private label vs national brand

Household Store Brand Proneness: A Framework

PAUL S. RICHARDSON Loyola University Chicago

ARUN K. JAIN University at Buffalo

ALAN DICK University at Buffalo

Store brands play an important role in retail grocery strategy. Yet, little recent research has examined

factors thought to influence the selection of store brand.s. This paper augments prior research by build-

ing an integratedframework within which to view private brand proneness. Factors found to in@ence

store brand proneness included familiarity with store brands, the extent to which consumers rely on

extrinsic cues such as price and packaging to judge product quality, intolerance for ambiguity, per-

ceived quality variation between national andstore brand products, perceived risk. perceived valuefor

money, income and family size. The results suggest that consumer.s’ negative perceptions of store

brands are driven primarily by the poor quality image of these products. Implications for marketing

strategy are presented.

INTRODUCTION

According to the RI, the volume market share of store brand grocery items has increased

from, 15.3% in 1988 to 19.7% in, 1993. Sales of private label cereals alone have increased

from $150 million in 1988 to over $400 million in 1993 (Bums, 1995). As a group, private

labels have higher unit market share than the top national brands in 77 out of 250 supermar-

ket product categories (Quelch and Harding, 1996). This increase in store brand market

share partly reflects retailers’ recognition that store brands represent an important strategic

asset for the firm. For example, unlike national brands which may be purchased at virtually

any chain, store brands are proprietary to the chains themselves. Large U.S. retailers are

now realizing that effective marketing of store brands can increase store loyalty, chain prof-

Paul S. Richardson, Loyola University Chicago, School of Business Administration, 820 North Michigan Avenue, Chicago, IL 6061 I. Arun K. Jain, University at Buffalo, School of Management, Samuel P. Capen

Professor of Marketing Research, Amherst, NY 14260-4000. Alan Dick, University at Buffalo, School of Management, Amherst, NY 14260.4COO.

Journal of Retailing, Volume 72(2), pp. 159-185, ISSN: 0022-4359 Copyright 8 1996 by New York University. All rights of reproduction in any form reserved.

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160 Journal of Retailing Vol. 72, No. 2 1996

itability, and product turnover (Liesse, 1993). Hence, it is important to better understand the decision making processes underlying private brand purchase.

Existing field studies of store brands have been exploratory in nature. Typically these studies have concentrated on developing customer typologies (e.g., Becherer and Richard, 1978; Bettman, 1974) or focused on testing correlational relationships between private brand attitude and socioeconomic or other explanatory factors (Coe, 1971; Frank and Boyd, 1965; Murphy, 1978). One weakness of these field studies is that possible interrelationships among variables have been ignored or examined in an ad hoc nature. Simil~ly, experimental studies have generally been limited to a single factor with treatments manipulated using artificial laboratory stimuli (Fugate, 1978; Sundel, 1974).

Thus, the purpose of this paper is to present a framework of the factors that might influence store brand proneness, The framework is based on findings in various areas of research and thus serves an integrative role. Additionally, two new concepts, not previously linked to private brand proneness (extrinsic cue reliance and intolerance of ~biguity) are integrated into the model. Also, to provide insight about the areas of greatest importance to managers, an examination of the relative effect sizes of all of the constructs influencing private brand proneness is conducted.

We first present a brief literature review concerning store brand grocery items. Following the literature review, we discuss the ~onstm~ts of the proposed model and present our research findings. We conclude with a discussion of the implications of the study, study limitations, and directions for future research.

LITE~TURE REVIEW

Research on store brand grocery items has taken two approaches. We first review studies which have examined correlates of private brand proneness. Next, we describe experimental investigations of private brand attitude.

Correlates of Private Brand Proneness

Exploratory investigations of correlates of store brand purchase dominate the empirical literature concerning private label brands. For example, Frank and Boyd (1965), found some evidence that store brand buyers are better educated, older, and have lower incomes than national brand buyers. Burger and Schott (1972) and Cunningham, Hardy and Imperia (1982) likewise found that store brand buyers have greater education. Contradicting the findings of Frank and Boyd, Coe (197 1) and Murphy (1978) found that store brand buyers belong to higher rather than lower income classes. Therefore, the results concerning socioeconomic correlates of private brand proneness are somewhat mixed.

Other work has focused on identifying personality and perceptual factors thought to relate to private brand proneness. Myers (1966) found that store brand buyers tend to be more enthusiastic, sensitive, and submissive than national brand buyers, Interestingly, in

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Household Store Brand Proneness 161

another test of personality characteristics on private brand attitude, Becherer and Richard

{ 1978) report that store brand buyers show greater levels of independence and rely less on

the behavioral norms of others. Finally, Bettman (1974) tested correlates of private brand

proneness using an information processing approach. Bettman found that the store brand

buyer can be distinguished from the national brand buyer on the basis of perceived quality

of the respective brands, perceived risk associated with store brand purchase, and familiar-

ity with store brands. In related research, marketers have tabulated and compared perceptions of store brands

relative to national brands and generic grocery items using a variety of dependent measures.

Invariably these studies have found that consumers perceive store brands to be inferior to

national brands but superior to generic grocery items on attributes such as overall quality,

taste, aroma, and reliability (Bell&i, Kruckeberg, Hamilton and Martin, 1981; Cunning-

ham et al., 1982; Hawes, Hutchens and ~~opoulos, 1982). Given the Private Label Man-

ufacturers Association’s claim that store brands are similar to national brands in terms of

intrinsic quality, these results suggest that there is a large difference between consumers’

perceptions and reality.

Experimental Investigations of Store Brands

Two early experiments concerning store brands were conducted by Sundel(l974) and

Fugate (1979). Sundel had consumers taste and then rate national and private label brands

of canned corn and fresh bread. No difference in evaluations were found for the bread; for

the corn the national brand was judged superior. The mixed findings can probably be attrib-

uted to the fact that consumers were used to buying regional or local brands of bread. These

are typically just as fresh as the national brands and constitute a large percentage of sales

in this product category. Fugate manipulated store brand packaging and tested whether manufacturer disclosure

on the packaging would influence store brand evaluation of cake mixes and ketchup. He

found that manufac~rer disclosure (i.e., writing on a store brand package that the store

brand was produced by a national manufacturer) had a positive effect on store brand eval-

uation, especially when the manufacturer disclosed was well known to subjects and this

information was prominently displayed. In a more recent study, Richardson, Dick and Jain (1994) examined the impact of extrin-

sic cues (e.g., price, packaging, etc.) on evaluation of private brand grocery products. They

found that consumers’ taste test evaluations of store brand grocery products were much

higher when the store brand products were repackaged as national brands and presented

with national brand prices. Additionally, they found that when national brand products

were tasted, consumer ratings were considerably lower when the national brand products

were represented to be store brands. This study is important because it suggests that a major

part of the evaluation of store brand products is based on the extrinsic cues of the product.

