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Intern. J. of Research in Marketing 27 (2010) 319–328
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Intern. J. of Research in Marketing
j ourna l homepage: www.e lsev ie r.com/ locate / i j resmar
The impact of brand extension success drivers on brand extension price premiums
Henrik Sattler a,⁎, Franziska Völckner b,1, Claudia Riediger a,2, Christian M. Ringle c,d,3
a University of Hamburg, Institute of Marketing and Media, Welckerstraße 8, D-20354 Hamburg, Germanyb University of Cologne, Department of Marketing and Brand Management, Albertus-Magnus-Platz 1, D-50923 Cologne, Germanyc TUHH - Hamburg University of Technology, Institute for Human Resource Management and Organizations, Schwarzenbergstraße 95 (D), D-21073 Hamburg, Germanyd University of Technology Sydney (UTS), Centre for Management and Organisation Studies (CMOS), City Campus, Building 5, 1-59 Quay Street, Haymarket, NSW 2001, Australia
⁎ Corresponding author. Tel.: +49 40 42838 8714; faE-mail addresses: [email protected] (H.
[email protected] (F. Völckner), Claudia.Ried(C. Riediger), [email protected] (C.M. Ringle).
1 Tel.: +49 221 470 7886; fax: +49 221 470 5648.2 Tel.: +49 40 42838 8714; fax: +49 40 42838 87153 Tel.: +49 40 42878 4420; fax: +49 40 42878 44194 Some studies measure consumers’ brand extension
purchase intentions (Aaker & Keller, 1990; Bhat & Redpurchase intentions can be interpreted as the conative1986), they may be subsumed within attitude-based m
0167-8116/$ – see front matter © 2010 Elsevier B.V. Aldoi:10.1016/j.ijresmar.2010.08.005
a b s t r a c t
a r t i c l e i n f oArticle history:First received in 10, August 2009 and wasunder review for 4 and ½ months
Area Editor: Els Gijsbrechts
Research into brand extensions has mainly focused on consumers’ extension evaluations without consideringan important financial implication: the ability of the extension product to charge a price premium. This studyanalyzes (1) the extent to which consumers are willing to pay a price premium for the extension product and(2) the impact of potential success drivers on consumers’ attitudes toward the extension and the extensionprice premium. The results show, for example, that perceived advertising support positively influencesconsumers’ attitudes toward the extension, but it does not directly affect the magnitude of the brandextension price premium. Furthermore, this study reveals monetary effects associated with these successdrivers (i.e., parent brand quality, perceived fit, marketing support for the brand extension, and consumerexperience with the extension category), which offer important information regarding how to allocateresources to various success drivers. For example, brand investments that increase perceptions of parentbrand quality by one unit (seven-point scale) tend to enhance the brand extension price premium of typicalfast moving consumer goods (average price of €2.04 in the study sample) by €.208, all else being equal.
x: +49 40 42838 8715.Sattler),[email protected]
.
.evaluations by asking aboutdy, 2001). However, becausecomponent of attitude (Fazio,easures of extension success.
l rights reserved.
© 2010 Elsevier B.V. All rights reserved.
1. Introduction
Brand extensions that use an existing brand name for new productintroductions (e.g., Hershey's mocha drink) represent a popularbranding strategy. Extending brands can be profitable, especiallywhen they exploit marketing efficiencies, such as lower new productintroduction costs (Keller, 2008). Thus, understanding the factors thataffect a brand's extension success has prompted much empiricalresearch (Aaker & Keller, 1990; Bhat & Reddy, 2001; Bottomley &Holden, 2001; Broniarczyk & Alba, 1994; Dacin & Smith, 1994; Sunde &Brodie, 1993; Völckner & Sattler, 2007). Such work provides importantinsights into factors that may influence consumers’ brand extensionevaluations in terms of their attitudes toward the extension product.4
These consumer evaluations offer important indicators of extensionsuccess (Czellar, 2003) because attitudes toward the product generallyrelate positively to purchasing behaviors (Ajzen & Fishbein, 1980).
However, attitude does not necessarily translate directly into financialsuccess for brand extensions (Sjödin, 2007).
An important financial implication of brand extensions is the extentto which the extensions can command price premiums (i.e., the abilityof the extension product to charge a higher price than an unbrandedequivalent product). The rationale for brand extension price premiumssuggests that the benefit of the brand ultimately should be reflected inconsumers’willingness to pay additionalmoney for the brand extensionproduct, comparedwith a private label or unbrandedproduct that offersthe same functional benefits (Aaker, 1991; Ailawadi, Lehmann,&Neslin,2003). From a managerial perspective, price premiums represent animportant outcomemeasure of brand equity (Ailawadi et al., 2003; Park& Srinivasan, 1994). Furthermore, because an extension's pricepremium plus the price of an unbranded equivalent indicates themaximum amount of money a consumer will pay for the product,knowledgeof anextension's price premiumenablesmarketers to designoptimal pricing policies and estimate demand. In addition, understand-ing the monetary effects of brand extension success drivers (e.g.,perceived parent brand quality, perceived fit, marketing support of theextension, and consumer experience with the extension category) cansupport decisions about how to allocate resources.
The use of brand extensions assumes that the parent brand'sfavorable associations, and thus parent brand equity, transfer to theextension product. However, only one existing study addresses therelated and managerially relevant questions about whether, and towhat extent, the branded extension product can actually command aprice premium. Therefore, this study focuses on analyzing and
320 H. Sattler et al. / Intern. J. of Research in Marketing 27 (2010) 319–328
understanding (1) the extension product's ability to charge a pricepremium and (2) the potential drivers of the brand extension's pricepremium.
DelVecchio and Smith (2005) have empirically investigated theeffect of the perceived fit between the parent brand and the extensioncategory on brand extension price premiums. Their study providesinitial and interesting insights into potential price premium drivers byshowing that the price premium relates positively to perceived fit andthat the relationship between price premium and perceived fitincreases with the level of risk perceived for the extension productcategory. However, they consider only two potential drivers, and theydo not assess the monetary values associated with these factors.Furthermore, they measure the brand extension price premiumdirectly by asking consumers how much they would be willing topay for the extension product, given the fair price for an averageproduct in that extension category. A longstanding criticism of suchmeasures is that directly stated willingness to pay is a poorrepresentation of consumers’ actual willingness to pay (Völckner,2006). In an attempt to address these unresolved issues, our researchmakes four key contributions.
