Journal of Business Research 58 (2005) 1112 – 1120
Recapturing store image in customer-based store equity: a construct conceptualization Katherine B. Hartman*, Rosann L. Spiro1 Kelley School of Business, Indiana University, Bloomington, 1309 East Tenth Street, Suite 328, Bloomington, IN 47405, USA Received 30 September 2003; received in revised form 1 December 2003; accepted 26 January 2004
Abstract This paper enhances previous conceptualizations of store image by introducing a new concept referred to as store equity, defined as the differential effect of store knowledge on customer response to the marketing activities of the store. As such, the goals of this paper are (1) to argue that store image, as it has been previously developed by marketing academics, is a necessary but insufficient construct to understand store performance and consumer behavior and (2) to discuss the enhanced conceptual and operational benefits of store equity as compared with store image. To accomplish these goals, the paper discusses the conceptualization and operationalization of customer-based store equity by explicitly comparing the concept to store image and discusses the implications for marketing practitioners by identifying the considerations for building and managing customer-based store equity. D 2004 Elsevier Inc. All rights reserved. Keywords: Store image; Customer-based store equity; Differential effect; Brand knowledge; Customer response
1. Introduction Since the introduction of Martineau (1958) of store image as a concept in the development of retail personality, marketing researchers have devoted considerable attention to developing the idea that consumers hold images of particular stores in their minds (e.g., Chowdhury et al., 1998; Berry, 1969; Kasulis and Lusch, 1981; Kunkel and Berry, 1968; Marks, 1976; Mazursky and Jacoby, 1968). Although definitions vary, store image has generally been defined as the way in which the store is defined in the shopper’s mind, partly by the functional qualities and partly by an aura of psychological attributes (Martineau, 1958). The original conception of store image ignited a stream of research, in which retailing researchers developed the underlying dimensions of store image, developed measurement techniques to operationalize store image, and empirically related the concept of store image to a wide variety of other constructs. * Corresponding author. Tel.: +1-812-855-8878; fax: +1-812-8556440. E-mail addresses:
[email protected] (K.B. Hartman),
[email protected] (R.L. Spiro). 1 Tel.: +1-812-855-1100; fax: +1-812-855-6440. 0148-2963/$ – see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2004.01.008
The primary motivation to study store image has been to investigate the function of store image as a predictor of consumer behavior and store performance. Among other relationships that can be found in the literature, extant research has suggested that store image is a predictor of the retailer choice (e.g., Grewal et al., 1998; Hildebrandt, 1988; Schiffman et al., 1977), a key construct in understanding the inferences of store and product quality (e.g., Baker et al., 1994; Darden and Babin, 1994), a predictor of store satisfaction (e.g., Bloemer and de Ruyter, 1998), an antecedent of competitive positioning (e.g., Burt and Carralero-Encinas, 2000; Pessemier, 1980), and a predictor of store loyalty (e.g., Bellenger et al., 1976; Lessig, 1973; Sirgy, 1985). Academically, Mayer (1989) suggests that store image has been one of the primary conceptual topics in academic retailing research. Practically, Steenkamp and Wedel (1991) suggest that the development and measurement of a favorable store image is a critical aspect of the retailers’ abilities to maintain their market positions. Driven by the generally accepted importance of store image as a concept to both academic researchers and business practitioners, this paper further develops the store image concept by introducing a new concept referred to as store equity. Paralleling the brand equity work by Keller
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(1993), store equity is defined as ‘‘the differential effect of store knowledge on customer response to the marketing activities of the store.’’ It is important to note that equity in both Keller’s definition and in this definition is a consumerbased concept rather than a financially based concept and is conceptualized at the channel of distribution level. As such, corporate retailers may have different store equities for different retailing distribution outlets including brick-andmortar stores, catalogs, and electronic storefronts, even though store images may overlap. The goals of this paper are (1) to argue that store image, as it has been previously developed by marketing academics, is a necessary but insufficient construct to understand store performance and consumer behavior and (2) to discuss the enhanced conceptual and operational benefits of store equity as compared with store image. To accomplish these goals, this article operationalizes customer-based store equity by explicitly comparing the concept with store image. Then, the article discusses the implications for marketing practitioners by identifying considerations for building and managing customer-based store equity. The article concludes by suggesting future research needs based upon the conceptual framework.
