Consumer-based retailer equity and retail patronage behaviors: interaction effect of involvement

Abstract

Purpose

Grounded on brand equity theory and theory of patronage behavior, this study aims to investigate the moderating effect of consumer involvement and shopping situations in the relationship between consumer-based retailer equity (CBRE) and retail patronage behavior.

Design/methodology/approach

The data is collected through a self-administered survey of 338 shoppers in the three biggest shopping centers in Pakistan. Moreover, the data is analyzed through multi-nominal (multiple) regression and interactions analysis.

Findings

Results revealed a significant effect of CBRE on patronage behavior and confirmed shopping purpose as a boundary condition in the CBRE-retail patronage behavior relationship. However, the study surprisingly reported that this relationship is not moderated by consumers’ involvement.

Research limitations/implications

Considering our focus on CBRE-based retail patronage behavior, the authors contribute to extant marketing/retailing literature that also yields ample openings for further research. The study offers valuable implications for retailers, especially for evaluating consumers’ behaviors.

Practical implications

This study assists retail-brand managers in best comprehending the CBRE-based patronage behavior paves the way for managers to increase retail patronage behavior.

Originality/value

Regardless of the growing comprehension of consumer-based brand equity and patronage behavior in marketing, more needs to be acknowledged about the relationship between CBRE/retail patronage behavior and related variables, as thus examined in this research.

Objetivo

Basado en la teoría del valor de marca y la teoría del comportamiento de patrocinio, este estudio investiga el efecto moderador de la implicación del consumidor y las situaciones de compra en la relación entre el valor del minorista basado en el consumidor (CBRE) y el comportamiento de patrocinio minorista.

Diseño/metodología/enfoque

Los datos se recogen mediante una encuesta autoadministrada a 338 compradores en los tres mayores centros comerciales de Pakistán. Además, los datos se analizan mediante regresión multinominal (múltiple) y análisis de interacciones.

Resultados

Los resultados revelaron un efecto significativo del CBRE en el comportamiento de patrocinio y confirmaron el propósito de compra como una condición límite en la relación CBRE-comportamiento de patrocinio minorista. Sin embargo, el estudio informó sorprendentemente de que esta relación no está moderada por la implicación de los consumidores.

Limitaciones/implicaciones de la investigación

Teniendo en cuenta que nos centramos en el comportamiento de patrocinio minorista basado en el CBRE, contribuimos a la literatura existente sobre marketing/minoristas que también ofrece amplias posibilidades para futuras investigaciones. El estudio ofrece valiosas implicaciones para los minoristas, especialmente para evaluar los comportamientos de los consumidores.

Implicaciones prácticas

El presente estudio ayuda a los gestores de marcas minoristas a comprender mejor el comportamiento de patrocinio basado en la CBRE y allana el camino para que los gestores aumenten el comportamiento de patrocinio minorista.

Originalidad

A pesar de la creciente comprensión de la equidad de marca basada en el consumidor y el comportamiento de patrocinio en marketing, es necesario reconocer más sobre la relación entre el comportamiento de patrocinio basado en la CBRE y las variables relacionadas, como se examinó en esta investigación.

目的

本研究以品牌资产理论和顾客行为理论为基础, 探讨了消费者参与和购物情境在基于消费者的零售商资产（CBRE）与零售顾客行为之间关系中的调节作用。

设计/方法/途径

数据是通过对巴基斯坦三大购物中心的 338 名购物者进行自填式调查收集的。此外, 还通过多项式（多元）回归和交互分析对数据进行了分析。

研究结果

结果表明, CBRE 对顾客光顾行为有显著影响, 并证实购物目的是 CBRE 与零售顾客光顾行为关系的边界条件。然而, 令人惊讶的是, 研究报告称这种关系并没有受到消费者参与度的调节。

研究局限/启示

考虑到我们对基于 CBRE 的零售顾客行为的关注, 我们为现有的市场营销/零售文献做出了贡献, 同时也为进一步研究提供了广阔的空间。本研究为零售商提供了宝贵的启示, 尤其是在评估消费者行为方面。

实践意义

本研究有助于零售品牌管理者更好地理解基于 CBRE 的顾客行为, 为管理者提高零售顾客行为铺平了道路。

原创性/价值

尽管市场营销中对基于消费者的品牌资产和顾客行为的理解不断加深, 但仍需进一步认识 CBRE/零售顾客行为与相关变量之间的关系, 正如本研究中所探讨的那样。

Citation

Sajid, B., Cheema, S. and Rather, R.A. (2023), "Consumer-based retailer equity and retail patronage behaviors: interaction effect of involvement", Spanish Journal of Marketing - ESIC, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/SJME-11-2022-0239

1. Introduction

In today’s highly volatile environment, the retail arena has witnessed irreversible transformation where retailers are facing stiff competition, developing and maintaining customer loyalty pose a big challenge for brick and mortar retailers, which calls upon to have a brand focus and marketing strategy to fortify the retailer’s brand (Morgan and Anglin, 1999). This brand focus can be taken as retailers’ concern with the strength of its brand in the market, positioning and consumer-perceived image (Han et al., 2021). Although the existing literature suggests store attributes, store image and other determinants of customer loyalty, still consumers’ intention to patronage a retail store is needed to be addressed extensively (Wel et al., 2012). Existing research suggests that brick-and-mortar retailers must battle for ensuring brand equity (e.g. customer attachment and loyalty), which becomes critical for them to build a strong bond with customers and earn their patronage (Badrinarayanan and Becerra, 2019; Liu et al., 2017; Pappu and Quester, 2021). The fact that retail brands also possess equity like all other brands (e.g. FMCGs, apparel, food, services, etc.) has been emphasized by leading practitioners and researchers in the domain of marketing (Pappu and Quester, 2006; Das, 2015). Retailer equity has emerged as one of the most significant concepts in the area of retail marketing management (Pappu and Quester, 2006; Das et al., 2012; Porral et al., 2015). Although previous literature explores the concept of customer loyalty (Liu et al., 2017; Wel et al., 2012), still customer patronage for retail stores under various shopping situations appears to be under-researched area.

