Food Quality and Preference 32 (2014) 289–298

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Food Quality and Preference

journal homepage: www.elsevier .com/locate / foodqual

Brand awareness–Brand quality inference and consumer’s riskperception in store brands of food products

0950-3293/$ - see front matter � 2013 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.foodqual.2013.09.006

⇑ Corresponding author. Address: Departamento de Financiación e InvestigaciónComercial, Facultad de CC. Económicas y Empresariales, Universidad Autónoma deMadrid, c/Francisco Tomás y Valiente, 5, Campus de Cantoblanco, 28049 Madrid,Spain. Tel.: +34 914973567; fax: +34 914978725.

E-mail addresses: natalia.rubio@uam.es (N. Rubio), javier.oubinna@uam.es (J.Oubiña), nieves.villasenor@uam.es (N. Villaseñor).

Natalia Rubio ⇑, Javier Oubiña, Nieves VillaseñorDepartment of Finance and Marketing Research, Business Studies Faculty, Autónoma University of Madrid, Spain

a r t i c l e i n f o

Article history:Received 29 May 2013Received in revised form 11 September 2013Accepted 12 September 2013Available online 29 September 2013

Keywords:Store brandsBrand awareness–brand quality inferenceFunctional riskRisk-reduction strategiesBrand identificationQuality consciousness

a b s t r a c t

Store brands (SBs) have currently become consolidated in the food market, have achieved an objectivequality similar to that of manufacturer brands and a competitive price. However, food retailers haveinvested little in communication about these brands, considering it enough to use proximity to the con-sumer and economies of scope derived from the presence of their own brands throughout the establish-ment. This paper explores the consequences of this communication strategy about SBs on the functionalrisk perceived by consumers for these brands and the consumer’s identification with them. We propose atheoretical model, contrast it empirically for food products, and perform a multigroup analysis of qualityconscious and non-quality conscious consumers. The results obtained reveal a negative effect of the infer-ence brand awareness–brand quality on the consumer’s identification with the SB as a result of thegreater functional risk perceived for these brands. This effect is substantially greater in quality consciousconsumers, a key segment for retailers since it constitutes the target of their premium SBs. The resultsshow retailers that investment in communication of SBs is absolutely necessary to dismiss SB functionalrisk and expand customer base by appealing to quality conscious consumers. The investigation has sig-nificant implications for the retailer’s strategy for marketing SBs in food products.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Brand identification is a fundamental antecedent of brand loy-alty and thus plays a crucial role in the consumer’s brand choiceand buying behavior (Ahearne, Bhattacharya, & Gruen, 2005). Thestudy of brand identification has focused predominantly on manu-facturer brands (Marin, Ruiz, & Rubio, 2009), and we find no re-search that focuses on the consumer’s identification with storebrands (SBs).

Although SBs were initially introduced in food markets as low-quality, low-price brands, distributors are attempting to improvethe quality of SBs and position them as the best choice on theshelves in terms of price/quality ratio. Currently, consumers per-ceive SBs as value brands, and manufacturers and distributors con-sider them as real brands that are beginning to have their ownidentity. In fact, the academic literature has produced some recentstudies praising their brand equity (Cuneo, López, & Yagüe,2012a,b).

SBs possess a set of characteristics that differentiate them frommanufacturer brands and make it necessary to rethink study of theconsumer’s identification with the brand in the specific context ofSBs. Perceived value and low investment in advertising communi-cation are common features distinctive to SBs. Taking advantage oftheir closer position to the consumer as members of the channel,food retailers have communicated their brands fundamentallythrough the establishment. Retailers have also benefitted fromeconomies of scope in communication deriving from commercial-ization of their brand in a large number of product categories.

Different studies stress the importance of advertising in brandawareness (Aaker, 1996; Buil, de Chernatony, & Martínez, 2013;Kirmani & Wright, 1989), as well as the importance of brandawareness in the perception of brand quality (Aaker, 1996; Builet al., 2013; Keller & Lehmann, 2003). While consumers draw con-clusions about the quality of a brand based on their evaluation ofits intrinsic attributes (Shaharudin, Mansor, & Elias, 2011; SuleAlonso, Paquin, & Levy Mangin, 2002), its packaging (Lavenka,1991; Rigaux-Bricmont, 1982) or its price (Cronley, Posavac,Meyer, Kardes, & Kellaris, 2005; Kardes, Cronley, Kellaris, &Posavac, 2004; Lim & Olshavsky, 1988), one of the elements thatmost strongly conditions perception of a product’s quality is thebrand name (Dawar & Parker, 1994). We will call the causal asso-ciation that many consumers make between recognized brand andhigh quality the brand awareness–quality inference. This paper

290 N. Rubio et al. / Food Quality and Preference 32 (2014) 289–298

analyzes the importance of this inference in the consumer’s identi-fication with the SB in food markets, and proposes its negativeindirect effect on identification through the functional risk the con-sumer perceives for these brands.

Although the perceived quality of SBs has improved due tofavorable evolution of their intrinsic and extrinsic attributes, thereis still a significant difference between the perceived risk of man-ufacturer and SBs to the disadvantage of SBs. The risk entailed inbuying a brand conditions significantly the entire process of theconsumer’s evaluation and comparison of manufacturer and SBs(Erdem, Zhao, & Valenzuela, 2004; Glynn & Chen, 2009; Richardson,Jain, & Dick, 1996). This risk affects the perceived value and theconsumer’s satisfaction with these brands and is thus also verylikely to affect the consumer’s identification with the SB.

