consumer evaluations of store brands: effects of store image and product attributes
TRANSCRIPT
Journal of Retailing and Consumer Services 11 (2004) 247–258
Consumer evaluations of store brands: effects of store imageand product attributes
Janjaap Semeijna, Allard C.R. van Rielb,*, A. Beatriz Ambrosinib
a Faculty of Management Sciences, Open University of The Netherlands, PO Box 2960, Heerlen 6401 DL, The Netherlandsb Faculty of Economics and Business Administration, Maastricht University, P.O. Box 616, Maastricht 6200 MD, The Netherlands
Abstract
The importance of store brands has increased. Many products carrying a label that is exclusively available from a specific retailer
chain have been introduced in recent years, with varying degrees of success. Retailers appear to pay little attention to the multiple
risks associated with adding new product categories to their store labels. We investigate how store image factors and various
categories of perceived risk associated with product attributes affect consumer evaluations of store-branded products. A structural
model is developed and tested, providing indications of the likelihood of store brand success in various product categories. Research
and managerial implications are provided.
r 2003 Elsevier Ltd. All rights reserved.
Keywords: Store brands; Store image; Perceived risk; Retailing; Consumer behavior
1. Introduction
The roles and importance of store brands, brands thatare exclusive to a particular store chain and compete inseveral product categories with major manufacturer’sbrands, have changed dramatically over the pastdecades. Store brands are evolving into full-fledgedalternatives, capable of competing successfully withthese manufacturer’s brands on quality as well as onprice (Quelch and Harding, 1996) and contributingsubstantially to profitability, store differentiation andstore loyalty (Corstjens and Lal, 2000). Sales volumesand market shares of store brands, as well as theirappeal to consumers have steadily increased (e.g. Dunneand Narasimhan, 1999; Nandan and Dickinson, 1994).Many retailers appear to view themselves increasingly asactive marketers of their own store brands, rather thanas passive distributors of manufacturers’ brands (cf.Richardson et al., 1994). Store brands can help retailersattract customer traffic and create loyalty to the store byoffering exclusive product lines and premium products(Corstjens and Lal, 2000; Dunne and Narasimhan,1999). In addition, store brands can help project a
lower-price image for retailers, increase their bargainingpower over manufacturers and producers of majornational brands, and lead to increased control overshelf space (Narasimhan and Wilcox, 1998). Carryingstore brands comes with numerous advantages, one ofwhich is the relatively high gross margin, which can be25–50% higher compared to manufacturer brands(Keller, 1993). This high margin mainly results fromthe more efficient marketing effort, the reduction ofmiddlemen, and economies of scale obtained in dis-tribution. Moreover, they present value to consumers byoffering a combination of ‘good quality’ and ‘better-value’ products, and reinforce the retailer’s name bothon the store shelves and in consumers’ homes (Fitzell,1992; Richardson et al., 1996a).
Store brands are prominent in supermarkets. Forinstance, in 1999 they exceeded dollar earnings ofmanufacturers’ brands in both food and non-foodsegments of US supermarkets. According to thePrivate Label Manufacturers’ Association (PLMA),one out of five items sold in American supermarkets,drug store chains and mass merchandisers is sold undera private or store brand. In the UK, the strongest storebrand market in Europe, they have a share of nearly40% of all grocery sales (Steenkamp and Dekimpe,1997). This implies that some product categoriesare actually dominated by store brands (Baltas, 1997).
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*Corresponding author. Tel.: +31-43-388-3778; fax: +31-43-388-
4918.
E-mail address: [email protected] (A.C.R. van Riel).
0969-6989/$ - see front matter r 2003 Elsevier Ltd. All rights reserved.
doi:10.1016/S0969-6989(03)00051-1
Some analysts expect that by 2005 close to 50% of allEU grocery sales will be represented by the top tenretailers. Therefore, the cumulative power carried bythese retailers and their store brands is significant (Lepir,2001).
When searching for lower priced alternatives at thelower end of the market, it appears that consumersprefer the guarantee that a familiar store name bringsrather than the risks associated with buying from alesser-known manufacturer brand (Baltas, 1997). Storebrands are becoming major brands in their own rightwith their own identities and quality images. They areincreasingly seen as important sources of profitability(Ailawadi, 2001; Ailawadi and Harlam, 2002), whichexplains why many new product lines are beingdeveloped for them, and associated marketing effortshave significantly increased.
1.1. Rationale for the study
Supermarket chains have been consolidating theirpositions through mergers and acquisitions. With fewerand bigger players competing in markets, retailers needto assess their strategies carefully, in order to gainmarket share. Developing a strong store brand can playan important role in this effort. However, a store brandcan be highly successful in some product categorieswhile being ineffective in others (Hoch and Banerji,1993). Differences among product categories appear tobe a cause of variance in store brand share both acrossmarkets and across retailers (Batra and Sinha, 2000;Dhar and Hoch, 1997).
For retailers, there are multiple risks associated withthe introduction of new products under a store label.Store brands are typically umbrella brands, or brandsthat include various distinct product categories. Anegative experience with one product category canprevent consumers from buying store brands in othercategories, and even erode customer confidence in thestore as a whole (Thompson, 1999). The larger thenumber of categories marketed by an umbrella brand,the more negative the spill-over effects that occur(Sullivan, 1990). Retailers should therefore first assessthe likelihood of acceptance of a new category under thestore label. This assessment can be made by investigat-ing consumer evaluations of store brands (Dick et al.,1996; Sethuraman and Cole, 1999) and assessing if andhow store related factors (Richardson et al., 1994;Richardson et al., 1996b) and product category attri-butes (Batra and Sinha, 2000; Raju et al., 2001) affectthis evaluation.