In fact, in this study, extrinsic cues played a much more important role in determining con-

sumers’ evaluations than did actual product ingredients.


The literature to date has identified a number of factors correlated with store brand prone-

ness. For example, we know that socioeconomic factors, perceptual factors, and the extrin-

sic cues identified with these products all seem to influence private brand proneness.

However, what is lacking is an attempt to integrate these disparate findings. For example,

the experimental studies point out the potential importance of extrinsic cues, however they

fail to provide a link between extrinsic cue reliance and the perceptual factors identified in

the literature (e.g., perceived risk, perceived quality, perceived value for money, etc.).

Since the extrinsic cues associated with store brand grocery products (e.g., cheaper prices,

simpler packaging, lack of brand image,‘etc.) tend to suggest that these products are of

lower quality than national brands, it would seem reasonable to argue that extrinsic reliance might influence other perceptual factors associated with store brands and that such percep-

tions might partly determine private brand proneness. Additionally, since extrinsic cue reli-

ance may differ among individuals, attempting to determine factors thought to influence

extrinsic cue reliance would likely be helpful in formulating marketing strategy. Conse-

quently, a framework which integrates these various findings would likely lead to greater

understanding and additional insights for marketers. The purpose of this paper is to introduce and test such a framework. We turn now to a

discussion of the proposed model. In so doing, we attempt to synthesize, offer additional

insights, and resolve some of the contradictions pertaining to the store brand literature

described above.

PROPOSED MODEL OF STORE BRAND PRONENESS

A flow diagram of the proposed mode1 is presented in Figure 1. The premise of the pro-

posed model is that the perceived value for money offered by store brands, the perceived

quality variation between national and store brand grocery items, the perceived risk asso-

ciated with store brand purchase, the degree to which consumers rely on extrinsic cues such as price and brand name in quality assessment, consumer familiarity with private label

brands, intolerance of ambiguity, and a variety of socioeconomic variables contribute either

directly or indirectly in explaining individual differences in private brand proneness. In the

following section we describe each of the constructs of the proposed model and offer the-

oretical support for the hypothesized relationships.

Private Brand Proneness

We define private brand proneness as the degree to which consumers are inclined to actually purchase store brand grocery items. In this sense, our definition of this construct is con-

sistent with that of all previous studies that have examined this construct. In the literature, private brand proneness has been measured either by calculating the percentage of grocery expenditures devoted to private label lines through the use of diary panel data (Cunning-

ham, 1961; Frank and Boyd, 1965; Rao, 1969) or by relying on consumers’ self reports


Pl4>0

!36>O

Perceived Quality P4<0

v I Variation q

Extrinsic Cue O’QV)

Perceived p, ,o Private Brand Value for ) Proneness

Money (PVM) (PBP)

Perceived

Figure I. Hypothesized Private Brand Proneness Framework

regarding the extent to which private label brands are selected (Bettman, 1974; Burgher and

Schott, 1972; Murphy, 1978). Most of the literature concerning store brands is quite old.

For example, we know of no recent study that has taken advantage of scanner data avail-

ability to measure this construct. Other measures of private brand attitude include stated

brand preference (Becherer and Richard, 1978; Coe, 1971) or attribute ratings collected

using paper and pencil measures (Bellizzi et al., 1981; Cunningham et al., 1982). In our

model, we posit that consumers’ propensity to purchase store brands depends on a variety

of constructs. The first of these constructs is perceived value for money.

Perceived Value for Money

Value for money implies consideration of quality not in absolute terms but in relation to

the price of a particular brand (i.e., utility per dollar). Thus, a lower priced product that has

desirable features (e.g., natural ingredients, real cream, extra virgin olive oil) may be

viewed as offering greater value for money than another brand sold at the same price but

comprised of less appealing attributes. An emphasis on value for money is an integral part of many retailers’ promotion efforts

(Davies, Gilligan and Sutton, 1986; Martell, 1986; McGoldrick, 1984; Patti and Fisk, 1982; Simmons and Meredith, 1984). This promotion strategy encourages consumers to consider

the quality of store brand grocery items not in absolute terms but in relation to their lower

price levels. Through these promotion efforts, retailers appeal to two different segments of

the market: (1) those consumers who believe that store brands are lower priced and of rel-


atively good quality, and (2) those consumers who believe that store brands are lower

priced but of relatively poor quality. The former segment of the market derives the full util-

ity associated with the price differential. The latter segment gains less utility but may still

buy store brands if the savings are greater than any perceived costs associated with tolerat-

ing “inferior” store brand ingredients. Other things being equal, greater value for money

perceptions of store brands will lead to higher levels of store brand purchase. Hence, we

hypothesize that:

HI: The greater the perceived value for money o#ered by store brands, the greater consumers’ private brand proneness.

Perceived Risk

The perceived risks associated with using store brands are an important determinant of

consumers’ propensity to favorably evaluate and purchase these products (Bettman, 1974;

Livesey and Lennon, 1978). Bettman (1974), for example, found that uncertainty regarding

store brand quaIity and perceptions of danger associated with store brand purchase are key

variables that dis~minate private prone from national brand buyers, Livesey and Lennon

(1978) further speculate that social risk inhibits the selection of particular kinds of store

brand grocery items according to the usage situation. For example, these researchers argue

that English consumers serve national brand tea to guests in social settings but consume less

expensive store brand tea when such behavior cannot be observed by significant acquain-

tances. Consistent with these findings, we hypothesize that:

H2: The greater the perceived risk associated with using store brands, the lower consumers’ private brand proneness.

H3: The greater the perceived risk associated with using store brands, the less favorable the value for m.oney perceptions of these products.

Perceived Quality Variation

Quality perceptions are a critical element in purchase decisions. In the case of consumer

non-durables, product quality is judged in terms of product pe~o~ance and the consis-

tency of performance over time with respect to intrinsic attributes. Store brands are gener-

ally evaluated inferior to national brands on a variety of intrinsic attributes such as taste,

texture, aroma, reliability of ingredients, nutritional value, and overall quality (Bellizzi et

al., 1981; Cunningham et al., 1982). These perceptions persist despite the fact that store

brand ingredients are subject to the same stringent FDA guidelines as those of national

manuf~turers. Thus, even if store brand quality were as good as that of national brands (as

the PLMA asserts), perceptions of store brand inferiority will likely serve to decrease favor-

able value for money perceptions. Hence, it is hypothesized that:


II4: The greater the perceived qualiry variation between national and store brand grocery items, the less favorable the value for money perceptions of store brands.

