Enhancing store brand equity through relationship quality in the retailing industry: evidence from Vietnam

Abstract

Understanding the factors that contribute to store brand equity in the Vietnamese retailing industry is important. This study expands the “stimuli” components in the stimuli–organism-response (S-O-R) framework by considering the role of store information transparency and examining its contribution to store brand equity as an indirect “response” through relationship quality (trust, commitment, and satisfaction) and as the “organism” in the Vietnamese retailing setting. Quantitative research was conducted with a sample of 465 retail customers collected by the Ho Chi Minh City Statistical Office, Vietnam. Structural equation modeling was used to test the research hypotheses, and the results confirmed access convenience, store information transparency, and preferential treatment as the stimuli while relationship quality was the organism and store brand equity was the response. In a developing country such as Vietnam, store information transparency is important. Specifically, the dedication-constraint mechanisms based on social exchange theory together with the cultural norms of Vietnam’s Confucian culture create a locked-in effect for the customer in the relationship with a retailer and resulted in high store brand equity. These findings offer insight into brand management literature and provide theoretical and managerial implications to increase the value of store brand equity in the Vietnamese retail industry.

Keywords:

• relationship quality
• store brand equity
• access convenience
• preferential treatment
• store information transparency
• S-O-R framework

PUBLIC INTEREST STATEMENT

This study provides insights into the understanding of which factors contribute to store brand equity in the Vietnamese retailing setting. Based on data obtained from interviews with 465 retail customers, the results confirmed access convenience, store information transparency, and preferential treatment as the stimuli while relationship quality was the organism and store brand equity was the response in the Stimuli-Organism-Response (S-O-R) framework.

This study highlights the role of store information transparency as well as relationship quality in enhancing store brand equity in the Vietnamese retail industry. Retail managers should focus on the role of access convenience, store information transparency in establishing a good relationship bond with their customers. When customers willing to develop an ongoing relationship with a retailer or a brand, resulting in positive store brand equity.

1. Introduction

The retail industry is facing intense competition in the marketplace, resulting in lower margins than those in other sectors (Troiville et al., 2019). Therefore, retailers recognized that they should invest more effort in brand building (Feuer, 2005). Building a strong brand remains a topical issue for both academics and practitioners (Tho et al., 2016). A brand is the most valuable asset for a company and a basis of consumers’ trust and confidence that serves as the basis of consumers’ decision-making process (Sasmita & Suki, 2015). Brand equity has been defined as “a set of brand assets and liabilities linked to a brand, its name and symbol, that add to or subtract from the value provided by a product or service to a firm and/or to that firm’s customers” (Aaker & Equity, 1991, p. 15). Brand equity adds value to the firm, leads to customer loyalty, creates a company’s competitive advantage, and higher negotiating power and margins (Majeed et al., 2021). In the retail industry, store brand equity is defined as “the incremental utility or value added to a retailer by its brand name” and (Jinfeng & Zhilong, 2009) stresses the importance of building a strong brand (Gil-Saura et al., 2013). Store brand equity is critical to store competitiveness (Gil-Saura et al., 2017). Building store-linked brand equity is important (Jinfeng & Zhilong, 2009) because it can increase the utility of a store and value (Gil-Saura et al., 2017). Brand equity in retail literature is an emerging concept that requires further exploration (Khaled et al., 2021). Analysis of brand equity with regard to the retailing sector is still limited (Gil-Saura et al., 2020) despite being a critical research area (Grewal & Levy, 2009). In addition, the nature of the variables that contribute to the formation of store brand equity require further investigation (Gil-Saura et al., 2016).

In recent years, Vietnam’s retail industry has experienced outstanding and impressive growth compared to other sectors in the economy. The Vietnamese retail sector was valued at US$172 billion in 2020, and total retail reached an estimated US$219.53 billion. The retail sales growth rate of Ho Chi Minh City in 2020 was 12% year-on-year and amounted to US$33 billion. In comparison to the 2020 figure, the total retail revenue growth in 2021 is expected to increase by three to four percent (Ngoc, 2021). According to a recent statistic, Ho Chi Minh City has total 110 traditional markets, 106 supermarkets, 2,469 mini supermarkets, and 28,700 convenience stores (Thi & Tat, 2021). With a population of more than 98.5 million people, Vietnam is ideal for brand-related research. In practice, most Vietnamese firms and retailers have not recognized the importance of brands and branding (Nguyen et al., 2011). Furthermore, Vietnamese customers’ shopping habits are changing; they now focus on a brand’s name and spend a lot of time researching brand information. They are becoming more sophisticated and engage in lengthy contemplation before making a purchase decision (Tho et al., 2016).