This paper is based on a study designed to develop abetter understanding of the conditions leading to successwhen a grocery product is made available under a storebrand. Based on the findings, grocery retailers will beable to focus on categories most compatible with their
respective store images. The problem statement guidingthis study is:
Which factors affect the success of store brands ingrocery retailing?
The following sub-questions were formulated:
(1) How do retailer attributes affect consumer evalua-tions of a store-branded product?
(2) How do product attributes affect consumer evalua-tions of store-branded products?
1.2. Approach
The article is structured as follows. First, existingliterature is reviewed and a number of propositions arederived. These are summarized into a theoretical model.Secondly, the research model and design are shown. Apresentation and discussion of the results follows. Next,implications of these results are discussed. Finally, thelimitations of the research and some suggestions forfurther research are presented.
2. Store brands
The concept of store brands is often used inter-changeably with terms such as ‘private label brands’ or‘own brands’ (cf. DelVecchio, 2001; Dick et al., 1996;Hoch and Banerji, 1993; Raju et al., 2001; Sethuramanand Cole, 1999). The positioning of the brand (e.g.premium, commodity) is a function of many differentvariables, such as the image of the store, quality of theproducts, and motivation of the retailer to invest in itspromotion (Davies, 1998; Kapferer, 1994). In somecases the store brand is closely associated with the storeitself, for instance in the case of Benetton and Gap,where own brands are sold exclusively. In other cases,the store brand is one of many brands available in thestore. This situation is typical for most grocery stores.
2.1. Development of propositions
How do retailer attributes influence consumer evalua-tions of store brands? Although grocery stores are facingproblems in differentiating themselves due to the lack ofa perceived core product/service and the need to addressthe broadest possible range of consumers and purchasesituations, Dick et al. (1995) observed that the storeimage acts as an important indicator of store brandquality. Store image is reflected in the store’s physicalenvironment (Richardson et al., 1996b), perceptionsrelated to its merchandise, and perceived service quality(Baker et al., 1994; Zimmer and Golden, 1988).Consumers use these cues to form an overall evaluationthat will affect their attitude toward the store as a whole,
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and potentially towards its store brands. This couldexplain why store brands outperform manufacturerbranded products in some cases. Examples are Harrodswith its premium brands, Sainsbury and Tesco withrelatively cheap, high-quality product lines, and Aldiwith its ‘no-frills’ stores and a clear focus on basicproducts at a low price (Fitzell, 1992). Consumers’buying decisions will thus be influenced by theirexperiences with the retail environment, the merchandiseand the level of service:
P1: There will be a direct positive relationshipbetween perceived store image and consumer atti-tudes towards store branded products.
In addition to effects of the store image, it has beentheorized that perceived product attributes affect theattitude of the consumer towards merchandise soldunder a store brand (DelVecchio, 2001). Steenkamp andDekimpe (1997, p. 927) affirm this by stating that ‘thepower of a store brand, even for a powerful retailer,varies dramatically across product categories’. Thesedifferences have been related to the perceived risksassociated with store brand purchases (Mitchell, 2001).By choosing among different brands, and depending onthe degree of involvement with each product, consumersmake trade-offs between the risks of losses they mayincur when purchasing the product and the value theyexpect. Different authors have categorized the risksassociated with the purchase of a product into differentgroups. Some authors have categorized them into fourgroups, namely functional or physical, psychosocial,financial and time related risks (e.g. Greatorex andMitchell, 1994; Mitchell and Greatorex, 1993). Othersemploy seven distinct risk types, namely financial,social, time-, performance, functional, psychologicaland overall risk (e.g. Stone and Gr^nhaug, 1993). Inthe case of groceries, functional and physical risksappear to be equivalent: a product that is not compliantwith functional (quality) standards could lead tophysical damage. In our view, perceived time risk, orthe risk that a consumer could waste more time bybuying one type of brand rather than another, does notdiscriminate between manufacturer brands and storebrands, and will therefore not be considered in thepresent discussion. An inclusion of overall risk does notseem to add value, since we are interested in thedifferential effects of various risk categories. It can beargued that in the case of purchasing groceriespsychological risk as defined by Stone and Gr^nhaug(1993) does not play a role. The category of social riskhas sufficient psychological aspects to rename it intopsychosocial risk. Functional, psychosocial and finan-cial risks thus remain to be considered, as they appear todiscriminate effectively between risks consumers associ-ate with buying manufacturer brands or store brands. In
the following subsections propositions with respect tothese effects will be formulated.
In addition to the physical performance of theproduct, functional risk is also related to a consumer’sperception of how difficult it is to produce a certainproduct category—the perceived difficulty is based ondifferent aspects, such as required technology andingredients. Therefore, the difficulty of producing acategory and the expected quality of the store brand willbe inversely related (cf. DelVecchio, 2001):
P2: Consumer attitude towards a store brandedproduct is inversely related to the functional riskassociated with the perceived difficulty for the retailerto produce that product.
