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This article was downloaded by: [Memorial University of Newfoundland]On: 02 August 2014, At: 05:20Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
Journal of Marketing ManagementPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/rjmm20
Evaluating brand extensions, fitperceptions and post-extension brandimage: does size matter?Francesca Dall’Olmo Rileya, Chris Handa & Francesca Guidoa
a Kingston University Business School, Kingston University, UKPublished online: 27 Jun 2014.
To cite this article: Francesca Dall’Olmo Riley, Chris Hand & Francesca Guido (2014) Evaluatingbrand extensions, fit perceptions and post-extension brand image: does size matter?, Journal ofMarketing Management, 30:9-10, 904-924, DOI: 10.1080/0267257X.2014.926962
To link to this article: http://dx.doi.org/10.1080/0267257X.2014.926962
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Evaluating brand extensions, fit perceptions andpost-extension brand image: does size matter?
Francesca Dall’Olmo Riley, Kingston University Business School,Kingston University, UK
Chris Hand, Kingston University Business School, Kingston University,UK
Francesca Guido, Kingston University Business School, KingstonUniversity, UK
Abstract This study contributes to the scant literature considering brandextensions in a competitive context and investigates whether the correlationbetween consumers’ beliefs about a brand’s attributes and the number of itsbuyers described in previous research occurs with regard to fit perceptions ofbrand extensions, extension evaluation and post-extension brand image. In ascenario experiment with real brands and fictitious extensions, members of acommercial UK panel evaluated high and low-fit extensions and post-extensionbrand images of competing brands of pet food. The relative size of each brand interms of the number of its buyers was used as a benchmark in the analysis. Forall extensions, results reveal a positive correlation between post-extensionbrand images, extension evaluations, fit perceptions and the number of brandbuyers. Results have implications for interpreting consumers’ perceptions of fit,evaluation of extensions and post-extension brand images of competing brands.
Keywords brand image; brand extension; fit; brand usage; double jeopardy
Introduction
Within the vast literature on brand extensions there is broad agreement amongresearchers that consumers’ evaluations of a brand’s extension depend on factorsrelated to the parent brand’s image, the extended category, perceived fit andconsumer characteristics (e.g. Aaker & Keller, 1990; Bhat & Reddy, 2001; Boush& Loken, 1991; Czellar, 2003; Reast, 2005; Völckner & Sattler, 2006; Zhang &Sood, 2002). Overall, brand image and perceived fit are considered to be of majorimportance in brand extension evaluations (Völckner & Sattler, 2006). In turn,consumers’ evaluations of a brand’s extension may affect the post-extension imageof the parent brand, in either a positive or a negative manner (e.g. Lane & Jacobson,1997; Loken & John, 1993).
The construct of brand image pulls together all the possible associations related toattributes, benefits and attitudes stored in consumers’ minds as a network consisting
Journal of Marketing Management, 2014Vol. 30, Nos. 9–10, 904–924, http://dx.doi.org/10.1080/0267257X.2014.926962
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of concepts and links (Anderson, 1983; Keller, 1993; Morrin, 1999). In the contextof brand extensions, pre-extension brand image reduces perceived risk andimproves the evaluation of the new good or service (Czellar, 2003; Milewicz &Herbig, 1994). For consumers, the brand can act as a signal of the quality of thenew product (Wernerfelt, 1988) and the evaluation process will be the result ofintegrating information about the parent brand with information arising from thenew item (Anderson, 1981). Focusing on specific types of brand associations,several authors have shown that extension evaluation depends on perceptions ofbrand quality (van Riel, Lemmink, & Ouwersloot, 2001; Völckner & Sattler,2006), affection for the brand (Sheinin & Schmitt, 1994) and reputation (Hem,de Chernatony, & Iversen, 2003).
Perceived fit is a crucial factor for the success of a brand extension as well as forpost-extension brand image. Fit refers to the degree of proximity between the brandand the new product (Czellar, 2003; Lei, Dawar, & Lemmink, 2008). As a basis of fitevaluation, consumers can assess the degree of category fit or similarity between thenew product and the pre-existing ones, and the image fit or general coherence withthe parent brand’s image (Bhat & Reddy, 2001; Czellar, 2003; Grime,Diamantopoulos, & Smith, 2002). Whatever the case, the higher the fit, the morepositive will be consumers’ evaluations of the extension (e.g. Boush & Loken, 1991;Seltene, 2004). According to categorisation and scheme-congruence theories, thecategorisation of the brand extension as a member of the parent brand categorytriggers the transference of perceptions and emotions stored in consumers’ minds(Boush & Loken, 1991; Park, Milberg, & Lawson, 1991). For this reason, theperceived fit between a brand and a new product will positively influence theevaluation of the extension (Aaker & Keller, 1990; Völckner & Sattler, 2006).Apart from influencing consumers’ evaluations of the extension, perceived fit alsohas a positive effect on the post-extension image of the parent brand itself (John,Loken, & Joiner, 1998; Loken & John, 1993). Conversely, the lower the perceivedfit, the higher the dilution of brand image (Loken & John, 1993; Martínez & deChernatony, 2004; Park, McCarthy, & Milberg, 1993).
A common feature of this well-established body of literature is the use of scenario-based experiments employing real brand(s) and fictitious extensions. The use offictitious extensions is useful as it enables the manipulation of the degree of fitwith the parent brand and with its ‘normal’ product/service offering. Typically,respondents are asked to evaluate the extension and the post-extension brandimage either of a single or, at most, of pairs of brands differing on a specificcharacteristic, such as quality (high versus low) or brand positioning (luxury versusfunctional) or the type of brand (products versus services) (e.g. Aaker & Keller, 1990;Kim, Lavack, & Smith, 2001; Pina, Dall’Olmo Riley, & Lomax, 2013). Thelimitation of focusing on one or, at most, two brands is that even the most realisticexperiments ignore an important reality, since ‘(their) participants evaluate extensionsin the absence of competition, although consumers rarely do so’ (Milberg, Sinn, &Goodstein, 2010, p. 544). In reality consumers are often faced with a choice betweenvery similar extensions of competing brands, and hence they need to evaluateextensions and their fit in relative terms, particularly from the point of view ofimage fit.