Previous research has shown three major antecedents of store brand equity: store reputation, store image dimensions (i.e., ambience and entertainment, staff, merchandise, ease of shopping, store status, other services, advertisement and promotion, and price as per Balaji & Maheswari, 2021ʹs study), and store prices (Calvo-Porral et al., 2013). However, the role of information transparency and the mechanism of how this variable contributes to the store’s brand equity has received little attention. In addition, customers in developing economies such as Vietnam usually face common service problems such as deceptive advertising, inadequate handling of complaints, lack of product quality, high price, and lack of adequate maintenance services (Lysonski et al., 2003). Due to information asymmetry in such markets, customers tend to be hesitant during purchasing (Baek & King, 2011). In uncertain and risky situations, customers use branding as a signal to support their decision-making process (Baalbaki & Guzmán, 2016). In a study of the banking industry, Loureiro and Sarmento (2018) employed the stimuli–organism-response (S-O-R) framework to examine brand equity as the “response” and to the best of our knowledge, limited studies have considered brand equity as the response in the retail setting. In addition, the dedication-constraint mechanisms based on social exchange theory (SET; Blau, 1964), together with the S-O-R framework, will better explain why customers in Vietnam’s Confucian culture locked in the relationship with a retailer and resulted in high store brand equity. Thus, the research has two main objectives:

First, the authors expand the “Stimuli” components in the S-O-R framework by considering the role of store information transparency and examine its contribution to store brand equity indirectly through relationship quality in the Vietnamese retailing setting.

Second, we apply the S-O-R framework to investigate the mediating role of relationship quality (trust, commitment, and satisfaction) as the “organism” in forming store brand equity which has been specified as the “response” in the Vietnam retail industry.

Developing a store brand equity is a top priority in the retailing industry, as the competition is high and consumer preferences constantly change. This study contributes to the literature by examining the relationships amongst relationship marketing tactics (access convenience, store information transparency, and preferential treatment), relationship quality (trust, commitment, and satisfaction), and store brand equity under the S-O-R framework, in context of retailing in Vietnam, an emerging market. The result will give a holistic picture of brand development in the Vietnamese market, and assist managers in choosing the right relationship marketing strategies for their business.

This study also clarifies how relationship quality can foster store brand equity, establishing a strong link between retailers and customers in the context of Vietnam’s Confucian culture, which may support managers in designing marketing actions and practices for maintaining a good relationship with their customers.

The remainder of this paper is organized into three major parts. The first presents the literature review around the S–O–R framework and store brand equity. The second part is devoted to the research methods including measurement scales, questionnaire design, and data collection. The last section describes the results and presents the conclusions and implications.

2. Literature foundation

2.1. The S-O-R framework

The S-O-R framework was developed by Mehrabian and Russell (1974). They argued that the shopping environment contains stimuli (S) that affects organisms (consumers; O) and results in a behavioral response (R). The “stimuli” in the S-O-R framework are considered as environmental factors that exert an influence on the cognitive and affective reactions of an individual (Eroglu et al., 2003). The “organisms” are defined as the “internal processes and structures intervening between stimuli external to the person and the final actions, reactions, or responses emitted” (Bagozzi, 1986, p. 46). Finally, the “response” represents consumers’ final decisions, which can be categorized as the approach or avoidance behaviors (Yu et al., 2021).

The S-O-R framework has been used widely in the retail context (Cattapan et al., 2022). In this framework, the stimuli emitted by a retail store serves as a set of “external” attributes that affect consumer’s perception (Thang & Tan, 2003) and consciously or subconsciously incite him/her into action (Loureiro & Sarmento, 2018). Following the previous study, this study introduces three relationship marketing tactics namely, access convenience, preferential treatment, and store information transparency as the stimuli.