A store’s image does not only serve as a directindicator of store brand quality, but also as a riskreliever (e.g. Mitchell and Greatorex, 1993; Mitchell andMcGoldrick, 1996). The relationship between storeimage and consumer attitude to a store-branded productcan thus be modeled as a mediated relationship. Therelationship is mediated by the risk perception, becausethe risk perception itself is affected by the qualityperception of the store (e.g. Baron and Kenny, 1986;MacKinnon et al., 1995; Venkatraman, 1990). As aconsequence we expect:
P2a: The effect of store image on consumer attitudetowards a store branded product is mediated by thefunctional risk associated with the perceived difficultyfor the retailer to produce that product.
Psychosocial risk is associated with the consumptionof the product and its symbolic aspects, such as beliefsand status (Batra and Sinha, 2000; DelVecchio, 2001).Psychosocial risk exists to the extent that the consumerbelieves that he/she will be negatively evaluated due tohis/her product (brand) choice. Nonetheless, not allproducts are consumed in public situations, that is,other people might not be aware that someone possessesand uses a certain product, when it is not highly visibleto others (Bearden and Etzel, 1982). The more visible orpublicly used a product category is, the smaller thechance that a consumer will use a store brand, due to itslower level of symbolic quality. Therefore, we expect aninverse relationship between usage visibility of theproduct (or ‘publicness’ cf. DelVecchio, 2001) andconsumer attitudes towards the store-branded product:
P3: Consumer attitudes towards a store brandedproduct are inversely related to the perceivedpsychosocial risk associated with the usage of theproduct.
Again, the store image could act as a risk reliever andit is expected that the effect of consumers’ perceptions ofthe retailer on their evaluations of store-branded
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products will be mediated by the perceived psychosocialrisk:
P3a: The relationship between store image andconsumer attitude towards a store branded productis mediated by the perceived psychosocial risk ofusage.
When considerable quality variance occurs within aproduct category, the likelihood of a consumer makinga poor purchase decision increases, and with it theassociated financial risk. The general expectation is thatin product categories with large quality variability, storebrand labels will appear lower in the quality spectrum(Hoch and Banerji, 1993; DelVecchio, 2001):
P4: Consumer attitude towards a store brandedproduct is inversely related to the perceived financialrisk associated with quality variance in the productcategory.
The store image could again act as a risk reliever andit could be expected that the effect of consumers’perceptions of the retailer on their evaluations of store-branded products will be mediated by the perceivedfinancial risk. Therefore:
P4a: The relationship between store image andconsumer attitude towards a store branded productis mediated by the perceived financial risk of usage.
The hypothesized relationships are summarized in theconceptual model represented in Fig. 1.
3. Research design
An experiment was designed and conducted todetermine the structural relationships between storeimage, perceived risk associated with various productattributes, and consumer attitude towards store-brandedproducts. In this section, criteria used for the choice ofstores in the study are discussed, followed by adiscussion of the criteria used for the choice of productcategories. Finally, the methodology is explained.
3.1. Case study—three grocery stores in The Netherlands
For convenience reasons we tested our propositions inthe grocery industry in The Netherlands. Store brandpenetration is around 20% in this market (Wileman andJary, 1997) while the three largest grocery chainsaccount for more than 60% of total retail sales(Steenkamp and Dekimpe, 1997). For the present studythree major and well-known grocery chains, AlbertHeijn (AH), Edah, and Aldi were selected. The threeselected chains vary substantially in areas such as thephysical design of the stores, the quality and assortmentof their merchandise, pricing and promotion strategies.
3.1.1. Albert Heijn
AH is owned by the ‘Royal Ahold’ group, at the timeof this study the third largest player in the globalretailing industry, operating 30 different chains, con-sisting of 9000 retail stores in 27 countries. AH is thelargest grocery chain in the Netherlands, with more than2300 outlets and a market share approaching 30%(Dekimpe and Steenkamp, 2002). The stores share anattractive design, offer a broad assortment of qualityproducts and brands, and carry a premium image. Theoverall price level is higher than at other chains. The AHstores sell approximately 4000 products under a storebrand—ranging from basic products such as milk andtoilet paper to more elaborate and premium products,including ready-to-eat meals, ‘gourmet’ ingredients, andkitchen utensils. All store-branded products include thestore name and logo on the packaging. In addition, AHoffers the Euroshopper brand—basic, everyday-useproducts at discounted prices—which do not carry thestore logo. Of the three stores investigated, AH has thelargest advertising budget. This advertising is focused onpromoting the store image and store brands, andincludes a free monthly magazine.
3.1.2. Edah
The Edah chain is part of the ‘Laurus’ group. Laurusoperate 1200 outlets in the Netherlands, including the‘Konmar’ and ‘Super de Boer’ stores. The group ownsmultiple chains in The Netherlands, Belgium and Spain,operating some 2400 grocery outlets altogether. Edah’simage is less prestigious than Albert Heijn’s, and itsprices are lower as well, but it is not considered adiscount chain. Six hundred products are carried underthe Edah private brand, carrying the name and logo ofthe store. Edah’s focus on product innovation is not asaccentuated as it is at AH. Nonetheless, the companyclaims to be similarly concerned with product packagingand presentation. Edah uses various channels toadvertise the brand, such as TV, radio, leaflets, andnewspapers. However, contrary to AH, Edah promotesmanufacturer brands in its advertising rather thanproducts with the Edah label.
