaluations for the subsequent extensions. Sullivan (1990) reports the

results from a research conducted on automobile brands; negative news about a certain

automobile brand significantly affected other models that bore the same brand name,

causing depreciation in their resale value.

Undesirable attribute associations: Most often fresh attributes are created with a brand

extension. The newly formed attributes of the extension if perceived as inconsistent or

conflicting with that of the parent brand; can be potentially damaging to the image of the

parent brand (Keller, 2003 and Aaker, 2004).

Diluting parent brand identity: Too many brand extensions can blur the brand identity,

resulting in confusion about the brand meaning in the minds of the consumers.

Furthermore Loken & John (1993) state that the parent brand name may be diminished

due to the failure of the brand extension. Extensions that remains unable to capitalize on

the parent brands image further cause damage to the parent brand name by diluting brand

image (Schlossberg, 1990; Brown, 1992). Brown (1992) illustrates this effect by giving

the example of the irreparable damage caused to Pierre Cardin and its prestige status due

the licensing of its brand name to approximately 850 products available world-wide.

2.2.5. Consumer Evaluation of Brand Extensions

A seminal study conducted by Aaker & Keller (1990) provided insights in to those constructs of

brand extensions that influenced consumers‟ attitude towards the extended brand. In their

exploratory study, qualitative, correlational and experimental research methods were used where

the data was collected from student population (Barrett et al, 1999). Aaker and Keller‟s (1990)

brand extension framework has been subject to immense scrutiny in the past. The correlational



aspect of their research has been replicated widely by several theorists like Sunde & Brodie

(1993), Nijssen & Hartman (1994), Bottomley & Doyle (1996).

2.2.5.1. Aaker and Keller’s (1990) Consumer Evaluation of Brand Extension

Aaker and Keller (1990) proposed a brand extension model based on the overall attitude of the

consumers. In other words, “the consumers‟ attitude towards the brand extension is a positive

function of the quality of the parent brand, the fit between the parent‟s brand category and the

extension category (measured in terms of transferability of skills and expertise from one category

to the other and the complementarity and substitutability of one category and the other), the

interaction of quality with three fit variables and the degree of difficulty in designing and making

a product in the extension category” (Bottomley and Holden, 2001, p. 495).

Summarizing the above factors that were stated as being crucial in determining the success of the

extended brand were (Aaker & Keller, 1990, p.29; Barrett et al, 1999),

"Attitude towards the original brand";

"Fit between the original parent brand and extension product classes".

"Perceived difficulty of making the extension"

Aaker and Keller (1990, p.30) further observed that „fit‟ was a function of three dimensions, they

are as follows,

“Complement: The extent to which consumers view two product classes as complements

Substitute: The extent to which consumers view two product classes as substitutes

Transfer: How consumers view relationships (design or making) in product

manufacture”.



Despite the fact that there have been wide acceptance and diffusion of Aaker and Keller‟s (1990)

findings, the subsequent replications provided varying results. Aaker and Keller (1990) in their

study concluded that they found no significant correlation between perceived quality of the

parent brand and its brand extensions. Bottomley and Holden (2001) after examining seven other

empirical replications of the original Aaker and Keller (1990) study, found that, (a) quality of the

parent brand and fit between the parent brand and the extension were the most determinant

factors in evaluating consumers attitude towards an extension.

2.2.5.2. Business-to-Business Brand Extension: Application of Aaker and Keller (1990) model

To the knowledge of the author only two studies have provided insights into the possibility of

extending a business-to-business brand. Phang et al. (2004) and Tang et al. (2008) in their study

examined the reciprocal effects of brand extensions on brand equity based on random choice of

B2B brands and their respective B2C extensions. They empirically replicated Aaker and Keller‟s

(1990) study on consumer evaluations of brand extension discussed above. In-order to examine

the application of brand extension in the business-to-business domain, they had to modify the

original Aaker and Keller (1990) model. Besides linking theory from consumer branding to

corporate branding, they also examined, extension acceptance in the B2B context by combing

different concepts of evaluating brand extensions. Besides the possibility of extending business-

to-business brands into the consumer market, in their study they found that variables

corresponding to the Aaker and Keller (1990) study were highly significant in explaining the

extension evaluation. They further observed that the effect of fit variable superseded that of other

variables. They concluded that besides perceptions of transferability and quality; the perceived

innovativeness and corporate social responsibility also played a large role in determining a

consumer‟s attitude towards a B2C brand extension.

Since Aaker and Keller‟s (1990) study forms the basis of several brand extension evaluation

studies including Phang et al. (2004), Tang et al. (2008) and in a way the current study; the

above discussion was dedicated to consumer evaluations of brand extension.



2.3. Problem Statement

Phang et al. (2004) and Tang et al. (2008) in their study only examined cross-sector extensions

(i.e. B2B to B2C), where the choice of extensions used, belonged to same class offering as the

parent brand. In other words, if the B2B parent brand was a product offering, the respective

consumer extension chosen was also a product offering; similar for service brands. Thus,

knowledge about consumers‟ attitude towards an extension, belonging to a non-related class

offering remains limited.

With a view to contribute to filling this gap, the current study examines cross-sector brand

extensions with the selection of one „product‟ B2B brand and one „service‟ B2B brand, where

each parent brand will be evaluated on the basis of two B2C extensions, (a) product offering and

(b) service offering. The brand extensions selected will be category based, i.e. they may not

belong to the parent brand class offering. Selection of category extensions will furthermore

provide insights on the overall attitude of consumers towards non-related brand extensions.



In this chapter we outline the strategy that was employed in this research, followed by a

discussion on the critical decisions involved in the research.

3.1. Research Hypotheses

The basis of this research is derived from a similar study conducted by Phang et al. (2004). The

author empirically replicated the Aaker & Keller (1990) model within the research context (i.e.,

business to business brand extension into consumer market). Realizing the nature of the current

study the same constructs as in Phang et al. (2004) will be used; except for the two fit variables

namely, Complementarity and Substitutability (from Aaker and Keller, 1990) and moderating

factors (from Phang et al., 2004).