Only a handful of brand extension studies has implicitly or explicitly consideredcompetitive effects. These exceptions include Sullivan’s (1992) and Oakley,Duhachek, Balachander and Sriram’s (2008) studies on the effect of the relative
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order of entry of extensions on their performance and Smith and Park’s (Smith &Park, 1992) research on the effect of the number of competitors on brand extensionsuccess. More recently, Milberg et al. (2010) investigated the impact of relative brandfamiliarity on extension evaluations among competing alternatives, while Meyvis,Goldsmith and Dhar (2012) tested how the availability of comparison brands affectsconsumer choices between extensions of better-fitting brands and extensions ofhigher quality brands. These studies have highlighted the importance of consideringthe relative competitive position of a brand in predicting the success of its extensions.For example, Milberg et al. (2010, p. 549) have shown that ‘fit effects are qualifiedby the competitive set into which the brand extension enters’ and that extensions of afamiliar brand perform better, regardless of fit, compared with high-fit extensions ofunfamiliar competitors. Similarly, Meyvis et al. (2012) found that, in a competitivesetting, the quality of the parent brand is more important than fit in the evaluation ofthe brand extension.
Our study contributes to the scant literature considering brand extensions in acompetitive context. Specifically, we address the fact that no previous study hassystematically compared how consumers evaluate the extensions of competingbrands within a product category and no previous research has considered thepotential effect of a brand’s number of buyers (i.e. its relative size) on consumers’perceptions of fit, on their general evaluations of the extension and on the resultingpost-extension brand image. Yet, empirical evidence over the past 40 years hasconsistently shown a usage factor, namely a strong correlation between consumers’beliefs about a brand’s attributes (e.g. ‘is good value for money’) with the brand’s size,in terms of the number of its buyers (or users) (e.g. Barwise & Ehrenberg, 1985; Bird& Ehrenberg, 1970; Castleberry & Ehrenberg, 1990; Romaniuk, Sharp, &Ehrenberg, 2007). We argue that a similar brand usage factor should also manifestitself in the context of other types of brand perceptions, namely extensionsevaluations, image fit, category fit and post-extension brand image. This goesbeyond the already known potential differences between how users and non-usersof a brand evaluate its extensions (e.g. Fu, Ding, & Qu, 2009; Kirmani, Sood, &Bridges, 1999).
With the purpose of investigating whether the usage factor described in previousresearch (e.g. Castleberry & Ehrenberg, 1990) does occur in the context of fitperceptions and of extension evaluations, this study compares consumers’evaluations of the extensions of competing brands within a product category (petfood). The initial (pre-extension) and final (post-extension) brand images ofcompeting brands are also compared in a similar manner. It should be noted that inthis paper we measure the percentage of respondents claiming to have ever bought(rather than ‘used’) a brand, although we employ the term usage factor. This isconsistent with Castleberry and Ehrenberg’s (Castleberry & Ehrenberg, 1990)original conceptualisation of usage factor to indicate the relationship between thepercentage of a brand’s buyers and the percentage of respondents stating a positivebelief about a brand.
The paper is structured as follows. The next section discusses the conceptualdevelopment of the hypotheses. This is followed by the research design andmethodology for the study. Then the paper presents the results of the hypothesestesting. In the final section, the paper discusses conclusions and implications of theresults.
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Development of hypotheses
There is extensive evidence showing that how many people state a favourable beliefabout a brand generally varies with howmany of them buy the brand and how often theydo so. If fewer people give a positive response (e.g. ‘tastes nice’) for brand B than forbrand A, this is mainly related to the fact that B has a lower market share and fewerfrequent buyers or users. This has been found for many different product categories overthe past 40 years, in different countries, and for free- and forced-choice questioning (e.g.Barnard & Ehrenberg, 1990; Barwise & Ehrenberg, 1985; Bird & Ehrenberg, 1970;Castleberry& Ehrenberg, 1990; Driesener& Romaniuk, 2006; Romaniuk et al., 2007).The explanation, as extensively documented in these references, is that very frequent orrecent buyers or ‘users’ of a brand nearly all say or imply that they ‘like it’ (e.g. that thebrand ‘tastes nice’, or thatmore generally they ‘intend to buy it’). In contrast, fewer of theless-frequent or less-recent buyers of the brand give such positive responses (say half),fewer still among infrequent buyers (about 20%), let alone among those who claim neveror virtually never to have bought the brand (about 10%). Since a small brand B hasrelatively fewer frequent (and fairly frequent) buyers comparedwith a big brand A, fewerpeople overall tend to give B a positive attribute response. But this is not because thebuyers of brand B feel differently about B from how buyers of A feel about A, but ratherbecause B has fewer buyers (i.e. a structural market share effect, rather than a ‘brandequity’ or ‘brand engagement’ effect).
We argue that this usage factor should manifest itself also when consumers’perceptions of fit and overall extension evaluations of different brands within aproduct category are considered and we expect to find a positive correlation withthe relative size of each brand, in terms of the number of its buyers.
As extensively discussed in the brand extension literature, fit can reflect both theperceived similarity between the new extension product and the one(s) normallyassociated with the parent brand and the image fit or general coherence of theextension with the parent brand’s image (Bhat & Reddy, 2001; Czellar, 2003; Grimeet al., 2002). We argue that since fit consists of perceptions relating to the parent brand,in terms of either its image or its category associations, perceived fit responses are similarin nature to other types of attribute belief responses to a brand (which generally varywithhow many people buy the brand). Based on this reasoning, we postulate:
H1. The higher the number of buyers of a brand, the greater the perception of fitbetween the brand and its extensions.