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Evaluationof Store Brand
PerceivedFinancial Risk
PerceivedPsychosocial Risk
PerceivedFunctional Risk
Store Image Product Class Store Brand
Antecedents Mediators Outcome
Store Image
-
-
-
-
-
-
+
Fig. 1. Conceptual model of direct and mediated effects.
J. Semeijn et al. / Journal of Retailing and Consumer Services 11 (2004) 247–258250
3.1.3. Aldi
Aldi is a German discount chain, successful in even themost entrenched local markets in Europe (10 countries),which has been expanding more recently into the US andAustralia. Aldi’s objective is offering good qualityproducts at an everyday low price (EDLP). The companypursues a low-cost strategy: investments in store design,staff, or product packaging are kept to a minimum. Aldialso avoids carrying products that duplicate otherproducts, which leads to a relatively narrow assortment.Each Aldi store carries some 1000 different products,with a focus on basic products and not on differentiationand innovation. With the exception of special temporarydeals on bulk volumes of particular branded products,the chain carries brands that are uniquely sold at Aldi.However, Aldi tends not to use its own name or logo toidentify its brands. Aldi is not known to utilize muchadvertising in order to promote the store itself. The mainmedia used are newspapers and the store leaflet—presenting special offers, often more focused on theavailability of temporary stock than on discounts.
3.2. Product selection
The product categories used in the case study wereselected based on availability and familiarity to con-sumers. The need for variance in the different risksassociated with the purchasing decision, functional,financial and psychosocial risk, guided us in selectingthe product categories. Wine, toothpaste, potato chips,and canned tomatoes were chosen. The categories wereclassified as follows: The ‘wine category’ was selected torepresent the highest psychosocial risk, as it has thehighest level of usage visibility; it also reflects highfunctional risk, because of the difficulty to produce wineand the physical consequences of the consumption of aninferior wine. It also represents a product category witha very-high-quality variance. Toothpaste carries med-ium psychosocial risk since it is not often used in publicsituations; nonetheless, no one wants to be associatedwith bad/cheap hygiene products. Moreover, it scoreshigh in functional risk because of health relatedconsequences, and there is significant quality variancein the category. The ‘potato chips’ category can beclassified as inexpensive (low financial risk), easy toproduce (low functional risk) and as having low tomedium psychosocial risk. And finally, the ‘cannedtomatoes’ category can be seen as the simplest one witha low level of visibility (psychosocial risk) and very lowlevel of functional risk—easy production and hardly anyquality variance among brands.
3.3. Questionnaire design and sampling
A questionnaire, consisting of 110 statements, wasdeveloped to test the model. Respondents were asked to
indicate their agreement with these statements on 7-point Likert type scales (totally disagree to totally agree,very bad to very good, and very unlikely to very likely).The survey consisted of two parts: In the first part,measuring the store image, respondents had to evaluatethe three chains. In the second part, the perceivedpsychosocial, functional and financial risks relating tovarious product categories, and the associated attitudesof the participants towards store-branded products weremeasured for each of the three chains. For our study, anE-mail message was used to approach potential respon-dents. An invitation to participate in the experiment wassent to approximately 200 students and 100 recentgraduates listed on an e-mailing list of the MarketingDepartment at the University of Maastricht. The E-mailcontained a hyperlink to an online questionnaire. Toincrease the response rate, a small raffle type lottery wasincluded. To increase the sample size the addresseeswere asked to forward the invitation to friends andcolleagues, thus creating a so-called snowball sample(Stevens et al., 1997).
The use of a student-based sample has been provenuseful in previous studies regarding branding andconsumer behavior (Biswas et al., 1999; Halstead et al.,1994; Sinha and DeSarbo, 1998; Sparks and Hunt, 1998;Stafford, 1998; Van Riel et al., 2001). Students are animportant part of the shopping population, prone tobuying (the generally cheaper) store brands and can thusbe considered experienced with respect to store brand/manufacturer brand choices.
3.4. Store image
Store image was measured with 15 indicator variables,adapted from previous store image studies (Baker et al.,1994; Birtwistle et al., 1999; Bloemer and de Ruyter,1998; Mazursky and Jacoby, 1986) and a retail servicequality research (Dabholkar et al., 1996). In a stepwiseprincipal component factor analysis, 4 items wereexcluded from the subsequent analysis, based on lowcommonality values (o0.35). The remaining items, aswell as the associated factor loadings, are listed inTable 6 in the appendix. Based upon the interpretationof the Scree test, three factors were identified, explaining70% of the variance. A value of 0.904 was found for theKMO test and for Bartlett’s test we obtained a w2 of7519.774 (df.=45, s=0.000). Reliability was tested withCronbach’s test and reported in Table 6 in the appendix.
3.5. Dependent variable
The dependent variable, consumer attitude towards the
store brand, was operationalized in accordance withprevious studies in branding research (Aaker and Keller,1990; Van Riel et al., 2001), by averaging two measures:the perceived overall quality of the store brand
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(1=inferior, 7=superior) and the likelihood of purchas-ing the store brand, assuming that the customer wasplanning a purchase in the product category (1=not atall likely, 7=very likely). For this variable, a reliabilitycoefficient a of 0.87 was obtained.