First, instead of using a self-explicated direct measure of pricepremium (i.e., “What would you be willing to pay?”; DelVecchio &Smith, 2005, p. 190), this study is the first to measure brandextension price premiums by examining discrete choice behavior ina choice-based conjoint (CBC) analysis setting. Because CBCrepresents the market process more realistically, it offers morevalid estimates than self-explicated approaches (Mitchell & Carson,1989; Sattler & Hartmann, 2008). As in real purchase decisions,respondents choose among product alternatives by trading offamong attributes (including price) and attribute values (Haaijer &Wedel, 2003).5
Second, we extend the scope of analysis by considering severalpotentially important success drivers that have not been analyzedpreviously in the context of brand extension price premiums.Specifically, we include major brand extension success driversidentified in previous research: the quality of the parent brand(Bottomley & Holden, 2001), the fit between the parent brand and theextension product (Aaker & Keller, 1990; Bhat & Reddy, 2001),perceived availability of the extension product in the distributionchannel (Völckner & Sattler, 2006), perceived advertising support forthe extension (Reddy, Holak, & Bhat, 1994), and consumers’experience in the extension product category (Swaminathan, Fox, &Reddy, 2001).
Third, by moving beyond the direct effects of these success drivers,this study is the first to assess potential indirect effects on brandextension price premiums through consumers’ attitudes toward theextension product. That is, we measure extension success in terms ofconsumers’ attitudes toward the brand extension and by brandextension price premiums, and then we analyze the impact of severalpotential brand extension success drivers on both measures. Weexpect that consumer attitudes toward the extension will influencethe brand extension price premium (Keller, 1993). By applying partialleast-squares (PLS) path modeling (Henseler, Ringle, & Sinkovics,2009), we simultaneously estimate the ordinary least-squaresregressions of the two recursive success measures on the brandextension success drivers. We then proceed with a mediation analysisto assess whether the effect of the success drivers is mediated byconsumers’ attitudes toward the extension product (Iacobucci,Saldanha, & Deng, 2007). In so doing, we differentiate the effects ofbrand extension success drivers on consumers’ attitudes toward theextension from the effects on brand extension price premiums. Forexample, we find that perceived advertising support has a signifi-cantly positive effect on consumers’ attitudes toward the extension
5 In addition to CBC, several other potentially appropriate methods can measureprice premiums or consumers’ willingness to pay (Gabor, 1977; Völckner, 2006).
product, but it has no significant direct effect on brand extension pricepremiums. The results of our PLS path model thus provide detailedinformation about the total effects of the success drivers, includingboth direct and indirect effects.
Fourth, our study quantifies for the first time the monetary valueassociated with important brand extension success drivers (parentbrand quality, perceived fit, marketing support for the brandextension, and consumer experience in the extension category)according to their incremental effects on the brand extension pricepremium. Because they reveal the extent to which investments ineach driver are worthwhile, these monetary effects provide importantinformation that should influence firms’ decisions about how toallocate their resources.
Our findings can help managers make more accurate extensioncategory and target group assessments by identifying productcategories and consumer segments that are promising in terms ofthe magnitude of the price premiums that can be earned by launchinga new product under an existing brand name. Furthermore, animportant component of a brand's financial value is its strategicoption or latent value (Srivastava & Shocker, 1991), which arises fromits potential to extend into new categories. An important determinantof a brand's strategic option value is the price premium that the brandcan earn in an array of extension categories. Therefore, understandingthe factors that influence brand extension price premiums shouldhelp managers assess the brand's overall financial value. Althoughprior research has investigated a multitude of ways to measure brandequity and the price premium consumers are willing to pay forexisting products (Ailawadi et al., 2003; Keller, 2008; Park &Srinivasan, 1994), the question of how tomeasure the price premiumsof new extension products, as well as what drives these pricepremiums, remains neglected.
The remainder of this article is organized as follows: in the nextsection, we describe the conceptual framework of our study. Thestudy design section details the procedure, sample, and measures ofthe empirical study, followed by the study's results. We conclude witha discussion of the implications of our findings.
2. Conceptual framework
The conceptual framework consists of three elements (see Fig. 1).First, we include the most important brand extension success driversidentified by previous research (listed earlier). Second, we modelbrand extension success as consumers’ attitudes toward the brandextension and their willingness to pay a price premium for the brandextension. We measure the price premium by examining discretechoice behavior. Most models of consumer decision-making follow astimulus–organism–response schema that assumes a causal effect ofattitude toward a product on choice (Jacoby, 2002). Several studiesnote that the attitude–behavior relationship is not perfect and can beweak (Ajzen & Fishbein, 1980; Wicker, 1969). However, it is stillwidely accepted that attitude positively affects choice, as in theFishbein model and its extensions (Solomon, Bamossy, Askegaard, &Hogg, 2006). In line with this reasoning, Keller (2008) definesconsumers’ attitudes toward a brand (extension) as a source ofbrand equity and the price premium of a brand (extension) as anoutcome measure of brand equity. Such definitions suggest a causaleffect of attitude on choice-based price premiums. Similarly, severalbrand extension studies indicate that consumers’ attitudes towardbrand extensions positively influence their brand purchases (Bhat &Reddy, 2001; Lane, 2000). We therefore postulate that consumers’attitudes toward the brand extension have positive effects on theirwillingness to pay a price premium. Consequently, we consider twodirect effects and one indirect effect of each success driver. The directeffects reflect the success drivers’ influence on consumers’ attitudesand the brand extension price premium. The indirect effects resultfrom the relationship between consumers’ attitude toward the
6 The positive effect of fit usually applies only if the parent brand offers highperceived quality. Because the basic logic of brand extensions is to transfer positiveassociations to a new product, usually only strong parent brands with high perceivedquality get extended (Aaker & Keller, 1990). In our data, we observed a high level ofperceived parent brand quality with average latent variable scores per analyzed brandextension product (Table 1) ranging from 4.2 to 5.2 on a seven-point scale. We thankan anonymous reviewer for highlighting this issue.
Fig. 1. Conceptual model.
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extension and the extension price premium, such that the driversindirectly affect the extension price premium through consumers’attitudes toward the extension (see Fig. 1). Third, because pricepremiums likely vary with consumers’ level of price sensitivity, wecontrol for this variance with a measure of consumers’ priceconsciousness as a covariate.