Similarly, brand image in general, as well as specific aspects relating to the parentbrand’s quality and its reputation are known to affect the evaluation of its extensions(Czellar, 2003; Hem et al., 2003; van Riel et al., 2001; Völckner & Sattler, 2006).Since consumers’ beliefs about a brand’s attributes strongly correlate with brand size,in terms of the number of brand buyers (or users) (e.g. Barwise & Ehrenberg, 1985;Castleberry & Ehrenberg, 1990), we expect that larger brands (i.e. brands with agreater number of buyers) will also achieve more positive evaluations for theirextensions than smaller brands (with fewer buyers). Hence we postulate:
H2. The higher the number of buyers of a brand, the more positive is theevaluation of its extensions.
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We also expect that since consumers’ beliefs about a brand’s attributes generallycorrelate with brand size (Castleberry & Ehrenberg, 1990), not only the initial pre-extension brand images, but also the final post-extension brand images will bepositively correlated with the brands’ number of buyers. With regard to the post-extension brand image, our expectation also follows logically from the previous twohypotheses that perceptions of fit and extension evaluation will be higher for brandswith a larger number of buyers and from earlier literature indicating that perceived fitand extension evaluation have a positive feedback effect on the post-extension imageof the parent brand (John et al., 1998; Loken & John, 1993; Martínez & Pina,2009). Hence our third hypothesis states:
H3. The higher the number of buyers of a brand, the more positive are the initialand the final brand image.
A further pattern repeatedly observed by researchers is that even among regular‘users’ of each brand (however usership may have been defined) fewer give afavourable response for a small than for a large brand (Barnard & Ehrenberg,1990; Dall'Olmo Riley, Ehrenberg, Castleberry, Barwise, & Barnard, 1997;Ehrenberg, Goodhardt, & Barwise, 1990). This variation in the number of users ofdifferent brands who ‘like’ them does not appear to be specific to the characteristicsof the particular brands, but is structural in nature: the fewer the number of brandusers (i.e. for the smaller brand B), the fewer of these fewer users also say that they‘like’ the brand. This is the so-called phenomenon of Double Jeopardy (DJ), firstnoticed by the sociologist McPhee. The theoretical explanation of DJ (McPhee,1963) is a statistical selection effect that happens every time two or more items(such as brands) only differ in their popularity (or their sizes) but are otherwise of‘equal merit’. DJ has been found to occur for a variety of loyalty and liking measureswhen consumers choose between or evaluate brands that are similar but differ in theirmarket share (Ehrenberg et al., 1990; Ehrenberg, Uncles, & Goodhardt, 2004). Sincefit perceptions, extension evaluations and pre- as well as post-extension brand imageare measures of consumers’ liking of the brand and its extensions, we argue that theDJ phenomenon should manifest itself also in this context. Hence we hypothesise:
H4a. Fit perceptions will be lower among the users of a small brand than amongthe users of a big brand.
H4b. Extension evaluations will be lower among the users of a small brand thanamong the users of a big brand.
H4c. Pre- and post-extension brand image will be lower among the users of asmall brand than among the users of a big brand.
Methodology
The pet food market was considered an appropriate setting for the study, since buyersof pet food do not purchase a brand for their own personal consumption. There isevidence in the literature that less direct experience leads to less concrete categoryand product knowledge and greater reliance on more general impressions about abrand (Dillon, Madden, Kirmani, & Mukherjee, 2001 cited in Czellar (2003)).
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Hence, any differences between pet food brands in fit perceptions, extensionevaluation and pre- and post-extension brand image are not likely to be related tobuyers of brand B having a different experience of B from how buyers of Aexperience A. We could therefore test more clearly for any patterns in the resultsindicating structural size effects like the ones we hypothesised.
The four top brands of dog food in the UK were used in the study: Pedigree,Bakers, Winalot and Cesar (Mintel Reports, 2012). The first three brands offer asimilar range of products at similar prices, but differ in terms of sales (andconsequently their market share): Pedigree sales = £202m; Bakers = £126m; andWinalot = £48m (Mintel Reports, 2012). The smallest brand Cesar (sales = £34 m,Ibid.) is a premium priced brand, offers only ‘wet’ food and its ‘tray’ packaging isunique.
First, the study required the selection of two hypothetical, yet believable,extensions for the four dog food brands. The use of hypothetical extensions forreal brands allowed for the manipulation of category and image fit (e.g. Bhat &Reddy, 2001; Montaner & Pina, 2009). A pretest was used with the aim toidentify two common extensions for the four brands, differing in terms ofsimilarity/non-similarity and coherence/non-coherence to the parent brands. Forsix hypothetical extensions (dog cage, nutritional supplement, fabric deodoriser,dog toy, vacuum cleaner and flea collar), pretest respondents were asked to judgethe similarity between each extension and the products usually offered by thebrands (category fit) and between the extension and the brands’ images (imagefit). Both measures employed 7-point Likert scales (1 = not at all similar/7 = verysimilar for category fit; and 1 = non-coherent/7 = very coherent for image fit)(see Bhat & Reddy, 2001). The pretest questionnaire was sent to 150 members ofthe commercial UK panel Petspanel. An introduction and a general statement onthe purpose of the survey (‘the survey is about dog food brands and theirpotential extensions’) was followed by a filter question asking respondentswhether they owned a dog or not. A randomiser was set in order to display thesix extensions and the four brands in a different order of succession each time.Eighteen responses to the pretest were received, a 12% response rate. Theresponse rate was low, but in line with the response rate usually obtained fromonline panels, as confirmed to the researchers by Petspanel. Eighteen responseswere deemed sufficient for the pretest purpose of identifying a high-fit and a low-fit brand extension to be used in the main study.