3.6. Risk factors
Since each of the risk factors had to be measured forfour products and for three different store brands, it wasdecided to operationalize them as straightforward,single item measures. The participants were asked toexpress their agreement with statements such as ‘AlbertHeijn would have problems to manufacture thisproduct’, or ‘I would mind that other people know thatI use this product from the Edah brand’ on seven pointLikert scales. In a pretest of the questionnaire thequestions were reformulated such as to convey theintended meaning optimally.
3.7. Sampling
One hundred and thirty-one participants filled out thequestionnaire. Data were screened manually and 3 caseswere deleted from the sample, since they contained alarge number of missing values. Each respondentanswered questions about three different stores andfour different product categories, which resulted in afactorial design of 1536 cases (3� 4� 128). Therespondents included 61 females and 67 males. Theaverage age was between 20 and 24 years old—68.1% ofthe respondents were in this age range. In addition,8.8% of the respondents were between 15 and 19 yearsold, 15.9% between 25 and 29 years, 1.8% between 30and 34 years, and finally 5.3% of the sample was olderthan 34 years.
4. Analysis and results
4.1. Testing the propositions
The theoretical model to be tested can be representedby the following set of equations:
Y ¼ g1 þ b1IL þ b2IM þ b3IS þ b4RFUN
þ b5RPSY þ b6RFIN þ e1; ð1Þ
RFUN ¼ g2 þ b7IL þ b8IM þ b9IS þ e2; ð2Þ
RPSY ¼ g3 þ b10IL þ b11IM þ b12IS þ e3; ð3Þ
RFIN ¼ g3 þ b13IL þ b14IM þ b15IS þ e4; ð4Þ
where the variables are: Y is the consumer attitudetowards the store brand; IL the store image (layout);IM the store image (merchandise); IS the storeimage (service); RFUN the functional risk; RPSY
the psychosocial risk; RFIN the financial risk; b theregression coefficients; g the intercepts; and e is the errorterms.
Before conducting the regressions following Eq. (1)the data were investigated on a descriptive level. Selecteddescriptives are reported in Table 1. It appears thatAH has the best and most consistent store imageamong participants: AH is followed by Edah andfinally by Aldi. A look at the means of consumers’attitudes towards the store brand reveals that althoughAH attained the highest level, Edah and Aldi are atsimilar levels. These differences are clearly less pro-nounced than the ones between the different storeimages.
From Table 1 it became clear that the retailer sampleis not homogeneous. It was therefore decided to createcorrelation matrices for the three retailers separately,including all core constructs, with the primary purposeof obtaining insight in the data structure. These matricesare presented in Table 2.
Significant correlations exist between most of thevariables, the highest level being between attitude
towards the store brand and perceived financial risk inthe AH and Edah samples, and between attitude towards
the store brand and store image in the Aldi Sample. Thisobservation is an indication that it may not be allowedto pool the data for the three retailers. Before anyfurther techniques could be applied, parameter stabilityover the three store brands had to be verified. F -tests(Chow, 1960) were thus applied to regressions accordingto model (1) of various combinations of the three partialsamples. For that purpose, two dummy variables wereintroduced with the following values:
D1 ¼ 1 : Albert Heijn and D1 ¼ 0 : not-AlbertHeijn
D2 ¼ 1 : Edah and D2 ¼ 0 : not-Edah
If D1 ¼ 0 and D2 ¼ 0 : Aldi:
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Table 1
Descriptives Store Brand Attitude (SBA)/Image Factors
Retailer SBA Layout Merchandise Service
Mean SD Mean SD Mean SD Mean SD
AH 4.77 1.44 5.7 0.92 6.1 0.91 5.3 0.96
Edah 4.20 1.46 4.6 1.02 4.8 1.07 4.6 1.03
Aldi 4.21 1.63 3.6 1.23 3.4 1.22 4.0 1.15
J. Semeijn et al. / Journal of Retailing and Consumer Services 11 (2004) 247–258252
The new model becomes:
Y ¼ g1 þ g2D1 þ g3D2 þ a1ðD1ILÞ þ a2ðD2ILÞ
þ a3ðD1IMÞ þ a4ðD2IMÞ þ a5ðD1ISÞ þ a6ðD2ISÞ
þb1IL þ b2IM þ b3IS þ a7ðD1RFUNÞ þ a8ðD2RFUNÞ
þ b4RFUN þ a9ðD1RPSYÞ þ a10ðD2RPSYÞ þ b6RPSY
þ a11ðD1RFINÞ þ a12ðD2RFINÞ þ b7RFIN þ e: ð5Þ
This equation is automatically reduced to Eq. (1) ifboth D1 ¼ 0 and D2 ¼ 0; turns into Eq. (6) if D1 ¼ 1;and into Eq. (7) if D2 ¼ 1:
Y ¼ g1 þ g2 þ g3 þ ðb1 þ a1ÞIL þ ðb2 þ a3ÞIM
þ ðb3 þ a5ÞIS þ ðb4 þ a7ÞRFUN þ ðb5 þ a9ÞRPSY
þ ðb6 þ a11ÞRFIN þ e; ð6Þ
Y ¼ g1 þ g2 þ g3 þ ðb1 þ a2ÞIL þ ðb2 þ a4ÞIM
þ ðb3 þ a6ÞIS þ ðb4 þ a8ÞRFUN þ ðb5 þ a10ÞRPSY
þ ðb6 þ a12ÞRFIN þ e: ð7Þ
If there are no differences between the stores, thisimplies that a1 ¼ a2 ¼ a3 ¼ a4 ¼ a5 ¼ a6 ¼ a7 ¼ a8 ¼ 0:This is our H0: We can test this hypothesis with theChow test statistic, defined as
RSSp � ðRSS1 þ RSS2Þ� �
=k
ðRSS1 þ RSS2Þ=n1 þ n2 � 2k: ð8Þ
This statistic has an F distribution with (k;n1 þ n2 � 2k) degrees of freedom. RSSP equals theResidual Sum of Squares of the OLS regression on thepooled sample, RSS1 equals the Residual Sum ofSquares of the regression on sample A and RSS2 equalsthe Residual Sum of Squares of sample B; where A andB represent the respective partial samples. Parameters n1
and n2 equal the number of observations in each partialsample, and k is the number of parameters.