2.1. Parent brand quality
A basic premise underlying the use of brand extensions is thatbrands that consumers perceive to have high quality provide greaterleverage for extensions than do brands associated with low quality(Aaker & Keller, 1990; Park & Kim, 2001). Consumers’ qualityperceptions of the parent brand and its products are an importantindicator of brand equity (Agarwal & Rao, 1996; Lehmann, Keller, &Farley, 2008). These perceptions act as surrogates of knowledge aboutthe extension product, which reduces purchase uncertainty andpositively influence extension success (Bhat & Reddy, 2001; Bottom-ley & Holden, 2001; Echambadi, Arroniz, Reinartz, & Lee, 2006; Smith& Park, 1992).
H1a. Perceived parent brand quality has a positive effect on consumers’attitudes toward the brand extension.
H1b. Perceived parent brand quality increases the magnitude of thebrand extension's price premium.
2.2. Fit between the parent brand and the extension product
In line with previous studies, we define perceived fit as theextent to which a consumer perceives the new product to beconsistent with the parent brand (Aaker & Keller, 1990). A poor fitbetween the parent brand and extension product may evokeundesirable beliefs and associations (e.g., extension productregarded as ridiculous or questions about the ability of the parentbrand to make the extension product). Empirical research showsthat a high (low) degree of fit positively (negatively) influencesextension success in terms of consumers’ evaluations of the
product (Aaker & Keller, 1990; Bhat & Reddy, 2001; Boush &Loken, 1991; Broniarczyk & Alba, 1994) and the price premium(DelVecchio & Smith, 2005).6
H2a. The fit between the extension product and the parent brand has apositive effect on consumers’ attitudes toward the brand extension.
H2b. The fit between the extension product and the parent brandincreases the magnitude of the brand extension's price premium.
2.3. Parent brand quality×fit interaction
The premise for extending an existing brand name is thatconsumers use their beliefs about the parent brand tomake inferencesabout the extension. Categorization and schema theories suggest thatthe degree to which consumers transfer their parent brand associa-tions to the extension product depends on the level of perceived fitbetween the extension product and the brand (Barsalou, 1983;Tversky, 1977). Specifically, brands represent categories that areassociated with specific beliefs, depending on the attributes associ-ated with their individual category members. A new instance (i.e.,brand extension) receives those category associations to the extentthat it is perceived to fit with or belong to the previously definedcategory (i.e., parent brand) (Boush & Loken, 1991). Greater perceivedfit between the parent brand and the extension product leads to agreater transfer of positive parent brand associations to the newproduct (Aaker & Keller, 1990; Bottomley & Doyle, 1996; Völckner &Sattler, 2006). Therefore, we expect a positive interaction between thequality of the parent brand and fit.
Table 1Parent brands and extension products.
Parentbrands
Category of parentbrand's focal products
Category ofextension products
Average across CBC pricelevels (overall: €2.04)a
Bonaqua Water Sports drinks €1.42Buitoni Pasta Pesto €2.29Coca-Cola Soft drink Flavored drinks €0.82Danone Yoghurt Dairy health drinks €2.19Duschdas Shower gel Deodorant €2.74Mars Chocolate bars Praline €0.87MeisterProper
Household cleaningagent
Detergent €4.14
Müller Milk Whey fruit drinks €1.47Pringles Chips Salsa €2.39WC Frisch In-tank toilet cleaner Liquid antibacterial
toilet cleaner€2.09
a The average across the three price levels used in the choice-based conjoint (CBC)reflect average market prices.
322 H. Sattler et al. / Intern. J. of Research in Marketing 27 (2010) 319–328
H3a. The positive effect of the parent brand quality on consumers’attitudes toward the brand extension increases as the level of perceivedfit increases.
H3b. The positive effect of the parent brand quality on the magnitude ofthe brand extension's price premium increases as the level of perceived fitincreases.
2.4. Marketing support for the extension product
When exploited properly, superior marketing resources result in acompetitive advantage that can translate into better new productintroduction strategies and lead to more successful new products. Theperceived advertising support that the extension product receives andits perceived availability in the distribution channel play critical rolesin determining the success of a new product (Klink & Smith, 2001;Reddy et al., 1994).
Advertising focused on the extension makes consumers aware ofthe performance bond at stake for the company, evokes positive brandextension associations, and increases consumers’ quality perceptionsof the extension product and other umbrella-branded products(Wernerfelt, 1988). Empirical evidence also indicates that perceivedadvertising support positively influences consumers’ evaluations ofthe product (Kirmani, 1990).
The perceived availability of the extension product in thedistribution channel (and thus retailers’ listing decisions) reflectsjudgments about product quality and uniqueness (Rao & McLaughlin,1989). Consequently, the availability of the extension product mayprovide an external cue signaling high product quality to consumers.Furthermore, the mere distribution of an extension, and thusperceived availability in the distribution channel, should have apositive awareness effect (Heeler, 1986) and increase extensionsuccess.
H4a. The perceived availability of the brand extension product has apositive effect on consumers’ attitudes toward the brand extension.
H4b. The perceived availability of the brand extension product increasesthe magnitude of the brand extension's price premium.
H5a. The perceived advertising support of the brand extension producthas a positive effect on consumers’ attitudes toward the brand extension.
H5b. The perceived advertising support of the brand extension productincreases the magnitude of the brand extension's price premium.
2.5. Consumer experience in the extension category
We expect that the frequency of purchases in the extensioncategory, which reflects consumers’ knowledge of or experience inthe extension category, will influence extension success. Frequentusers tend to evaluate a new product more positively because theylike the familiar category (Goldsmith, 2000; Goldsmith & Hauteville,1998), which should lead to a positive consumer experience effecton both attitudes and price premiums. However, the extent to whichconsumers rely on the brand name in their purchase decisionsshould be governed by their level of knowledge about the productcategory (Smith & Park, 1992). According to cue utilization theory,consumers rely on certain cues that serve as surrogate indicators ofproduct quality (Cox, 1967; Olson & Jacoby, 1972). If consumershave minimal information, they are likely to base their inferences onan established brand name, which provides an “information chunk”that combines various pieces of information about product attri-butes. If the consumer is a novice rather than an expert in theextension category, he or she is more likely to rely on a known brandname, which should lead to a negative effect of consumer experienceon attitude (i.e., less experienced consumers exhibit more favorable
attitudes toward an extension product by a known brand).Furthermore, less experienced consumers should be more willingto pay a price premium for an established brand, whereas experts orfrequent users may be less inclined to do so. Because the direction ofthe effect of consumer experience is unclear, we leave it as anempirical question.