The perceived quality variation between national and store brand grocery items is also

likely to directly influence the perceived risk associated with buying these products. For

example, perceptions of high quality variation may lead to the belief that store brands lack

desired att~butes, will fail to perform as expected, will be less reliable, or may meet with

social or family disapproval. Hence, we hypothesize that:

HS: The greater the perceived quality variation between national andpri- vate label brands, the greater the perceived risk associated with using private label brands.

Extrinsic Cue Reliance

Extrinsic cues are product related attributes such as brand name, packaging, and price

which are not part of the physical product (Olson, 1972). Extrinsic cues form the image of

the product and reflect marketing strategies independent of the physical characteristics of

the product (e.g., ingredients, texture, color). Consumers make extensive use of extrinsic

cues in brand evaluation (See Purwar, 1982; Rao and Monroe, 1989 for a review of this lit-

erature). For example, Jacoby, Olson and Haddock (1971), and Wheatley and Chu (1977)

found strong brand image effects on product evaluation. Extrinsic cue effects on product

evaluation have also been found for packaging and labeling (McDaniel and Baker, 1977)

and store image contextual cues (Andrews and Valenzi, 1970; Park and Winter, 1979). Unfavorable perceptions of store brand quality may be fostered by consumers’ reliance

on extrinsic cues when making quality judgments (Jacoby et al., 1971; Olson, 1972; Olson

and Jacoby, 1973; Vale& and Andrews, 1971). Store brands are frequently presented in

unimaginative, inexpensive looking packages, have little promotions support on which a

more favorable image may be built, and are priced below national brands. To the extent that

consumers rely on such surrogate cues in quality assessment, it is likely that consumers

may perceive large differences in quality between national and competing store brands as

a result. Hence, it is hypothesized that:

H6: The greater the re&znce on extrinsic cues in qua~i~ assessment, the higher the perceived quality variation between national and store brand grocery items.

Extrinsic cue reliance may also aggravate the perceived risk associated with buying store

brands. For example, the lack of advertising and absence of a well known brand name typ-

ically associated with store brands may heighten unce~~nty regarding store brand quality.

Similarly, lower store brand prices may signal inferior or unreliable ingredients to consum-

ers. In addition, the less prestigious image of private label brands may heighten perceived


social risk and constrain the usage of store brands to particular situations such as when these products cannot be seen by significant acquaintances. Hence we hypothesize that:

H7: The greater the reliance on extrinsic cues in quality assessment, the higher the perceived risk associated with store brand purchase.

Familiarity

Familiarity denotes brand comprehension, product knowledge, or skill in judging the cri- teria needed to evaluate products (Howard and Sheth, 1969). Wolinsky (1987) argues that differences in consumer familiarity with grocery items makes it possible for manufacturers to adopt “mixed brand” strategies in which identical or similar ingredients are marketed in both national and store brand packaging. The national brand is targeted to those consumers who have less product knowledge and consequently evaluate grocery items using easy to process extrinsic cues such as price or brand name. The store brand, on the other hand, is targeted to those consumers whose skill and expertise makes possible reliance on a wider range of cues including those intrinsic to the product (Wolinsky, 1987). These findings are consistent with cue utilization theory which predicts that consumer familiarity acts to decrease reliance on price and brand name because of consumers’ ability to synthesize a greater range of cues in quality assessment (Raju, 1977; Valenzi and Eldridge, 1973; Wheatley, Walton and Chiu, 1977). Hence, it is hypothesized that:

HS: Greater familiarity with store brands results in less reliance on extrinsic cues in the quality assessment process.

Consumers familiar with store brands consider these products with a greater level of information and confidence. As a result, Bettman (1974) posits that store brand familiarity serves to increase private brand proneness by decreasing the perceived risk and perceived quality variation associated with these brands. When familiarity is high, the perceived danger of selecting store brands decreases and the certainty that store brands offer an acceptable level of quality increases. Consistent with Bettman, we hypothesize that:

H9: Greater familiarity with store brands results in higher private brand proneness.

HlO: Greater familiarity with store brands results in lower perceived risk associated with using these products.

Hll: Greaterfamiliarity with store brands results in less perceived quality variation between national and store brand grocery items.

Intolerance of Ambiguity

Individuals differ in the manner in which they react to intrusive stimuli. Intolerants of ambiguity are those individuals who shun rather than integrate intrusive elements (Pinson, Jain and Malhotra, 1980). Intolerants of ambiguity experience discomfort when confronted


with novel situations or products (Blake, Zenhausen, Perloff and Heslin, 1973; Budner,

1962). Such individuals are resistant to change because of their inability to synthesize addi-

tional information into a pre-existing belief structure (Shaffer and Hendrick, 1974). Intol-

erants of ambiguity choose familiar over unfamiliar stimuli and seek highly structured,

objective, and defined approaches to decision resolution. Such individuals also tend to be

more conventional in their approach to problem solving (Budner, 1962). Since intolerants

of ambiguity are reluctant to include ambiguous information into pre-existing belief struc-

tures, these individuals tend to reduce situations to a “right way” or “wrong way” dichot-

omy. Specifically, according to Smock (1955), intolerants of ambiguity are likely to

respond only to the known or most familiar elements in the choice situation. Store brands

are likely to be viewed as more ambiguous than national brands since these products lack

a brand name that identifies the producer of these products. Given this ambiguity, we

expect that intolerance of ambiguity has a negative effect on private brand proneness. For- mally, we hypothesize that:

H12: The greater consumers’ intolerance of ambiguity, the lower the level of private brand proneness.

We further expect that intolerance of ambiguity increases consumers’ propensity to

believe that store brands offer poor value for money. Intolerance of ambiguity has been

defined as the “tendency to perceive (i.e., interpret) ambiguous situations as sources of

threat” (Budner, 1962). Since the intrinsic quality of store brands may be unknown to con-

sumers or ambiguous, consumers intolerant of ambiguity may be more likely to be skeptical

of private brand quality and assume that these products offer poor value for money. Hence, we hypothesize that:

H13: The greater consumers’ intolerance of ambiguity, the less favorable the value for money perceptions of private label brands.