Consumers prefer to shop from stores that offer them a good shopping experience and greater value exchange (Kautish et al., 2021, 2022). This value can be offered by managing brand equity. Brand equity is conceptualized in terms of incremental value imparted to the product due to the existence of brand (Aaker and Jacobson, 2001). Similarly, Aaker (1991, 1996) coined the value of brand equity by emphasizing that brand equity creates value for both customers and firms (Aaker and Jacobson, 2001). However, Keller (1993) states that high brand equity promises a competitive advantage by generating high differentiation, high brand knowledge and consumer response (Keller, 1993). Consumer-based perspective of brand equity entails that the brand knowledge creates a point of differentiation in the minds of the consumers, which further affects their response to the marketing of the brand, referred as customer-based brand equity (CBBE) (Tynan et al., 2010). Paralleling these efforts, Hartman and Spiro (2005) define retailer equity as “the differential effect of store knowledge on consumer response to the marketing of store” (Arnett et al., 2003). It is asserted that retail store knowledge stems from the knowledge in the minds of consumers about retailers based on awareness, favorable associations and store image (Keller, 2003). In the words of value associated by the consumer with the name of a retailer, as reflected in dimensions (of retailer awareness, retailer association, retailer perceived quality and retailer loyalty) is termed customer-based retailer equity (CBRE) (Pappu and Quester, 2006).

Loyalty is a process, not just an act (Torres‐Moraga et al., 2008), where both attitudes and purchase or repurchase behavior should be taken into account. Traditionally, according to Bloemer and Kasper (1995), loyalty can be defined as spurious loyalty or inertia (Gil-Saura et al., 2013), which implies high probability behavior and low commitment to repurchase (Dick and Basu, 1994), consists of revisiting or rebuying in a store (Bloemer and Kasper, 1995) based on situational signals (Dick and Basu, 1994), whereas patronage, in addition to repeat purchase, involves a choice and decision behavior based on consumer preferences (Mellens et al., 1996) and intentions. It includes a strong bonding and relationship. If a customer’s purchase pattern is repeated over a series of purchase tasks, this behavior is called patronage (Guiltinan and Monroe, 1980). Sometimes, repeat patronage can be primarily rooted in higher transaction costs, switching costs and/or lack of alternatives (Morgan et al., 2000). We followed one of the recent studies (Liu et al., 2017), which also explored the significance of CBBE factors (i.e. brand awareness, brand image, perceived quality and brand loyalty) on customer’s brand attitude and their consequent purchase intention. Thus, retail store choice and patronage have been widely studied across the world (Dahana et al., 2022). There is still vast scope for research as the retailing environment changes rapidly, which leads to changed shopper expectations and realignment of the choice set of stores (Han et al., 2021). As shoppers even change their store choice because of emerging retail formats, it needs to be evaluated to retain consumers (Gehrt and Yan, 2004; Sinha and Banerjee, 2004). This study sought to examine the effect of retailer equity on consumer behavior in patronizing a retail store, following brand equity theory and theory of patronage behavior.

The current study focuses on the conceptualization that the behavior of human beings depends on situational factors. However, existing studies focused on examining the influence of situational factors in the goods market, but only a few studies address it in the retail arena (Koay et al., 2020). Published research revealed that besides lifestyle and good shopping experience, consumer shopping behavior is also affected by situational factors (Gehrt and Shim, 2002).

Retailers are very fascinated in how shoppers build their (re)purchase decisions, and as why, whether, or when a shopping visit leading toward purchase (Zhuang et al., 2006). This knowledge is important in devising marketing and branding strategies (Gehrt and Shim, 2002) as well as retailing planning (Koay et al., 2020). The marketing research has exposed various elements that can impact consumers (shoppers) purchase decisions, like psychological/individual attributes and social, cultural and environmental factors (Zhuang et al., 2006). We extend these studies by investigating the role of shopping situations (i.e. self-shopping and gift-giving) and consumer’s shopping involvement. Drawing on the theory of consumer involvement (Hupfer and Gardner, 1971), it is expected that different product attributes cause different degrees of involvement in consumer minds. These differences in involvement are a cause of variation in consumers’ purchase decisions and store selection. Thus, when consumers purchase, the extent of their involvement affects purchase intention (Swoboda et al., 2009). Mitchell (1979) understands involvement as a state of activation, motivation or interest that occurs if a stimulus is particularly relevant for the individual or generates situation-related consequences. Based on this notion, it is asserted that apart from the level of involvement, different product categories involve different shopping behavior, as it is claimed that consumer shopping behavior differs for gifts and groceries (Kim, 2012).

The contribution of this study is reflected that high retailer (brand) equity fosters customer loyalty or purchase intention (Abbasi et al., 2023; Castañeda García et al., 2018; Liu et al., 2017), although the impact of retailer equity on building customer patronage behavior is overlooked by researchers (Kim et al., 2020; Mansouri et al., 2022). In addition, consumer shopping behavior varies in different shopping situations, which calls upon for investigation of the CBRE effect in building and sustaining customer patronage when their level of involvement is different and their purchase situation varies (Raut et al., 2019; Benoit et al., 2019). To our best knowledge, the study is the first one to investigate the nature of CBRE and retail patronage relationships under boundary conditions like shopping situations and consumer involvement by using brand equity theory and theory of patronage behavior. Therefore, the study aims to investigate the impact of CBRE on consumers’ retail patronage behavior, the extent to which situational contingency (like, self-shopping and gift-shopping) moderates the relationship between CBRE and retail patronage behavior and the influence of shopping involvement act as a boundary condition in the relationship between CBRE and consumer behavior to patronize a retailer.

2. Literature review and hypotheses development

Branding plays a pivotal role in retailing, its highly competitive nature fosters patronage behavior (Gil-Saura et al., 2013). Retail store choice and patronage have been widely studied across the world (Sinha and Banerjee, 2004). It is found with keen interest that consumers form an impression of brands, and this impression later influences consumer’s choice decisions and shopping behavior (Liu et al., 2017).