A Chow test was first conducted on the pooled sampleof AH and Edah. An F -value of 2.74 was obtained. Thisvalue is larger than 2.01, the cut-off value of Fð0:05;7;1040Þ:Therefore H0; stating homogeneity of the pooled sample(AH-Edah) was not accepted. Furthermore a Chow testwas conducted on the pooled sample on the one hand,and Aldi on the other. The F -value we obtained, 8.92,was again higher than 2.01, the cut-off value ofFð0:05;7;1549Þ: This implied the rejection of H0 for thepooled sample of AH and Edah on the one hand andAldi on the other. The regressions and mediation testswere thus performed separately for the three retailers inorder to tests the propositions. To investigate Proposi-tions P1, P2, P3 and P4, regression analyses wereperformed: attitude towards the store brand wasregressed on the main variables, the store image factorslayout, merchandise and service, as well as the perceivedrisks associated with purchasing different productcategories: functional risk, psychosocial risk and financial
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J. Semeijn et al. / Journal of Retailing and Consumer Services 11 (2004) 247–258 253
risk. The results of these regressions are summarized inTable 3.
4.2. Attitude towards the store brand
Our first proposition stated a direct, positive andlinear relationship between store image and attitude
towards the store brand. Three store image factors weremeasured. The correlations found in our data (see Table2) as well as the mostly significant regression parametersfound (see Table 3) confirm the proposition for the threefactors and the three retailers to different degrees.Results for Edah and Aldi confirmed the proposition forall three factors. Surprising was the absence ofsignificant effects for layout and service in the case ofAH, while the merchandise factor did show the expectedeffect. Hence, it can be concluded that store image
perceptions influence consumers’ judgment of storebrand quality in a positive sense, albeit to differentdegrees for different retailers, and Proposition P1 istherefore supported by the data. The more highly aconsumer thinks of a store the more positively he/shewill evaluate store-branded products.
4.3. Product attributes and associated risks
Proposition P2 was concerned with the effect ofperceived functional risk. A negative relationship wasexpected between the functional risk associated with aspecific product category and attitude towards that
product category carrying a store brand. Support forthe existence of this relationship, in the form of thehighly significant regression parameters (see Table 3),was found for the three retailers and Proposition P2 wasthus confirmed.
Proposition P3 predicted an inverted relationshipbetween the perceived psychosocial risk associated withusing a product and the attitude towards that product
carrying the store brand. Support for the existence of thisrelationship, in the form of the highly significantregression parameters (see Table 3), was again found
and Proposition P3 was thus also confirmed for all threeretailers.
Proposition P4 predicted a negative relationshipbetween the perceived financial risk associated withpurchasing a product in a category with large qualityvariance, and the attitude of the consumer towardsproducts in that category carrying a store brand. Astrong and significant regression coefficient was foundfor all retailers, which confirms Proposition P4.
To test the predicted mediation effects (Baron andKenny, 1986), hypothesized in P2a, P3a and P4a, Sobeltests were conducted (MacKinnon and Dwyer, 1993;MacKinnon et al., 1995; Sobel, 1982) on the factorsobtained for the independent variable (IV), the DV andfor the mediators. The test statistic Z was calculatedaccording to the following formula:
Z ¼a�bffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
ðb2�s2a þ a2�s2
b þ s2a�s2
bÞq : ð9Þ
In this equation, a represents the unstandardized pathcoefficient of a regression of the IV (store image) on themediator (risk perception), b and c the unstandardizedpath coefficients of a regression of the mediator and theIV on the DV (consumer attitude). An overview of theSobel Tests performed to assess the data for mediation ispresented in Table 4.
Based on the above, the original conceptual modelwas adapted. The adapted model is presented in Fig. 2.
The new model explains a number of predicted effects.Many terms were found significant and displayed theexpected signs. The variables with the largest directeffects on consumers’ attitude towards the store brand
were store image and financial risk. A summary of thepropositions and their status is presented in Table 5.