From the pretest results, nutritional supplement and fabric deodoriser wereselected, respectively, as the high-fit and low-fit hypothetical extensions to be usedin the main study, as they differed significantly (p < 0.01) for all of the four brands interms of both Category Fit (CAFI) and Image Fit (IMFI). The mean category fit andimage fit are reported in Table 1.
Table 1 Pretest results: selection of extensions.
Pedigree Bakers Winalot Cesar
CAFI IMFI CAFI IMFI CAFI IMFI CAFI IMFI
Nutritional Supplement 4.60 5.20 4.25 4.41 4.25 4.88 3.94 4.63
Fabric Deodoriser 2.06 2.38 2.24 2.53 2.50 2.86 2.19 2.69
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After the pretest, the main study included two questionnaire versions: one for thelow-fit extension (fabric deodoriser) and the other for the high-fit extension(nutritional supplement). Participants were asked questions concerning theirperceptions of the functional, affective and reputational image of each of the fourbrands, the perceived category and image fit and their evaluation of the hypotheticalextension. Then, assuming the existence of the extension, they made a newassessment of the extended brand image. All items employed 7-point Likert-typescales from extant literature (see Table A1 in Appendix). Respondents were also askedto indicate which of the four brands they had ever bought. The questionnaires wereadministered through Qualtrics and were sent to dog owner members of the UKcommercial panel Petspanel. Each version of the questionnaire was sent to 1200panel members, who had not already been involved with the pretest. A similarintroduction, filter question and randomiser as in the pretest were used. After oneweek, 126 responses were received for the low-fit version of the questionnaire (11%response rate) and 189 for the high-fit version (16% response rate). From the latterset of responses, 126 were randomly selected, to ensure an equal sample size.Response rates were again in line with expectations for this kind of samplerecruitment. Possibly the lower response rate for the low-fit extension was due tothe lower interest generated by this extension. The demographic profile of the twofinal samples was very similar (high-fit sample: 17% male and 83% female, 48% 16–45 52% >45 years old; low-fit sample: 16% male and 84% female, 43% 16–45 57%>45 years old). The final sample sizes in each group compare favourably with thesample sizes employed in other published brand extension studies (e.g. Fu et al.,2009; Milberg et al., 2010; Pina et al., 2013). Furthermore, while respondents inextant research often were students (e.g. Fu et al., 2009; Milberg et al., 2010) ourrespondents were all dog owners, real buyers of pet food. This factor contributes tothe reliability of our results, although the response rates were low.
Results
The analysis of the results was conducted in three stages. First, the effectiveness of themanipulation checks was verified. The descriptive analysis of the perceived fit of thetwo extensions confirmed the low degree of category and image fit between all fourdog food brands and the fabric deodoriser extension, and the high fit with thenutritional supplement extension, consistent with the pretest results. Next, thepsychometric properties of the variables were examined, analysing theirunidimensionality, reliability and statistical validity. All variables were found to beunidimensional (across brands and for both high-fit and low-fit samples); exploratoryfactor analysis supported the extraction of a single factor each for brand image,category fit, image fit and extension evaluation. Reliability was assessed viaCronbach’s alpha and Fornell and Larcker’s Composite Reliability. All Cronbach’salpha values (across brands and the two samples) were above 0.7 and the compositereliability values above 0.9 (the results are presented in Table A2 in Appendix).Finally, the hypotheses were tested.
The first step for the hypotheses testing stage was to calculate the percentage ofrespondents who said had ‘ever bought’ each of the four brands. This measure isequivalent to the ‘penetration’ measure used in buying behaviour research (e.g.Ehrenberg et al., 2004) and is a commonly used proxy for the brand’s market
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share or size of the brand (e.g. see Castleberry & Ehrenberg, 1990). As evident inTable 2, in both versions of the questionnaire the relative size of the brands by thepercentage of respondents who said had ‘ever bought’ each of them corresponds tothe relative size (or market share) of the brands when actual sales are considered (seeMintel Reports, 2012 sales data reported above).
We tested each hypothesis in two ways. First we correlated the percentage ofrespondents who said had ‘ever bought’ each of the four brands with the percentageof respondents scoring the extension fit, extension evaluation and brand image (pre-and post-extension) above the neutral midpoint of four in the 7-point Likert-typescales used throughout the study. We did this for consistency with Castleberry andEhrenberg (1990) who had established the usage factor by correlating the percentageof buyers of each brand with the percentage of respondents who, with a free choice,pick-any approach, had associated a brand with an attribute from a list read to them.In our study, such correlations are based on only four data points (corresponding tothe four brands); hence the statistical power of the correlation test is low. Since ourmeasures employed Likert scales based on the brand extension literature (instead ofthe free-choice pick-any methods employed by Castleberry & Ehrenberg, 1990), wedid also undertake a more robust test of our hypotheses using repeated measuresANOVA to test for differences in fit, extension evaluation and image across the fourbrands.
Extension fit perceptions
Table 2 reports the percentage of respondents agreeing (% rating 5–7 on Likertscales) that the two extensions were a good fit for each of the brands.
Results in Table 2 show a strong positive Pearson correlation throughout betweenthe relative size of a brand (in terms of the percentage of ever buyers) and bothdimensions of extension fit, for both the high-fit and low-fit extensions. Particularlyfor the high-fit extension, the market leader Pedigree achieves much higherperceptions of category and image fit than the smaller brands. The dominance ofthe market leader is confirmed by the means category fit and image fit perceptionsreported in Table 3 below.
Results of repeated measures ANOVA with Greenhouse-Geisser correction inTable 3 show that in three out of four instances, the mean category fit and image
Table 2 Extension fit perceptions (% rating 5–7 on Likert scales).