On the other hand, consumers differ considerably in their qual-ity consciousness (Sproles & Kendall, 1986), and analysis of theeffect of brand awareness–quality on the consumer’s identificationwith the SB should control for this issue. In this study, we thereforeperform a multi-group analysis based on the consumer’s qualityconsciousness and compare the results obtained. We find thatquality consciousness moderates the effect of brand awareness–quality on perceived functional risk for SBs. Quality consciousconsumers are more brand conscious and place more trust in theperformance of recognized and advertised brands. They perceivemore functional risk for SBs and thus tend to dismiss their satisfac-tion and identification with these brands. The study results haveinteresting implications for retail management of these brands.

2. Literature review

SBs have greater penetration in the European market than inthe U.S. One of the reasons the academic literature gives for thisdifference is the greater perceived value of SBs in Europe than inthe U.S. (Erdem et al., 2004). The perceived value of a brand in-volves considering brand quality not in absolute terms but relativeto its price (Richardson et al., 1996). Perceived value forms as a re-sult of the consumer’s experiences purchasing and consuming abrand (Cronin, Brady, & Hult, 2000). Sethuraman (1992) finds that,although most consumers choose SBs primarily for their advantagein price, quality plays a more significant role than price in thesuccess of SBs, especially if we understand this success fromthe long-term strategic perspective. Since the perceived qualityof SBs affects their perceived risk, their perceived value, consumersatisfaction, and consumer brand identification, it is important tounderstand the aspects of the brand that determine perceivedquality and how perceived quality affects and is related to thesekey elements in the success of any brand.

2.1. Perceived functional risk of SBs

One of the issues most strongly influencing the perceived qual-ity of a brand is its brand awareness (Aaker, 1991, 1996; Buil et al.,2013; Dawar & Parker, 1994; Keller and Lehman, 2003). Consumersassign high quality to prestigious brands. Such brands thereforeenjoy greater credibility for the consumer and ultimately greatervalue (Erdem & Swait, 1998; Erdem, Swait, & Louviere, 2002).Awareness encourages the perceived quality of the brand and thusalso its credibility due to lower perceived functional risk for thebrand.

This investigation defines perceived risk as the expectation ofcertain results or events that may occur and that are negative orsuspect. The consumer faces four main kinds of risk in the processof deciding to buy a product: functional, financial, psychological,and social (Dowling & Staelin, 1994; Kaplan, Szybillo, & Jacoby,1974). Functional risk indicates the performance or utility

conceived for the product, financial risk the potential loss of moneythat can occur in any transaction, psychological risk the possibleconsequences of mental uneasiness connected with a transaction,and social risk the bad image that consuming a product may givean individual in the eyes of others. This study analyzes the effectof the brand awarenesss–quality inference on perception of the func-tional risk of SBs. Functional risk is directly linked to perceivedquality, an issue that constitutes the main point of resistance toacquiring SBs in products of mass consumption (DelVecchio,2001; Liljander, Polsa, & Van Riel, 2009; Méndez, Oubiña, & Rubio,2011; Richardson et al., 1996).

In choosing a brand, the consumer faces uncertainties thatmake it difficult to evaluate the functional risks involved in thepurchase. To reduce these uncertainties the consumer uses risk-reduction strategies such as (1) information gathering from per-sonal (friends, family) and commercial (packaging, salespersons)sources, (2) well-known brands, (3) reassurance (e.g., through pri-vate testing, free samples), (4) brand loyalty, (5) price, and (6) storeimage (Mitchell & McGoldrick, 1996; Schiffman & Kanuk, 2006).Knowing the main risk reduction strategies that the consumer usesin choosing a manufacturer brand vs. an SB is vital to retailers inmanaging their service and in providing a risk-reduction marketingmix for consumers (Johnson & Bruwer, 2004; Lacey, Bruwer, & Li,2009).

Based on a review of over 100 articles, Mitchell and McGoldrick(1996) highlight the search for information and well-knownbrands as the main risk-reduction strategies used by consumers.However, the use and hierarchy of risk-reduction strategies varyby product, individual profile, and type of purchasing establish-ment (among other issues), making it advisable to limit study ofthese strategies to specific contexts. Bruwer, Fong, and Saliba(2013) find that the main risk reduction strategy for purchasingwine in specialty wine stores is information gathering, for whichthey obtain significant differences between low and high perceivedrisk individuals, followed by seeking reassurance through tastingand price. For wine acquired in restaurants, however, Lacey et al.(2009) identify tangible product attributes as the most significantrisk-reduction strategy, followed by advice from staff and the res-taurant’s reputation.

To evaluate store and manufacturer brands comparatively forproducts of mass consumption, consumers seek and use informa-tion from the extrinsic attributes (e.g., brand name, price) andthe intrinsic attributes of the product (e.g., ingredients, texture).These attributes help the consumer to make his or her own evalu-ation of quality (Wernerfelt, 1988; Zeithaml, 1988). Extrinsic attri-butes have been traditionally valued more highly in manufacturerbrands than in SBs. It is thus reasonable to think that consumerswho are guided more strongly by extrinsic attributes as indica-tors of perceived quality perceive lower functional risks in manu-facturer brands than in SBs. Erdem et al. (2004) find that thebuyer’s initial uncertainty is usually greater for SBs than formanufacturer brands; and Erdem and Swait (1998), Erdem et al.(2002), Schiffman and Kanuk (2006) argue that consumers use arisk-reduction strategy when they buy prestigious manufacturerbrands, to which they assign high perceived quality.

Consumer reliance on extrinsic attributes of a product is likelyto be the main explanation for the lower perceived quality ofSBs. In fact, González, Díaz, and Trespalacios (2006) find that con-sumer reliance on extrinsic attributes of the product is negativelyrelated to the perceived quality in SBs vs. manufacturer brandsand positively related to the difference in risk between SBs andmanufacturer brands.