2.1 Consumer-based retailer equity and brand equity theory

The concept of brand equity gained popularity since the end of the 1980s (Troiville and Cliquet 2015). Early research on brand equity has emphasized financial aspects, but later on CBBE grabbed more attention (Liu et al., 2017). The majority of CBBE works signify key theoretical frameworks, like Aaker’s CBBE model and Keller’s CBBE theory. Keller (1993) conceptualizes brand equity as a brand power that is built in the consumer’s minds on the basis of what they have learned, seen, felt and heard about a brand. Retailer equity has recently emerged in marketing literature (Das, 2015; Arnett et al., 2003) were the first to conceptualize retailer equity as a multidimensional construct comprising dimensions: name awareness, retailer associations and service quality and store loyalty, wherein practitioners and marketing researchers (Aaker, 1991, 1996; Keller, 2003) asserted that similar to brands, the retailer also possess equity (Pappu and Quester, 2006), which is termed as CBRE (Pappu and Quester, 2006; Das, 2015; Das et al., 2012).

Retail equity is conceptualized as “the differential response of store knowledge on consumer response to the marketing activities of the store”(Hartman and Spiro, 2005). Previous literature reflects that successful retail branding is of immense importance in influencing consumer perceptions and driving store choice behavior and loyalty (Porral et al., 2015). The early researchers emphasized four dimensions of retailer equity, i.e. store loyalty, name awareness, perceived quality and retailer associations (Pan and Zinkhan, 2006). Arnett et al. (2003) asserted retailer equity as a multidimensional construct comprising five dimensions such as name awareness, store loyalty, service quality and retailer association, which is further bifurcated into two subdimension of product quality and perceived value. It is asserted that retail association is a better dimension of retailer equity than store image because an image is reflected by the retailer associations (Keller, 2003; Jinfeng and Zhilong, 2009), and customer’s strong associations with brands reflect high brand equity (Yoo et al., 2000).

Keller (2003) considers awareness as an ability to identify the brand by linking the brand name, its logo, symbol, etc., under different conditions to link certain associations in the memory (Keller et al., 2011). Furthermore, Pappu and Quester (2006) followed Arnett et al. (2003) conceptualization and treated “retailer awareness” as a different dimension of retailer equity. Arnett et al. (2003) underpins “service quality as a dimension of retailer equity. Zeithmal (1988) defined it as a consumer’s judgment about a retailer’s overall excellence and superiority. However, Darley and Johnson (1993) claims that product quality perception and preferences of a product are closely related to choosing behavior and further influences store patronage behavior. Aaker (1991, 1996) conceptualizes quality as an intangible part of brand equity and relates it with overall feelings about a brand that affects market share, price and profitability (Pan and Zinkhan, 2006). Arnett et al. (2003) asserted store loyalty, in line with Oliver (1997), as a firm’s commitment to consistently repurchase or repatronize a product or service of preference in the future. However, this conceptualization is very much similar to the definition of brand loyalty that is generally adopted by marketing practitioners in the world of marketing literature (Yoo et al., 2000). Based on this similarity, it is asserted that the concept of brand loyalty has simply given an extension to “retail store loyalty” and is termed as retailer loyalty (Koo, 2003). In this regard, Yun et al., (2012) relates store loyalty and commitment with retail patronage intention.

The theoretical foundation of this study is derived from brand equity theory (Aaker, 1991, 1996; Keller, 1993; Liu et al., 2017) and theory of patronage behavior (Sheth, 1983). Theory of patronage behavior postulates that social values influence on retail patronage behavior. The theory focuses on the role of a social group, like friends and family, as a source of information that helps in image formation, which later influence the patronage intention and patronage behavior (Park et al., 2008). Research on brand equity and patronage behavior in shopping environments not only develops the theoretical insights regarding the theory of brand equity and patronage behavior theory but also assists inform managerial decisions on fostering CBRE/patronage behavior strategies (Keller, 1993; Liu et al., 2017; Sheth, 1983). We propose that brand equity theory and theory of patronage behavior might build a more inclusive description of CBRE/involvement underlying a customer’s retail patronage behavior process.

2.2 Conceptualization of retail patronage behavior

Branding seems to play a pivotal role in retailing and its highly competitive nature fosters patronage behavior (Islam and Rahman, 2016; Keller, 2003; Rather et al., 2018). It is believed that retail store choice and patronage have been widely studied across the world (Sinha and Banerjee, 2004). Osman (1993) simply defines patronage behavior as the repeat purchase behavior at a particular retail store for either the same products or any other. Shim and Kotsiopulos (1992) defined patronage behavior as store choice behavior that represents an individual’s preference for a particular store for purchasing products. Pan and Zinkhan (2006) identified retail patronage as having two dimensions:

1. store choice (a consumer’s choice to patronize a particular store); and

2. frequency of visit (how often a shopper patronizes that store).

They also found that retail image was a major predictor for explaining shopping frequencies. However, Zhang et al. (2023) related store image to the retail association, perceived quality and retail awareness, whereas Keller (1993) asserted that retail association is a better dimension of retailer equity than store image because the image is reflected by retailer associations (Jinfeng and Zhilong, 2009). Furthermore, it is observed that consumers may form impressions of brands and these impression later influence consumer’s choice decisions and shopping behavior (Islam et al., 2018). Moreover, Porter and Claycomb (1997) supported that favorable retail equity significantly influences patronage behavior.

The impact of retailer equity on retail patronage behavior still needs to be probed (Liu et al., 2017). However, patronage intentions reflect the likelihood that a customer will shop at a retail store again, whereas loyalty is a deeply held commitment to a specific brand or a particular retailer (Evans et al., 1996). If a customer’s purchase pattern is repeated over a series of purchase tasks, this behavior is called patronage (Guiltinan and Monroe, 1980). Image formations mental processes whereby information and experiences are processed and evaluated, resulting in predispositions that generally guide patronage (Evans et al., 1996). The closer the store’s image to the consumer’s needs, the more positive the individual’s predispositions toward that store and the greater the probability that the consumer will shop in the store. At the same time, retail loyalty is the consumer’s preference for consistent repurchases from specific retailer over time different from retail patronage (Liu-Thompkins et al., 2022).