2. Comparing the store image conceptualizations to the concept of store equity The evolution of the conceptualization of store image has progressed in several directions. The following discussion highlights three of these directions. Following this discussion, the article compares these conceptual dimensions to those of store equity. 2.1. Conceptualizations of store image Store image has a long history of changing conceptualizations. This change indicates the difficulties that researchers have in defining the construct (e.g., Sewell, 1974). Martineau (1958) defines store image as the way in which the store is defined in the shopper’s mind, partly by the functional qualities and partly by an aura of psychological attributes. He thought of store image as part of the retail store’s personality. Adding to this definition, by integrating learning theory, Kunkel and Berry (1968) define store image as the total conceptualized or expected reinforcement that a person associates with shopping at a particular store. Thus, the original conceptions essentially argued that store image is a developed from consumers’ objective and subjective perceptions learned over time. James et al. (1976) and Lindquist (1974/1975) argue that a store image is not only a summation the various perceptions of attributes but is also a function of the importance weights and interactions among these attributes. Relevant attributes include fashionability, salesmanship, outside attractiveness, and advertising (Marks, 1976). Marks (1976, p.
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37) captures the importance and interaction perspective succinctly by stating, ‘‘(store image) is not merely the sum of objective individuals associated with the stores; rather, a store’s image is a composite of dimensions that consumers perceive as a store. Store image is an overall picture that is more than the sum of the parts, for the parts interact with one another in the consumer’s mind.’’ Thus, this later perspective treated store image as a function of a multiattribute model of differently weighted subjective and objective store-related attributes with the interdependent dimensions that combine into an overall impression of the store. A few researchers explore the idea that store image is not necessarily developed from a piece-meal-based information processing system, as previously argued by the multiattribute models, but rather developed from a category-based information processing system relating acquired information to existing categories. Mazursky and Jacoby (1968) states that a store image is composed of (1) a cognition and/or affect; (2) which is (are) inferred; (3) either from a set of ongoing perceptions and/or memory inputs attaching to a phenomenon; and (4) and which represent(s) what the phenomenon signifies to an individual. Keaveney and Hunt (1992) suggests that a store image is developed by comparing incoming information to existing category information in memory, and, therefore, store image is not only a function of the image of a particular store but also of the images and associations in the memory of existing store and/or retail categories. Thus, the most recent conceptualization integrates not only the perceptions and beliefs about a particular store but also the macrolevels of general schematic associations including the perceptions and beliefs of general categories of retailers (e.g., discount, department, or grocery stores). Although the conceptualization has progressively developed by explicitly incorporating theories of learning, perception, and integration, the current dominant conception describes a store image as the total impression represented in the memory as a gestalt of perceived attributes associated with the store, which are both independent and interdependent in consumer’s memory learned from current and previous exposure to stimuli. Keaveney and Hunt (1992) suggest that store image is based upon a category-based information processing system, in which newly acquired information is integrated with existing information through schemas held in the memory. Therefore, examining a store’s image in isolation of other images and associations in consumer memories may be an erroneous method of predicting store performance and consumer behavior. However, this idea may be developed one step further by suggesting that the network of associated attributes forming a store image is only one dimension of a broader construct referred to as store equity. Store equity will better capture the effects of store image on consumer behaviors and beliefs as well as on store performance. The following discussion develops the concept of store equity and explains how this concept
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allows store image to be examined in a different, yet promising, way. 2.2. Conceptualizing customer-based store equity This development of the concept of store equity draws upon the conceptualization of customer-based brand equity of Keller (1993). Keller defines customer-based brand equity as the differential effect of brand knowledge on consumer response to the marketing of the brand. This construct is deconstructed into three concepts. First, the differential effect of the brand is determined by comparing consumer response to the marketing of a brand with the response to the same marketing of a fictitiously named or unnamed version of the product or service. Second, brand knowledge is defined as brand awareness and brand image, characterized by conceptualizations and relationships among brand associations. Third, consumer response to marketing is defined as consumer perceptions, preferences, and behavior arising from marketing mix activity (e.g., brand choice). In sum, ‘‘a brand is said to have a positive (negative) customer-based brand equity if consumers react more or less favorably to the product, price, promotion, or distribution of the brand than they do to same marketing mix element when it is attributed to a fictitiously names or unnamed version of the product or service’’ (Keller, 1993, p. 8). Paralleling the definition of Keller (1993) of brand equity, store equity is ‘‘the differential effect of store knowledge on customer response to the marketing of the store.’’ The following section deconstructs this definition by discussing each one of the components in turn and discuss the relationship between store image and store equity.