3.1.1. Brand Knowledge

Keller (2003) suggests, in-order to draw conclusions about a brand‟s quality it is a prerequisite

that one has to be familiar with the brand. Thorbjornsen (2005) supporting the above view

suggests that brand knowledge is an important variable for determining parent brand feed-back

effects. “The level of familiarity with the parent brand influences the way in which consumers

process information about the brand extension” (p.250). Hence if the appropriateness of the

extension is to be evaluated, knowledge of the parent brand is necessary (Thorbjornsen, 2005).

Therefore we hypothesize the following:

H1: Higher degrees of knowledge about the business-to-business parent brand are associated

with more favourable attitudes toward the consumer brand extension.



3.1.2. Attitude towards the parent brand

Aaker and Keller (1990) conceptualize overall attitude in terms of consumer‟s perception of the

overall quality of the brand. According to Zeithaml (1988) quality is often used by consumers as

an assessment of a products superiority or excellence. Explaining the effects of perceived quality

she further states that inferior quality perceptions toward the parent brand can prove harmful for

an extension and on the other hand high quality perceptions toward the parent brand can benefit

an extension. Aaker and Keller (1990) in their study concluded that they found no significant

correlation between perceived quality of the parent brand and its brand extensions. However,

subsequent replications that followed have (e.g., Sunde and Brodie, 1993; Bottomley and

Holden, 2001; Phang et al., 2004; Tang et al., 2008) found a direct positive correlation between

perceived quality of the parent brand and the extension. Therefore we hypothesize the following:

H2: Higher quality perceptions towards the business-to business parent brand are associated

with more favourable attitudes towards the brand extension.

3.1.3. Innovativeness

According to Aaker and Keller (1998) marketing efforts directed towards product innovativeness

lead to perceptions of corporate expertise and thus have a positive impact on corporate brand

extensions. They further state that, being an innovator induces perceptions of being up-to-date

with technology, engineering and other specialized skills facilitating positive consumer

evaluations of the extension. Therefore we hypothesize the following:

H3: Higher perceptions of innovativeness toward the business-to-business parent brand are

associated with more favourable attitudes toward the consumer brand extension.



3.1.4. Corporate Social Responsibility

Aaker and Keller (1998) suggest that “corporate marketing activity can provide a direct

marketing benefit by improving perceptions and evaluations of a corporate brand extension”.

They further suggest that the credibility and trustworthiness of the firm will be lauded if

marketing activities are directed towards the environment and community. Supporting the above

view, Kitchen (2003) states that it is this undeniable responsibility, of all corporate firms to

deliver betterment programs directed towards the environment and society that enhances the

image of the parent brand and the new brands introduced.

In the study conducted by Phang et al. (2004), corporate social responsibility and environmental

concerns were treated as separate variables. In the current study environmental concerns was

included as a part of CSR with a view of the change in policy against CSR by the European

Commission (2006, p.2) where CSR is defined as “a concept whereby companies integrate social

and environmental concerns in their business operations and in their interaction with their stake

holders on a voluntary basis”. Therefore we hypothesize the following hypothesis:

H3: Perceptions of corporate social responsibility of the parent business-to-business brand has

no effect on the attitude towards the consumer brand extension.

3.1.5. Fit between the original brand and extension: Transfer

Boush and Loken (1991) propose that, if the parent brand and the extension are perceived as

being similar, the attribute associations of the original brand are transferred to the extension.

Aaker and Keller (1990) put forth a similar view that, if consumers perceive a „fit‟ between the

parent brand and the extension, it will help transfer quality perceptions of the parent brand to the

new brand extension. They further state, “if there exists‟ a poor fit, it will not only detract from

the transfer of positive associations, but may actually stimulate undesirable beliefs and

associations” (p.30). Therefore we hypothesize the following:



H2: The transfer of a business-to-business parent brand’s perceived quality is enhanced when

the product classes (of the parent and the consumer brand extension) in some way fit together.

When the fit is weak, the transfer is inhibited.

Aaker and Keller (1990) hypothesized two other dimensions of fit, namely, Complementarity

and Substitutability. When the parent brand and the extension can be consumed together, they

complement each other and on the other hand, if the extension can be utilized as a replacement of

the parent brand, the extension is a substitute. According to Bottomely and Holden (2001) a

brand extension by definition cannot substitute a parent brand. In the current research context

complement cannot serve as an evaluation dimension as the end customers of the parent brand

and the extension are different. Hence the two dimensions will be omitted to keep within the

scope of this research.

3.1.6. Difficulty

Aaker and Keller (1990) give us the last variable difficulty, which refers to the perceived

difficulty of making the brand extension. They state that if a brand is perceived to be too easy or

too difficult to make, it generates a negative attitude towards the extension. Therefore we

hypothesize the following:

H4: The relationship between the difficulty of making the product class of the extension and

the attitude toward the extension is positive.

3.1.7. Moderating Factors

Aguinis (1995) suggests “the existence of a moderating effect implies that the relationship

between two variables varies as a function of the value of a third variable, labeled a moderator”.

Many studies over the years have made use of moderator variables. However concerns regarding

the difficulties involved in the use of moderator variables have been raised in the recent past by



some authors (e.g., Aguinis, 1995; Cronbach, 1987). Aguinis (1995) suggests that conclusions

regarding moderator variable hypothesis may lead to incorrect inferences, indicating no

moderating effect. Further contending the use of moderator variables he states that moderator

variables generally generate very low statistical significance value. In a multiple regression

analysis, significance is the probability of rejecting a null hypothesis of no moderating effect. In

case the significance value generated by the model is low, the statistical error becomes higher

(Evans, 1985; McClelland & Judd, 1993). As a result researchers may erroneously dismiss

models that include moderating effects. Some interaction effects were assessed by Phang et al.