5. Conclusion and implications
The purpose of this study was to explore thecombined effects of retailer and product attributes on
ARTICLE IN PRESS
Table 3
Results of the analyses: direct effects
Retailer Albert Heijn Edah Aldi
Adj. R2 ¼ 0:402; F ¼ 59:617; N ¼ 517 Adj. R2 ¼ 0:410; F ¼ 61:429; N ¼ 516 Adj. R2 ¼ 0:306; F ¼ 38:876; N ¼ 510
Independent variables b (B) t s b (B) t s b (B) t s
Constant 3.728 7.324 0.000 3.497 9.113 0.000 3.842 10.835 0.000
Layout 0.010 0.258 0.797 0.150 3.615 0.000 0.138 3.045 0.002
Merchandise 0.240 5.824 0.000 0.104 2.518 0.012 0.197 4.310 0.000
Service 0.022 0.582 0.561 0.132 3.202 0.001 0.090 2.182 0.003
Functional risk �0.297 �8.266 0.000 �0.183 �5.021 0.000 �0.165 �4.429 0.000
Psychosocial risk �0.114 �3.285 0.001 �0.117 �3.307 0.001 �0.162 �4.249 0.000
Financial risk �0.373 �10.617 0.000 �0.401 �11.353 0.000 �0.299 �8.105 0.000
J. Semeijn et al. / Journal of Retailing and Consumer Services 11 (2004) 247–258254
consumer attitude towards store-branded productsin grocery stores, and to make recommendationswith respect to the most appropriate product cate-gories for new product introduction. Effects for storeimage and three product attributes were hypothesized.The effects were measured in an empirical studyincluding two general grocery stores and a discountstore.
5.1. Store image and quality
Differing store image perceptions across chains are aconsequence of diversity in retail strategy, store designand commitment to serving customers’ needs. Basedon previous research (Richardson et al., 1994, 1996b),a strong relationship was expected between store image
and attitude towards the store brand. Direct andmediated effects were hypothesized. Three storeimage factors were considered: layout, merchandise andservice. Direct effects of all three factors were observedfor two out of three retailers. In the case of AHno significant direct effects were found for Layoutand Service, although associated correlations suggestedthese effects. In the case of AH, the effect of merchandise
was stronger than in the case of the two otherretailers, however. Store image can therefore be con-sidered an important predictor of attitude towards a
store brand.
5.2. Product attributes and related risks
In previous studies, several product attributes havebeen identified as antecedents of store brand success inspecific product categories (DelVecchio, 2001): Com-
plexity, quality variance, and visibility. In the presentstudy, these product attributes have been related to risksto the consumer when purchasing a store brand product.A negative effect of the perceived risks on consumers’evaluations of products sold under a store brand waspredicted. It was also hypothesized that some risks canbe relieved by the perceived store image.
5.2.1. Product complexity and functional risk
Product complexity was associated with perceivedfunctional risks of the product and measured as theperceived difficulty for the store to manufacture it, as aresult of required specialized technological knowledgeand ingredients. It was observed that the less likely theconsumer perceives a certain retailer to be able toproduce a specific product, the more likely it is that theconsumer develops a negative attitude towards such aproduct carrying that retailer’s store brand. From thestudy it became clear that all retailers were able toneutralize some of the functional risk with their storeimage, albeit to different degrees. Clearly the Aldi storeimage has little influence on perceived functional risk.
5.2.2. Visibility of product usage and psychosocial risk
Our research confirmed that public usage of a productreduces the chance that consumers will buy a storebrand, due to the lack of (symbolic) quality. In productcategories where risk of public exposure of the productis an important issue, a manufacturer’s brand will oftenoutperform a store brand. All three retailers are able toneutralize psychosocial risk by their store images.
5.2.3. Quality variance and financial risk
Quality variance within a product category wasexpected to be positively related to the perceived riskof choosing a low quality product and therefore oflosing money. Strong support is present in the data forthe view that perceived quality variance within acategory is related to a negative evaluation of store-branded products in that category. This finding leads to
ARTICLE IN PRESS
Evaluationof Store BrandMerchandise
Physical Layout
Service
PerceivedFinancial Risk
PerceivedPsychosocial Risk
PerceivedFunctional Risk
Store Image Product Class Store Brand
Antecedents Mediators Outcome
-
-
-
-
-
-
-
+
+-
+
-
Fig. 2. Revised model based on empirical observations.
Table 4
Mediating effects of store image factors on perceived risk factors (Z-values)
Retailer: Albert Heijn Edah Aldi
Functional Psychosocial Financial Functional Psychosocial Financial Functional Psychosocial Financial
Layout + + + 3.54�� 4.19�� NS NS 4.14�� NS
Merchandise 3.70�� 2.82�� NS 3.10�� 3.58�� NS 1.93� 2.33� NS
Service + + + 5.03�� 2.99�� NS NS 2.09�� NS
+=no effect expected, NS=not significant, �effect is significant at the 0.05 level, ��effect is significant at the 0.01 level.
J. Semeijn et al. / Journal of Retailing and Consumer Services 11 (2004) 247–258 255
the conclusion that when quality variance within aproduct category is high, it is likely that consumers willchoose manufacturer branded products over storebrands, to reduce the financial risks associated withthat purchase. None of the store image factors was ableto relieve this risk.
5.3. Implications
More and more products, including grocery products,are perceived as commodities. This adds to the interestin, and importance of store brand research. The appealof manufacturers’ brands may wane when consumersbecome increasingly well informed about products witha commodity-like nature. Renewed interest on the partof manufacturers to produce for store brands is there-fore likely (Corstjens and Lal, 2000; Steenkamp andDekimpe, 1997). The role of supermarkets and grocerystores is currently evolving to one of principally service-focused providers. Providing ‘One-Stop Shopping’service creates an obvious benefit to consumers (Semeijnand Vellenga, 1995). Offering an increasing variety of‘store-certified’ goods, with clear labeling, would be partof such a service. The reduction of risk, the building oftrust, and the time savings afforded to hurriedconsumers will likely contribute to store loyalty (Dicket al., 1996).