The “organisms” include the “perceptual, physiological, feeling, and thinking activities” (Bagozzi, 1986, p. 46). Herein, relationship quality has three distinct components namely, trust, commitment, and satisfaction as the “organism (O)” (Cattapan et al., 2022; Izogo et al., 2017; M. Zhang et al., 2018) that reflects customers’ perceptions of their relationship with a particular retailer (De Wulf et al., 2001).

Finally, the response in S-O-R framework refers to customers’ final reactions, such as psychological reactions, in the form of attitudes and/or behavioral reactions (Koo & Ju, 2010). Brand equity usually manifests in the form of a customer’s future intentions (Marquardt, 2013). We follow Loureiro and Sarmento (2018) and propose store brand equity as the “response (R)” in the S-O-R framework.

3. Research hypothesis

3.1. Stimuli and organism

As per social exchange theory (SET) it classifies the relationship marketing tactics into three types of benefits: concrete, symbolic, and compound (Huang, 2015). Thus, store information transparency provides customers with concrete and confident benefits (Gwinner et al., 1998), access convenience provides customers with concrete benefits, and preferential treatment provides customers with both concrete and symbolic benefits (Cropanzano & Mitchell, 2005).

In the context of this research, relationship quality is a disaggregated construct because it has better explanatory power than global measure (Izogo, 2016). Following the norm of reciprocity of SET (Cropanzano & Mitchell, 2005), we posit that customers will repay retailers’ marketing efforts by holding a favorable attitude toward the retailer (Huang, 2015), such as trust, commitment, and satisfaction.

3.1.1. Access convenience and relationship quality

In this study, access convenience is defined as the “consumers’ perceived time and effort expenditures to initiate service delivery” (Berry et al., 2002, p. 7). Access convenience is determined by the physical location, parking availability, and operating hours (Jones et al., 2003) and the availability of services in different channels such as online, by phone, or in person (Seiders et al., 2007).

Whenever customers initiate a transaction with a retailer, they will invest their own resources, such as money (Marmorstein et al., 1992), time, and effort (Feldman & Hornik, 1981) according to customer resource allocation theory (Batsell, 1980). In addition, they exchange their cognitive, emotional, social, economic, and physical resources with a retailer (Blau, 1964). The formation of a relationship is based on subjective cost–benefit analyses and the comparison of alternatives (Homans, 1974). Thus, customers will calculate the benefits they receive from retailers and the costs they incur when engaging in relationships according to SET (Thibaut & Kelley, 1959). Due to modern life pressure, customers nowadays experience the pressure of stress and a shortage of time and energy (Roy et al., 2018). Retailers develop marketing tactics to minimize customer effort with easily accessible stores (Troiville et al., 2019). The time-saving aspect of convenience principally motivates customers to strengthen their relationship with a retailer (Seiders et al., 2007). Following the norm of reciprocity of SET (Cropanzano & Mitchell, 2005), customers tend to reciprocate positively toward a retailer who provides them benefits such as service convenience (Roy et al., 2018). The accessibility of service providers strongly influences customer satisfaction (Dai & Salam, 2014; Kaura et al., 2015; Seiders et al., 2007). Based on the above arguments, we propose the following hypotheses:

H1a: Access convenience has a positive impact on trust.

H1b: Access convenience has a positive impact on commitment.

H1c: Access convenience has a positive impact on satisfaction.

3.1.2. Store information transparency and relationship quality

Store information transparency is a marketing tactic that aims to improve customer experience with a retailer (Liu et al., 2015) and provide customers with accurate and honest information about a retailer offering such as products, services, promotions, and prices. The sharing of information is active and intentional, and all information is accessible and objective (Merlo et al., 2018).