Fit perceptions
% ‘ever bought’ Category fit % Image fit %
High-fit quest. Low-fit quest. HF LF HF LF
Pedigree 50 75 57 25 59 31
Bakers 45 61 35 27 42 27
Winalot 39 35 42 20 48 25
Cesar 25 30 37 20 42 24
Correlation with ‘ever bought’ 0.61 0.86 0.65 0.96
Note: HF = High-Fit extension (nutritional supplement); LF = Low-Fit extension (fabric deodoriser).
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fit perceptions of the market leader Pedigree are significantly different from thesmaller brands. For the smaller brands, mean category and image fit perceptionsare very similar, at about 4 for the high-fit extension and at about 3 for the low-fitextension. Image fit for Winalot’s low-fit extension is also significantly different fromthe other brands, but in the context of no significant differences for this brand in theother instances, we can only assume that this is a quirk in the data.
Overall, the results in Tables 2 and 3 support the first hypothesis and are consistentwith the usage factor reported in previous research on attribute beliefs responses (e.g.Castleberry & Ehrenberg, 1990).
Extension evaluation
Respondents’ evaluations of the two extensions are examined next. Similar to fitperceptions, the percentage of respondents positively evaluating the two extensionscorrelates strongly with the percentage of people buying each brand (see Table 4). Asin the case of fit perceptions, the percentage of respondents positively evaluating thetwo extensions is higher for the ‘larger’ brand Pedigree and then is decreasingly lowerfor brands with a lower number of buyers. As expected, extension ratings of the high-fit extension are higher throughout than the extension ratings of the low-fit
Table 4 Extension evaluation (% rating 5–7 on Likert scale).
Extension evaluation
% ‘ever bought’ Favourability % Perceived quality %
High-fit quest. Low-fit quest. HF LF HF LF
Pedigree 50 75 48 34 54 54
Bakers 45 61 34 28 39 32
Winalot 39 35 33 23 42 28
Cesar 25 30 26 25 39 36
Correlation with ‘ever bought’ 0.88 0.93 0.65 0.71
Note: HF = High-Fit extension (nutritional supplement); LF = Low-Fit extension (fabric deodoriser).
Table 3 Mean extension fit perceptions.
Fit perceptions
% ‘ever bought’ Category fit Image fit
High-fit quest. Low-fit quest. HF LF HF LF
Pedigree 50 75 4.73* 3.08 4.90* 3.51*
Bakers 45 61 4.07 3.00 4.27 3.24
Winalot 39 35 4.16 2.94 4.36 3.33*
Cesar 25 30 4.13 2.83 4.33 3.20
Sig <0.01 0.07 <0.01 0.01
Notes: HF = High-Fit extension (nutritional supplement); LF = Low-Fit extension (fabric deodoriser).Sig = Significance from repeated measures ANOVA with Greenhouse-Geisser correction.* = significantly different from other brands.
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extension, except that the perceived quality of Pedigree’s low-fit extension is as highas the perceived quality of its high-fit extension. It would seem that, for the marketleader, quality perceptions of the parent brand transfer also to low-fit extensions.
The mean extension evaluations in Table 5 above again confirm the dominance ofthe larger brand Pedigree over the three smaller brands. Results of repeated measuresANOVA with Greenhouse-Geisser correction show that with the exception offavourability towards the low-fit extension, all mean extension evaluations ofPedigree are significantly higher than the mean extension evaluations of the smallerbrands.
ANOVA results again show that, for the HF extension, Pedigree is evaluatedsignificantly higher for both Favourability and Perceived Quality than all the other,smaller, brands. For the LF extension, although the ANOVA significance level forFavourability is less than 5%, the post hoc test does not identify significantdifferences between pairs of means. Examination of effect size measures (partial etasquared = 0.03 while tests of between brand contrasts gave effect sizes of <0.02)suggested the differences were small and so we do not regard them as significant. ForPerceived Quality, Pedigree’s LF extension not only is perceived as havingsignificantly higher quality than the other three brands, but also achieves anaverage quality rating similar to its HF favourability rating. This again indicatestransfer of quality perceptions, for the largest brand, even to a low-fittingextension. Overall, results in Tables 4 and 5 support Hypothesis 2.
Brand image
Perceptions of initial (pre-extension) and final (post-extension) brand image areexamined next. Percentage rating results (5–7 on Likert scale) and mean brandimage scores are reported in Tables 6 and 7, respectively.
Respondents rated Pedigree, which is the biggest brand, as the brand with thestronger image both before and after the extensions. For the other brands, both initialand final overall brand image ratings are broadly consistent with the respective brandsize. Cesar, however, seems to distort all the findings, including the correlations with‘ever bought’. Nonetheless, this can be attributed to the fact that Cesar is a brand thatdiffers from the others as it operates in a niche market, with a very narrow product
Table 5 Mean extension evaluation.
Extension evaluation
% ‘ever bought’ Favourability Perceived quality
High-fit quest. Low-fit quest. HF LF HF LF
Pedigree 50 75 4.06* 3.55 4.54* 4.09*
Bakers 45 61 3.45 3.26 3.80 3.60
Winalot 39 35 3.50 3.29 4.12 3.76
Cesar 25 30 3.40 3.19 4.12 3.66
Sig <0.01 0.04 <0.01 <0.01
Notes: HF = High-Fit extension (nutritional supplement); LF = Low-Fit extension (fabric deodoriser).Sig = Significance from repeated measures ANOVA with Greenhouse-Geisser correction.* = significantly different from other brands.
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line, i.e. ‘wet’ food. Indeed, previous research on the relationship between brandimage and usage had identified exceptions of this kind (e.g. Barwise & Ehrenberg,1985; Castleberry & Ehrenberg, 1990). If the ‘different’ brand Cesar is excludedfrom the analysis, the correlations between the relative size of the brand and theinitial and final brand image scores are strong and positive.