Though, retail patronage is consumers’ emotional commitment based on consumers’ experience and feeling toward a store and intent to have long-term belonging with the store (Pan and Zinkhan, 2006). In retail patronage, the consumer owns that brand or retail store. Whereas, retailer loyalty is the attitudinal behavior that leads toward retail patronage, which further demonstrates the actual behavior of the consumer (Pan and Zinkhan, 2006). Literature reflects that customer-based retail brand equity involves a shortcut in the mind of the consumer, which is retrieved from the memory of past shopping experiences and good purchases, which in turn affects future patronage and reduces the influence of the competitors’ efforts (Porral et al., 2015). Furthermore, studies revealed that CSR activities like respect for consumers could impact consumers’ loyalty toward their retailer (Louis et al., 2019).

2.3 Interaction of consumer-based retailer equity and retail patronage behavior

One of the most prominent themes in the marketing literature in recent years has been a merging of research streams relating to consumer-based brand equity and customer loyalty (Liu et al., 2017; Pawar and Raut, 2019). Customer-based retail brand equity is conceptualized as a shortcut in the minds of consumers that recalls the most salient past shopping experiences that give them satisfaction and purchased goods, which affect future patronage and reduce the potential influence of competitor’s marketing strategies (Dwyer et al., 1987). However, the effects of store image on consumer loyalty behavior have been widely studied over the years, but the impact of retail equity on consumer patronage behavior is still limited (Zhang et al., 2023).

The current study aims to fill this void by extending CBBE measurement to retailer equity measurement, whereas using retail awareness, retail association and retail loyalty, perceive quality by using brand equity theory (Das, 2015), and it follows the assertion that store image is related to retailer equity dimensions such as retailer awareness, retailer association and retailer perceived quality (Jinfeng and Zhilong, 2009). Literature reveals that favorable retailer equity significantly influences patronage behavior (Pappu and Quester, 2021; Porter and Claycomb, 1997). It is also asserted that customer trust is important in gaining retail customer loyalty, in a socialized world, customer trust positively influences customer intention to buy at a particular brand (Khan et al., 2022). Recently, Liu et al. (2017) verified the importance of CBBE factors (i.e. brand awareness, brand image, perceived quality and brand loyalty) on customer’s brand attitude and their consequent purchase intention with luxury hotel brands, whereas Dahana et al. (2022) identified the role of store patronage, motivation and marketing efforts in developing cross-buying behaviors within online shopping malls. Grounded on brand equity theory and theory of patronage behavior, the positive impact of consumer-based retailer equity (CBRE) can enhance consumer’s retail patronage behavior by raising their brand associations, awareness, perceived quality and loyalty. Following these arguments, we posit:

H1.

Consumer-based retailer equity positively affects retail patronage behavior.

2.4 Moderating role of shopping situations

The causal relationship between shopping situations and store choice was first investigated by Mattson (1982), it was revealed that situational attributes like time pressure and shopping for gifts versus for oneself influence store visit likelihood and saliency of store attributes (Mattson, 1982). As noted, research revealed that good shopping experience and besides lifestyle, consumer shopping behavior is also impacted by situational factors (Gehrt and Shim, 2002). However, research on situational influences is generally described as examining the relationship between various shopper characteristics and retailing features or point-of-purchase situations. It is asserted that shopper characteristics might include involvement, attitude and ethnicity (Morgan and Anglin, 1999). The current study focuses on the conceptualization that the behavior of human beings depends on situational factors. In a study conducted by Mattson (1982), it was found that situational attributes, such as time pressure and gift-versus self-shopping, can influence the selection of retail stores and attribute salience.

Situational contingencies in the context of gift-giving might fall into any of these dimensions (Mattson, 1982). A physical dimension of the gift-giving situation might involve whether a gift will be given to a person living nearby or in another city (Morgan and Anglin, 1999). A social dimension of gift-giving relates to the involvement of other persons (Anaza, 2014). Gift-giving naturally involves other people. A task definition dimension is defined as a situation in which consumers have a particular objective in mind (Benoit et al., 2019). Finally, temporal dimensions relate to time of day, length-of-time, doing two things at once and similar issues (Morgan and Anglin, 1999). For gift-giving, whether a consumer’s shopping is time-pressured might be a relevant issue. The current study sought to emphasize on social and task dimensions of the gift-giving situation in an apparel product category.

Numerous studies have examined situational contingency in consumer behavior. Among those are studies of single versus multiple product purchase tasks (Stoltman et al., 1990, Van Kenhove et al., 1999), personal usage in comparison with gift-giving shopping behavior (Mattson, 1982; Gehrt and Yan, 2004) and home versus away from home usage (Ratneshwar and Shocker, 1991). The research has also examined situational influence among various product categories, including the apparel (Belk, 1975), banking services (Srivastava et al., 1981) and retailers (Van Kenhove et al., 1999). An extensive stream of researchers studied moderating role of age and gender (Khare, 2012; Khare et al., 2014), including the gender of a gift recipient, but the current study addresses shopping orientation, such as self-shopping and gift-shopping as a boundary condition, which ensures its originality. In light of the abovementioned discussion, the current study sought to emphasize on social and task dimensions of the gift-giving situation in an apparel product category and aims to investigate whether these shopping situations cast any effect on the relationship between retailer equity or consumer patronage behavior or not? Thus, we posit:

H2.

Shopping situations significantly moderate the relationship between retailer equity and retail patronage behavior.