In the cue utilization literature, intolerance of ambiguity has been identified as an impor-

tant construct that affects reliance on extrinsic cues such as price and brand name. Consum-

ers intolerant of ambiguity are more likely to seek familiar, more easily identifiable, and

less ambiguous cues when making choices among competing brands in the marketplace

(Etgar and Malhotra, 1981). Such consumers are likely to reject cues that are difficult to

judge or which lend themselves to multiple interpretations. Extrinsic cues such as brand

name, packaging, and price are more easily recognized, processed, and interpreted than are

intrinsic cues (purwar, 1982). Hence, we hypothesize that:

H14: The greater consumers’ intolerance of ambiguity, the greater the reliance on extrinsic cues in quality assessment.

Socioeconomic Variables

Most investigations of private brand proneness have sought to investigate the degree to which a variety of socioeconomic variables can explain this construct. The rationale behind


this literature is that since store brands are less expensive than national brands, store brands should logically appeal to individuals in distinct socioeconomic group(s). For example, Frank and Boyd (1965) used a battery of 14 socioeconomic variables for a sample of 491 households and cross-sectional data for 32 products and reported that private brand proneness is negatively associated with income, but positively associated with education and the

number of persons in the family. However, taken together, these variables explained only 7% of variance in the dependent measure. In another study, Myers (1966) employed a bat-

tery of 15 socioeconomic and 8 personality variables for a sample of 347 female shoppers and cross-sectional data for 27 products. Myers found that socioeconomic variables had virtually no predictive power in distinguishing the private brand prone from the non-private

prone consumer. Other studies by Bettman (1974), Burgher and Schott (1972), and Fugate (1979) likewise found socioeconomic variables to be ineffectual in discriminating the private brand prone from the national brand prone consumer.

Significant results have been reported in only two other studies. Coe (1971), using a sam-

ple of 100 housewives and data for 25 products, reported that middle income housewives are significantly more private brand prone than are lower income consumers. Similarly, Murphy (1978), using a sample of 309 female shoppers and data for 3 products, reported that consumers in high income classes are significantly more prone to purchase store brands than are consumers in lower or middle income classes. The conflicting findings reported above may simply be an artifact of the different products, sample sizes, and dependent mea-

sures used in the various investigations. Given that researchers have not explored the impact of socioeconomic variables on pri-

vate brand proneness for almost twenty years, it seems timely to take another look at this topic. A further examination of the impact of socioeconomic variables on private brand proneness may reveal whether relationships have changed over time. In addition, including socioeconomic variables in the proposed framework affords the opportunity to test

the importance of these variables relative to perceptual factors in determining private brand proneness. We test the effect of four socioeconomic variables: (1) income, (2) education, (3) age of the primary grocery shopper of the household, and (4) family size.

Traditionally, private label grocery products have been merchandised on the basis of

price. The purchase of private label rather than national brands results in significant savings to households. By purchasing store brands, households may stretch their grocery budgets and fight inflation. Lower income households have a greater incentive to purchase store brands because of financial pressure (Frank and Boyd, 1965). Hence, it is hypothesized

that:

HE Greater household income results in lower private brand proneness.

In regards to education, the direction of the relationship with private brand proneness is less obvious. On the one hand, education may act as a surrogate measure of income. Other things being equal, more highly educated individuals may possess greater income and thereby enjoy more liberty in brand choice. As a result, national brands may be preferred despite their higher prices. The result would be a negative association between education and private brand proneness. On the other hand, the selection of store brands takes a certain amount of cognitive resources. More highly educated individuals may be better able to dis-


criminate between national and store brand grocery items and be better able to process

product related cues. Less highly educated individuals, on the other hand, may be less able

to deal with the ambiguity of store brands or accurately process ingredient or other infor-

mation regarding intrinsic product attributes. If this is the case, education may be positively

associated with private brand proneness. In the absence of strong theoretical support for a

directional effect of education on private brand proneness, we hypothesize:

H16: Education influences private brand proneness.

The age of the primary grocery shopper of the household is also likely to influence pri-

vate brand proneness. Other things being equal, older shoppers have greater shopping

expertise than younger shoppers. Whereas younger shoppers may rely on simple heuristics

when selecting brands, older shoppers are likely to have developed more sophisticated

choice processes in brand choice. For example, younger, inexperienced shoppers may be more inclined to rely on brand name or price when selecting products and limit their pur-

chases to well established national brands. Older, experienced shoppers, on the other hand,

may have developed the expertise needed to evaluate brands using harder to process intrinsic cues and consider store brands as viable alternatives to national brands for a wider range

of products. Hence, we hypothesize:

H17: The older the primary grocery shopper of the household, the greater the private brand proneness of the household.

Of the four socioeconomic variables included in the study, the influence of family size

may offer the easiest prediction. Regardless of income or education, the greater the size of

the family, the fewer the resources that are available to make ends meet. Consequently, it

is reasonable to expect that the greater the size of the household, the higher the proportion

of the grocery budget devoted to private label rather than national brands. This may explain Frank and Boyd’s finding of a positive relationship between family size and private brand

proneness. We hypothesize:

H18: The larger the size of the household, the greater the private brand proneness.

METHODOLOGY

We tested the model in Figure 1 though a field investigation in a large northeastern metro-

politan area. Shoppers in a mall were randomly intercepted and requested to participate in a study being sponsored by a prominent local institution of higher education. Subjects were asked to complete a questionnaire and return it within a week in an attached business reply envelope to qualify for participation in a cash giveaway. The analysis described here is based upon data from 582 subjects from whom complete model-related information was

available. This represents a response rate of 19.7%.


Measurement

Standard demographic questions were used to obtain information regarding household

income (yl), education (yz), age of the primary grocery shopper of the household (yg), and size of the household (~4). Intolerance of ambiguity (INT) was measured using Budner’s

(1962), 16-item scale. A higher score suggests greater intolerance of ambiguity &). A Lik- ert-type question asking respondents their familiarity (y6) with store brand grocery items

served as the indicator of familiarity (FAM). Extrinsic cue reliance (ECR) in brand selection was measured through four Likert-type questions asking about reliance on brand name (xl),

advertising (x2), packaging (x3), and price (x4) in brand evaluation. To measure perceived quality variation (PQV), respondents were asked to indicate their agreement/disagreement with statements regarding differences in quality (x=J, reliability (x6), and nutritional value (x7) between nationally advertised and store brand grocery items. The two indicators of perceived risk (PRS) measured were social risk (xs) and functional risk associated with private brand purchase (x9). Perceived value for money (PVM) was measured by asking the respondents whether store brands offer good value for money (xlo) or are a waste of money (x, 1).