3. Differential effect The first component of the definition, differential effect, is the objective and subjective perception-based comparison of the particular object, place, or person to a similar, yet distinct, object, place, or person. This idea of differential effect is tied closely to the category-based information processing arguments made by Keaveney and Hunt (1992), which suggest that the store knowledge held in a customer’s memory is not necessarily classified in isolation but is a relative evaluation based upon the strengths of the information links to similar, yet distinct, categorization schemas. Thus, customers may demonstrate a differential effect of store knowledge by having different responses to a specified store as compared with a generic store category. On two ends of the continuum, customers may exhibit a relatively negative or relatively positive perception of any specific store (e.g., Kroger, Target, Gap, Toys-R-Us) subjectively classified under a broader schema of the generic, yet associated, store category (e.g., grocery stores, discount retailers, specialty clothing stores, toy stores). Therefore, the
customers’ differential effect is based upon the subjective perceptions of the store knowledge held in individuals’ memory systems. For example, marketing practitioners have recognized the differential effect that Target stores has compared with the generic store category of discount store chains by a popular culture modification of their store name, Target, to the French sounding, tar’zha, which has been argued as indicating that customers who shop at Target truly perceive the company as fundamentally different from its nearest competitors (Scally, 1999). Theoretically, this phenomenon may suggest that some consumers may perceive Target stores as fundamentally different than their perceived closest competitors, and, thus, consumers demonstrate a differential effect towards Target when presented with alternative choices. Unlike the traditional conceptualizations of store image that capture the gestalt of perceived attributes associated with the store, the differential effect component of consumer-based store equity relies upon conceptualizing the specific store relative to other retailers (i.e., retailers, in general, specific retailing categories, or specific retailing distribution channels) rather than specific to the isolated store. For example, traditional conceptualization of store image may capture the fact that a consumer may hold positive store images for both Toys-R-Us and KB Toys, which researchers would use to predict performance. However, because s/he have may only have strong images of toy stores and not of the specific retailer, this consumer may not demonstrate any differential effect for either retailer as compared with his/her perceived generic store category because the image is associated with the store category rather than the specific store itself. Although the traditional ability to determine images associated with a store is useful, it would be more useful to marketing practitioners to determine if the image is only associated with a specific store or if the image is shared among its competitors. Thus, the conceptualization of customer-based store equity integrates the differential effect of specific store knowledge to a similar, yet distinct, store.