H6a. Consumer experience in the extension category has a significanteffect on consumers’ attitude toward the brand extension.
H6b. Consumer experience in the extension category significantlyinfluences the magnitude of the brand extension's price premium.
3. Research design
3.1. Selection of parent brands and extension products
We test the hypotheses with a variety of real parent brands andreal extensions in the German fast moving consumer goods (FMCG)industry. From an initial set of 80 randomly-drawn parent brandsfrom important FMCG categories (food, drinks, detergents, andhygienic products), we select those that (1) achieve an aided recallof greater than 50% and (2) are considered as strong or very strongbrands (with a sufficient variance in perceived brand strength). Weuse these two selection criteria because brand extension strategiestypically apply to relatively well-known and strong brands (Keller,2008). Furthermore, we focus on extension products launchedimmediately preceding the data collection to limit potential survivalbias issues. The selection process relies on a pretest with aconvenience sample of 135 consumers and market informationobtained from the LPV New Products Database (LPV is “Lebensmittel-praxisVerlag,” an information service for the German FMCG industry).Based on these criteria, we select 10 of 79 potential parent brands,representing seven food and three nonfood categories, with oneextension product for each brand (Table 1).
3.2. Measures of brand extension success
3.2.1. Consumers’ attitudes toward the extension productMost empirical studies of consumers’ evaluations of brand
extensions measure consumers’ attitudes toward the extensionproduct (Aaker & Keller, 1990; Boush et al., 1987; McCarthy, Heath,& Milberg, 2001; Taylor & Bearden, 2002). We use a seven-point scaleto measure the likability of the extension product (“How do you likethe extension product?” 1=don't like it, 7=like it), as used often inprevious studies to measure consumers’ attitude toward the exten-sion product (Broniarczyk & Alba, 1994; Yeung & Wyer, 2005).
Table 2Measures of brand extension success drivers.
Success drivers Items References
Parent brandquality
How would you rate the qualityof PARENT BRAND CORE-PRODUCT? (1=low, 7=high)
Aaker and Keller(1990)
PARENT BRAND is of higherquality than other brands.(1=strongly disagree,7=strongly agree)
Fit between parentbrand and extensionproduct
To what extent does EXTENSIONPRODUCT fit the remainingproducts of PARENT BRAND?(1=does not fit at all, 7=fitsvery well)
Martin and Stewart(2001, second item);Boush and Loken(1991)
How similar is EXTENSIONPRODUCT to the remainingproducts of PARENT BRAND?(1=not similar at all, 7=verysimilar)
Perceived availability EXTENSION PRODUCT isavailable in many supermarkets.(1=strongly disagree,7=strongly agree)
Völckner and Sattler(2006)
On my last shopping trip,EXTENSION PRODUCT reallyattracted my attention.(1=strongly disagree,7=strongly agree)
Perceived advertisingsupport
EXTENSION PRODUCT is wellsupported in terms ofadvertising. (1=stronglydisagree, 7=strongly agree)
Lane (2000); Völcknerand Sattler (2006)
How often did you noticeadvertising for EXTENSIONPRODUCT in recent months?(1=not at all, 7=very often)
Consumer experiencein the extensioncategory
How often do you shop withinEXTENSION CATEGORY?(1=never, 7=very often)
Swaminathan et al.(2001)
Covariate:Price consciousness a If I purchase a product in
EXTENSION CATEGORY, I findmyself checking the price evenfor small items. (1=stronglydisagree, 7=strongly agree)
Ailawadi et al. (2001)
Within EXTENSION CATEGORY, Icompare prices of at least a fewbrands before I choose one.(1=strongly disagree,7=strongly agree)It is important for me to get thebest price for the products I buyin EXTENSION CATEGORY.(1=strongly disagree,7=strongly agree)
a Ailawadi et al. (2001) measure price consciousness as a general disposition; wemeasured it in the specific context of the extension category, which might introduce aconnection to willingness to pay a price premium for the extension. This possible biaslimits the explanatory power of the covariate.
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3.2.2. Brand extension price premiumTo measure the price premium, we apply a choice-based conjoint
approach with brand name and price as attributes (Ailawadi et al.,2003). For many FMCG categories, information other than brand andprice is of secondary importance in consumers’ purchase decisions(Rao & Monroe, 1989). A brand extension price premium reflectsconsumers’ willingness to pay an additional amount of money for theextension product in comparison with a private label (or unbranded)product. The private label mimics how the brand extension wouldperform if it had no brand name, and thus serves as a comparisonproduct to estimate the brand extension price premium (Ailawadi etal., 2003).7 We consider four levels of the brand attribute: a privatelabel, the brand extension, and two main competitors. We identifycompetitors by asking the respondents in a pretest to state importantbrands within the category. For each product category, we include thetwo brands statedmost often in the pretest. To choose the three levelsof the price attribute, we select regular market prices that cover theentiremarket range of prices in the extension category (see Table 1 forthe average prices across the three price levels in the CBC, whichreflect average market prices).
Respondents in the main study participate in several discretechoice tasks. Specifically, we present them with seven choice setsembedded in a CBC design, including one holdout task to assesspredictive validity. Each choice set contains four product alternatives(i.e., conjoint stimuli) and a no-purchase option. We generate arandomized design using the complete enumeration procedureprovided by the SawtoothCBC software, which considers all possiblestimuli and chooses each stimulus to produce the most nearlyorthogonal design for each respondent (Orme, 2006).
We conduct a single CBC analysis for each of the 10 brandextension products, and we estimate the price premium as thedifference in utility between the brand extension and the private labelproduct, divided by the utility per price (Kohli & Mahajan, 1991; Park& Srinivasan, 1994). For each subsample (i.e., extension product), weuse a hierarchical Bayes model to estimate the part-worth utilities atthe individual respondent level (see Section 3.5 for additional details).
3.3. Measures of success drivers and the covariate
To measure the success drivers, we employ measurement scalesfrequently used in prior brand extension success studies (thoughthere is a chance that the findings are sensitive to alternativemeasures or definitions). In Table 2, we list the items used to measurethe success drivers.