Based on the aforementioned, we propose the followinghypothesis:

H1: The greater the inference brand awareness–brand quality,the greater the functional risk perceived in the SB.

N. Rubio et al. / Food Quality and Preference 32 (2014) 289–298 291

2.2. Perceived value of SBs

Richardson et al. (1996) suggest that retailers put more empha-sis on quality than on low prices to improve consumers’ perceptionand increase sales of their own brands. These authors recommendthat retailers use different methods to increase perception of SBquality. To achieve this goal, retailers can invest in advertising,encourage consumer product experience through sampling (Sprottand Shimp, 2004; Goldsmith, Flynn, Goldsmith, & Stacey, 2010), in-vest in store image, or choose to develop SBs in food products thathave low quality variation across brands and are strongly associ-ated with quality in consumers’ mind (i.e., the signature product)(Bao, Bao, & Sheng, 2011). This strategic orientation would helpretailers to expand their customer base by appealing to qualityconscious consumers (Bao et al., 2011; Sprott and Shimp, 2004).

Consumers perceive manufacturer brands as safe brands,brands with less variation in the quality of their products thanSBs (Montgomery & Wernerfelt, 1992). The credibility and trustachieved by manufacturer brands over time have contributed con-siderably to their perceived value (De Wulf, Odekerken-Schröder,Goedertier, & Van Ossel, 2005). In contrast, the higher perceivedrisk of SBs has acted to the detriment of their perceived value(Richardson et al., 1996). Therefore, both manufacturer brandsand SBs give the consumer value, but manufacturer brands haveconsolidated their value through quality, whereas SBs have consol-idated theirs through price. Although it is true that the quality ofSBs has improved substantially over time, recent studies find that,although their objective quality is similar to that of manufacturerbrands, their perceived quality continues to be significantly lower(Méndez, Oubiña, & Rubio, 2008; Méndez et al., 2011).

Based on the foregoing, we establish the following studyhypotheses:

H2. Quality consciousness positively moderates the effect of theinference brand awareness–brand quality on the functional riskperceived in the SB, making this effect stronger for consumers withgreater quality consciousness.

H3: The greater the functional risk perceived for the SB, thelower the perceived value of these brands.

2.3. Consumer’s satisfaction and identification with SBs

Perceived risk is related to the losses and negative conse-quences anticipated if one makes the wrong choice. It is thus rea-sonable to expect that, when the perceived risk of a service or abrand increases, the satisfaction with that service or branddecreases (Cronin et al., 2000; Dowling & Staelin, 1994; Gocek &Beceren, 2012; Hallowell, 1996; Hu, Kandampully, & Juwaheer,2009; Johnson, Garbarino, & Sivadas, 2006 and Johnson, Sivadas,& Garbarino, 2008, among others). Further, Gocek and Beceren(2012) indicate that perceived risk is one of the main factors influ-encing customer satisfaction. Nador (2012) warns that perceivedrisk affects the success of marketing strategy for the brand or firmand underscores the importance of managing it effectively. Alongthese lines, the study by Johnson et al. (2006, 2008) proposes thatthe company reduce the risk that the consumer perceives for itsbrand by providing purchase guarantees that increase the brand’sperceived value and thus satisfaction with it as a possible manage-ment strategy.

Based on the foregoing, we propose the following hypothesesconcerning SBs:

H4: The greater the functional risk perceived for the SB, thelower the consumer’s level of satisfaction with it.

H5: The greater the perceived value of the SB, the greater theconsumer’s satisfaction with it.

Satisfying the consumer involves achieving the consumer’spleasure in consuming the brand and desire to repeat this

experience. This is one of the fundamental strategic concepts inmarketing, since it generates an explicit relationship between theprocesses of purchase and consumption and the post-purchasephenomenon (Hunt, 1983).

Brand satisfaction has a positive influence on the relationshipbetween consumer and brand (Gocek & Beceren, 2012), more spe-cifically, on one of the most important aspects of this relationship,the brand identification. According to the theory of social categori-zation and identification, an individual identifies with a social cat-egory when the social category (and the social identity associatedwith it) improves his or her self-esteem. An identified individualwill show positive pro-category behavior to preserve the attrac-tiveness of this social identity (and thus his/her self-esteem)(Bhattacharya & Sen, 2003; Tajfel & Turner, 1985).

Brands can be social categories with which consumers identify.The academic literature defines the consumer’s identification withthe brand as self-connection with a brand (Fournier, 1998), con-gruence of self-image between consumers and brands (Kressmannet al., 2006), or the consumer’s involvement with a brand (Prit-chard, Havitz, & Howard, 1999). Ahearne et al. (2005) define it as‘‘an active, selective, deliberate act motivated by the satisfactionof one or more needs for self-definition (for example: ‘‘Who amI?’’)’’.

Empirical studies (Ahearne et al., 2005; Marin et al., 2009) findthat consumers with stronger brand identification are more likelyto ‘‘get hooked’’ on pro-brand activities in favor of the brand, suchas word of mouth and brand loyalty. When articulating their self-perception, individuals go beyond their personal identity and de-velop a social identity. Brand identification shows the degree towhich the brand expresses and improves individual identity(Kim, Han, & Park, 2001). Individuals who identify with a particularbrand experience a positive psychological result in the form of im-proved self-esteem and are more likely to act favorably toward thebrand (Donavan, Janda, & Suh, 2006).

SBs can express and improve the identity of individuals satisfiedwith the purchase experience at the retailer (Bitner, 1992; Verhoefet al., 2009) and their experience consuming these brands (Brakus,Schmitt, & Zarantonello, 2009). They can also express and improvethe identity of individuals who perceive a value for these brandsthat reinforces their self-image as intelligent customers. Thevalue-conscious consumer and smart shopper are concepts associ-ated with the attitude and purchase of SBs in various academicstudies (Burton, Lichtenstein, Netemeyer, & Garretson, 1998;Dabholkar, 1996; Garretson, Fisher, & Burton, 2002; Jin & Suh, 2005).