4. Store knowledge The second component of the store equity definition, store knowledge, is conceptualized as consisting of a store name node in memory, to which a variety of associations are linked (Keller, 1993). These informational associations to the store name comprise what has been traditionally referred to as a store’s image. Arguably, the store knowledge component may have the most important implications for developing a conceptualization of store equity based upon the current conceptualizations of store image. The theoretical basis for the conceptualization of store knowledge is the associative network memory of nodes and links that form a schema in the consumer’s memory (e.g., Keller, 1993; Krishnan, 1996). The notion of a schema parallels the prior discussion that suggests that store image is conceptualized
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as an overall impression of the store, made up of interdependent associations with the store. Paralleling the brand arguments of Keller (1993) in terms of a store, store knowledge comprises both store awareness, measured by the strength of the store name as a node in the memory network, and store image, measured by the attributes associated with the store. Therefore, store image researchers’ dominant conceptualization of store image is congruent to the definition of brand image of Keller and can be defined as the perceptions of a store as reflected by associations with the store held in the memory. However, store image is not the only dimension of store knowledge that contributes to a retailer’s store equity. Store knowledge is also comprised of store awareness, which is the ability of a consumer to recognize the store name and to recall the store name, which will activate associations in memory that form a consumer’s store image. Similar with previous work on store image (e.g., Kasulis and Lusch, 1981; Mazursky and Jacoby, 1968), store knowledge is theoretically depicted as a memory model represented in the consumers’ minds. Although memory models differ in their underlying assumptions, most memory models view memory in terms of various pieces of information and the links between these concepts (e.g., Krishnan, 1996). Basically, memory is composed of pieces of information represented by nodes and links between these nodes, represented by associations, which is termed a schema (e.g., Krishnan, 1996). Theoretically, a node becomes a potential source of activation from other nodes, either when external information is being encoded or when internal information is being retrieved from long-term memory (e.g., Keller, 1993). When one information node is activated through either recall or recognition, a person can access the associations held in the memory through spreading activation, depending upon the strength of the association (e.g., Krishnan, 1996). Thus, this connected network of informational nodes comprises the extent of the customer’s store knowledge, which includes both store awareness and store image. First, store awareness is the informational node associated with the store name. The strength of store awareness in the memory is reflected by the ability to identify the store under different conditions, including store recognition or the ability to recognize previous exposure to a store when given the store name as a cue and store recall or the ability to retrieve the store when given the retailing category or some other cue (Keller, 1993). Store awareness plays an important role in decision making for three reasons: (1) it may be important for a customer to think about a store when they think about the store category; (2) store awareness may play an important role in consideration sets; and (3) store awareness will influence the formation and strength of a store association in store image because the store name node is a necessary condition for establishing store image, and the strength of the store name node may effect how easily
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associations can be attached to the store name (Keller, 1993). Furthermore, the importance of the store name has been demonstrated in previous retailing research. For example, Grewal et al. (1998) argued that a store’s name is an information-rich cue to its image and hypothesized that the more positive the store name (or the reputation associated with the store), the more positive the buyers’ perceptions of the store are. Although the effects remain to be realized, store awareness should have an increasingly important role with retailing on the Internet. For example, if a consumer is engaging in goal-directed Internet search behavior to acquire product information for a new toy, the toy product category might activate the ‘‘Toys ‘R’ Us’’ store name node in the consumer’s schematic memory. As such, if the consumer were relying on their ability to recall possible retailers, the strength of store awareness would increase the likelihood that the consumer would explore the retailer’s web site for information. On the other hand, a consumer may use a search engine or an electronic shopper to find sites that contain product information about the new toy, and the consumer would be given a list of possible retailers. As such, if the consumers were relying on their ability to recognize possible retailers, the strength of store awareness would increase the likelihood that the consumer would choose to search the retailer’s web site. The second component of store knowledge is store image, which is the gestalt of perceptions and attributes linked to a store, as reflected in associations held in the memory (e.g., Grewal et al., 1998; Marks, 1976; Mazursky and Jacoby, 1968; Zimmer and Golden, 1988). Although researchers have investigated various attributes of a store image, store image scales suggest that the important attributes include general attributes (i.e., merchandise), store appearance, and salesmanship/service (Manolis et al., 1994) based upon functional, experiential, or symbolic benefits (Keller, 1993). Because the preceding discussion detailed the conceptualizations of store image, the following discussion will be limited to how this conceptualization fits into customer-based store equity. Based upon a customer’s experience with a specific store, store category, or retailers in general, the attributes associated with a store can vary according to their favorability, strength, and uniqueness (Keller, 1993). While favorability is a function of the customer’s beliefs that the store has attributes and benefits that satisfy their needs and wants, such that a positive image is formed, the strength is the function of both the quantity and quality of the information associated with the store (Keller, 1993). On the other hand, the uniqueness of the association is the extent to which the information is not shared with other competing stores, which may or may not be positive associations (Keller, 1993). Using the Target example discussed earlier, the customers described have both favorable and unique associations with Target as compared with other mass merchandising, discount retailers.