In measuring the ultimate dependent variable (private brand proneness), an attempt was made to create a measure that reflected consumers’ overall likelihood of purchasing store

brand grocery products. Consequently, we consulted with store brand managers to identify

products which had both national and private brand versions widely available in the local market, and which would be commonly included in a typical grocery basket. The managers identified the 28 product categories shown in Table 1. A survey of the local grocery chains

confirmed that store brand counterparts to the national brands were available for the selected products. To measure private brand proneness, subjects in the survey were asked whether they regularly bought each product, and if so the frequency with which the product was a

store brand: never (“I”), rarely (“2”), sometimes (“3”), often (“4”), or always (“5”). A private brand proneness index (PBP) was constructed by summing responses across the 28 products and adjusting the total score for the number of products subjects actually bought (x12).

With the exception of private brand proneness, all other items were measured using a six- point Likert-type scale anchored by definitely disagree-definitely agree. A sample item used to operationalize each construct and Cronbach alpha are presented in Table 2.

TABLE

Products Comprising the Grocery Basket

Bacon

Bottled Juices

Butter/Margarine

Canned Tuna

Canned Vegetables

Canned Fruits

Canned Soups

Cereal (Hot or Cold)

Cheeses

Chip Dip

Cookies

Crackers

Eggs Frozen Vegetables

Frozen Orange Juice

Ice Cream

Jams/jellies/Preserves

Ketchup/Mustard

Liquid Laundry Detergent

Mayonnaise/Salad Dressing

Pancake Syrup

Paper Towels

POP Potato Chips

Relish/Pickles

Spaghetti/Pasta Sauce

Spaghetti/Pasta

Vegetable Oil


TABLE 2

Sample Items Used in Scales

Total

# of Coefficient

Construct /terns Typical Statement Alpha

Intolerance of Ambiguity 16 An expert who doesn’t come up with a definite 0.56

answer probably doesn’t know too much.

Familiarity 1 I am very familiar with the various store brand gro- -

cery items available in the market place.

Extrinsic Cue Reliance 4 The more famous the brand name of a grocery 0.76

item, the better the quality.

Perceived Quality Variation 3 There is a great deal of difference in overall quality 0.81

between nationally advertised and store brand gro-

cery items.

Perceived Risk 2 The purchase of store brand grocery items is risky 0.39*

because the quality of store brands in inferior.

Perceived Value for Money 2 Store brand grocery items offer great value for 0.36*

money.

Note: *Represents coefficient of correlation.

Partial least Squares (PLS) Models with latent Variables: A Brief Exposition

The model of household private brand proneness was specified, and its parameters were estimated using Herman Wold’s (1975,1982) Partial Least Squares (PLS) approach to structural equation modeling. The PLS model can be best understood through its arrow scheme. Figure 2 shows an example. The arrow scheme involves manifest or directly observed vari-

ables (x,, x2, x3, yl, y2, y3, zl, z2, z3) and latent or indirectly observed variables (LX, Ly, L,). The latent variables are a weighted linear combination of their respective manifest variables.

Thus, for example, Lx is a weighted linear combination of xl, x2, and x3. These are referred to as “outer relations.” The relations among the latent variables or “inner relations” are the

causal-predictive core of the model. In PLS (Bookstein, 1980), the latent variables (Lx, L,,,

L,) capture their respective manifest variables (x-ness, y-ness and z-ness) in the context of the joint linear determination of the dependent latent variable (z-ness) by the independent latent variable(s) (x-ness and y-ness). It will be noticed that the arrow scheme does not hypothesize any direct relationship between the manifest variables. In PLS, the modeler

specifies structural relationships between the latent variables and not between the discrete

observed variables (Papademetrion and Hopple, 1982). The PLS approach has been suc- cessfully applied in a variety of contexts and disciplines. These include psychology, sociology, political science, economics, chemistry and biology (Papademetrion and Hopple, 1982). In marketing, PLS has been employed to study consumer exit and voice caused by dissatisfaction (Fomell and Bookstein, 1982) and user interaction with decision support systems (Zinkhan, Jochimethaler and Kinnear, 1987). An excellent review of the history and use of PLS is provided by Geladi (1987).


figure 2. An Example of a PLS Model with Latent Variables

Model Description

The PLS model consists of two sets of equations: the structural and measurement equations. The structural equations specify the relationships among the latent variables and may be written as follows:

u = (m x 1) is a columu vector of unobserved dependent variables;

r; =(nx 1)’ IS a column vector of unobserved independent (predictor) variables;

p=t m x m) is a matrix of de~ndent variable ~~f~~ients;

T = (RI x n) is a matrix of coefficients for the independent variables; and,

E=( m x 1) is a column vector of residuals.

The measurement equations specifying relations between the manifest and latent variables are:

y = ATpi? - _.“_ -

(2)

Household Store Brand Proneness

x = h&+6 _ -- _

173

(3)

where,

y = (p x 1) is a column vector of observed dependent variables;

x = (q x 1) is a column vector of observed independent variables;

4, = (p x m) is a matrix of regression coefficients of y on n ; _ - +X = (q x n) is a matrix of regression coefficients of x on 5 ;

_ - _E = Ip x 1) is a column vector of errors of criterion measurement; and,

6 = (q x 1) is a column vector of errors of predictor measurement.

For convenience all variables are assumed to be standardized. Linear regression equations are used to model the relations between the variables. The

latent variables are estimated as weighted aggregates of their respective indicators. The

PLS algorithm (Lohmiiller, 1989) uses an iterative procedure to estimate weights for the indicators and regression coefficients. The method is described in detail by H. Wold (1975). The assessment of convergent and discriminant validity in the PLS context may be under- taken using the approaches developed by Fomell and Larcker (198 1) and Fomell, Tellis and

Zinkhan (1982). Significance of the parameters can be tested by using Tukey’s jackknife technique.

RESULTS

Validity Testing

Before testing for the significance of relationships in our structural model, we need to establish the convergent and discriminant validity of the various constructs in the measurement model. To assess convergent and discriminant validity, Fomell and Larcker (1981)

and Fomell, et al (1982) have proposed using average shared variance (p,,). From equation (2), the variance shared by the construct rJj estimated by different measures yij can be com- puted as follows:

where,

1 = measures of rlj;

Xi, = loadings of yy on ~j; and,

j = 1, . . . . m.