While the primary concern of this paper was not the variation in brand imagebefore and after the extension, at this stage we should note that the largest brandPedigree appears to be the one to gain the most, in terms of brand image, from ahigh-fit extension, but also to lose the most from a low-fit one. Pedigree’s brandimage after a high-fit extension is six percentage points higher than its brand imagebefore the extension; its brand image after a low-fit extension is six percentage pointslower than its pre-extension image. High-fit extensions do not seem to alter brandimage perceptions of the smaller brands; however, the two smallest brands Winalotand Cesar appear to gain in brand image from low-fit extensions (even though theirfit perceptions and extension evaluations were low). These results need furtherprobing in future research.
Table 7 Mean initial and final brand image scores.
% ‘ever bought’ Initial brand image Final brand image
High-fitquest.
Low-fitquest.
High-fitquest.
Low-fitquest. HF LF
Pedigree 50 75 4.44* 4.69* 4.51* 4.59
Bakers 45 61 3.81 3.98 3.82* 3.90*
Winalot 39 35 3.98 4.17 4.27 4.44
Cesar 25 30 4.16* 4.19 4.28 4.39
Sig <0.01 <0.01 <0.01 <0.01
Notes: HF = High-Fit extension (nutritional supplement); LF = Low-Fit extension (fabric deodoriser).Sig = Significance from repeated measures ANOVA with Greenhouse-Geisser correction.* = significantly different from other brands.
Table 6 Initial and final brand image (% rating 5–7 on Likert scale).
% ‘ever bought’ Initial brand image %Final brandimage %
High-fitquest.
Low-fitquest.
High-fitquest.
Low-fitquest. HF LF
Pedigree 50 75 42 48 48 42
Bakers 45 61 26 26 26 26
Winalot 39 35 29 27 27 34
Cesar 25 30 32 34 34 42
Correlationwith ‘ever bought’
0.33 0.56 0.32 −0.10
Correlationwith ‘ever bought’excluding Cesar
0.73 0.74 0.82 0.34
Note: HF = High-Fit extension (nutritional supplement); LF = Low-Fit extension (fabric deodoriser).
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Finally, ANOVA results in Table 7 confirm that the brand with the highestpercentage of buyers (Pedigree) also achieves the highest mean brand image scoresboth before and after the extension. For the three smaller brands, the mean initial andfinal brand image scores vary around the mid-point of 4 on the 7-point Likert scalealthough, as remarked earlier on, Cesar tends to be a little different from the rest.
Overall the results in Tables 6 and 7 support hypothesis H3, which postulated apositive relationship between initial and final brand image with the relative size of thebrand.
In the next section we test the last hypotheses concerning the occurrence of the DJphenomenon in fit perceptions, extension evaluations and post-extension brandimage.
Double jeopardy
In this section of the paper we analyse the fit perceptions, extension evaluations, pre-and post-extension brand image for the respondents who have ‘ever bought’ eachbrand, rather than among all respondents (as reported in the previous section). Thisallows us to test for the occurrence of the DJ pattern. Results are reported in Tables 8and 9 below, as percentage ratings (5–7 on Likert scales) and as mean scores,respectively.
The data in Tables 8 and 9 show a consistent pattern, namely that fit perceptions,extension evaluations, pre- and post-extension brand image tend to be lower amongthe buyers of smaller brands than among the buyers of the brand leader (albeit withsome slight deviations for Winalot in the high-fit extension scenario). This patternoccurs for both the low-fit and the high-fit extension. The recurring exception to thispattern is Cesar, which, as already noted, is positioned differently from the otherbrands and is not, therefore, of ‘equal merit’ with its competitors. When Cesar isexcluded, the correlations of fit perceptions, extension evaluations, pre- and post-extension brand image with the relative size of the brand are consistently high.Hypotheses H4a–H4c are therefore supported.
Discussion
Our study has addressed the fact that no previous research has systematicallycompared how consumers evaluate the extensions of competing brands within aproduct category. By focusing on the extensions of one or, at most two brands,extant research has given no consideration to the relative position of a brand in themarketplace and to the reality that consumers rarely evaluate extensions in theabsence of competition. Thus, extant brand extension research examining the effectof brand image on fit perceptions and extension evaluations has concluded that theabsolute strength of a brand’s image is the determinant of how its extensions areevaluated. In contrast, our study has provided compelling evidence that a brand’simage, its extension evaluations, fit perceptions and post-extension brand imageratings are all strongly correlated with the number of buyers of a brand, relative toits competitors, in effect its relative size. The results of the hypotheses testing aresummarised in Table 10 below.
The findings of our study are significant for both brand extensions theory andpractice. In terms of theory, our study has shown that perceptions of fit, extension
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Table
8Fitperceptions,
extensionevaluation,initialandfinalbrandim
ageamongeverbuyers
ofeach
brand(%
rating5–7onLikert
scale).
Fitperceptions%
Extensioneva
luation%
Brandim
age%
%‘eve
rbought’
Category
fit
Imagefit
Favo
urability
Perceivedquality
Initialbrandim
age
Finalbrandim
age
High-fit
quest.
Low-fit
quest.
HF
LF
HF
LF
HF
LF
HF
LF
High-fit
quest.
Low-fit
quest.
HF
LF
Pedigree
50
75
68
20
73
30
65
37
89
49
66
54
68
57
Bakers
45
61
54
21
56
26
52
39
59
43
58
50
57
47
Winalot
39
35
55
16
61
23
49
25
61
39
60
49
62
53
Cesa
r25
30
52
24
51
32
58
40
74
55
77
69
80
57
Correlation
with‘ever
bought’
0.73
−0.01
0.78
0.10
0.19
0.34
0.18
−0.09
−0.72
−0.46
−0.72
−0.15
Correlation
with‘ever
bought’
excluding
Cesa
r
0.80
0.88
0.65
0.98
0.92
0.88
0.79
0.97
0.68
0.88
0.50
0.24
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Table
9Meanfitperceptions,
extensionevaluation,initialandfinalbrandim
ageamongeverbuyers
ofeach
brand.