Two seven-point scales measure parent brand quality by askingconsumers to rate the overall quality of the parent brand (Aaker &Keller, 1990) in both an absolute sense and relative to competingbrands (Cronbach's alpha= .603; average variance extracted[AVE]=.703; composite reliability [CR]=.824). To measure the fitbetween the parent brand and the extension product, we askrespondents to indicate, on two seven-point scales, whether theextension product is similar to other parent brand products andwhether it fits with the other parent brand products (Cronbach'salpha=.772; AVE=.806; CR=.892) (Boush & Loken, 1991; Martin &Stewart, 2001). The perceived availability of the extension product isoperationalized according to whether the extension product (1) isavailable in many supermarkets and (2) attracted the respondent'sattention on his or her last shopping trip (Cronbach's alpha=.918;
7 Private labels do not always have minimum or no brand value; in some cases, theyadopt high price and quality positions and gain substantial brand value (e.g., Tesco inthe United Kingdom, EDEKA-Selection in Germany). However, for this study, weensure the private labels in each category are positioned with low prices and averagequality levels, such that they should have no or very low brand value. To enhance thegeneralizability and replicability of our findings, we use private labels from traditionalsupermarkets that are common throughout the world (cf. popular private labels ofhard discounters in Germany).
AVE=.924; CR=.961) (Völckner & Sattler, 2006). We measureperceived advertising support of the extension product with twoitems that indicate the advertising pressure perceived by consumers(Cronbach's alpha=.721; AVE=.763; CR=.864) (Lane, 2000). Theconsumer's experience in the extension category equals the frequencyof purchases in that category (Swaminathan et al., 2001). Therespondents indicate on a seven-point scale how often they havepurchased in the extension category (1=never, 7=very often).
Finally, price premiums are likely to vary with consumers’ levels ofprice sensitivity. To control for this variance, we measure consumers’price consciousness with three items adopted from Ailawadi, Neslin,and Gedenk (2001). The responses on seven-point scales (Cronbach'salpha=.820; AVE=.646; CR=.843) are averaged into one measureof price consciousness as a covariate.
9 We tested for several other interaction effects between the success drivers butfound no significant interaction effects on price premium in the expected direction.More specifically, we expected positive interaction effects between (1) fit andadvertising support (Lane, 2000; Klink & Smith, 2001), (2) parent brand quality andadvertising (Lane, 2000), (3) fit and availability (Klink & Smith, 2001), and (4) parentbrand quality and availability, but in all cases, we found insignificant results.
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3.4. Data collection
We collected the data using a consumer survey through an onlineaccess panel. The 1000 potential respondents received e-mailinvitations to fill out an Internet questionnaire, which resulted in518 completed interviews.
Each respondent evaluated one brand extension. A comparisonbetween the sample and the adult population in Germany revealed thatthe respondents’ demographics were similar to those of the overallpopulation in termsof gender. In termsof age, thegroupaged18–34 yearswas overrepresented in the sample, which might be attributed to greaterInternet penetration among younger consumers. Although informationabout respondents’ purchasing behaviors in the brands/categories underinvestigationwouldbepreferable todemographic information,wedidnothave such details. Because we were interested in construct associations(instead of descriptive insights), which are less sensitive to sampledeviations, we refrained from weighting the sample elements.
3.5. Calculating the brand extension price premium
To measure the predictive validity of the CBC data, we draw on hitrates that assess the extent to which amodel estimated with the choicetasks designed for part-worth estimation correctly predicts an individ-ual respondent's observed choice behavior in the holdout task. We usethe first choice rule to compute hit rates; this rule assumes that eachrespondent chooses the product alternative with the highest utility forhimor her, independent of the relative strengthof preferencewithin thechoice set (Huber, Wittink, Fiedler, & Miller, 1993). The results indicatethat the predictive validity is good for all 10 subsamples. The percentageof correctly estimated holdout choices (hit rates) ranges from 65.8% to88.1%. Furthermore, our models achieve face validity because the pricevectors show plausible negative values for all respondents.8
To estimate the individual brand extension price premiums, weuse the CBC hierarchical Bayes procedure (Sawtooth CBC, Orme,2004), which proceeds in an iterative manner and recursivelygenerates draws of model parameters (Arora & Huber, 2001). Atotal of 20,000 preliminary iterations and 10,000 additional iterationsserve to generate the parameter estimates, with every tenth iterationsaved. Consequently, 1000 utility draws are available for everysubject. For each respondent, we divide the 1000 values of theindividual part-worth utility distribution of the brand extensionattribute level by the corresponding 1000 values of the part-worthdistribution of the price vector (Natter & Feuerstein, 2002). The levelsof the brand attribute are dummy coded, with the private label as thereference level. Because the brand extension price premium reflectsconsumers’willingness to pay more for the extension, compared withthe private label, the part-worth utility for the brand extension level,divided by the price vector, indicates the brand extension pricepremium. Calculating the mean of the resulting price premiumdistribution reveals the average price premium of the brand extensionproduct at the individual respondent level, which serves as adependent variable (brand extension success) in the subsequentregression analyses.
4. PLS path model analysis
4.1. Model estimation and evaluation
To test our hypotheses, we apply PLS path modeling (Lohmöller, 1989;Wold, 1975) to estimate our theoretical model using the software appli-cation SmartPLS (Ringle, Wende, and Will, 2005). We incorporate the
8 Four respondents indicated an implausible (i.e., positive) price vector and,therefore, were excluded from further analysis. The remaining sample consists of514 cases. Beyond face validity and hit rates, we do not have data to test the externalvalidity of the CBC results, which limits the generalizability of our findings.
interaction effect betweenparent brandquality andfit9 into the pathmodelby applying a commonly-used two-stage approach (Chin, Marcolin, &Newsted, 2003;Henseler&Fassott, 2010).10 Becauseweexclude15outliers(2.9%) from the analysis, with standardized residuals greater than +3 orlower than−3 (Hocking, 2003), the final model is based on 499 cases.
ThePLSpathmodel estimationprovidesR2valuesof .392 for theattitudeconstruct and .170 for the price premium construct, which suggests goodexplanatory power of themodel.We check the latent constructs in the pathmodel for multicollinearity. All variance inflation factors (VIF) have a valueof less than 2 (see Table 3)—which is clearly below the critical value of 10—so we perceive no severe multicollinearity problems (Belsley, Kuh, &Welsch, 1980; Kleinbaum, Kupper, & Muller, 1988).