The same method may be employed to compute pvC for &. According to Fornell et aI. (1982) a reasonable condition for satisfying convergence is that pvC for a construct should exceed OS. The p, for the model ranged between 0.59 (ECR) and 0.73 (PQV). Thus, there is a reasonable degree of convergence of the constructs, i.e., different indicators of each construct are in agreement. An acceptable test of discriminant validity (Fomell et al., 1982) is for the variance shared between any two constructs to be less than the variance shared between a construct and its measures. In ali cases, this condition was met. Thus, the various ~ons~cts differ from each other offering disc~minant validity for the constructs used in this investigation

TABLE 3

Measurement Model Parameter Estimates

Construct and Observed Variabels

Age

Yl

Family Income

Y2

Education

Y3

Size of Family

Y4

Intolerance of Ambiguity (INT)

Ys

Familiarity (FAM)

Yb

Extrinsic Cue Reliance (ECR)

xt

x2

x3

x4

Perceived Quality Variation (PQV)

x5

x6

x7

Perceived Risk (PRS)

X8

x9

Perceived Value for Money (WM)

Xl0

x11

Private Brand Proneness (PBP)

x12

Notes: a. Fixed parameters

Loadings Error Variance

1 .I30 O.Ood

1 .oo o.ooa

1 .oo O.OOd

1 .oo 0.003

1 .oo o.ooa

1.00 o.ooa

0.77 0.41

0.80 0.37

0.75 0.43

0.75 0.44

0.87 0.24

0.89 0.21

0.80 0.35

0.76 0.43

0.90 0.20

0.89 0.21

0.76 0.42

1.00 o.ooa

PVC

1.00

1 .oo

1 .oo

1.00

1 .oo

1 .oo

0.59

0.73

0.69

0.68

7 .OO


Structural Coefficients

Structural coefficients for the basic model are presented in Table 4. The t-values are from the jackknife parameter estimates and jackknife standard errors (Fenwick, 1979; Gray and Schucany, 1972). Three of the hypothesized direct paths to private brand proneness-those beginning with respondent’s intolerance of ambiguity (H12), education (H16), and age (H17)-were not found to be statistically significant. To gain a more accurate understanding of the relationships, the basic model was modified by deleting these three paths. The results of the revised model are shown in Table 4 and Figure 3.

Fifteen structural coefficients are statistically significant at the 0.01 level or better. PLS provides standardized estimates and hence coefficients between constructs can be interpreted in the same way as one would interpret standardized regression coefficients in clas- sical ordinary least squares regression. We find that perceived value for money is a significant predictor of household private brand proneness (Hl: ppvM,pBp = 0.144). Thus, households that perceive greater value for money in private label brands exhibit a higher propensity to buy these products. Higher perceived risk associated with buying private

TABLE 4

Structural Parameter Estimates and t-Values for Hypothesized and Revised Models

Hypothesized Mode/ Revised Mode/

Standardized Standardized

Parameter/ Stfuctufa/ Structural

~e~ationsb;~ Coefficients &-Value RJ Coefficients t-Value R’

H,: PVM -+ PBP 0.145 28.27 0.144 la.42

H,: PRS I) Pm -0.092 -10.97 -0.084 -9.92

H,: PRS -+ PVM -0.286 46.33 -0.286 -46.33

H,: t’QV -+ PVM -0.329 -46.40 -0.329 -46.40

H,: PQV -+ PRS 0.336 40.58 0.336 40.58

H,: ECR -+ PQV 0.568 131.52 0.568 131.52

H,: ECR -+ PRS 0.224 33.92 0.224 33.92

H,: FAM-+ECR -0.266 -45.12 -0.266 -45.12

H,: FAM -+ PBP 0.401 70.43 0.403 74.91

H,“: FAM -+ PRS -0.271 -29.64 -0.217 -29.64

H,,: FAM -+ PQV -0.231 -54.28 -0.231 -54.28

H,,: INT -+ PEP 0.012 0.37

H,J: INT -+ PVM -0.117 -24.64 -0.117 -24.64

H,,: INT -+ ECR 0.251 35.41 0.251 35.41

H,,: FIN -+ PRP -0.114 -21.14 -0.121 -31.71

H,,: EDU -+ PBP -0.002 -0.18

H, ?: AGE -+ PBP -0.037 -0.25

H,,: FSZ -+PBP 0.089 10.97 0.097 12.06

Structural Equations CR*)

Extrinsic Cue Reliance (ECR) 0:145 0.145

Perceived Quality Variation (PQV) 0.451 0.451

Perceived Risk (PRS) 0.391 0.391

Perceived Value for Money (PVM) 0.334 0.334

Private Brand Proneness (PEP) 0.302 0.300


Intolerance for Ambiguity

i3,3<-0.117

(INT)

Value for - Money (PVM)

Private Brand W Proneness

(PBP)

PAM)

Figure 3. Revised Model withy Estimated Parameter Coeficents

label brands results in poorer value for money perceptions (H3: PPRS,PVM = -0.286) and, ultimately, decreases private brand proneness (H 2. . p ~~~~~~~ = -0.084). The greater the perceived quality variation between national and store brand grocery items, the less favorable the value for money perceptions of store brands (H4: I3 PQV,PvM = -0.329), and the greater

the perceived risks associated with store brand purchase (H5: PPQV,PRS = 0.336). House- holds that are inclined to rely on extrinsic cues in quality assessment perceive greater vari-

ation between national and store brand quality (H6: PECR,PQV = 0.568) and greater risk in store brand purchase (H7: PECR,PRs = 0.224). However, the good news for retailers is that

greater familiarity with private label brands results in less reliance on extrinsic cues in quality assessment (HS: PFAM,ECR = - 0 266) greater private brand proneness (H9: PFAM, PBP _

= 0.403), less perceived risk (HlO: PFAM,PRS = -0.217), and less perceived quality varia-

tion between national and store brand offerings (Hll: PFA~,P~V = -0.23 1). Importantly, greater intolerance of ambiguity results in less favorable value for money perceptions

(HI31 PINT,PVM = -0.117) and greater propensity to rely on extrinsic cues when judging

product quality (H14: PrNT,ECn = 0.25 1). In terms of the socio-demographic characteris-

tics, more affluent households exhibit lower propensity to buy private label brands (HE: &IN,PBP = -0.121). Finally, consistent with our predictions, the larger the households’ size, the greater the private brand proneness (H18: f3FSZ,PBP = 0.097).