Based on the foregoing, we formulate the last two hypotheses:H6: The greater the consumer’s satisfaction with the SB, the

greater the identification with the SB.H7: The greater the perceived value of the SB, the greater the

degree of identification with the SB.Fig. 1 presents the theoretical research model.

3. Methodology

To contrast the hypotheses proposed, we performed an empiri-cal study of people responsible for shopping in their householdswho stated that they purchase SBs in food products. In the firstphase of the research, we performed twenty in-depth interviewsof individuals from the study group. From these, we obtainedexploratory starting information that enabled us to determinethe relationship between consumers and SBs and thus subse-quently to design a better questionnaire. Specifically, the questionsposed to the consumers in the in-depth interviews enabled us todetermine in detail the perceptions and attitudes of the individualsresponsible for buying these brands. We could then determine pos-sible issues that influenced their purchase, explore consumers’

Brand awareness-quality inference

SB satisfaction

SB identification

SB perceived value

SB functional risk

H3

H4

H7

H5

H1

H6H2

Qualityconsciousness

Source: Developed by the authors

Fig. 1. Theoretical model.

292 N. Rubio et al. / Food Quality and Preference 32 (2014) 289–298

image of the manufacturers, retailers, and consumers of these SBs,and analyze how these consumers explain and interpret the lowerprice of SBs, among other issues.

The in-depth interviews were performed with Spanish residentschosen through non-random sampling with quotas for gender, age,occupation, and number of members in the household. Participantswere mainly recruited by the snowball sampling method (theauthors’ friends and colleagues were asked to refer a friend withwhom the authors were not acquainted). One of the main advanta-ges of this sampling method is the ease and speed in obtaining thequotas desired, while one of its main disadvantages is that respon-dents engaged in similar social circles may share attitudes and be-liefs (May, 2001). The results of the in-depth interviews allowed usto design the questionnaire, use language adapted to the intervie-wee, and adapt the items used in past research to the specificcontext.

The second phase of the research was quantitative. Data werecollected through self-administered questionnaires from Spanishresidents in Spain. The information came from a personal surveyat the exit of 54 purchase establishments belonging to sevenhypermarkets and supermarkets from five significant commercialgroups in Spain (Mercadona, Eroski, Carrefour, Día, and Auchan).These five groups have a very strong presence in Spain, in termsof both commercial surface (around 52% of the commercial surfacein m2 in 2010) and sales volume in food products (around 64% ofthe sector’s income in 2010) (The Brattle Group, 2012). The num-ber of establishments per group was determined according to thecommercial surface share in m2 of each group in 20101 (14 estab-lishments for Mercadona, 13 for the Eroski group, 12 for the Carre-four group, 10 for Día, 5 for Auchan). The establishments werechosen according to different urban areas based on income, retailcompetition, and means of transportation.

At the exit of the commercial establishments, students in the fi-nal year of graduate courses in marketing who possessed generaltraining in market research and specific training in SBs recruitedshoppers who agreed to complete a self-administered question-naire approximately 10 min in length. We obtained a total of 877questionnaires (20 per establishment); 804 were considered valid2.

The items that we used to measure the concepts proposed comefrom the adaptation of scales used previously in the academic lit-erature. Specifically, to measure the brand awareness–qualityinference, we adapt the items employed by Richardson et al.(1996), Dick, Jain, and Richardson (1997), and Sethuraman andCole (1997), as well as those from DelVecchio (2001) in extrinsic

1 Mercadona (13.2%), Eroski (12.2%), Carrefour (12%), Día (9.3%), and Auchan (5.2%).We use share of commercial surface instead of share of sales to avoid possible bias inthe results due to Mercadona’s outstanding leadership in sales and in its own brandsin Spain.

2 Mercadona (201), Eroski (191), Carrefour (185), Día (149), Auchan (78).

cue reliance. To measure perceived value, we use the items that re-fer to value from the scale for SB attitude developed by Burtonet al. (1998). We adapt the measure for brand satisfaction fromthe research of Oliver (1980), and we construct the scale for func-tional risk following the operationalizations of Stone & Gronhaug(1993); Dholakia (1997). For consumer identification with the SB,we adapt the well-established scale proposed by Mael andAshforth (1992). Finally, we measured the consumer’s qualityconsciousness with three statements from the scale developed bySproles and Kendall (1986): ‘‘Getting very good quality is veryimportant to me,’’ ‘‘In general, I usually try to buy the best overallquality,’’ and ‘‘I make a special effort to choose the very best qualityproducts.’’ We obtained an Alpha Cronbach of 0.73 for this scale,which guaranteed its reliability.

Not all consumers are equally sensitive to quality, nor do theyshow the same degree of involvement in it (Sproles & Kendall,1986). To determine the moderating effect that quality conscious-ness has on the causal effect of the brand awareness–quality infer-ence on SBs’ perceived functional risk (H2), we classify consumersinto two segments, those with a high degree of involvement inquality and for whom quality is the main factor determining theirpurchase decisions (designated as ‘‘quality conscious consumers(QC consumers)’’), and those for whom the attribute of quality doesnot have as much relevance (designated as ‘‘non-quality consciousconsumers (NQC consumers).’’ We identify these two segments byapplying a TwoStep cluster analysis to the survey respondents’ re-plies on the three items used to measure quality consciousness.The results obtained with TwoStep cluster analysis were validatedwith the results obtained using Ward’s method. Both proceduresprovide nearly identical results.