The findings of this study have implications fordecision-makers in the grocery business. It is criticalthat profitable new product opportunities can beidentified, by investigating the circumstances in whichproduct categories will be beneficial to a store brandassortment (Ailawadi, 2001; Raju et al., 2001). Thepresent study has provided some new insights into thismatter. New store brand products have greatest
potential in product categories associated with lowfunctional, psychosocial and financial risk. Conversely,products in a category with large quality variance andhigh public visibility are more likely to fail. Dhar andHoch (1997) point to the fact that retailers can take thelead in the further development of store brands. Thepresent study confirms that developing, nourishingand sustaining a store image can create opportunitiesto achieve differentiation and positioning relativeto other chains and sell profitable store brands. Retailersshould therefore focus on aspects, such as storeenvironment, merchandise quality and value, andcustomer service.
5.4. Limitations and suggestions for further research
The analysis was based on data collected about fourproduct categories that were available from threeretailers, evaluated by a select group of consumers,and collected through a questionnaire that was adminis-tered on-line. It would be valuable to further test themodel with data from more retailers in different(international) markets, with a wider range of productcategories, or in different sectors, and to include moreconsumer-level variables, as previously suggested byBatra and Sinha (2000). An analysis of heavy storebrand users and a comparison of brand pairs (manu-facturers’ and store brands) have also been suggested(Ailawadi, 2001; Raju et al., 2001).
In the present study significant differences were foundbetween the three retailers. This points at the fact thatthe resulting model is not complete. An attempt todistinguish conceptually between explicitly branded (asin the case of AH and Edah) and un-branded storelabels (as in the case of Aldi), or between private labels
ARTICLE IN PRESS
Table 5
Status of the propositions
No. Proposition Proposition status
Albert Heijn Edah Aldi
1 There will be a direct positive relationship between perceived store image and consumer
attitude towards store branded products.
| | |
2 Consumer attitude towards a store branded product is inversely related to the functional
risk associated with the perceived difficulty for the retailer to produce that product.
| | |
2a The effect of store image on consumer attitude towards a store branded product is
mediated by the functional risk associated with the perceived difficulty for the retailer to
produce that product.
| | (|)
3 Consumer attitudes towards a store branded product are inversely related to the
perceived psychosocial risk associated with the usage of that product.
| | |
3a The relationship between store image and consumer attitude towards a store branded
product is mediated by the perceived psychosocial risk of usage.
| | |
4 Consumer attitude towards a store branded product is inversely related to the perceived
financial risk associated with quality variance in the product category.
| | |
4a The effect of store image on consumer attitude towards a store branded product is
mediated by the financial risk associated with the perceived difficulty for the retailer to
produce that product.
� � �
J. Semeijn et al. / Journal of Retailing and Consumer Services 11 (2004) 247–258256
and store brands could be a first step to further improveunderstanding of consumer evaluations of store brands.
Furthermore, no individual propositions were devel-oped for the effects of the different store image factorson the various categories of perceived risk. A betterunderstanding of the effects of the various store imagefactors could lead to a greater strategic consistency andbetter resource allocation decisions.
Acknowledgements
The authors wish to express their gratitude to theeditor and the anonymous reviewers for providing themwith helpful comments and invaluable suggestions forimprovements.
Appendix
Composition of store image factors (factor loadings)is given in Table 6.
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Item Layout
ða ¼ 0:70ÞMerchandise
ða ¼ 0:82ÞService
ða ¼ 0:78Þ
Physical facilities are visually appealing 0.78
Store layout is clear 0.86
Easy to find articles in promotion 0.74
Merchandise is available when needed 0.83
Store offers high quality merchandise 0.87
Store offers broad assortment 0.88
Employees are knowledgeable 0.75
Employees are courteous 0.81
No problems when returning items 0.68
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Janjaap Semeijn is Professor of Marketing and Logistics in the
Management Sciences department at the Open University of the
Netherlands and an Associate Professor of Logistics and Supply Chain
Management in the department of Marketing at Maastricht Uni-
versity. He received a Master’s degree at the American Graduate
School of International Management and a Ph.D. in Logistics
Management at Arizona State University (1994). He has published
in various international journals, such as Transportation Journal,
International Journal of Logistics Management and International
Journal of Physical Distribution and Logistics.
Allard C.R. van Riel is an Assistant Professor in Logistics and
Marketing in the department of Marketing at Maastricht University.
He holds a degree in Philosophy from the University of Amsterdam
and has been active in the International Publishing Industry for almost
ten years. His Ph.D. research focused on Marketing Decision Making
under Uncertainty in the area of IT-based Service Innovation (2003).
He published in a variety of international journals, such as the Journal
of Service Research, the International Journal of Service Industry
Management, Journal of Services Marketing, European Management
Journal, and Total Quality Management, as well as in various edited
books.
Ana Beatriz Ambrosini recently completed her Master’s degree in
International Business in the department of Marketing at Maastricht
University.
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