2.5 Moderating role of consumer shopping involvement

Mitchell (1979) understands involvement as a state of activation, motivation or interest that occurs if a stimulus is particularly relevant for the individual or generates situation-related consequences (Calvo-Porral and Nieto-Mengotti, 2019). Based on this notion, it is asserted that apart from the level of involvement, different product categories involve different shopping behavior, as it is claimed that consumer shopping behavior differs for gifts and groceries (Kim, 2012). Hupfer and Gardner (1971) and Lastovicka and Gardner (1979) operationalized involvement by having subjects state the “importance” of the product class. Mitchell (1979) understands involvement as a state of activation, motivation or interest that occurs if a stimulus is particularly relevant for the individual or generates situation-related consequences. It is evoked by factors specific to the individual, to the stimulus or the situation and reflects the willingness to act upon the stimulus cognitively or emotionally. Drawing on the theory of consumer involvement (Lastovicka and Gardner, 1979), it is expected that different product attributes cause different degrees of involvement in consumer minds. These differences in involvement are a cause of variation in consumers’ purchase decisions and store selection. Therefore, when consumers purchase, the extent of their involvement affects purchase intention (Swoboda et al., 2009).

Research examined the moderating role of involvement while analyzing retailer attribute perceptions on CBRE (Swoboda et al., 2009). For example, Rather et al. (2021) examined the moderating role of involvement into the linkage between customer experience/cocreation and behavioral intent with tourism brands, whereas Abbasi et al. (2023b) verified the importance of consumer involvement between the consumer engagement and e-WOM with destination brands. However, the current study aims to investigate the moderating effect of consumer involvement in shopping situations (self-shopping, gift giving) while studying a relationship between CBRE and retail patronage behavior (Figure 1):

H3.

Consumer shopping involvement significantly moderates the link between retailer equity and retail patronage.

3. Materials and methods

This study investigates the moderating effect of consumer involvement and shopping situations in the relationship CBRE and retail patronage behavior. For this purpose, a questionnaire is developed to conduct a self-administered survey. Afterward, the data is analyzed by applying multiple linear regression. The statistical program SPSS 21 is used to analyze the primary data.

3.1 Research design, context and data collection

The study was conducted at three shopping centers (e.g. Chen One, Nishat Linen [NL] and Ideas) in two metropolitan cities of Pakistan, Multan and Lahore. Data collection was done through mall-intercept surveys from September 2021 to March 2022, and respondents were requested to fill a self-administered survey. The participants were primarily described regarding the objective of the research, and they were also advised that involvement in the current study was voluntary before the study was conducted. Keeping in view the aim of the study, the population was taken as consumers aged between 18 years and above who shopped at any retail outlet at Lahore and Multan. As the population of this study is too big that it is nearly impossible to access, so nonprobability sampling, such as cluster sampling, was deployed. A further survey was conducted with every second shopper through systematic sampling within three clusters of Chen One, NL and Ideas. Through systematic sampling, a convenient sample of 338 respondents was drawn. The sample size of the study was chosen, based on the requisite number involved by statistical tools like regression analysis. For details of a minimum requirement of a sample, see Hair et al. (2006).

Data collection was completed during quite a few days of the week and at weekends. To ensure maximum generalizability and maximum variance, the self-administered survey was conducted with consumers in various apparel stores among shoppers at two Chen, four NL and four Ideas stores in Multan and Lahore. The selection of various branches of three shopping centers was made based on the conceptualization of specialty retail stores. Therefore, all the retail stores are expected to be homogeneous in terms of the merchandise they carry. We pretested the questionnaire by using a convenience sample from 24 consumers of these shopping centers. Results of descriptive statistics showed that the items were appropriate and relevant to the pretested respondents. A few refinements were noted and added to the questionnaire. Demographic characteristics included information on gender, age and marital status. About 170 questionnaires were filled in at Lahore and 200 at Multan. Whereas, 32 questionnaires were excluded from the analysis as they were incomplete. Finally, 338 properly filled, useable pairs of responses were found to be available for analysis, yielding a response rate of 91%.

3.2 Measures

The variables of the current study were measured on different-point Likert scales to avoid common method biases (Podsakoff et al., 2003). Four dimensions of CBRE consist of a total of 23 item scales, namely, retailer awareness – four, retailer associations – 10, retailer perceived quality – five and retailer loyalty – three-item scale by Pappu and Quester (2006). These items were measured on a seven-point Likert scale, which includes anchors ranging from 1 = strongly disagree to 7 = strongly agree. Consumer shopping involvement (CSI) consists of 10-item scales measured on a semantic scale adapted from the consumer behavior (Schiffman and Kanuk, 2000). Retail patronage behavior was measured through customer’s shopping center visit frequency labeled as 4visit/month, 2 = 2visit/month, 3 = 1visit/month, 4 = 1visit/2 month, whereas store preference was assessed through “you prefer to shop from these lifestyle products of store during: regular days, sales days, and/or both (Pan and Zinkhan, 2006). In addition, consumers were asked to mention their profile, like gender, age and family status. The items of shopping situations (gift shopping and self-shopping) were adopted from Gehrt and Yan (2004). These two attribute factors were regressed against shopping situations by using dummy variable coding (Gehrt and Shim, 2002).

Demographic characteristics showed that female respondents (59%) were higher involved in shopping than males (41%). The average age of respondents was 25 years (SD 0.74) approximately 60% of respondents fall under the age group of 21–30 years, as youngsters were found more enthusiastic about shopping at apparel specialty malls, particularly at shopping centers. The sample includes 67.5% of respondents who belong to joint families and approximately 32.5% are from separate families. Moreover, 55% of respondents reported that they like to shop with their family, whereas 27% preferred individual shopping. Furthermore, 27% of respondents like to visit in sales duration, whereas 57% shop during both sales and 15% during regular days. However, 88% of respondents intended to recommend these shopping centers to others; 41% of respondents prefer NL for self-shopping, whereas 37% preferred Chen only 22% like to shop Ideas for self-shopping; approximately the same pattern is visible for gift-shopping (Table 1).

3.3 Analysis

The in-depth review of previous literature allowed using multiple linear regression (Gunst and Mason, 2018) to investigate the moderating effect of consumer involvement and shopping situations in the relationship between CBRE and retail patronage behavior.