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The comparisons of customer store images have a great impact on determining a retailer’s store equity. For example, using six different product categories and an external index of brand equity, Krishnan (1996) found that brands with high equity, as compared with brands with low equity, have a greater number of associations, more net positive associations, fewer unique associations from the category, and more unique associations from competing brands. In terms of retailing, previous research has also demonstrated strong, unique, and favorable associations to be important in determining the favorability of the overall store image (e.g., Hildebrandt, 1988).
store. Store knowledge is central to this definition because high (low) levels of store awareness and positive (negative) store image should increase (decrease) the differential effect of a particular store compared with other stores and/or generic store categories on consumer responses. As such, a major component of store equity is store image, as previous retailing researchers have developed, but the construct of store equity also provides a broader conceptualization, taping into the equity the retailer holds for customers as an input to customer behaviors and store performance. The following section will highlight this point by comparing the traditional operationalizations of store image to a few proposed operationalizations of store equity.
5. Customer responses The third component of store equity is the customer response to marketing activities, as defined in terms of customer evaluations, preferences, and behavior (e.g., brand or store choice) based upon the marketing mix activity. While the prior discussion of store knowledge was primarily concerned with customer perceptions, customer response refers to the customer’s processing of those perceptions to form subsequent comparative evaluations, preferences, behavioral intentions, or behavior. Although Keller (1993) suggests that this consumer response to a brand is reflected in their response to marketing activities, such as price, promotion, or distribution of the product, the customer may also respond to the store as a physically or humanistically characterized object or place in terms of retail personnel, product assortment, pricing strategy, location, or other retailer-level elements of the marketing activity. However, parallel to brand activities, customer response can also be dynamic and change over time if retailers change their directions and positioning or if consumers modify their store knowledge. The customer response component of the customer-based store equity conceptualization is concerned with the customer’s reaction to some element of the marketing activities of the store. This reaction may be described in terms of attitude, preference, or choice. The comparison of the reactions of a specifically named store to the reactions of a fictitiously or unnamed store allows the researcher to arrive at the store equity that a specific store has, above and beyond the generic store category, with respect to one or more aspects of the marketing of the store. Thus, a store is said to have positive (negative) store equity if customers react more (less) favorably to the marketing activity of a store than they do to the same marketing activity when it is attributed to a fictitiously named or unnamed version of that store (Keller, 1993). In summary, this article offers a new construct for retailing research, namely store equity. Paralleling the conceptualization of consumer-based brand equity of Keller (1993), store equity is the differential effect of store knowledge on customer response to the marketing activities of the
6. Comparing the operationalizations of store image to store equity To visualize the concept of customer-based store equity, as well as the compare store equity to store image, the following section will discuss the operationalizations of store image and of customer-based store equity. The former section will highlight two historical measurement debates among researchers, while the latter will discuss how the operationalization of customer-based store equity may address the underlying issues of these debates. 6.1. Operationalizations of store image In contrast to the progression and development of the construct of store image, the operationalization of store image has been more difficult and fragmented in previous research (e.g., James et al., 1976; Mason and Mayer, 1970; McDougall and Fry, 1974/1975; Swan and Futrell, 1980; Wu and Petroshius, 1987) and, arguably, incongruent with the construct’s conceptual framework (Keaveney and Hunt, 1992). Generally, three different types of operationalizations have been used to measure store image: semantic differential scales, multiattribute scales, and unstructured free-response data, such as content analysis of interviewing data. The differences in the measures for operationalizing store image have occurred primarily because some researchers argue for the use of structured techniques (Chowdhury et al., 1998; Marks, 1976; Menezes and Elbert, 1979; Reardon et al., 1995; Swan and Futrell, 1980), while others suggest that unstructured techniques are more accurate (e.g., Jain and Etgar, 1976/1977; Keaveney and Hunt, 1992; Zimmer and Golden, 1988). The primary thrust of the debate is concerned with how to best capture the gestalt of consumers’ store images and the practicality of the measurement techniques for both applied and pure research. Focusing research efforts less on the measurement of store image only and more on the concept of store equity may minimize some operationalization issues. The following discussion presents two possible methods for operationalizing store equity in future research.