(2004) in addition to the above described effects. However, in the current study, the inclusion of

any moderating factors has been avoided due to the aforesaid reasons.

3.2. Research Design

Based on the reasoning in section 3.1, the following research model was developed containing

the factors that was used to predict overall attitude of consumers towards the B2C brand

extensions. The [+/-] signs next to the independent variables denote whether the type of

relationship with the dependent variable is positive or negative. The variables or factors that will

be used in this study to examine consumer evaluations of brand extensions (within the research

context), are illustrated below;



Figure 3. Schematic diagram for theoretical framework



3.2.1. The current model

Y = α + β 1 K + β 2 Q + β 3 I + β 4 C + β 5 T + β 6 D + Ɛ

Where the dependent variable,

Y = attitude towards the brand extension = [likelihood of purchase + overall quality]/2

And where the independent variables,

K = Parent Brand Knowledge

Q = Overall Quality

I = Innovativeness

C = Corporate Social Responsibility

T = Transfer

D = Difficult

In other words, the consumers‟ attitude towards the brand extension is a positive function of the

familiarity with the business-to-business parent brand, quality of the business-to-business parent

brand, the fit between the business-to-business parent brand category and the consumer

extension category (measured in terms of transferability of skills and expertise from one category

to the other), the perceived innovativeness and the perceived corporate social responsibility of

the business-to-business parent brand and the degree of difficulty in designing and making the

consumer extension.



Jankowicz (2005) opines that a method is a systemic and orderly approach taken towards the

collection and analysis of data so that accurate and consistent inferences can be made from the

results yielded (p.220). Hence the necessity for the following, structured approach.

3.3. Purpose of study

A research can be classified either as (a) exploratory, (b) descriptive or (c) hypothesis testing

based on the purpose of its study (Sekaran, 2000). The current study followed a deductive

approach, where the research model was tested using constructs and conclusions were made by

interpreting the meaning of the results from the data analyzed. Hence, hypothesis testing was the

purpose of this study.

3.4. Type of Investigation

Sekaran (2000) opines that the type of investigation to be employed must be clearly determined

for any research. An investigation is either (a) causal or (b) correlational. The former helps to

establish a cause and effect relationship among the constructs and the latter helps to understand

the associations between constructs. Jankowicz (2005) mentions that a causal investigation “goes

beyond simple exploration and description, it looks for reasons of the events or situations being

studied” (p.199). Since the objective was to predict „Overall Attitude‟ towards the B2C

extensions through a set of independent variables, the nature of this study was causal.

3.5. Extent of Interference

Sekaran (2000) opines that the extent of interference by the researcher depends on the type of

investigation employed for a research - causal or correlational. In a correlational study there is

minimum interference from the researcher and the study occurs in a natural environment

(Sekaran, 2000). On the other hand in a causal research the researcher tends to manipulate



certain variables so as to observe the effects of the manipulated variables on the dependent

variable (Sekaran, 2000). In the current study, the extent of interference was minimal as

manipulation of variables was not essential since the variations were to occur naturally within the

independent variables.

3.6. Study Setting

A study can be conducted in either a (a) contrived or (b) non-contrived setting (Sekaran, 2000).

A contrived setting is when the researcher modifies and manipulates the natural environment; in

contrast a non-contrived setting is when the events are allowed to transpire naturally without any

modification to the environment (Sekaran, 2000). Sekaran (2000) also states that a research that

aims to predict a cause-effect relationship using the same natural environment, where

interference is as much as the manipulation with the independent variables, are called field

experiments. Although the nature of the current study was causal, the extent of interference was

minimal from the researcher hence the study was piloted in a non-contrived setting.

3.7. Measures and Measurements

Sekaran (2003) opines that in-order to measure variables, there are four basic scales available to

a researcher, namely, (a) nominal, (b) interval, (c) ordinal and (d) ratio. Since the objective was

to predict overall attitude by measuring variables, the scale used was interval. On an “interval

scale the distances between each interval on the scale are equal, right along the scale, from the

low end to the high end” (Wharrad, 2004, p.1). The following properties of the interval made it

appropriate scale for this study, (1) According to Hair et al. (2003) an interval scale allows the

differences between each interval points on the scale to be meaningfully interpreted; (2) They

further mention that an interval scale contains the properties if both ordinal and nominal scales,

enabling complicated calculations; (3) There is no absolute zero in an interval scale. In other

words zero is arbitrary in an interval scale. Since a zero point could not be used for variables

affecting overall attitude, the interval scale was used; further restricting the use of a ratio scale.



There are different types of scales available to a researcher, such as Staple scale, Thurstone

differential scale, Likert scale etc. in order to measure attitude and its components (Albaum,

1997). Ajzen (2005, pg. 3) defines attitude as “a disposition to respond favourably or

unfavourably to an object, person, event or institution”. Ajzen (2005) suggests that attitude is a

hypothetical construct; and due to its inaccessibility to direct observation, inferences can be

made only through measurable responses.

Aaker and Keller (1990), Sunde and Brodie (1993), Bottomley and Doyle (1996), Phang et al.

(2004), Tang et al. (2008), in their study to evaluate consumer brand extensions used a 7 point

likert scale, an interval scale, to assess overall quality of each parent brand and their respective

extensions (where 1= poor and 7= outstanding). A likert scale measures attitude through a series

of questions, to which a respondent records his/her degree of agreement or disagreement

(Albaum, 1997; Brody & Dietz, 1997; Likert, 1932). Since the objective is to measure attitude

towards B2C brand extensions, likert scale which is a widely used rating scale will be used in the

current research. Moreover respondents are generally well aware of its usage and it is easy to

construct and administer a likert scale (Albaum, 1997). The rest of the variables, brand

knowledge, innovativeness, corporate social responsibility, transfer and difficult will also be

measured through a 7 point likert scale where 1= totally disagree and 7 = totally agree.