The mathematical model of multiple linear regression is as follows:

Y=β0+β1X1+β2X2+…+βiXi+εt

Here, x characterizes the compilation of predictors x1, x2,… xi in the model, and β1, β2,…βi act for the corresponding regression coefficients and ∈ is the random error or interruption in the experiment (Kost et al., 2021).

Multiple linear regression allows the investigator to account for all of these potentially important factors in one model. The advantages of this approach are that this may lead to a more accurate and precise understanding of the association of each individual factor with the outcome. Whereas linear regress only has one independent variable impacting the slope of the relationship, multiple regression incorporates multiple independent variables. Each independent variable in multiple regression has its own coefficient to ensure each variable is weighted appropriately (Ngo and La Puente, 2012).

4. Results

4.1 Reliability and validity

The statistical program SPSS 21 was used for the analysis of data. All variables showed strong Cronbach’s alpha values and demonstrated satisfactory values ranging from above 0.70 (Table 2). Descriptive analysis and correlations also provided satisfactory values (Table 2). Furthermore, we measured the composite reliability and validity of the items and the outcomes showed above average of 0.70 Cronbach’s alpha and internal reliability with CR (Fornell and Larcker, 1981). Followed by Fornell and Larcker (1981), validity through average variance extracted (AVE) criterion, all scales indicated satisfactory convergent validity values meeting the threshold of 0.50.

Finally, discriminant validity was measured by following Fornell and Larcker’s (1981) AVE, and correlation criterion, all pairs of variables showed correlation (off-diagonal elements), which was lower than the square roots of AVE approximations (diagonal elements), present adequate evidence of discriminant validity (Hair et al., 2006).

4.2 Multi-nominal multiple regression analysis

To explore the impact of CBRE dimensions on the retail patronage behavior of consumers, multi-nominal (multiple) regression analysis has been applied. The literature revealed patronage behavior could be measured based on visit frequency and store preference. So, the researchers used the frequency of shopping center visits and shopping center preference as measures of retail patronage behavior. The impact of CBRE dimensions on retail patronage behavior was assessed by running multiple regression analyses.

As the dependent variable is multiple (frequency of shopping center visit and shopping center preference) and patronage behavior is categorical so, multi-nominal regression was applied for frequency and preference separately and found the highest Mc Fadden 0.18 for shopping center preference. However, the pseudo-R square is not considered a good measure of model strength and does not convey the same results as linear regression; thus, linear regression is considered as an alternative.

The regression results for the main effects for both visit frequency (Table 3, Model 1) and preference (Table 3, Model 3) are shown separately. For all main effects of predictors variable on criterion variables, consumer-based retailer equity_Chen One (CBRE_CO), consumer-based retailer equity_Nishat Linen (CBRE_NL) and consumer-based retailer equity_Ideas (CBRE_Id) entered as independent variable and frequency as a dependent variable in the first step and CBRE of three shopping centers along with CSI and shopping situation (shown as a choice) taken as predictors in the second step. CBRE in the case of Chen One and Nishat Linen (CO and NL), significantly predicted patronage behavior. As Table 3, Model 2 depicts (CBRE_CO (β = 0.369, p=<0.05), CBRE _NL and frequency (β = 0.378, p ≤ 0.05). However, CBRE_Id did not predict patronage behavior (β = 0.093, ns). The interaction of the potential intervening and independent variables was applied to see the moderation effect to test H2/H3. Results were obtained on the basis that if the interaction (Independent*Intervening) is found significant, then it will be suggested that the intervening variable has a moderating effect on the relationship between independent and dependent variables. The formula used to check moderation through multiple interactions is y∼x1 * x2 * x3 * x4.

Frequency ∼ CBRE_CO * CBRE_NL * CBRE_ID * CSI * SS

Dependent Variable ∼ Interaction of all independent variable

4.3 Interaction effects

The interaction of CBRE (independent variable) and shopping situation, which is taken as a choice (moderating variable) here, proves to have a moderating effect, whereas CSI did not prove to be a moderator. Table 4 summarizes the significant interactions generated through the multiple interaction approach. The choice is proven to be a moderator between CBRE_CO and frequency and between CBRE_NL and frequency at a 10% confidence interval, which is quite acceptable; however, CSI was not proven as a moderator in any case. H2 predicted that the relationship between CBRE and patronage behavior is moderated by shopping situation (choice in case of self-shopping and gift-shopping) (p ≤ 0.01); hence, H2 is accepted.H3 predicted that the relationship between CBRE and patronage is moderated by shopping involvement, whereas CSI is not proven to intervene in the relationship and H3 is rejected.

5. Discussion and conclusion

Rooted in CBBE model developed by Aaker (1991, 1996) and expanding the brand equity theory suggested by Keller (2003) and Liu et al. (2017), the present study examines the shopping situations and consumer’s shopping involvement between CBRE and retail patronage behavior. This study expands the body of literature embedding the retail-level approach into marketing studies, which is rather neglected area so far (Ailawadi and Keller, 2004; Dahana et al., 2022; Pappu and Quester, 2021). Based on this gap, thus, this research investigated the relationship between CBRE and retail patronage behavior, with the moderating effects of shopping situations and consumer’s shopping involvement by using brand equity theory and patronage behavior theory. Building on extant marketing and retailing literature, we suggest CBRE has positive effects on retail patronage behavior. The findings are consistent with the current knowledge in service marketing, which recommends CBBE’s significance in effecting consumer’s purchase intent or patronage behavior for brands (Liu et al., 2017; Pappu and Quester, 2021). Similarly, the findings are in line with Zhang et al. (2023) that verified retail brand equity’s role in developing consumer shopping experience as well as shopping value. Furthermore, by studying the moderating effects of shopping situations and CSI, this study also contributes to the extant marketing literature regarding consumer’s intentions and particularly their preferences and visits to shopping malls (Swoboda et al., 2009). Findings revealed a significant effect of CBRE on patronage behavior and confirmed shopping purpose as a boundary condition in the CBRE-patronage behavior relationship. While results surprisingly suggested CBRE-patronage behavior relationship is not moderated by CSI. These findings provide important theoretical and practical implications, as delineated below (see Conclusions and Implications):

1. Conclusions

   • Rooted in CBBE model developed by Aaker (1991, 1996) and expanding the brand equity theory suggested by Keller (2003) and Liu et al. (2017), the present study examines the shopping situations and consumer’s shopping involvement between CBRE and retail patronage behavior.