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6.2. Operationalizing customer-based store equity Following the recommendations of Keller (1993) for operationalizing customer-based brand equity, two basic approaches are useful for measuring customer-based store equity; they are complementary methods and can be used together. First, researchers may assess the potential sources of customer-based store equity by measuring the customers’ store knowledge. This is an indirect approach because the differential effect on consumer response is inferred from the customers’ differential associations. Second, researchers can attempt to measure customer-based store equity by assessing the impact of store knowledge on customer responses to the marketing activities of a store. This is seen as a direct method because the customer’s response is measured directly rather than inferred. The indirect approach to measuring store equity would include measurements of store awareness and store loyalty (Yoo and Donthu, 2001). Store awareness can be measured through a variety of aided and unaided recall or recognition tasks such as asking respondents for the names of a store within a generic store category or for the recognition of specific store names. Because the previous discussion of store knowledge identified store awareness as a central component, this is a central concern to measuring store equity because stores with higher store equity should be easier for consumers to recall and recognize. However, because the stores with lower store equity may also be easily recalled if consumers have strong negative associations, measuring store image is also important in assessing the impact of store knowledge on customer-based store equity. Measuring store image may use structured (i.e., semantic differential or multiattribute measurement scales) or unstructured techniques (i.e., content analysis of freeresponse data). However, regardless of the measurement technique employed, it must measure customer-specific perceptions of a named store relative to an unnamed or fictitiously named store because comparing the characteristics of stores’ associations is imperative to assessing the equity of the store. The relationships among store associations should be measured to account for how customers compare characteristics with regard to congruence, competitive overlap, and leverage (Keller, 1993). Congruence is the extent to which associations are shared with other stores; competitive overlap is the extent to which associations are linked to the store category; and leverage is the extent to which other associations linked to a store association become secondary associations for the store (Keller, 1993). Potential measurement techniques for obtaining these data would be similar with the store image techniques discussed previously, with modifications in research design to include relative perceptions rather than absolute perceptions. While the attributes traditionally associated with store image measurement techniques (e.g., merchandise, atmo-
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sphere, appearance, convenience, salesmanship/personnel, etc.) provide the basis for the data collection measures, the important distinction between the traditional measure of store image and the proposed indirect measure of store equity is the inability of the former to account for the identification of a store name when a customer is prompted with a cue (e.g., store category, generic store, product categories, etc.), as well as the uniqueness of the store attributes when a customer is prompted to respond to similar questions about similar, yet distinct, unnamed or fictitiously named stores. Because traditional measures of store image already account for the gestalt of the image in customers’ minds, the benefit of the proposed indirect measure of store equity is the ability to measure if and how this image is shared with other stores. The direct approach to measuring customer-based store equity requires a true experimental design, in which the experimental group responds to an element of the marketing program when it is attributed to a real store, while the control group responds to that same element when it is attributed to a fictitiously named or unnamed version of the store. The rationale behind the direct measurement is that participants would respond to the fictitiously named or unnamed version of the store in coordination with their general category store knowledge, while subjects would respond to the real store in coordination with their specific store knowledge. Comparing the treatment effect would provide an estimate of the named store’s equity beyond the equity of a general store category (Keller, 1993). As compared with the indirect approach, the benefit of the direct approach would be the researcher’s ability to measure respondents before and after some treatment. For example, a researcher could detail a scenario about a store, modifying some element of the marketing mix for both a named (for the experimental group) and some unnamed store (for the control group) to be used as the treatment. Following exposure to the stimuli, the researcher could measure reactions to the treatment and the store and compare the responses of the two groups. While the researcher would be required to consider experimental realism when constructing the treatment and conducting the experiment (Keller, 1993), the treatment effect would directly account for the differential effect of the customer’s specific store knowledge on customer response to the marketing activities of the store.
7. Building and managing customer-based store equity: implications for practitioners The framework may assist managers in building and managing customer-based store equity. Thus, the following discussion focuses on the managerial insights gleaned from this conceptualization of store equity.