Table 1 shows the differences between the two segments for thevariables in the model. The variance analysis performed shows sta-tistically significant differences in brand awareness–quality infer-ence and functional risk. QC consumers use brand as an indicatorof quality more often (MeanQC = 3.37; MeanNQC = 3.08) and per-ceive greater functional risk in purchasing SBs (MeanQC = 3.55;MeanNQC = 3.27).

We used multi-item 7-point Likert scales from 1 (disagree com-pletely) to 7 (agree completely). Tables 2 and 3 describe the scalesused with their corresponding items. We estimated the empiricalmodel using structural models of covariance with the statisticalpackage AMOS 19.

4. Results

4.1. Measurement model

For each of the samples, we confirmed the quality of the mea-surement scales, as recommended by Byrne (2001). We performed

Table 1Differences between QC consumers and NQC consumers.

Variable/construct QC n = 439 NQC n = 365 Total F-snedecor

Brand awareness–quality inference 3.37 (1.30) 3.08 (1.11) 3.23 (1.27) 10.605⁄⁄⁄

SB functional risk 3.55 (1.60) 3.27 (1.29) 3.42 (1.47) 6.991⁄⁄⁄

SB perceived value 4.09 (1.48) 4.21 (1.17) 4.15 (1.35) 1.840SB satisfaction 4.44 (1.34) 4.55 (1.09) 4.49 (1.23) 0.594SB identification 4.16 (1.51) 4.20 (1.24) 4.17 (1.39) 0.128

Standard deviation in parentheses.⁄⁄⁄p < 0.01.

Table 2Analysis of reliability and validity of measurement scales for the sample of QC consumers.

Variables Li Ei Reliability Validity

AlphaCronbach

Compositereliability (CR)

Average varianceextracted (AVE)

Convergentvalidity

Awareness–quality inference t = 11.44⁄⁄⁄

v1: When the product is not from a recognized brand, it is lower quality 0.77 0.41 t = 12.69⁄⁄⁄

v2: The ‘‘more famous’’ the brand name, the better the quality of a product thatcarries that name

0.87 0.25 0.86 0.86 0.55 t = 11.80⁄⁄⁄

v3: Brand name is a determining issue in purchasing a product 0.70 0.51 t = 15.14⁄⁄⁄

v4: The more a product is advertised, the better its quality 0.73 0.47 –v5: I feel secure purchasing a brand whose advertising I have seen in some

communications medium0.61 0.63

SB functional riskv6: Purchasing a well-known manufacturer brand (MB) is safer than

purchasing a well-known SB0.81 0.34 0.86 0.86 0.68 t = 17.84⁄⁄⁄

v7: SBs have worse performance than MBs 0.86 0.26 t = 18.85⁄⁄⁄

v8: A product with a ‘‘famous’’ MB will perform better than an SB, even if theSB is from a recognized establishment

0.79 0.37 t = –

SB perceived value 0.88 0.88 0.71v9: For many products, the best purchase (for price/quality ratio) is generally

the SB0.82 0.33 t = 19.65⁄⁄⁄

v10: Considering value for money, I prefer SBs to MBs 0.88 0.23 t = 21.52⁄⁄⁄

v11: When I buy an SB, I always feel that I am getting a good deal 0.83 0.32 t = –SB satisfaction 0.88 0.90 0.71v12: With SBs, I always get what I am looking for 0.84 0.30 t = 18.17⁄⁄⁄

v13: SBs always meet my expectations as a consumer 0.84 0.30 t = –v14: My choice to buy SBs is a wise one 0.92 0.16 t = 20.56⁄⁄⁄

SB identification 0.88 0.89 0.73v15: I feel identified with SBs 0.75 0.44 –v16: When someone praises SBs, I feel exactly the same way 0.90 0.19 t = 19.41⁄⁄⁄

v17: I feel proud of SBs 0.91 0.18 t = 19.51⁄⁄⁄

Significance level: ⁄⁄⁄p < 0.001.Li: Standardized loading; Ei = (1 � R2): error variance; CR ¼

PLið Þ2

PLið Þ2þ

PvarðEiÞ

AVR ¼P

L2P

LþP

varðEÞ.

N. Rubio et al. / Food Quality and Preference 32 (2014) 289–298 293

a confirmatory factor analysis with the AMOS 19.0 program. Theresults showed very satisfactory fits in both samples for modelingthe five factors proposed. In the sample of QC consumers, the rela-tionship X2/df was 1.994, close to the maximum threshold of 2 rec-ommended by Bentler (1989). The values of the CFI and AGFI were0.979 and 0.924, respectively, higher than the minimum value of0.9 recommended by Bentler (1989) and Bentler and Bonett(1980). The value of the RMSEA was 0.048, lower than the maxi-mum value of 0.06 suggested by Hu and Bentler (1999). In the sam-ple of NQC consumers, the values obtained also respect the limitssuggested in the academic literature (X2/df = 1.673, CFI = 0.976,AGFI = 0.924 and RMSEA = 0.043).

Tables 2 and 3 show the results for reliability and validity forboth samples (QC consumers and NQC consumers). In all cases,the statistics used for reliability–the Alpha Cronbach and compos-ite reliability–are higher than the minimum value of 0.70 (Hair,Anderson, Tatham, & Black, 1998). The variance extracted is in allcases higher than or equal to a variance of 0.5, and all items havesufficient convergent validity, since all of the parameters are statis-tically significant.

We also confirmed the discriminant validity in both samples. InTable 4, we see that the root of the percentage of variance

extracted for each construct is in all cases higher than the correla-tion between each pair of concepts.