3.8. Sampling Design

According to Kent (2007) the quality of the research is affected by the quality of the sample

chosen and hence sample design forms an integral part of the overall research design. Sample

designs for any research are “unique combination of elements” (pg. 235) and hence the following

factors must be taken into consideration when determining the sample design.



3.8.1. Definition of Population

Kent (2007) defines „cases‟ as “entities whose characteristics are being recorded by the

researcher or elements who possess the information sought by the researcher” (pg. 227). A

quantitative research requires more than just one or two cases; a large set of cases. This set of

cases is the population. According to Malhotra and Birks (2006) „population‟ is defined in terms

element, sampling unit, extent and time. „Element‟ is the object from which information is

desired (Chaves de Melo, 2009); in the case of a survey research it is generally the respondent.

The original Aaker and Keller (1990) study as well as many others that followed including

Phang et al. (2004) had samples drawn from student population. Hence the element in the current

study was also „students‟. Whatever entity is being sampled is referred to as the „sampling unit‟

(Kent, 2007). In the current study the sampling unit was Kingston University. „Extent‟ refers to

the geographical boundaries of the research (Chaves de Melo, 2009; Kent, 2007). As this study

was conducted within UK, the extent was defined as UK. „Time‟ refers to the period in which the

research was conducted. The current study was conducted in the year 2010.

3.8.2. Sampling Frame

Kent (2007, pg. 231) defines „sampling frame‟ as “a complete list of units (See sampling unit,

section 6.7.1) from which the sample is drawn”. In the current study the survey was conducted

solely at Kingston University Business School, UK; where the respondents were students of the

university. Since the sample population was adequately specified and easily accessible, a

sampling frame was not required in the current study.



3.8.3. Sampling Procedure

Sampling Procedure can be classified as either, (a) Probability or (b) Non-Probability sampling

(Malhotra and Birks, 2006).

(a) Probability Sampling: Probability samples, also known as random samples are ones in

which each member of the population have a known chance of being selected (Kent,

2007; Malhotra and Birks, 2006). There are four kinds of probability (sampling, namely,

stratified, systematic, cluster and simple random sampling (Kent, 2007).

(b) Non-Probability Sampling: In non-probability sampling as the selection is subjective

the chances of selecting a case from the population of cases is not calculable (Kent,

2007). In other words the selection of samples is non-random where some units are more

likely to be selected than others (Chaves de Melo, 2009; Malhotra and Birks, 2006). Non-

probability sampling can be classified into four types, namely, snowball, quota,

judgemental and convenience sampling (Kent, 2007).

Prior to deciding on the sampling technique to be employed for any research factors like time

and cost constraints and the research objectives must be taken into consideration. According to

Jankowicz (2005) convenience sampling technique incurs minimal expenditure and is less time

consuming. Moreover the sample population is also easily accessible. Here respondents are

chosen based on the convenience of the researcher (Kent, 2007). Convenience sampling, a non-

probability sampling technique was employed for the current study. In this sampling technique

the respondents are readily available.



3.8.4. Sample Size

The statistical and technical team of the National Audit Office (1999) suggests that three factors

must be considered before determining the sample size, which are as follows;

1. Margin of error: The estimate taken from samples is subject to some inexactness, hence

there will be some margin of error with inference to the population. The larger the sample

size, the less is the margin of error.

2. Amount of variability: It refers to the range of values and opinions of the population.

The more the variability, lesser the accuracy in the estimate taken from a sample and thus

it affects the size of the sample required.

3. Confidence level: It refers to the level of certainty that the population figure is within the

sample estimate. The higher the confidence level the researcher wishes to have, the larger

the size of the sample needs to be.

However, in Phang et al. (2004) study, a total of 103 students were sampled. Since the current

study also examines the generalizability and reproducibility of the above mentioned study a

sample size of 100 students (minimum) was selected.

3.9. Data collection Method

According to Kent (2007), data is commonly treated as “the facts”. Simply put, they are a

collection of records that have been systematically constructed by researchers or individuals.

There are different types of data; one of them being primary and secondary data. The former

consists of data that have been specifically constructed for the project at hand and the latter

consists of data that was constructed for previous projects/study. In the current study both

primary data collection techniques will be employed as primary data is more accommodating and

provides latest information (Jankowicz, 2005).



3.9.1. Quantitative Method

The two types of primary data are (a) quantitative and (b) qualitative data. Kent (2007) states that

“Quantitative data are derived from numerical records; sometimes these numbers refer to

magnitudes or calibrations recorded in respect of an individual or a group of individuals” (pg.

117). On the other hand qualitative data consists of “words, phrases, text or images” (Kent, 2007,

pg. 87).

According to Fielding and Pillinger (2008), in-order to draw scientific generalizations from the

samples chosen than a broader population a quantitative approach is useful. Moreover to

formally test hypotheses a quantitative study is required. Also as the current study is a replication

of Phang et al. (2004), the same data collection method, i.e. quantitative, was used. Since attitude

is the dependent variable, the quantitative data focuses on assessing consumers‟ evaluation of

brand extensions by measurement of attitude in relation to the previously discussed variables.

3.10. Questionnaire Design

After evaluating various quantitative data collection techniques; collection of data via paper

questionnaires was employed. Kent (2007, pg. 151) defines a questionnaire as “any document

that is used as an instrument with which to capture data generated by asking people questions

and which furthermore: 1) lists all the questions a researcher wishes to address to each

respondent, 2) provides space or some mechanism for recording the responses, 3) puts questions

in a logical sequence, 4) draws accurate information from respondents, 5) standardizes the

format of the questions and 6) facilitates data processing”. In other words, questionnaires help

systemize the data collection process and therefore help in achieving consistent results which can

be analyzed in a coherent manner (Kent, 2007).

Although different researchers will have different approaches towards designing a questionnaire,

the current study follows the stages prescribed by Kent (2007).