We test the discriminant validity of the latent variables in the PLSpathmodel using Fornell and Larcker's (1981) criterion, which requiresthat the square root of each latent variable's AVE is greater than thelatent variable's correlation with any other construct in the model. Aswe show in Table A1 in the Appendix, each latent variablemeets Fornelland Larcker's criterion in support of discriminant validity.
Finally, because the data for all themodel variables came from singlerespondents in a one-time survey, common method variance mightinfluence some postulated relations in the PLS path model. Weseparated the survey section about success drivers and consumers’attitudes from the survey portion involving the CBC procedure. Inaddition, we asked about some success drivers prior to (and some otherdrivers after) the item regarding consumers’ attitudes, andwemixed allthe items among several distraction items. Specifically, we asked aboutconsumers’ experience in the extension category, their price conscious-ness, and the perceived advertising support of the extension productand then proceededwith some distraction items, followed by perceivedparent brand quality. Next,we asked about consumers’ attitudes towardthe extension product, again followed by some distraction items. Wethen asked about the perceived fit between the parent brand and theextension product as well as the perceived availability of the extensionproduct. The questionnaire closed with the CBC part. To test for thepotential existence of common method bias, we applied Harman's(1976) single-factor test. The first factor accounts for only 24% of theoverall variance, which indicates that common method variance likelydoes not affect the results (Podsakoff & Organ, 1986). Because this testsuffers some limitations (Kemery & Dunlap, 1986), we also adopted themarker variable approach (Lindell & Whitney, 2001; Malhotra, Kim, &Patil, 2006; Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Morespecifically, we applied Lohmöller's (1989) extended PLS algorithmand used several marker variables to estimate the loadings on everyitem in the PLS path model, in addition to each item's loading on itstheoretical construct. A comparison of the estimated path modelrelationships with and without each of the additional marker variablesshows no notable differences, and all theorized paths maintain theirlevel of statistical significance. Thus, neither the traditional single-factortest nor the marker variable approach suggests a threat of commonmethod bias (Podsakoff et al., 2003).
4.2. Testing the hypotheses (direct effects)
InTable 3,weprovide theparameter estimates of the success drivers’direct effects on attitudes toward the extension and brand extension
10 Please note that the interactions terms are scaled in such a way that the maineffect of one driver represents its impact for average values of the other driver.Because we use standardized data, an increase in driver X1 by one standard deviationpoint (from 0 to 1) implies a change of the slope of driver X2's main effect by the valueof the interaction effect X1*X2 (Henseler & Chin, 2010).
11 In conformance with the nonparametric PLS path modeling approach, we apply anonparametric bootstrapping procedure to test the significance of the mediatingeffects (Henseler et al., 2009). While the Sobel test is the most commonly used methodto assess mediating effects, simulation studies reveal that bootstrapping offers a betteralternative, at least in PLS path models, because it does not impose any distributionalassumptions (Mackinnon, Lockwood, Hoffman, West, & Sheets, 2002; Preacher &Hayes, 2008).12 Because we estimate the brand extension price premium as a function of thesuccess drivers, covariate, and consumers’ attitude toward the extension product(with attitude as a function of the success drivers), the total effects (Table 4, column 8)on the price premium do not necessarily equal the respective coefficients of the pricepremium equation (Table 3, column 8).
Table 3Results of PLS path model estimations.
Descriptive statistics Attitude toward brand extension Brand extension price premium
Mean sd Max.VIFa
b b se b t-value b Elasticity b b se b t-value b Elasticity
Attitude toward brand extension 4.23 1.560 1.649 – – – – .196*** .046 4.261 .838Parent brand quality 4.787 1.087 1.452 .416*** .038 10.947 .471 .126*** .040 3.163 .610Fit between parent brand and extension product 4.953 1.275 1.240 .226*** .041 5.512 .265 .106*** .037 2.853 .531Parent brand quality×Fit between parent brand andextension product
24.290 9.466 1.032 .033ns .027 1.222 –
(interaction term).104*** .035 2.971 –
(interaction term)Perceived availability 3.203 1.791 1.337 .124*** .036 3.417 .094 .102** .050 2.040 .330Perceived advertising support 3.723 1.518 1.242 .070* .036 1.927 .062 −.012ns .029 .414 –
(ns effect)Consumer experience in the extension category 4.290 1.793 1.075 .101*** .036 2.824 .103 .022ns .028 .788 –
(ns effect)Price consciousness 4.611 1.548 1.037 – – – – −.080ns .065 1.231 –
(ns effect)
Notes: b = path coefficient, sd = standard deviation, se = standard error, ns = not significant,⁎pb .10,⁎⁎pb .05,⁎⁎⁎pb .01 (two-sided test; sample size: 499).a The values represent the maximum variance inflation factor (VIF) of the latent constructs in the PLS path model.b We apply a nonparametric bootstrapping routine to test the significance of the PLS path modeling results.
325H. Sattler et al. / Intern. J. of Research in Marketing 27 (2010) 319–328
price premium. We also provide the standard errors, t-values, andsignificant levels obtained by applying a nonparametric bootstrappingroutine (which is the standard method to test the significance of PLSpath modeling results; Henseler et al., 2009). We also report themeansand elasticities of the success drivers at their respective means toindicate their relative importance.
In support of H1a andH1b (Table 3),wefind that parent brand qualityhas a significant positive impact on attitude toward the extensionproduct and brand extension price premium. Parent brand quality is thestrongest driver of consumers’ attitude and willingness to pay a pricepremium (Table 3, columns 8 and 12). In H2a and H2b, we predict thatthe fit between the parent brand and the extension product has apositive impact on attitude and price premium, respectively. Bothhypotheses receive support. The fit variable is the second mostimportant factor in the attitude and the price premium models(Table 3, columns 8 and 12), underlining the dominant position ofperceived fit as a key success driver in brand extension research. Inaddition, the positive effect of parent brand quality on themagnitude ofthe brand extension's price premium increases as the level of perceivedfit increases, in support of H3b. Moreover, in support of H4a and H4b,perceived availability positively influences consumers’ attitudes towardthe extension product and their willingness to pay a price premium.