Finally, we examine the measurement invariance between thetwo groups as follows. First, we perform a multigroup confirmatoryanalysis and find that the results show satisfactory fit(X2 = 381.382; df = 208; X2/df = 1.834; CFI = 0.978; NFI = 0.953;IFI = 0.978; GFI = 0.948; AGFI = 0.924; RMSEA = 0.032). Second, weimpose the restriction of equality of parameters for the two sam-ples and compare the results for goodness of fit for the restrictedmodel with the results for the goodness of fit for the unrestrictedmodel (DX2 = 12.58; Ddf = 12; p = 0.4 > 0.01). Since we do not seesignificant worsening in the model’s fit, this result guarantees thatmeasurement invariance is fulfilled. Thus, the differences that weobserve between the causal relationship models will be due tothe causal relationships themselves and not to the measurementof the constructs.

4.2. Causal relationship model

We estimate the model in Fig. 1 using structural equationsmodeling, without including the moderating effect (H2). The fit ob-tained is satisfactory (X2 = 238.946; df = 108; X2/df = 2.212;

Table 3Analysis of reliability and validity of measurement scales for NQC consumers.

Variables Li Ei Reliability Validity

AlphaCronbach

CompositeReliability (CR)

Average VarianceExtracted (AVE)

Convergentvalidity

Awareness–quality inference t = 8.37⁄⁄⁄

v1: When the product is not from a recognized brand, it is lower quality 0.75 0.45 0.82 0.83 0.49 t = 8.88⁄⁄⁄

v2: The ‘‘more famous’’ the brand name, the better the quality of a productthat carries that name

0.78 0.40 t = 8.68⁄⁄⁄

v3: Brand name is a determining issue in purchasing a product 0.62 0.62 t = 10.69⁄⁄⁄

v4: The more a product is advertised, the better its quality 0.78 0.40 –v5: I feel secure purchasing a brand whose advertising I have seen in some

communication medium0.56 0.69

SB functional riskv6: Purchasing a well-known manufacturer brand (MB) is safer than

purchasing a well-known SB0.75 0.43 0.84 0.84 0.64 t = 14.80⁄⁄⁄

v7: SBs have worse performance than MBs 0.82 0.32 t = 16.00⁄⁄⁄

v8: A product with a ‘‘famous’’ MB will perform better than an SB, even if theSB is from a recognized establishment

0.83 0.32 t = –

SB perceived value 0.83 0.83 0.62v9: For many products, the best purchase (for price/quality ratio) is generally

the SB0.77 0.38 t = 14.62⁄⁄⁄

v10: Considering value for money, I prefer SBs to MBs 0.79 0.41 t = 14.97⁄⁄⁄

v11: When I buy an SB, I always feel that I am getting a good deal 0.81 0.35 t = –SB satisfaction 0.83 0.86 0.67v12: With SBs, I always get what I am looking for 0.82 0.34 t = 13.30⁄⁄⁄

v13: SBs always meet my expectations as a consumer 0.80 0.37 t = —v14: My choice to buy SBs is a wise one 0.84 0.30 t = 13.68⁄⁄⁄

SB identification 0.85 0.85 0.65v15: I feel identified with SBs 0.79 0.37 –v16: When someone praises SBs, I feel exactly the same way 0.80 0.36 t = 15.74⁄⁄⁄

v17: I feel proud of SBs 0.82 0.33 t = 16.08⁄⁄⁄

Significance level: ⁄⁄⁄p < 0.001.Li: Standardized loading; Ei = (1 � R2): error variance; CR ¼

PLið Þ2

PLið Þ2þ

PvarðEiÞ

AVR ¼P

L2P

LþP

varðEÞ.

294 N. Rubio et al. / Food Quality and Preference 32 (2014) 289–298

CFI = 0.983; NFI = 0.970; IFI = 0.983; GFI = 0.967; AGFI = 0.953;RMSEA = 0.039), and all of the proposed hypotheses are confirmed.The path coefficients for the overall model appear in Table 5.

We now consider the moderating effect and perform a multi-group structural analysis for the segments of QC consumers andNQC consumers. We compare the results of the two models—thefirst, unrestricted model, and a second model, on which we imposethe restriction of equality for the structural parameters in the twosegments (restricted model). The results for goodness of fit show asignificant worsening in the model when we impose the restric-tions of equality on the structural relationships. This suggests thatsome restrictions cannot be sustained. See Table 6.

Table 7 shows the non-standardized structural parameters foreach of the segments considered and the critical ratios obtainedfor the differences. In comparing the models, we must rememberthat we use non-standardized parameters due to the possible pres-

Table 4Analysis of discriminant validity for both pairs of samples (QC consumers and NQC consu

Brand awareness–quainference

Brand awareness–quality inference QC consumers 0.74NQC consumers 0.70

SB functional risk QC consumersNQC consumers

SB perceived value QC consumersNQC consumers

SB satisfaction QC consumersNQC consumers

SB identification QC consumersNQC consumers

The data in the table that appear in bold on the diagonal are the square root of the AVEThe data above the diagonal correspond to the correlations between pairs of constructs

ence of differences in the standard deviation of each construct be-tween the samples (Iglesias & Vázquez, 2001). We use a t-testbased on the expression t = (bi–bj)/square root (Si

2 + Sj2), in which

bi and bj represent the coefficients to be contrasted and Si and Sj

their respective standard errors (Hair et al., 1998), to calculate sta-tistical significance of the differences between parameters.

Quality consciousness moderates the effect of the brand aware-ness–brand quality inference on perceived functional risk in SBs(H2); that is, the intensity of the relationship proposed in H1 dif-fers statistically for QC and NQC consumers. The rest of the hypoth-eses proposed in this study are contrasted in both samples andyield similar intensity for both groups (see Table 7).