The stages involved in a questionnaire design are depicted in the figure below;

Figure 4. Steps in questionnaire design

Kent, R. (2007, p.152) Marketing Research: Approaches, Methods and Applications in

Europe, High Holborn House: Thomson Learning.

3.10.1. Specifying the data required

According to Kent (2007) for an academic researcher there will be ambiguity on the kind of data

to be collected; hence the research proposal serves as a point of reference for the researcher.

Since the current study is a replication of a previously conducted research, there is more

specificity with respect to the data that is required. Since the current research attempts to



examine consumer attitude towards a brand extension, the data required are the consumers‟

responses towards the consumer brand extensions with respect to a set of B2B parent brand

specific factors and B2C brand extension specific factors. They are as follows;

B2B parent brand specific factors: Brand Knowledge, Overall Quality, Innovativeness,

Corporate Social Responsibility

B2C brand extension specific factors: Transfer, Difficult

3.10.2. Questionnaire Administration Method

A questionnaire may be administered face-to-face, over the telephone, via post or electronically.

According to Jankowicz (2005), in contrast to the other techniques face-to-face surveys offer

many advantages to the researcher. A face-to-face survey solves obstacles such as incomplete

subject lists; respondents who do not have access to a computer or telephones can be contacted

easily; moreover in face-to-face administration of questionnaires, as the interviewer is present to

prompt and guide the respondents, more complex and varied questions can be included (Kent,

2007). Taking the above factors into consideration the questionnaires were administered face-to-

face at Kingston University.

According to Collis and Hussey (2009) face-to-face questionnaires can be, either (a) interviewee

orientated or (b) interviewer orientated. In the latter the interviewer asks questions to the

respondents and records the answers himself. In the former, it is the respondent who records the

answers into the questionnaire; as was the case in the current study.

3.10.3. Questionnaire Content

At this stage the wording, format and the layout of the questionnaire was critically examined.

The questionnaire prioritized using structured questions; only questions that were relevant to the

research objectives were included in the questionnaire. As the questionnaire was being



administered to individuals who had no in-depth knowledge about the study, it was crucial to

phrase the questions in a way that was easy to comprehend. In the current study, the

questionnaire was derived from the original Phang et al. (2004) study. However, besides

including questions pertaining to the amended constructs, certain business jargons that were used

in Phang et al. (2004) were replaced with simple words, within the research context. Two

globally recognized B2B brands were chosen for this study, namely, Xerox and DHL. The

following scenario for both brands was created, explaining the consumer brand extensions,

XEROX has identified a flourishing market for „digital cameras‟ and with a view of the growing

trend in sharing images and pictures on the web, „web album‟ by Xerox is also being introduced.

Both will be available to you by the end of this year.

DHL commits its expertise in international express, air and ocean freight, road and rail

transportation and international mail services to its customers. To cover all of your extensive

service needs with the right level of focus and expertise, DHL now also plans to operate as

„Packers and Movers‟. Also a thoughtful, stylish & innovative product to make travel more

enjoyable DHL will soon introduce its „travel luggage product line‟.

Furthermore the inclusion of sensitive details about respondents, except for demographics such

as age and gender, was avoided.

3.10.4. Questionnaire Drafting

At this stage special attention was given to the sequence of questions, assuring that the

respondent relates to the subsequent question. This is called routing, defined by Kent (2007, pg.

153) as “guiding whoever is completing a questionnaire to answer questions that are appropriate

when these depend on responses to earlier questions”. As already mentioned [Refer section

3.1.1], in-order to draw conclusions about a brand‟s quality it is a prerequisite that one has to be

familiar with the brand, hence questions pertaining to brand knowledge were specified first,

followed by quality. Attention was also given to the sequence of the questions pertaining to



business-to-business parent brand specific factors and consumer brand extension specific factors.

The latter were specified first followed by consumer brand extension specific questions.

3.10.5. Piloting

Bryman and Bell (2003) opine that pilot-testing is particularly essential when the questionnaire is

interviewee orientated, which was the case in this study. Pilot-testing helps to identify those set

of questions that the respondents may feel are ambiguous or are uncomfortable with (Bryman

and Bell, 2003). Kent (2007, pg. 154) opines that Pilot-testing helps to identify those questions

that “(1) do not mean what the researcher intended, (2) have been missed out completely, (3)

people do not understand or find too difficult, (4) everybody gives the same answer to, i.e. do not

discriminate, (5) give response categories that do not allow some respondents to answer in ways

that are relevant to them, (6) have routings that leave the respondent „stranded‟ in the middle of

the questionnaire or lead them to inappropriate sections of the questionnaire”.

Since the response was based on a limited set of brands, the concern was more regarding the

choice of B2B brands and their respective B2C brand extensions. A set of fifty students of

Kingston Business School were administered the pilot questionnaire. Based on the results of the

Pilot-testing, amendments were made to the choice of B2C brand extensions and the final draft

was prepared. The final questionnaire is presented in the appendix section.



Since the objective was to predict the „Overall Attitude‟ towards the B2C extensions through a

set of independent variables the appropriate test to employ was multiple regression. It helps to

understand how independent variables explain the dependent variable collectively and

individually (Kent, 2007). Assuming the relationship to be linear, a multiple linear Regression

test to examine the relationship between the dependent variable „Overall Attitude‟ and six

independent variables namely; „Brand Knowledge, Overall Quality, Corporate Social

Responsibility, Innovativeness, Transfer and Difficult‟; was used.

4.1. Reliability assessment

Reliability is used when predictions are made by variables that are developed through summation

of scales in objective models. It is essential to examine if the respondents would elicit similar

responses if encountered with same questions at a different time scale. The variables are said to

be reliable if consistent responses are elicited by respondents every time the test is administered

to them (Cronbach, 1951). According to Osborne and Waters (2002) as more independent

variables are added to the regression equation with low levels of reliability, the likelihood that

the variances accounted for will not be distributed proportionately, increases. These inconsistent,

un-apportioned variances may lead to erroneous findings. Hence it is necessary to check for

reliability before performing a regression analysis.