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7.1. Building customer-based store equity Building positive customer-based store equity requires marketing practitioners to create a familiar store name with favorable, unique, and strong associations in the minds of customers. Imbedded in this recommendation for building positive store equity are two components: store identities and the associations with the store. Store identities are considered as the name and/or logo associated with the store, which may vary by the strength of information in customer’s knowledge. In congruence with prior research on brand identities (e.g., Alba and Hutchinson, 1987), a store’s name may impact the processes by which a store is recalled or recognized. For example, past research suggests that words more frequently used (high-frequency words) are easier to recall than words less frequently used (low-frequency words), but low-frequency words are easier to recognize than high frequency words are (e.g., Lynch and Srull, 1992). Therefore, deciding whether to emphasize recall or recognition properties in choosing a store name depends upon the competitive environment (Keller, 1993). While conventional wisdom may argue that a store name is less important in the traditional brick-and-mortar environment as compared with the importance of a brand name, retailers are beginning to face a changing competitive environment within the Internet, which is making store and/or domain name an important factor in e-commerce retailing. For example, CompUSA’s online division was renamed cozone.com in late 1999, which quickly resulted in decreased sales after the name change, and was subsequently dissolved in mid-2000 (Gilbert, 2000). One argument for the company’s quick decline in sales has been that consumers responded more negatively to the perceptions of an unknown name in comparison is the known name ‘‘CompUSA,’’ who had a high brand name recognition in traditional retailing (Gilbert, 2000). As such, the concept of customer-based store equity would suggest that CompUSA did not take advantage of the strength of their store name to utilize their customer-based brand equity in the e-commerce environment. Building customer-based store equity also involves creating store knowledge with favorable, unique, and strong associations to the store name. These associations may be primary associations, which are directly linked to the store name, or secondary associations, which are indirectly linked to store name through some other node in the customer’s knowledge schema (Keller, 1993). For example, primary associations with a specific store could be the store’s atmosphere, customer service, or location, while secondary associations could be the attitudes towards a particular brand that the store carries, perceptions about the general area in which the store is physically located, or the beliefs about a generic store category or retailing in general. In order for marketing managers to build store equity, marketing managers would need to not only create favorable, unique, and strong primary associations with the store but also evaluate
and create favorable, unique, and strong secondary associations with the store. A review of past research on store image reveals a thorough understanding of the effects of building favorable, unique, and strong primary associations embedded in store image, including how positive store associations predict retailer choice (e.g., Hildebrandt, 1988; Grewal et al., 1998; Schiffman et al., 1977), store satisfaction (e.g., Bloemer and de Ruyter, 1998), competitive positioning (e.g., Burt and Carralero-Encinas, 2000; Pessemier, 1980), and store loyalty (e.g., Bellenger et al., 1976; Lessig, 1973; Sirgy, 1985). On the other hand, far less emphasis in prior retailing research has been placed upon understanding secondary associations and their impact on customer behavior. These secondary associations are important for building customer-based store equity in terms of understanding leverage, as well as competitive overlap specific associations, held in the customers’ minds. For example, when discussing how images are formed through category-based information processing, Keaveney and Hunt (1992, p. 171) suggest that researchers ‘‘no longer focus exclusively on identification of store attributes or the importance of those attributes. . .Instead, questions of interest would include categorization processes and schema development, activation, and change.’’ In terms of building customer-based brand equity, the answers to these ‘‘questions of interest’’ would enable managers to potentially leverage positive secondary associations while forming unique associations with a specific store name to minimize negative secondary associations. 7.2. Managing customer-based store equity Because store equity captures the differential effect of store knowledge on customer responses to marketing activities, marketing practitioners should manage store equity by (1) examining the knowledge structure in the customer’s minds to (2) create marketing activities that capitalize on the potential of these knowledge structures (Keller, 1993). The first part of the recommendation involves measuring customers’ aggregate store knowledge as well as measuring how the knowledge of a specific store is distinct (both positively and negatively) from the generic store category or retailers in general. Essentially, this would allow marketers to focus on those needs and wants of their customers that can be uniquely satisfied by the store. These measurements would provide managers with the information to maintain strong, favorable, and unique primary associations with the store while leveraging (minimizing) potential positive (negative) associations related to the generic store category or retailing environment, the products or brands carried, or other identified important secondary associations. The second part of the recommendation involves evaluating how tactical options available to managers will create these knowledge structures desired by the management and/ or customer. Essentially, retailers need to recognize how the
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company’s marketing activities might enhance, modify, or negatively alter their customers’ knowledge structures (Keller, 1993). For example, based upon marketing practitioners assessment of the needs/wants of their customers, as well as an assessment of their customers’ store knowledge structures, managers of a specific store should make tactical marketing decisions (e.g., store atmosphere, employee appearance, product mix lines and width, pricing strategies) based upon the concept of leveraging the positive store category associations and/or minimizing the negative store category associations rather than relying only upon managing the associations only with a specific store name.