In the sample of QC consumers, the negative relationship for thebrand awareness–brand quality inference and perceived functionalrisk of SBs is significantly more intense (0.88 in QC vs. 0.65 in NQC).The consumers more interested in quality, those for whom quality

mers) according to the method of average variance extracted.

lity SB functionalrisk

SB perceivedvalue

SBsatisfaction

SBidentification

0.72 �0.26 �0.22 �0.210.58 �0.15 �0.18 0.090.82 �0.37 �0.37 �0.350.80 �0.28 �0.39 �0.23

0.84 0.71 0.820.79 0.56 0.75

0.86 0.760.82 0.68

0.850.81

of each construct..

Table 5Estimation of the relationship model.

Model relationships Standardized coefficient t-Value

H1: Inference brand awareness ? brand quality ? Perceived SB functional risk 0.67 15.21⁄⁄⁄

H3: Perceived SB functional risk ? Perceived SB value for money �0.34 �8.36⁄⁄⁄

H4: Perceived SB functional risk ? SB satisfaction �0.16 �4.79⁄⁄⁄

H5: Perceived SB value for money ? SB satisfaction 0.61 15.53⁄⁄⁄

H6: SB satisfaction ? SB identification 0.36 8.62⁄⁄⁄

H7: Perceived SB value for money ?SB identification 0.56 12.59⁄⁄⁄

⁄⁄⁄p < 0.01.

Table 6Comparison of nested models in the multigroup analysis.

Fit statistics X2 (df) CMIN/DF DX2 (df) p CFI GFI AGFI RMSEA

Structural model without restrictions 388.204 (216) 1.797 0.978 0.947 0.925 0.032Structural model with restricted parameters 415.847 (234) 1.777 27.643 (18) 0.068 0.977 0.943 0.926 0.031

Table 7Results of the multigroup analysis.

Model relationships QC consumers (non-standardizedcoeffs.)

NQC consumers (standardizedcoeffs.)

CR

H1: Inference brand awareness ? brand quality ? Perceived SB functionalrisk

0.88⁄⁄⁄ 0.65⁄⁄⁄ 2.18⁄⁄

H3: Perceived SB functional risk ? Perceived SB value for money �0.36⁄⁄⁄ �0.25⁄⁄⁄ �1.47H4: Perceived SB functional risk ? SB satisfaction �0.10⁄⁄⁄ �0.21⁄⁄⁄ 1.78H5: Perceived SB value for money ? SB satisfaction 0.57⁄⁄⁄ 0.46⁄⁄⁄ 1.58H6: SB satisfaction ? SB identification 0.36⁄⁄⁄ 0.41⁄⁄⁄ �0.61H7: Perceived SB value for money ? SB identification 0.49⁄⁄⁄ 0.55⁄⁄⁄ �0.68

CQ: Quality conscious.NCQ: Non-quality conscious.CR: Critical Ratio for differences between parameters.t = 1.65 for p < 0.1; t = 1.96 for p < 0.05, and t = 2.58 for p < 0.01.

N. Rubio et al. / Food Quality and Preference 32 (2014) 289–298 295

is a determining factor in their purchase choices, use brand as anindicator of quality and perceive greater risk in the performanceof SBs.

The total effect of perceived functional risk for SBs on satisfac-tion with these brands is similar in both samples, specifically�0.31 [(�0.36�0.57) �0.10] in QC consumers and �0.33[(�0.25�0.46) �0.21] in NQC consumers. However, in the segmentof QC consumers, the indirect effect through value (�0.21) is con-siderably more intense than the direct effect (�0.10). The oppositeoccurs in the segment of NQC consumers, where the direct effect(�0.21) is considerably more intense than the indirect effectthrough value (0.12).

It is also interesting to note that the total effect of the brandawareness–brand quality inference in each of the constructs ishigher (in absolute value) for the segment of QC consumers thanfor the segment of NQC consumers. Thus, the total effect on per-ceived functional risk of SBs is 0.88 in QC consumers and 0.65 inNQC consumers. The effect on perceived value of SBs is �0.31 inQC consumers and �0.16 in NQC consumers, the effect on satisfac-tion with SBs�0.27 in QC consumers and�0.21 in NQC consumers,and the effect on identification with SBs �0.25 in QC consumersand �0.17 in NQC consumers.

Finally, we would point out the high proportion of variance ex-plained by the different constructs in both samples, although theexplanatory values achieved in the segment of QC consumers arehigher than those obtained in the segment of NQC consumers. Spe-cifically, the variance explained for identification with the SB isR2 = 0.73 in QC consumers and R2 = 0.66 in NQC consumers; thevariance explained for the perceived functional risk of SBs isR2 = 0.52 in QC consumers and R2 = 0.33 in NQC consumers; and

the variance explained for satisfaction with SBs is R2 = 0.52 in QCconsumers and R2 = 0.37 in NQC consumers.

5. Conclusions

The results obtained in this research enable us to contrast ourhypotheses and thus confirm the correct functioning of the pro-posed model to explain the influence of the brand awareness–brand quality inference on the consumer’s degree of identificationwith the SB.

Brand communication contributes to brand awareness, andconsumers use brand awareness on a great number of occasionsas both a guarantee of quality and a risk-reduction strategy. Themore aware consumers are of a brand and the more this awarenessinfluences the attribution of quality to the brand, the greater theperceived risk in the proper functioning of SBs as compared withmanufacturer brands. Perceived functional risk is a decisive factorin the configuration of SBs’ value and in consumers’ satisfactionwith these brands. Specifically, the effect of perceived functionalrisk on satisfaction is not only direct but also indirect through per-ceived value. Both the perceived value of SBs and satisfaction withthem affect the consumer’s identification with these brands posi-tively and significantly.