4.1.1. Cronbach’s alpha

Cronbach‟s alpha serves as the numerical coefficient of reliability (Hatcher, 1994). “It is the

average of all possible split half coefficients resulting from different ways of splitting the scale

items” (Cronbach, 1951; Phang et al, 2004, pg. 47). As a rule of thumb an alpha value of 0.7 and

more is considered reliable (Malhotra and Birks, 2003). However the alpha value tends to go up

as the number of scale items increase. In the current study as there are only two to three items per

construct the benchmark will be 0.5.



The reliability assessment revealed that the two independent variables, „Corporate Social

Responsibility and Innovativeness‟ had an alpha coefficient exceeding 0.5. Consumers‟

evaluation of brand extensions was measured by the dependent variable „Overall Attitude‟ which

is the average of two variables, (a) the perceived overall quality of the extension and, (b) the

likelihood of purchasing the extension, had an alpha coefficient above 0.5 (for all four B2C

extensions) and hence all the variables were considered reliable. The table 4.1 below presents a

summary of the results yielded from the analysis.

4.2. Regression Analysis

Multiple Regression analysis consists of five steps, 1) Estimating the regression model and

examining overall fit; 2) eliminating outliers and checking for multicollinearity; 3) checking if

variables are statistically significant; 4) displaying results; 5) checking if the four assumptions

are met (Hair et al., 2006; Chaves de Melo, 2009).



Step 1 - Estimating the Regression Model and Examining Overall Fit

PASW (Predictive Analytics Software) was used to carry out multiple regression. To estimate

the regression model and assess the overall fit the R2

was first examined, which indicates the

goodness of fit of the model or how much collectively the independent variables explain total

variation on the dependent variable (Hair et al., 2006). Information presented in Table 4.2 below

is a summary of the R square and the adjusted R square values- “the deflated estimate that takes

into account the number of variables and sample size” (Kent, 2007, p.411).

However, prior to drawing any conclusions about overall fit of the model, it is crucial to negate

any concerns of model over-fitting. The closer the adjusted R2 is to R

2, the less is the concern of

over-fitting. The table 4.1 above indicates that the adjusted R2 is close to R

2; however a formal

test is necessary to examine the statistical significance of R2.

The test is based on the probability that the R2 across the sample size will not be equal to zero

(Hair et al., 2006). Prior to conducting the test a level of significance needs to be determined



which denotes that R2 could be equal to zero. The significance level used is 0.05. The same will

be used in the rest of this study.

The following hypothesis was formulated;

H0: R2 = 0 or all regression coefficients are zero

HA: R2 > 0 or not all regression coefficients are zero – significantly greater than zero.

α = 5% (level of significance)

The table 4.3 indicates that the significance for all the B2C brand extensions were high (sig <

0.05). On the strength of this the null hypothesis was rejected; which means that all R2 are

greater than zero and/or that not all regression coefficients are equal to zero.



Step 2 - Checking Outliers and Multicollinearity

The next step involved is eliminating outliers and checking for multicollinearity. According to

Hair et al. (2006), outliers are atypical (by definition) infrequent observations. The inclusion of

even one outlier has a significant influence on the slope of the line of regression. Hence it is

necessary to eliminate outliers from the dataset. The „Casewise Diagnostics‟ table on PASW

output; indicates the presence of outliers in the dataset. As the output did not produce a Casewise

Diagnostics table, it was taken that there were no outliers present in any of the regressions.

O'Brien (2007) explains that independent variables are said to be multicollinear if there exists a

high correlation among them. In other words the multicollinear variables explain the dependent

variable on the same terms. Ideally there must be a high correlation between the independent and

the dependent variable and not in-between the independent variables. Incase the independent

variables are found to be multicollinear, they have to be eliminated from the model.

The VIF (Variance Inflation Factor) value indicates whether there exists multicollinearity

between any independent variables. A VIF value exceeding 10 suggests high correlation between

those independent variables. The table 4.4 below suggests that VIF value for all the independent

variables (for all four B2C brand extensions) is well below 10 and hence negates any concerns of

multicollinearity between the independent variables (Kleinbaum et al., 2008).



Step 3 - Examining Statistical Significance of Independent Variables

According to Hair et al. (2006), assessing the statistical significance of variables is deemed

important at this stage as this analysis is performed on the basis of a sample population and not

on a census. Like the R2 was tested previously, this test is also based on the probability that the

coefficients across the sample size will not be equal to zero.

The following hypothesis was formulated for each independent variable;

H0: The coefficient of „Brand Knowledge‟ equals zero

HA: The coefficient of „Brand Knowledge‟ is not equal to zero – Significantly different

from zero

α = 5% (level of significance)

The table above (see sig. value for all four B2C extensions) indicates that only „Overall Quality‟

is significant for all four brand extensions (sig < 0.05). Also „Transfer‟ variable is significant for



Xerox Web Album. On the strength of this, at this stage, we reject H0 only for „Overall Quality‟

(for all four B2C extensions) and also for „Transfer‟ (only Xerox Web Album); which means that

only the above mentioned coefficients are not zero. Now, since not all the independent variables

were statistically significant, we eliminated variables that had the lowest significance (sig > 0.05)

one by one, starting with the highest significance value. Only the significance value for

„Difficult‟ changed from 0.056 to 0.040 which was below 0.05 (sig < 0.05). Elimination of other

non-significant variables showed no signs of change in the remaining variables for all four brand

extensions. Hence on the strength on this we reject H0 for „Difficult‟ variable (only for DHL

Packers & Movers). A summary of the same is displayed in table 4.5.

Step 4 - Displaying Results

At this stage after the elimination of non-significant variables the multiple Regression test was

run again. Now, we realized that the R2 values for all four brand extensions model had changed;

the adjusted R2 were now closer to the R

2 value in contrast to the initial analysis. A summary of

the final results are shown in table 4.6. The closeness of the R2 and the adjusted R

2 values negate

concerns of over-fitting for the existing models.