Fitperceptions
Extensioneva
luation
Brandim
age
%‘eve
rbought’
Category
fit
Imagefit
Favo
urability
Perceivedquality
Initialbrandim
age
Finalbrand
image
High-fit
quest.
Low-fit
quest.
HF
LF
HF
LF
HF
LF
HF
LF
High-fit
quest.
Low-fit
quest.
HF
LF
Pedigree
50
75
5.13
3.21
5.46
3.68
4.76
3.77
5.25
4.29
5.14
4.99
5.14
4.83
Bakers
45
61
4.58
3.19
4.81
3.55
4.21
3.78
4.55
4.04
4.65
4.62
4.58
4.57
Winalot
39
35
4.80
2.93
5.07
3.17
4.49
3.27
4.94
4.07
4.82
4.67
5.01
4.63
Cesa
r25
30
4.73
3.23
4.79
4.37
4.48
3.66
5.26
4.37
5.84
5.10
5.39
4.62
Correlationwith‘ever
bought’
0.43
0.40
0.67
−0.24
0.20
0.65
−0.33
−0.09
−0.74
−0.08
−0.59
0.68
Correlationwith‘ever
bought’excludingCesa
r0.55
0.96
0.55
0.99
0.44
0.93
0.39
0.69
0.60
0.61
0.89
0.99
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evaluation and post-extension brand image conform to well-known patterns ofassociation between the size of a brand (measured in terms of either its marketshare or the number of its buyers, or users) and consumers’ beliefs responses aboutthe attributes of that brand (e.g. Barwise & Ehrenberg, 1985; Castleberry &Ehrenberg, 1990; Romaniuk et al., 2007).
This usage factor has been so far overlooked in brand extension research, even inthe few studies that have considered the relative competitive position of a brand inevaluating the success of its extensions (e.g. Meyvis et al., 2012; Milberg et al., 2010).Furthermore, as mentioned, the majority of studies has not considered thecompetitive context of brand extensions and has thus focused on the absolutestrength of a brand’s image as the determinant of how its extensions are evaluated.In contrast, the results of our study provide convincing evidence that differences inextension fit perceptions and extension evaluations between brands do not reflectdifferences in the absolute strength of the parent brands’ images. Rather, suchdifferences mainly reflect how many people buy each brand. An additionalsignificant finding of this study is that the usage factor equally applies to both high-fit and low-fit extensions.
Furthermore, we have shown the occurrence of the DJ pattern (e.g. Ehrenberget al., 1990, 2004), namely that fit perceptions, extension evaluations, pre- and post-extension brand image tend to be lower among the buyers of smaller brands thanamong the buyers of the brand leader. Thus the buyers (or ‘users’) of a smaller brandB do not necessarily like B and B’s extensions (whether high fit or low fit) to the sameextent as buyers of the larger brand A like A and its extensions. This variation isstructural rather than being specific to the image strength of particular brands: thefewer the number of brand users (e.g. for the smaller brand Bakers), the fewer ofthese fewer users also say they ‘like’ the brand and its extensions. The recurringexception to this pattern in our data was for a brand (Cesar) not of ‘equal merit’ withits competitors. However, when this brand was excluded from the analysis, thecorrelations of fit perceptions, extension evaluations, pre- and post-extension brandimage with the relative size of the brand were consistently high. This is furtherevidence of the importance of examining brand extensions in their competitive
Table 10 Summary of hypotheses testing.
Hypotheses Outcome
H1 The higher the number of buyers of a brand, the greater the perceptionof fit between the brand and its extensions.
Supported
H2 The higher the number of buyers of a brand, the more positive is theevaluation of its extensions.
Supported
H3 The higher the number of buyers of a brand, the more positive are theinitial and final brand images.
Supported
H4a. Fit perceptions will be lower among the users of a small brand thanamong the users of a big brand.
Supported
H4b. Extension evaluations will be lower among the users of a small brandthan among the users of a big brand.
Supported
H4c. Pre- and post-extension brand image will be lower among the usersof a small brand than among the users of a big brand.
Supported
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context, in order to capture the exceptional instances where functional differencesbetween brands have an impact on the outcomes of their extensions and the instanceswhere the only relevant differentiator is market share.
Another important outcome of our research is the evidence throughout the resultsfor all respondents and the results among users of the parent brand – that being themarket leader (in terms of size) bestows a considerably large advantage in terms of fitperceptions, extension evaluation and both pre- and post-extension brand image,when the extension is a close fit. This would seem to echo findings in both the brandequity and the buying behaviour literatures. In the brand equity literature, marketshare is considered as one indicator of brand strength alongside the ability of thebrand to demand a price premium and to achieve high customer loyalty (e.g.deChernatony, McDonald, & Wallace, 2011; Keller & Lehmann, 2003). In thebuying behaviour literature there is evidence that high share brands enjoy excessiveloyalty compared to their competitors, over and above the levels predicted bystochastic models such as the Dirichlet model (e.g. Danaher, Wilson, & Davis,2003; Fader & Schmittlein, 1993). However, when the extension is not regardedas a good fit with the parent brand’s image or with the category, the market leader’sextra advantage is somewhat dampened.
Related to the above, a further contribution of our study in terms of both theory andpractice pertains to the much-discussed, in the literature, potential dilution effects oflow-fit extensions on the post-extension brand image of the parent brand (e.g. John et al.,1998; Lei et al., 2008; Loken & John, 1993). While the primary concern of our studywas not the variation in brand image before and after the extension, we have noted thatthe largest brand appears to gain the most, in terms of brand image, from a high-fitextension but also to lose the most from a low-fit one. In contrast, high-fit extensions didnot seem to alter brand image perceptions of the smaller brands; however, the twosmallest brands appeared to gain in brand image from low-fit extensions (even thoughtheir fit perceptions and extension evaluations were low). While these results needfurther probing in future research, they provide further evidence of the importance forboth academic researchers and practitioners of considering the effect of brand extensionson the parent brand image in a competitive context.