   • The findings are consistent with the current knowledge in service marketing, which recommends CBBE’s significance in effecting consumer’s purchase intent or patronage behavior for brands.

2. Theoretical and managerial implications

   • This study expands the body of literature embedding the retail-level approach into marketing studies, which is rather neglected area so far.

   • It is necessary for brand and retail/marketing managers to know the dynamics typifying consumer-perceived brand performance indicators, including CBRE.

   • The results may help marketers in building marketing/branding strategies in the competitive market adopting CBRE and assist more effective communications between marketing authorities and consumers in the increasingly altering environments.

6. Implications

6.1 Theoretical implications

The current study makes various contributions to marketing and retailing literature. The stream of literature contains different approaches to the measurement of retail (brand) equity (Ailawadi and Keller, 2004; Liu et al., 2017; Swoboda et al., 2013). Most of the authors generally agree with Keller’s well-known conceptualization of extending the concept of brand equity to measuring retailer equity (Ailawadi and Keller, 2004; Dahana et al., 2022; Porral et al., 2015). The current study used brand equity theory, to extend the CBBE dimensions to the measurement of CBRE. We adopted brand equity theory to examine the CBRE effect on consumers’ behavior toward patronizing retail shopping centers, and the results revealed that the frequency of shopping center visits acting as an effective measure of retail patronage behavior. While this study disapproves store preference as a measure of retail patronage. This result contradicts Pan and Zinkhan’s (2006) finding that the frequency of shopping center visits along with shopping center choice measures patronage behavior. Moreover, it also contradicts Thang and Tan’s (2003) claim that shopping center preference can be deployed to measure retail patronage.

The result shows a significant effect of CBRE on patronage behavior, thus extending researchers, including Dahana et al. (2022) and Pappu and Quester (2006, 2021). Our results support Allaway et al., (2011) assertion that there is a significant link between CBRE and consumer behavior in patronizing a shopping center (Liu et al., 2017). Previous studies also addressed the shopping situation as an antecedent to the retail format preference (Gehrt and Yan, 2004). To our best knowledge, no study has investigated the moderating role of shopping situations in liking retailer equity with patronage behavior to date, thereby broadening authors including Benoit et al. (2019) and Swoboda et al .(2013). This study thus empirically explores the moderating effect of consumer shopping situations on consumer behavior to patronize a shopping center. We reported the most surprising result about consumer involvement, as hypothesized retail patronage behavior is not proved to be moderated by consumers’ involvement. This result contradicts the finding of moderating effect of consumer involvement on CBRE (Swoboda et al., 2013).

Furthermore, consumer behavior in patronizing a shopping center is also being affected by the city. The results of this study reveal a significant variation in the shopping behavior of shoppers at Lahore and Multan at upscale specialty shopping centers. The findings supplement the findings by, as it is asserted that location is very important in the shopping centers context (Kapferer and Bastien, 2009). In addition, it also posed that the strength of the effects of retailer equity and location accessibility on shopping center patronage depends on the local competitive context (Swoboda et al., 2013).

Finally, as outlined, this study reveals the frequency of shopping center visits as a good measure of patronage behavior rather than shopping center preference and the result is consistent with the claim that retail shops preference is secondary to brand preference (Park et al., 2008). Another important finding of the current study is that shopping situations such as self-shopping or gift-shopping cast an effect on consumer behavior in patronizing a shopping center. Hence, this finding supports the assertion that shopping situations strongly affect patronage behavior as compared to shopping center attributes (Park et al., 2008). Relatedly, brand equity theory has not been effectively examined and developed for retail shopping context to assist various stores to (re)design their marketing/branding strategies on the basis of brand awareness, perceived quality, association and loyalty. Our study findings not only contribute toward the expansion of brand equity theory/patronage behavior theory, and their fundamental mechanisms, but also offer valuable practical/managerial implications for marketing (branding) strategies for retailers.

6.2 Practical implications

The current research suggests important implications for retail managers and marketers. In a highly volatile retail environment, where a retailer is facing cut-throat competition, high retail equity is of great importance in influencing consumers’ thinking, perceptions and shopping centers choice as well as patronage to ensure competitive advantage (Dahana et al., 2022; Pappu and Quester, 2021). In other words, it is necessary for brand and retail/marketing managers to know the dynamics typifying consumer-perceived brand performance indicators, including CBRE (e.g. Ailawadi and Keller, 2004; Keller et al., 2011; Pappu and Quester, 2021). The results may help marketers in building marketing/branding strategies in the competitive market adopting CBRE and assist more effective communications between marketing authorities and consumers in the increasingly altering environments. Identifying the implication of such issues, we investigated the role of CBRE in the advancement of retail patronage behavior via the moderating effects of consumer involvement and shopping situations, generating extensive managerial implications.

Furthermore, the tremendous evolution in the retailing environment leads to changing shopper expectations and preferences as well as poses a big challenge to a retailer to earn customer loyalty and patronage (Dahana et al., 2022; Kautish et al., 2022). We thus revealed the importance of managing retailer equity and its contribution to fostering consumer patronage. As the cost of maintaining (retaining), a consumer is much lower than that of attaining a new consumer (Pan and Zinkhan, 2006) this tactic must generate imperative strategic benefits, contributing to firm/brand performance.