Interpreting the Importance of Predictor Variables

Variables exert influence through both simple direct and complex indirect causal chains (Schmidt, 1979; Davis, 1985). For example, in Figure 3, perceived quality variation


between national and private label brands (PQV) is hypothesized to have a direct influence

on value for money perceptions of these products (&.Qv,PvM). Concurrently, it also exerts

influence through its effect on the perceived risk associated with buying store brands

(BPQv,PRS). Perceived risk has a direct influence on perceived value for money #&s,~~M).

The indirect effect is the product of indirect path coefficients (e.g., &~v,pRs*&~~,pv~)

while the total effect is the sum of direct and indirect effects:

PPQv,Pvh4* = PPQV,PVM + @PQV,PRS x P ~Rs,Pvd

Where PPQ”,PvML represents the total effect of PQV on PVM. In some cases there will be more than one indirect path. For example, while FAM has a

direct path to PRS, there are three indirect paths: FAM + ECR + PRS; FAM + PQV +

PRS; and FAM + ECR + PQV + PRS. In such cases, all of the indirect effects are

summed and added to the direct effect to obtain the total effect. It follows that indirect effects may play an important role in understanding the nature of

the influence exerted by variables. As Noonan (1982) has pointed out, the question of sta-

tistical significance is not relevant for the total effects. These follow as a corollary of the

inner structure of the model, and hence the issue of statistical significance enters only when

deciding which direct paths should be retained in the model. Table 5 presents each of the

total effects for the final model. A comparison of direct path coefficients from Table 4 indicates that the most important

single construct predicting private brand proneness is brand familiarity (PFAM = .403). Rel-

atively speaking, perceived value for money (PPvM = -.144), family income (PFIN = -.144),

family size ( PFsz = .089), and perceived risk (p PRs = -0.0X4), in that order, have substantially

lower influence on private brand proneness. An examination of total effects indicates that

the extent of reliance on extrinsic cues (ECR) has strong indirect effects on various con-

structs. For example, although it has no direct effect on perceived value for money, the indi-

rect effect is -0.315. Furthermore, the direct effect of ECR on perceived risk (PRS), 0.224,

TABLE 5

Total Path Coeffkients for theRevised Model*

Dependent

Constructs INT FAM

Independent Constructs

ECR PQV PRS PVM FIN FSZ

INT - - - - -

FAM - -

ECR

PQV PRS

PVM

FIN

FSIZ

PBP

Notes:

0.251 -0,266 _ _ _ _ _ _

0.143 -0.382 0.568 - - -

0.104 -0.405 0.415 0.336 - - -

-0.180 0.243 -0.315 -0.425 -0.286 -

- - - - -

- - - - - -

-0.031 0.472 -0.063 -0.085 -0.125 0.144 -0.121 0.097

‘Values in the table refer to the total effect of the column variable on the row variable. For example the total effect of perceived risk on private brand proneness is -0.125. This is obtained by adding the direct effect of PRS on PEP C-.084) to its indirect effect through PVM (-0.286 x 0.144 = -0.041).


while ifipressive, only tells part of the story. When factoring in not only its direct effect, but also its indirect effect through PQV, its total effect is nearly doubled to .415. Finally,

while perceived quality variation between national and store brands and the extent of reliance on extrinsic cues have no hypothesized direct effects on private brand proneness, they exert noteworthy negative influences on private brand proneness through their indirect effects.

DISCUSSION

Previous research has shown correlations between private brand proneness and a number of other socioeconomic, perceptual, and individual difference variables. This research has

attempted to integrate these disparate findings into a cohesive framework to better understand the interrelationships between the variables thought to influence private brand proneness. By taking such an approach, it is posited that greater insight can be gained in the management of retailers’ private brands.

An examination of the relative importance of the factors influencing private brand proneness reveals that familiarity with retailer’s private label brands is critical. The large relative importance of familiarity suggests that consumers who are familiar with private label prod-

ucts are likely to view them as high quality, low risk products, producing good value for the money. Consumers who lack experience with such brands are likely to view them with

skepticism and consider them to be risky choices. Such perceptions may lead consumers to discount store brand quality and lower perceived value for money. Lack of familiarity may also serve to increase reliance on extrinsic cues such as brand name, packaging, and price in quality assessment-areas in which retailers’ private brands suffer from deficiencies relative to their national brand counterparts. Our findings suggest that an important first step

in building greater consumer acceptance of retailers’ private brands is to increase consumer familiarity with them. Familiarity with retailers’ private label brands could be increased through in store taste tests, blind comparisons with national brands, distribution of free samples, or issuing store brand coupons to buyers of competing national brands at the

checkout counter. Also of importance is consumers’ reliance on extrinsic cues in quality assessment. This

reliance exerts strong negative effects on consumers’ attitudes towards store brands. Extrinsic cue reliance greatly heightens perceptions of quality variation between national and store brands and increases perceptions of risk associated with using these products. The PLMA asserts that store brand ingredients are as good if not better than those of national brands. However, in the absence of information concerning intrinsic quality, extrinsic cues serve as surrogate indicators of quality. Cues such as price, brand name, and packaging are easily recognizable and interpreted. Our results suggest that simple improvements in the extrinsic cues associated with store brands may go a long way towards increasing consumer acceptance of private label brands. European retailers understand this and have been successful in increasing store brand market share through dra- matic improvements in package design, labeling, advertising, and branding strategies

(Hester, 1988). This has contributed to the market success of companies such as Carrefour


which commands respectable market shares for its store brands (Ody, 1987). Given that store brands offer higher margins, investments in creating a more favorable image for private label brands may offer large returns and increase retailers’ competitiveness vis-a-vis

national manufacturers. Consistent with perceptual studies of store brands (Bellizi et al., 1981; Cunningham et

al., 1982; Myers, 1966), we find that misgivings regarding store brand quality are a

major problem facing these products. Our results suggest that perceived quality variation is derived in large part from extrinsic cue driven inferences. However, for retailers to

improve their competitive position in the market, it is important that they also pay close attention to maintaining high levels of intrinsic product quality. It may not be enough to have good quality. What may be needed is comparable qualityyuality which matches or even exceeds that of leading national brands. This will require that retailers be aware of consumer requirements and benchmark store brand quality against the category leader to achieve superiority. To the extent that there are geographic differences in consumers’ needs, retailers may be able to take advantage of their local dominance in particular mar-

kets. The success of Wegman’s cola (McCarthy, 1992) can be partially attributed to management’s success in benchmarking their product against the category leader in the customer segment and communicating the benefits of this store brand product to consumers.