The results obtained from our modeling have significant strate-gic implications for food retailers, since they show the importanceof brand awareness as a strategy for reducing risk for buyers of SBsin general, and especially for quality-conscious buyers.

Decreasing the perceived risk in the functioning of a productshould constitute one of the main challenges retailers undertake

296 N. Rubio et al. / Food Quality and Preference 32 (2014) 289–298

in managing their own brands, especially in the case of consumersfor whom quality is the fundamental purchase attribute. Retailersshould engage in sufficient communication on the SB to increaseits recognition and prestige and thus to encourage its connectionwith quality.

In designating their brands, distributors have used primarilytheir own name on the label (label brand) or umbrella names forsets of product categories. These brand strategies have permittedthe retailer to use its establishments as showcases for communica-tion and to take advantage of economies of scope derived from therepetition of the name/names of their brand throughout theestablishment.

In this way, food retailers have achieved significant successeswith their own brands, among these, gaining high market partici-pation in European countries and consolidating SBs’ positioningin value. However, academic research on this positioning showsconsensus on the evaluation of price, perceived as competitive rel-ative to manufacturer brands, but no consensus on the evaluationof quality. Numerous studies find that the objective quality of SBsand manufacturer brands is similar, but consumers continue toperceive manufacturer brands as having higher quality as com-pared to SBs when the brands are known.

The results obtained in this study warn of that minimal retailinvestment in communication about these brands can have anegative effect on their perceived performance. Retailers’ com-munication on their own brands throughout the establishmenthas been insufficient to achieve perceptions of quality adequateto these brands’ levels of objective quality. Further, if the resultsobtained show that the retail investment in communication isimportant in food products, it will surely be crucial in marketsfor non-perishable goods, where the consumer is less familiarwith these brands and uses extrinsic attributes to a greater ex-tent in his/her purchase choice. Insufficient communication onSBs in these markets is surely the reason that they have failedto take off.

The results of this study also show that communication aboutSBs is crucial in segments of quality conscious consumers. Thegreater acceptance of SBs in food products has encouraged manyretailers to adopt a segmented brand strategy for portfolios of theirown brands. Currently, in a large number of establishments, dis-tributors commercialize not only their traditional SBs, which arepositioned in value, but also their premium SBs, with a higher qual-ity that sometimes exceeds the quality of the leading manufacturerbrands. The target of these premium SBs is consumers who areconcerned with quality and do not mind paying a higher pricefor the better product.

Retail investment in brand awareness is extremely important inimproving QC consumers’ perception of SB value. The negative ef-fect of the inference brand awareness–brand quality on perceivedvalue of the SB is significantly greater in QC consumers than inNQC consumers. In QC consumers, the inference brand aware-ness–brand quality has a strong negative effect on perceived func-tional risk of SBs as compared to manufacturer brands, and thisperceived functional risk decreases SBs’ perceived value. In thissegment of QC consumers, manufacturer brands continue to holdthe leading position. Retailers have not yet invested sufficientlyin awareness of their own brands to be able to consolidate themin this segment.

Traditionally, SBs have targeted NQC consumers. These con-sumers are more sensitive to price and less sensitive to quality.Here, the effect of the brand awareness–brand quality inferenceon the perceived value of the SB is lower than in the segment ofQC consumers, but the sign obtained is also negative and signifi-cant. This result warns us that any strategy to consolidate andgrow SBs in this segment must include the importance of attempt-ing to create greater brand consciousness through appropriate

investment in communication. Lack of investment increases theperceived functional risk of SBs as compared to manufacturerbrands and decreases SBs’ potential for success.

It is thus important for retail establishments to contribute todecreasing the perceived functional risk of SBs by improving theirimage and how they are evaluated. Companies should do this notonly through the presence of SBs throughout the establishmentbut also by advertising investment and informal control of the pur-chase experience (Aurier & Lanauze, 2011). It is true that such astrategy requires a certain level of investment and a sacrifice forthe retail firm. But future gains in respect for the chain, trust,and value of the brand, satisfaction and identification are likelyto reward that sacrifice. SBs should seek to achieve high levels ofidentification if they wish to compete successfully with manufac-turer brands. Under no circumstances should retailers abandonthe effort to achieve high identification with their brands, sincebrand identification is crucial to true loyalty to the brand. Insofaras consumers perceive value in SBs, they will identify with SBs,that is, will perceive what these brands represent to them on thelevels of both self-image and social image. The main route avail-able to retailers to increase the perceived value of these brands isreducing their perceived functional risk through greater invest-ment in awareness. To the extent which retailers achieve this, theywill also get greater satisfaction and identification of the consumerwith the SB.

This study is not exempt from limitations, which could be takeninto account in future research. First, our study analyzes data fromthe Spanish food market and for SBs in general. It is advisable toconsider other countries and product categories in which SBs areless accepted (e.g., categories of non-perishable goods) and to dif-ferentiate between value and premium SBs and among the SBs ofdifferent commercial labels. As to the origin of the model, it wouldbe interesting for future research to investigate in greater depththe factors determining consumers’ associations of brand aware-ness and perceived quality, as well as to identify other possible is-sues that condition the perceived functional risk of SBs. Finally, itwould be useful to perform other investigations that incorporateother components of the brand’s perceived risk into this model,such as financial, psychological, and social factors.

Acknowledgements

The authors wish to acknowledge the financial support of theFundación Ramón Areces (research project: ‘‘El capital cliente enmercados minoristas de gran consumo’’), Ministry of Economyand Competitiveness (research project Ref. ECO2012-31517) andUAM+CSIC (research project Ref. CEMU-2012-34).

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