Step 5 - Checking Assumptions

The assumptions can be assessed by examining the residuals. The following assumptions will

explain if our data is suitable for linear regression (Hair et al., 2006);

1. Homoscedasticity – variance of error terms

2. Independence of error terms

3. Linearity

4. Normally distributed error terms

Homoscedasticity

Homoscedasticity refers to equality of variances of the error. The scatterplot of residuals reflects

the constant variances of error terms. Ideally the concentration of scores must be along the zero

line in the centre. The scatterplots for all the four B2C brand extensions showed a widespread

distribution of scores on both sides of the zero line; suggesting that this assumption was partially

met [See Figure 5].



Figure 5. Scatterplot

Independence of error terms

Independence of error term refers to the individuality of each predicted value. In other words it

determines whether there is a relation between the predicted value and any other prediction (Hair

et al., 2006). The Durbin Watson test determines the error dependency of the predicted value. As

a rule of thumb the Durbin Watson value must be between 1.5 and 2.5 to satisfy this assumption.

An assessment of the Durbin Watson value for three B2C brand extensions showed values

between the given benchmarks, except for DHL Packers and Movers (2.551). Since the value

was not a notable deviation from the benchmark, it was accepted. A summary of the Durbin

Watson results is displayed in the table 4.7 below.



Normally distributed error terms

Normally distributed error terms refer to the normal distribution of residuals around the predicted

scores of the dependent variable (Pallant, 2005). Normality can be assessed by examining the

histogram of residuals. The histogram for Xerox Digital Camera and DHL Packers & Movers

shows a slight positive skewness whereas the histogram for Xerox Web Album and DHL Travel

Luggage has a negative skewness. The histogram for all four B2C extensions, form a bell-shaped

curve suggesting that this assumption was met [See Figure 6].



Figure 6. Histogram

Linearity

This is an assumption that suggests that the underlying relationship between the residuals and the

dependent variable follow a straight line. Linearity can be assessed through the Normal P-P Plot

of Regression Standardized Residuals. The P-P Plots [See P-P Plot Graph, Figure 7] indicate that

most residuals follow the straight line, suggesting that the data broadly follows a normal

distribution. On the strength of this observation we conclude that the assumption of linearity was

fully met.



Figure 7. Normal P-P Plot of Regression Standardized Residual

Since all four assumptions were partially/fully met, the above model was considered acceptable

for performing a legitimate regression analysis.



This section is divided into two parts; the first part is dedicated to a discussion of the results

related to the research hypotheses. The second part presents a discussion on theoretical and

managerial implications, followed by a discussion on limitations and directions for future

research.

5.1. Results and Discussion

As the findings of this study are based on a limited set of brands; generalizations beyond that set

is avoided in the following discussion;

The following tables illustrate the beta coefficient and significance values of the current study as

well as the significance values of both Phang et al. (2004) and Tang et al. (2008). To effectively

compare the yielded results, the following tables are presented.



Source: Phang et al. (2004, p. 55)



Source: Tang et al. (2008, p. 408)

1. H1. Brand Knowledge: The results from the analysis for Brand Knowledge showed no

significant effect on the dependent variable (Overall Attitude), which is in line with

Phang et al. (2004) findings [Refer Table 5.1 and 5.3]. In other words Brand Knowledge

is not a significant determinate for either product or service. The rationale for this effect

could be that the above mentioned brand extensions were perhaps considered unrealistic

by the respondents. Hence, on the strength of the above results we conclude that Brand

Knowledge remains to be an insufficient condition for evaluating brand extensions. The

fact that Brand Knowledge was not significant for any of the brand extensions also

suggests that a cognitive processing of a brand is essential to evaluate an extension (Fiske

and Pavelchak, 1986) than just familiarity with the brand name.

2. H2. Overall Quality: The factor with the highest positive effect on Overall Attitude was

the perceived Overall Quality of the parent B2B brand. The results suggested that the

inferred attribute beliefs enhance the evaluation of a B2B to B2C brand extension.

Similar observations were also made by Phang et al. (2004) and Tang et al. (2008),



[Refer Table 5.3 and 5.4] where their findings (consistent with the current study)

indicated a positive correlation of regression weights, between Overall Quality of the

parent B2B brand and the Overall Attitude of their respective B2C brand extensions

[Refer Table 5.1]. This suggests that consumers are able to draw some inferences about

overall quality of the brands, even with their lack of experience with B2B brands. The

beta value at the brand extension level was highest for DHL (B2C product) extension

„Travel Luggage‟ at 0.753 [Refer Table 5.1] suggesting that quality perceptions of DHL

service B2B brand was most significant in determining overall attitude towards the above

mentioned brand extension. This further suggests that quality perceptions towards the

DHL brand is associated with more favourable attitudes toward the above mentioned

DHL extension. Beta coefficients for B2B product and service brands indicate that

perceptions of quality are significant in both offerings.

3. H3. Innovativeness: In contrast to Phang et al. (2004) findings, innovativeness was

found to be an insufficient factor to evaluate a consumer brand extension. The beta values

further suggest that innovativeness is a lesser predictor of Overall Attitude than Quality.

Except for Xerox Web Album (-.213) [See Table 5.1] all the other B2C extensions had a

positive beta value suggesting that perceptions of innovativeness towards the B2B Xerox

brand are not favourably associated with attitudes towards Xerox Web Album service

brand extension. The above results also support Nijssen et al. (2006) observations that, as

a product extension may use current products‟ and processes‟ technology, it will be

subject to minimal change in manufacturing staff‟s capabilities; a service extension on

the other hand may require resources/ staff to learn or master new service procedures. On

the strength of the regression analysis results for all for B2C brand extensions we reject

this hypothesis.