We find that promotional strategies emphasizing value for money may have a positive and significant effect on private brand proneness. However, it is clear from our results that such a promotional strategy may not be very effective if consumers perceive quality variation or risk associated with store brand purchase. This is consistent with the findings of Hoch and Banerji (1993) who found that high quality and consistency are much more important than price in determining market share for private label products. In addition, it may be that lower store brand prices themselves hurt value for money perceptions: That is,

by lowering store brand prices, retailers may simply be signaling poorer store brand quality. This calls into question the wisdom of relying on a low price strategy to move store brands.

Instead, a better focus may be to position store brands on the basis of quality. An emphasis on quality might be coupled with attempts to lessen the perceived risk associated with buying store brands. Perceived risk could be minimized by conducting in-store taste tests, pub-

licizing the results of independent testing agencies, offering money back guarantees, and conducting image building campaigns to favorably portray the private label buyer as “smart” and “quality conscious”.

The successful French hypermarket Carrefour aggressively promotes comparative information about store brands vis-a-vis national brands and maintains a mid-range pricing pol-

icy which compares favorably to the category leader. Their private label brands are typically not the cheapest version of the product. This has enabled them to gain as much as 25% of their turnover from private labels.

We concur with Bettman (1974) that an information processing approach to private

brand purchasing behavior holds promise. We find that intolerants of ambiguity, for example, process product related cues differently and rely on easier to process extrinsic cues such as price and brand name. Since private label brands lack easily decipherable brand related information, intolerants of ambiguity are inclined to perceive less value for money associated with store brands. This finding further suggests that retailers may draw a larger

180 journal of Retailing Vol. 72, No. 2 1996

store brand franchise by improving the packaging, labeling, and promotional support associated with private label brands.

LIMITATIONS

Our study provides some interesting insights into factors which influence consumer private

brand proneness. The proportion of variance explained by our model, although favorable when compared to past studies, is modest. The findings presented here should be validated using a new sample. We adopted a self-report measure of private brand proneness for

twenty-eight products. Although this measure is an improvement over single-item measures typically used in previous research, it would be useful to employ a behavioral measure of this construct. Using panel data, one could track the actual number of private label brands purchased and use this information to develop a better picture of the effects of the variables hypothesized to influence consumers’ decisions to buy store brands. Lack of such

data and resource constraints prevented us from employing such an approach. The measure of private brand proneness employed in this investigation asked consumers

to rate the frequency with which they purchase a store brand for various products. Subjects may have different interpretations of what “rarely” or “sometimes” means. This could con-

tribute to random noise in the measures, thus decreasing our ability to detect significant relationships.

Next, it should be recognized that several of the predictor concepts (e.g., perceived risk,

perceived value for the money, etc.) might take on different values for a given consumer in different product categories. The measures of these predictor variables were general (i.e., not product specific). The key dependent variable (private brand proneness) encompasses many different packaged grocery products and it is possible that consumers’ perceived risk, perceived value for money, etc., differ across these different product categories. Conse-

quently, our global variable measures could not capture these differences. This is likely to have added to random error in the model and decreased the efficiency of our parameter estimates making it more difficult to find significant results. There is, however, no reason to believe that this introduced any systematic bias in the estimates.

Furthermore, it could be argued that consumers’ decisions to buy a particular store brand may depend on the type of product under consideration. For example, a given household may be more prone to buy store brands of low rather than high involvement products. In addition, buying motives may play a role in purchase decisions of store brands. For exam-

ple, consumers may be more prone to select store brands for “think type” rather than “feel type” products. Thus, consumers may prefer national brands for high involvement-feel type products such as toothpaste but consider store brands for low involvement-think type products such as cooking oil. To offer insight into product type differences, future researchers might consider analyzing private brand proneness separately for each of the four quad- rants of the FCB Grid (Vaughn, 1986).

We suggest that additional items should be developed for each of our constructs to improve their reliability and content validity and to provide more rigorous tests of their dimensionality. Two of our scales had only two items and the scale for familiarity had only

household Store Brand Proneness 181

one item. It could be argued that this inadequate sampling of the construct domains resulted in underestimation of the strengths of the hypothesized relationships. The low alpha value of the intolerance of ~bi~i~ scale (a = S65) should be contrasted with 0.49 reported by Budner (1962). He defended the low Cronbach’s alpha on the grounds that “the scale is free from artifacts such as acquiescence and social desirability which, because they are consistent, tend to maximize reliability estimates. There is also the nature of the construct, itself, the de~nition of which posits a complex, multidimension~ construct. Since increasing complexty of a trait increases the probability that individuals will exhibit unique patterns of the component elements, it is generally true that the more complex the construct, and the more complex the measure, the lower will the reliability of the estimate be.” Although Bud- ner’s intoler~ce of ~biguity scale is most commonly employed in behavioral research, future researchers might consider employing scales developed by Norton (1975) or McDonald (1970) which are longer but exhibit higher reliability.

Finally, this study has ignored cultural differences which might partially account for the greater success of private label products in Europe. Future research could attempt to understand the role culture plays in this process.

CONCLUSfON

Store brands are products owned and branded by retailers. These products have been enor- mously successful in Europe where chains like Carrefour (France), Migros (Switzerland), Esselunga (Italy), and Sainsbury’s (England) have achieved significant market shares for their private label brands. Store brands help retailers increase store traffic and customer loyalty by offering exclusive lines under labels not found in competing stores. They offer higher margins, increase control over shelf space, and give retailers greater bargaining

power in the channel of distribution. North American retailers are gradually recognizing the potential power of brand name ownership as witnessed by the success of Loblaws in Can- ada and Kroger in the U.S. These chains generate a quarter of their revenue from the sales of their private label brands. Despite the importance of store brands, little is known about what motivates consumers to buy private label brands. We have proposed and estimated a model of household private brand proneness. Our study findings have important manage- rial implications. Future research should attempt to incorporate improved measures of the various predictor constructs employed in this study (e.g., incorporating product-specific measures of the perceptual variables to reduce error variance and using more items in the scales for perceived risk, perceived value for the money and familiarity to improve their content validity and reliability). In addition, using behavioral as opposed to self-report measures of private brand proneness would increase confidence in the findings.

Ac~owl~~en~ Partial support for this project was provided by a research grant from a major international supermarket chain which wishes to remain anonymous. Their support is gratefully acknowledged. The authors wish to acknowledge the research assistance of Mr. Amit Bhatnagar. The authors thank the editor and three anonymous JR reviewers for their invaluable help in revising the manuscript.


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