In conclusion, awareness of the usage factor is crucial to the correct interpretation ofconsumers’ perceptions of fit and of their evaluation of the extensions and post-extension brand image of competing brands, within a product category. Ignoringsuch patterns, and exceptions thereof, may lead managers and academic researchersalike to draw the wrong conclusions about the performance of a brand and of itsextensions. This is particularly important for the brand leader in a product categorysince our results indicate that brand leaders may have the largest advantage overcompetitors for a high-fit extension, but may suffer the greatest dilution in case of alow-fit extension. Furthermore, employing the usage factor as a benchmark isimportant also in terms of understanding how consumers evaluate brand extensionsin segmented markets, i.e. markets where brands have different characteristics in termsof price and functional features, as in the case of the premium brand Cesar.
Further research
Further research should replicate the study in different product categories that, like petfood, are not purchased for own consumption, as well as in product categories that are
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bought for own or family consumption. Ideally, further research should consider productcategories with a large number of competing brands to enable clear correlation patternsto emerge between brand usage and extension evaluation and brand image responses.Further research of this kind would generalise the results to product categories withdifferent characteristics and would consolidate the importance of evaluating brandextensions in a competitive setting. Finally, brand usage rates have not been consideredin previous brand extension research, although the usage rates for a particular brand areknown to influence the structure and contents of consumer brand association networksand the strength of various types of associations in such networks (Oakenful &McCarthy, 2010). Future research should compare brand extensions’ evaluationsamong consumers who purchase each brand with different frequency as well as withnon-users. This may give interesting insight on the effect of different levels of pastexperience (or of no experience) with the brand on how its extensions are evaluatedand on post-extension brand image.
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Appendix
Table A1 Scales used in the questionnaire.
Scale Measured concept
Brand Image Functional Image (FUIM) (initial/final)
Martı́nez and Pina(2009)
FUIM1i/FUIM1f: The products have a high quality
FUIM2i/FUIM2f: The products have better characteristics thancompetitors’
FUIM3i/FUIM3f: The products of the competitors are usuallycheaper
Affective Image (AFIM) (initial/final)
AFIM1i/AFIM1f: The brand is nice
AFIM2i/AFIM2f: The brand has a personality that distinguishesit from competitors
AFIM3i/AFIM3f: It’s a brand that doesn’t disappoint itscustomers
Reputation (REIM) (initial/final)
REIM1i/REIM1f: It’s one of the best brands in the sector
REIM2i/REIM2f: The brand is very consolidated in the market
Perceived Fit (FIT) Category Fit (CAFI)
Aaker and Keller (1990) CAFI1: The extension is similar to the brand’s products
Taylor and Bearden(2003)
CAFI2: The firm’s resources are helpful to make the productextension
Image Fit (IMFI)
IMFI1: The product extension fits with the brand image
IMFI2: Launching the extension is logical for the company
IMFI3: Launching the extension is appropriate for thecompany
Extension Evaluation EXEVA1: Favourability of the extension
(EXEVA) EXEVA2: Perceived quality of the extension
Aaker and Keller (1990)
Pryor and Brodie (1998)
Ever Bought Which of the brands below have you ever bought?
Dall’Olmo Riley et al.(1997)
Dall’Olmo Riley et al. Evaluating brand extensions: Does size matter? 923
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About the authors
Dr Francesca Dall’Olmo Riley is Associate Professor in Marketing at Kingston UniversityBusiness School, UK. Her research on branding and on online grocery shopping has beenpublished in the International Journal of Research in Marketing, Journal of Business Research,the European Journal of Marketing and other international journals.
Corresponding author: Dr Francesca Dall’Olmo Riley, Kingston University Business School,Kingston upon Thames KT2 7LB, UK.
Dr Chris Hand is a Senior Lecturer in Marketing at Kingston University Business School, UK.His research interests include online shopping, customer loyalty, arts marketing and culturaleconomics. His research has been published in journals such as the European Journal ofMarketing, the International Journal of Advertising, the International Journal of MarketResearch and the Journal of Cultural Economics.
Francesca Guido graduated from Kingston University Business School with a Master inMarketing, with Commendation. During the final stages of the Master programme atKingston University, Francesca completed a period of work experience at CM-research, amarket research agency operating in the veterinary sector. This gave her the opportunity tocollect the data for her dissertation, which was the starting point of the research discussed inthis paper.
Table A2 Psychometric properties of variables.
Pedigree Bakers Winalot Cesar
CA CR CA CR CA CR CA CR
High-Fit sample
Initial Brand Image 0.95 0.96 0.95 0.96 0.95 0.97 0.96 0.96
Final Brand Image 0.95 0.96 0.97 0.96 0.96 0.97 0.96 0.97
Category Fit 0.78 0.90 0.79 0.91 0.75 0.89 0.82 0.92
Image Fit 0.93 0.96 0.95 0.97 0.93 0.96 0.93 0.95
Extension evaluation 0.89 0.95 0.95 0.97 0.89 0.95 0.89 0.95
Low-Fit sample
Initial Brand Image 0.95 0.96 0.96 0.97 0.96 0.97 0.96 0.97
Final Brand Image 0.96 0.97 0.96 0.97 0.96 0.97 0.97 0.97
Category Fit 0.72 0.88 0.76 0.89 0.80 0.91 0.77 0.90
Image Fit 0.97 0.97 0.97 0.98 0.94 0.96 0.95 0.97
Extension Evaluation 0.92 0.94 0.92 0.96 0.88 0.95 0.90 0.95
CA = Cronbach’s Alpha; CR = Composite Reliability.
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