Our results also show that perceived advertising support andconsumer experience in the extension category have mixed effects onthe success measures. In support of H5a, perceived advertising supporthas a significant (pb .10) and positive influence (but a weak effect size)on consumers’ attitudes. However, we do not find a significant effect ofperceived advertising support on the price premium (H5b). Consumerexperience in the extension category significantly and positivelyinfluences attitudes toward the extension product, in support of H6a.However,wedonotfinda significant effect on thebrand extension pricepremium. Finally, we find that price consciousness, as a covariate, doesnot have a significant effect on price premium.
4.3. Testing the path relationship between attitude and price premium
We assume that consumers’ attitudes toward the brand extensionhave positive effects on their willingness to pay a price premium(Section 2). The path analysis method proposed by Cohen, Carlsson,Ballesteros, and Amant (1993) allows for empirically testing the pathrelationship from attitude toward the extension product to brandextension price premium (Alternative 1), as opposed to the other wayaround (Alternative 2) (Sun & Zhang, 2006). The total squared errors(TSE) are .176 for Alternative 1 and .198 for Alternative 2, indicating a12.5% change [(.198− .176)/.176]. By calculating Cohen's (1988) d-value[(TSE2–TSE1)/s, where s is the pooled standard deviation of TSE values],
we can assess the TSE change as small (d-value=.2), medium (.5), orlarge (.8). The Cohen d-value estimated for the TSE difference betweenAlternative 1 and Alternative 2 is .45, amedium–strong change indicatingthat the PLS path model relationship from attitude to price premium(Alternative 1) is preferable. We thus find empirical support for ourtheoretical assumption that consumers’ attitudes toward the brandextension have positive effects on their willingness to pay a pricepremium for it.
4.4. Mediation analysis
To test whether consumers’ attitudes toward the brand extensionmediates the relationships between the success drivers and the brandextension price premium, we conduct a mediation analysis.11 Theresults indicate strong partial mediation for these three success drivers:parent brand quality, fit between extension product and parent brand,and perceived availability (variance accounted for=39.4%, 29.3%, and19.1%, respectively). In contrast, perceived advertising support, con-sumer experience in the extension category, and the interaction termbetween parent brand quality and fit are not mediated by attitude (seeSection 4.5). Table 4 (column 5) contains each success driver's indirecteffect on the brand extension price premium, resulting from the impactof the success driver on consumers’ attitude and the effect of consumers’attitude on the price premium.
4.5. Total effects of success drivers on brand extension price premium
The sum of all direct effects (e.g., the path relationship from parentbrand quality to brand extension price premium) and indirect effects(e.g., the path from parent brand quality through attitude toward thebrand extension to brand extension price premium) in the path model(Fig. 1) represents the total effect of each success driver (e.g., parentbrand quality) on the price premium. We calculate the total effects(Table 4, column 8) by summing the direct (column 2) and indirect(column5) path relationships.12 The total effects computation allows us
Table 4Direct, indirect, and total effects on brand extension price premium.
Direct effect Indirect effectb Total effect c
b a se a t-value a b a se a t-value a b a se a t-value a Total elasticity d
Attitude toward extension product .196 *** .046 4.261 – .196 **** .046 4.261 .838Parent brand quality .126 *** .040 3.150 .082 *** .021 3.905 .208 **** .036 5.778 1.007Fit between extension product and parent brand .106 *** .037 2.865 .044 *** .013 3.385 .150 **** .037 4.054 .751Parent brand quality×Fit between extension product and parent brand .104 *** .035 2.971 .007 ns .008 .875 .111 **** .035 3.171 Interaction termPerceived availability .102 ** .050 2.040 .024 ** .011 2.182 .126 *** .052 2.423 .408Perceived advertising support −.012 ns .029 .423 .014 ns .047 .290 .002 ns .045 .971 –
(ns effect)Consumer experience in the extension category .022 ns .028 .788 .020 ns .036 .556 .042 ns .042 .990 –
(ns effect)Price consciousness −.080 ns .065 1.231 – −.080 ns .065 1.227 –
(ns effect)
Notes: b = path coefficient, se = standard error, ns = not significant, ⁎ pb .10,⁎⁎ pb .05,⁎⁎⁎ pb .01 (two-sided test; sample size: 499).a We apply a nonparametric bootstrapping routine to test the significance of the PLS path modeling results.b To calculate the indirect effect of a variable X on price premium, we multiply the regression coefficient for that variable in model 1 (attitude toward brand extension) with the
regression coefficient for attitude toward the brand extension in model 2 (extension price premium).c To calculate the total effect of a variable X on price premium, we sum the direct (column 2) and indirect (column 3) effects of that variable.d To calculate the total elasticity of a variable X (brand extension price premium), we multiply the total effect of X with the mean value of X and divide the product by the mean
value of the price premium.
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to assess the total monetary impact associatedwith each success driver,which we use to calculate total elasticities (Table 4, column 11),evaluated at the mean. The total elasticities indicate the total relativeimpact of the success drivers on the brand extension price premium.
Parent brand quality has the strongest total effect on price premium,and it is associatedwith the highest total elasticity.Wefind a substantialmonetary effect associated with the quality of the parent brand; anincrease in perceived parent brand quality by one unit (seven-pointscale) increases the brand extension price premium by €.208 (Table 4,column 8). In perspective, the average price across all products in oursample was €2.04 (Table 1). Thus, an increase in the price premium by€.208 equals almost 10% of the average product price.
To illustrate the monetary value of a high-quality brand, we drawon the quality ratings in our sample. The mean difference betweenbrands with the most and least favorable quality evaluations in oursample equals .976 scale points. That is, ceteris paribus, a high-qualitybrand can command a price premium of 20 eurocents (.976×€.208)relative to a brand with lower quality. Because even small changes inprice have a strong impact on revenue and earnings (Marn & Rosiello,1992), this finding indicates a remarkable and economically substan-tial result. Furthermore, our comparison of the direct and total effects(Table 4) reveals that parent brand quality indirectly enhancesconsumers’ willingness to pay by €.082 through its positive effecton consumers’ attitude toward the extension. Thus, ignoring thisindirect effect underestimates the monetary impact of the quality ofthe parent brand by 8.2 eurocents.