This study also provides a research framework of understanding retail patronage behavior through the lens of CBRE. Understanding and measuring retailer equity dimensions may help industry practitioners and marketers in manipulating CBRE dimensions in their retail strategy with the aim of building and maintaining consumer patronage toward their retail shopping centers (Badrinarayanan and Becerra, 2019). Furthermore, this study can facilitate retail/brand managers in categorizing customers on the basis of their shopping purposes and situations. It is revealed that shoppers in the metropolitan city of Pakistan showed different shopping behavior suggesting the managerial implication of devising separate retail mix strategies for shoppers belonging to different regions, cities or contexts. Understanding differences in shopping orientations like self-shopping and gift shopping involve specialty retail shopping center’s strategies aimed at enhancing the shopping experience of their customers in pursuit of retail patronage behavior and increased revenue (Anaza, 2014; Benoit et al., 2019). Categorizing shoppers on the basis of shopping situations and consumers’ involvement might help retail/brand managers in deciding on advertising and other promotional strategies toward well-defined market segments, which will further result in maintaining sustainable retailer equity in an emerging/developing country like Pakistan.

6.3 Limitations and future research

In the past, the majority scholars’ focus remained on measuring retail patronage behavior and shopping center preference based on shopping center visit frequency. Future studies may focus on studying customer’s recommendations to the shopping center to their friends or colleagues as a measure of retail patronage behavior. Second, the current study is restricted to one category of retail brand, upscale lifestyle specialty shopping centers. It focuses on two main Pakistani cities, Lahore and Multan. Thus, further research is expected to conduct in different marketers, cultures and contexts including tourism, hospitality, etc.

Third, the results of the study can be improved by using other methods/techniques, including mixed methods, qualitative or experimental approaches. Given the nature of products being sold in different retails, the retailer equity inferences can be different. Hence, future research can replicate the current study in other retail formats (Kautish and Sharma, 2019). Fourth, the current study underpins data collection through a mall intercept survey. However, it can also be done through methods including online for future studies. Fifth, future works may incorporate more situational/contextual variables, including firm/brand corporate-social-performance and competition intensity in the proposed model (Bozkurt et al., 2023). Finally, future research can test CBRE by including different factors like brand love, social influences and self-esteem, brand engagement (Islam et al., 2020; Khan et al., 2022), trust, brand satisfaction or experience (Mansouri et al., 2022; Satar et al., 2023), to ascertain the additional insights.

Figures

Figure 1.

Conceptual framework

Table 1.

Respondent’s demographic statistics

Variable	Cases (%)
Gender
Male	139 (41)
Female	199 (59)
Age (years)
<20	24 (7)
20–30	202 (60)
31–40	81(24)
41–50	27 (8)
>50	4(1)
Marital status
Married	129 (38)
Unmarried	209 (62)
City
Lahore	155 (46)
Multan	183 (54)
Family status
Separate	112 (33)
Joint	226 (67)
Shopping with
Individual	88 (26)
Friends	58 (17)
Family	192 (57)
Shopping preference
Regular	54 (16)
Sales	85 (25)
Both	199 (59)
Recommendation
Yes	297 (88)
No	41(12)

Table 2.

Correlations, descriptive statistics, reliability and scale validity

Demographic	Mean	SD	α	CR	AVE	1	2	3	4
Sample size (N = 338)
Consumer-based retailer equity (CBRE)	5.61	0.94	0.923	0.924	0.616	(0.78)
Shopping situations (SS)	5.73	1.07	0.884	0.921	0.708	0.47**	(0.86)
Consumer’s shopping involvement (CSI)	5.54	1.06	0.737	0.755	0.634	0.48**	0.45**	(0.75)
Retail patronage behavior (RPB)	5.81	0.61	0.718	0.713	0.567	0.24**	0.26**	0.39**	(0.81)

Notes:

Cronbach’s alpha (α), composite reliability (CR), average variance extracted (AVE); *p < 0.05; **p < 0.01 (two tailed); square roots of average variance extracted (AVE) are described in parentheses alongside the diagonals

Table 3.

Results of regression analysis

Model	DV	IV	F-value	β values	t-value	p-value
1	Frequency		29.566
Multiple R	0.493	CBRE_CO		0.377	7.198	0
R2	0.243	CBRE_NL		0.368	6.344	0
Adjusted R2	0.235	CBRE_Id		0.125	2.149	0.032
2	Frequency		23.852
Multiple R	0.551	CBRE_CO		0.369	7.279	0*
R2	0.303*	CBRE_NL		0.378	6.724	0*
Adjusted R2	0.291	CBRE_Id		0.093	1.653	0.099
		CSI		0.133	2.573	0.011
		SS		0.217	4.285	0
3	Preference		24.727
Multiple R	0.460	CBRE_CO		0.228	4.256	0
R2	0.212	CBRE_NL		0.086	1.452	0.148
Adjusted R2	0.203	CBRE_Id		0.354	5.962	0
4	Preference		15.208
Multiple R	0.466	CBRE_CO		0.225	0.4174	0
R2	0.217	CBRE_NL		0.089	1.500	0.135
Adjusted R2	0.203	CBRE_Id		0.364	6.071	0
		CSI		0.046	0.846	0.398
		SS		0.061	1.137	0.257

Notes:

Consumer based retailer equity (CBRE), Consumer’s shopping involvement (CSI), Shopping situation (SS), Chen-One shopping center 1 (CO), shopping center Nishat Linen 2 (NL), shopping center Ideas 3 (ID)

Table 4.

Results of interaction analysis

Interaction effects	Estimate std.	Error	t value	p (>|t|)
CBRE_CO: CSI	4.63728	4.45596	1.041	0.2990
CBRE_ID: CSI	4.75203	5.81640	0.817	0.4147
CBRE_NL: CSI	5.94913	5.72807	1.039	0.2999
CBRE_CO: SS	11.07481	6.35934	1.742	0.0827
CBRE_ID: SS	10.66465	7.92583	1.346	0.0796
CBRE_NL: SS	15.59666	8.41018	1.854	0.0648

Notes:

Multiple R-squared: 0.3304, Adjusted R-squared: 0.253, F-statistic: 4.266 on 31 and 268 DF, p-value: < 2.8e-11; Consumer based retailer equity (CBRE), Consumer’s shopping involvement (CSI), Shopping situation (SS), Chen-One1 (CO), Nishat Linen 2 (NL), Ideas 3 (ID)