8. Future research directions: evaluating the implications of customer-based brand equity Based upon the preceding discussion, there are a few research directions to further develop the conception and operationalization of customer-based store equity. Generally, future research would need to empirically assess (1) the efficacy of customer-based store equity as compared with other constructs and (2) the antecedents and consequences of customer-based store equity. The first general area of research would help future researchers to understand the validity of the construct based upon an assessment of the nomological network, while the latter general area of research would help future researchers to understand the empirical and causal relationships among concepts (Schwab, 1999). To address the validity of the construct, here are two specific research suggestions. First, future research needs to conduct empirical research to develop direct and indirect measures for operationalizing customer-based store equity as well as compare these measures for their efficiency. Because previous research has indicated a need to provide marketing practitioners with reliable and efficient measures of concepts related to store performance (e.g., Reardon et al., 1995; Swan and Futrell, 1980), developing and comparing the direct and indirect measures of customer-based store equity would be invaluable to future pure and applied business research. The hypothesis for comparing the direct and indirect measures of customer-based store equity is that researchers will find the two methods complementary to one another rather than dichotomous. Yet, the direct measure may be difficult to operationalize with respect to the need for experimental realism. Second, future research needs to compare the predictive ability of the measurements of customer-based store equity to the measurements of store image. While the arguments have addressed these differences conceptually, another assessment would require understanding how operationalizations of customer-based store equity and store image help predict customer behaviors, especially within different competitive environments (i.e., brick-and-mortar retailing, catalog retailing, and ecommerce retailing). The hypothesis for comparing the
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predictive abilities of customer-based store equity and store image measurements is that customer-based store equity will better predict customer responses because it accounts for store awareness and secondary associations with the store name, which will be significantly more important for predicting customer behavior in nontraditional, competitive environments such as e-commerce retailing. Two additional future research suggestions address the empirical and causal relationships. First, future research needs to address how customer-based store equity is an antecedent to the different stages of the customer decisionmaking. For example, researchers should address how customer-based store equity influences the customers’ information search, consideration sets, store and product choice, and postpurchase behaviors. The hypothesis is that customer-based store equity plays a major role in predicting the customers’ consideration sets as well as store choice and may play a minor role in information search and postpurchase behaviors because customer-based store equity accounts for the comparison between specific store options. Second, future research needs to address the antecedents of customer-based store equity including customer experiences, attitudes, beliefs, and perceptions. For example, research could be conducted to determine how the equity of generic store categories may influence the customer-based store equity of specific stores. The hypothesis is that secondary associations, including attitudes and perceptions about generic store categories and retailing competitive platforms (i.e., e-commerce), will play a significant role in determining the customer-based store equity of a specific store.
9. Conclusion Because the goal here is to provide future academic researchers with another tool for empirical studies, as well as provide marketing practitioners with additional guidance for managing tactical marketing decisions, the value of this conceptualization is found in suggesting the areas of consideration that researchers have yet to address, which will improve the understanding of customers and their behavior. Based upon theoretical foundations and activities of past research, as well as a consideration of changing competitive retailing environments, future research should continue to develop the understanding of the retailing environment by using the concept of customer-based store equity to add value to the scientific and practical knowledge of retailing.
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