The fit variable has the second highest total effect on price premium,with a monetary potential of 15 eurocents (Table 4, column 8), whichimplies that enhancing the perceived fit by one unit increases theextension's ability to charge a price premiumby €.150. For our sample ofextension products, the difference between a high-fit extension(mean=5.7) and a relatively low-fit extension (mean=4.2) is 1.5scale points. Ceteris paribus, a high-fit brand extension can command aprice premium of 22.5 eurocents (1.5×€.150) over a low-fit extension.In addition, the total effect of the interaction between fit and parentbrand quality on the brand extension's price premium (.111) issignificant in the bootstrapping procedure. However, the indirect effectof the interaction term through attitude on price premium is notsignificant (.007). Consequently, we only consider the significant directmonetary effect of the interaction term between fit and parent brandquality (.104; see Table 4).
The total monetary effect associated with the perceived availabil-ity of the extension product on the willingness to pay a price premiumequals €.126, so that an increase in perceived availability by one unitincreases the brand extension price premium by 13 eurocents
(Table 4). Again, we draw on our sample of extension products toillustrate the financial value of such high perceived availability. In oursample, the mean range of perceived availability is 2.588 scale points,which implies that higher perceived availability enables a brandextension to earn a price premium of up to 33 eurocents(2.588×€.126) compared with extension products with (substantial-ly) lower perceived availability in the distribution channel.
Finally, the effects of perceived advertising support and consumerexperience in the extension category on price premium are notsignificant; neither are the corresponding total effects (Table 4). Theinsignificant effect of advertising might reflect the notion supportedby cue utilization theory, which states that consumers tend to rely onavailable diagnostic cues as surrogate indicators of product quality toevaluate products that have just been introduced in the market (Cox,1967; Olson & Jacoby, 1972). Because consumers use the brand nameas an information chunk or composite of missing information (Olson,1977), the perceived quality of the parent brand and its perceived fitwith the extension category might largely determine consumers’extension product evaluations, and dominate the effects of advertis-ing at early stages of the product's life cycle.
5. Implications
Research on brand extension success focuses mainly on consumers’evaluations of the extension product. However, such research forgets animportant financial implication: the ability of the extension product tocharge a price premium. From a managerial perspective, price premiumsoffer an important source of brand equity, and knowledge about thesepremiums is critical for managers who want to design optimal pricingpolicies. In addition, knowing the monetary effects of specific brandextension success drivers offers important information for allocatingresources. We measure brand extension price premiums by examiningdiscrete choice behavior in a CBC analysis. Our study is the first to analyzethepotential drivers of (1) consumers’ attitudes toward the extension and(2) the extension price premium. Furthermore, this study reveals themonetary effects associated with several key success drivers, includingparent brand quality, perceived fit, marketing support of the brandextension, and consumer experience in the extension category.
Several important managerial insights emerge. Investing in parentbrand quality is a particularly valuable strategy because it increasesnot only consumers’ attitudes toward the extension product but alsothe price premium the product can command. Greater perceivedparent brand quality, increased by one unit (on a seven-point scale),enhances the brand extension price premium of typical FMCGs (withan average price of €2.04 in our sample) by €.208, all else being equal.
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Likewise, our results reveal strong monetary effects associated withthe perceived fit between the parent brand and the extension product(€.150) and the perceived availability of the extension product(€.126). The extension product's perceived availability not only buildsawareness, and thereby increases the probability of the extensionproduct being bought, but it is also valued by consumers at anadditional price premium of €.126 (on average). In contrast, perceivedadvertising support might be relevant for generating initial aware-ness, but it has only a small and indirect effect on the brand extensionprice premium. Therefore, managers might want to shift their brandinvestments from the advertising budget to retail marketing.Furthermore, our findings indicate that it is reasonable to targetexperts or frequent users of the extension category because they tendto evaluate the extension product more favorably and therefore aremore willing to pay a price premium for an established brand.
Finally, our results provide detailed information about the totaleffects of the success drivers. The total effects (Table 4) are greaterthan the coefficients in the price premium equation (Table 3) becauseof the indirect effects that function through consumers’ attitudestoward the extension (when both direct and indirect effects arestatistically significant). Thus, managers must consider drivers’ directeffects on economic success measures and their indirect effectsthrough pre-economic success measures (e.g., attitude toward theextension product). Ignoring potential indirect effects might result in
Table A1Correlation matrix and square route of each latent variable's average variance extracted.
Brandextensionpricepremium
Attitudetowardextensionproduct
Parentbrandquality
Fit betweenextensionproduct andparent brand
Brand extension price premium naAttitude toward extension product .346*** naParent brand quality .291*** .540*** .839Fit between extension product andparent brand
.245*** .406*** .335*** .898
Parent brand quality×fit .109** .045ns .006Ns −.033nsPerceived availability .214*** .311*** .219*** .196***Perceived advertising support .100** .222*** .165*** .095**Consumer experience in theextension category
.104** .199*** .095** .111**
Price consciousness −.062ns −.013ns −.014Ns .018ns
Notes: The square root of each latent variable's average variance extracted appears on the⁎pb .10, ⁎⁎pb .05, and ⁎⁎⁎pb .01 (two-sided test; sample size: 499).
over- or underestimations of the success drivers’ effects and thussuboptimal managerial decisions.
This study also provides interesting bases for further research. Forexample, researchersmight look into the costs associatedwith an increasein certain success drivers to help managers assess the net effect of anincrease in the brand extension price premium and the correspondinginvestments. Further research should also analyze the extent towhich ourresults generalize to other industries, such as consumer durables orservices.Moreover, an important component of a brand'sfinancial value isits strategic option or latent value, which arises from its potential toexpand intonewproduct categories. Further researchmight incorporate amodel of brand extension price premiums into models of a brand'sfinancial value,whichwould enhance our ability to assess andunderstandthemonetary value of brands. Existing financialmeasures of brand equityhave neglected the option value of extending brands into new categories.
We did not use longitudinal data to test the causal effect of attitudetoward the extension product on the brand extension price premium.Moreover, within our CBC setting, the number of competitorsremained stable across the categories; thus, we did not test theextent to which competition affects the price premium measured.Both of these issues remain for further research.
In general, this study demonstrates the need for brand extensionresearchers to take the monetary consequences of brand extensionstrategies explicitly into account in their studies.
Appendix
Parentbrandquality×fit
Perceivedavailability
Perceivedadvertisingsupport
Consumer experiencein the extensioncategory
Priceconsciousness
na.081* .962.003Ns .420*** .873.065Ns .201*** .096** na
.130*** .063ns .098** .087* .804
diagonal, na = not applicable (single item), ns = not significant,
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