4. H4. Corporate Social Responsibility: In contrast to Phang et al. (2004) findings, we

observe that CSR is an insufficient determinant to evaluate a consumer brand extension.

There is a noteworthy difference in the importance of CSR when products and service

brands are compared; beta is higher and positive for B2B product brands than service



brands [Refer Table 5.2]. A possibility for the inflation of beta coefficients could be

because the response from the sample population was brand specific. Also as

environmental concerns was included as a part of CSR in this study with a view of the

change in policy against CSR by the European Commission, 2006 (CSR is defined as a

concept whereby companies integrate social and environmental concerns in their

business operations and in their interaction with their stake holders on a voluntary basis)

the beta values are observed differently for CSR in the current study. At the brand

extension level the beta values for both DHL brand extensions, namely, DHL Travel

Luggage (product) and DHL Packers and Movers (service) had a negative value [Refer

Table 5.1] suggesting that the perceptions of Corporate Social Responsibility toward the

B2B service brand DHL has a negative effect on the attitude towards its B2C brand

extensions. On the strength of the results yielded from the regression analysis we accept

that perceptions of corporate social responsibility of the parent B2B brand has no effect

on the attitude towards the consumer brand extension.

5. H5. Transfer: Transfer a fit variable, in contrast to Phang et al. (2004) and Tang et al.

(2008), was not a substantial enough condition to evaluate a consumer brand extension of

a B2B parent brand. It was found to be significant only for Xerox Web Album service

brand extension [Refer Table 5.1; 5.3 and 5.4]. However the beta value was negative for

the above mentioned B2C brand extension suggesting that the B2C extension was

considered unrealistic by the respondents [See H1]. A comparison between B2B product

and service brands with a negative beta coefficient suggest that current skills and

resources of a company are not perceived as being transferrable form B2B to B2C

markets. In conclusion the B2C brand extensions lack ‘fit’ with their respective parent

brands (except for Xerox Web Album).

6. H6. Difficult: The difficult variable was found to be significant only for DHL Packers

and Movers B2C service brand extension. Also both the product brand extensions

namely, Xerox Digital Camera and DHL Travel Luggage; had negative beta values of -

0.006 and -0.007 [Refer Table 5.1] respectively suggesting that consumers perceived



B2C „product‟ extensions to be more difficult to make than service brand extensions. On

comparing B2B product and service brands we found that beta value (positive) for

service B2B brand (DHL) was more than product B2B brand (Xerox) which is in line

with our observations at the extension level that manufacturing a product extension is

more difficult than establishing a service brand extension [Refer Table 5.2].

5.2. Summary of Findings and Conclusion

As already established, by Phang et al. (2004) and Tang et al. (2008) the possibility of extending

business-to-business brands into consumer markets is re-substantiated by the current study.

However there is a significant difference in the results yielded in the current study as compared

to Phang et al. (2004) and Tang et al. (2008). The varying results could be because of the B2C

extensions chosen for this study, i.e. product and service extensions for each B2B brand.

However, Overall Quality remains to be a significant factor in evaluating a brand extension. The

observations‟ from the above findings is summarized in the table below.



5.2.1. Theoretical Implications

The current study contributed to the extant academic literature in the following way; it provided

evidence on the attitudes of consumers with respect to consumer brand extensions belonging to

non-related class offerings. Ries and Trout‟s (1990) observations were further substantiated by

the findings in this study, i.e. a brand extension different from the parent brand category may not

be accepted by the consumers. This also suggests a greater lack of fit with category extensions.

Secondly the current study also provides evidence that Phang et al. (2004) model can be

contextually adapted for evidence on B2B extensions.

5.2.2. Managerial Implications

“Whether to extend a B2B brand to a consumer market remains a predominantly managerial

topic” (Phang et al., 2004), thus this study further contributes to the management of business-to-

business brands. As already mentioned there is a lack of theoretical evidence on the brand

extension strategy in the business-to-business context. After examining the feasibility of

extending a B2B brand using category based extensions, we conclude that the brand extension

will be most successful if there exists‟ a fit between the parent brand B2B brand and the

consumer extension. Results also showed that, the quality of the parent brand plays an important

role in brand extension acceptance and hence a well-established brand with higher perceptions of

quality is more likely to have a successful extension. Furthermore this study suggests that

managers must be careful about the choice of extension for a B2B brand. If possible they must

extend the brand within the same category. There is a risk involved in detaching the brand

extension category, since the attribute associations or resources may not be perceived as

transferrable to the extended brand. Factors like CSR and Innovativeness were found to have no

significant effect on extension acceptance. Since the findings were based on a limited set of

brands (Xerox and DHL), it would be reasonable to mention that, companies must direct their

marketing activities in-order to enhance their reputation as being socially responsible and

innovative which will facilitate the success of their brand extensions.



5.2.3. Limitations and Suggestions for Future Research

There are certain limitations to this study which indicates the scope for future research. Firstly,

brand extensions were measured only from the consumers‟ perspective. As also addressed by

Phang et al. (2004) it will be relevant in the context of this study to take into account the

perspective of the existing B2B customers (B2B buyers) about the consumer brand extensions. In

other words, “the reciprocal impacts of consumer brand extensions on brand equity can be

measured with respect to both consumers and business-to-business customers” (Phang et al.,

2004). Secondly, the sample population chosen for Aaker and Keller‟s (1990) consumer

evaluations of brand extensions and the subsequent replications including Phang et al. (2004)

and the current study were students. Students may not necessarily represent the general

population. In other words, students may not be the end consumers of the brand extensions.

Hence for future research a sample other than students is recommended. Thirdly, the B2B brands

were randomly selected for this study. A preliminary research on popular B2B brands and their

inclusion in the survey may reflect a more appropriate evaluation of the brand extensions and the

degree of fit with the parent brand.



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APPENDIX

Appendix 1: Questionnaire Design

Final Dissertation Copy

Documents

Transcript of Final Dissertation Copy