In developing markets, the purpose of transparency is to reduce information asymmetry and moral hazard, thus preventing businesses from forming opportunistic behaviors (Bessire, 2005). A retailer uses a signal to communicate intangible characteristics or benefits to its customer credibly (Baek et al., 2010). The willingness of a retailer to share objective information about its offerings or make all relating information accessible signals to the customers that the retailer has nothing to hide (Hennig-Thurau et al., 2010). Information transparency can simplify a customer’s decision-making process (Merlo et al., 2018), leads to favorable customer outcomes (Liu et al., 2015), and fosters the customer–retailer relationship (Waddock, 2004). Store information transparency signals a retailer’s goodwill, providing customers with benefits and reducing their anxiety and risk perception (Gwinner et al., 1998; Liu et al., 2015). Thus, such efforts from a retailer may be rewarded with greater customer trust (Medina & Rufín, 2015), and satisfaction (Kang & Hustvedt, 2014; Spena et al., 2012). In addition, in cultures rooted in Confucianism, such as Vietnam (Le & Ho, 2020), customers tend to support the retailers that follow traditional Confucianism’s ideal ethical standards (Cheung & Yeo-chi King, 2004). Based on the above argument, we propose these hypotheses:

H2a: Store information transparency has a positive impact on trust.

H2b: Store information transparency has a positive impact on commitment.

H2c: Store information transparency has a positive impact on satisfaction.

3.1.3. Preferential treatment and relationship quality

Preferential treatment refers to a customer’s perception regarding retailers’ treatment of, and service to, their regular customers being better than their nonregular customers (De Wulf et al., 2001). In applying preferential treatment tactics, retailers provided customers with compound benefits such as gift certificates, discounts, and increasing a customer’s perception of personal recognition (Cropanzano & Mitchell, 2005).

Preferential treatment implies that regular customer of a retail store will receive a higher service level compared to nonregular customers (Huang, 2015). The benefits of preferential treatment such as economic and customization benefits (Gwinner et al., 1998) help a retailer to create a strong psychological bond with its customer (De Wulf et al., 2001) and results in customer trust, satisfaction, and commitment (Gwinner et al., 1998). The benefits a retailer offers to its regular customers implies that the relationship is worth maintaining, thus strengthening customer commitment (Morgan & Hunt, 1994). Preferential treatment has a positive relationship with trust, commitment (S. Chou & Chen, 2018; Lacey et al., 2007; Ma et al., 2018), and customer satisfaction (Yen & Gwinner, 2003). Hence, we propose the following hypotheses:

H3a: Preferential treatment has a positive impact on trust.

H3b: Preferential treatment has a positive impact on commitment.

H3c: Preferential treatment has a positive impact on satisfaction.

3.2. Organism and response

In a retail setting, store equity is defined as “the differential effect of store knowledge on customer response to the marketing of the store” (Hartman & Spiro, 2005, p. 1114). Store brand equity refers to the associations in the consumers’ minds, preference, and the pride of being a customer of a particular retail store, as well as the continued patronage of the store (Loureiro & Sarmento, 2018). Brand equity evaluations are likely to be based heavily on the strength of the ongoing relationship with a service provider (Lovelock et al., 2007).

3.2.1. Trust and store brand equity

Trust refers to the customers’ beliefs regarding a retailer, including their benevolence, competence, and integrity (Doney & Cannon, 1997). Benevolence reflects a customer’s belief that a retailer is not opportunistic. Competence refers to a retailer’s ability to keep their promises and fulfill customer needs and expectations (De Wulf & Odekerken-Schröder, 2003). Integrity refers to a retailer’s honesty and willingness to take full responsibility for their actions (S. W. Chou & Hsu, 2016).

The dedication-constraint mechanisms based on SET (Blau, 1964) provided two distinct mechanisms that affect customers’ perception and response (Chou & Hsu, 2106). The constraint mechanisms such as trust and calculative commitment serve as barriers based on customers’ investment in the relationship that results in them being “locked-in” a relationship (Chou & Hsu, 2106). The phrase “locked-in” a relationship refers to a situation in which a customer feels secure and bound to the relationship with a retailer (Harrison et al., 2012). Relationship quality constructs such as satisfaction, trust, and commitment positively impact brand equity (Marquardt, 2013; Morgan & Hunt, 1994). Customer trust is a significant determinant of brand equity (Gil-Saura et al., 2013; Jevons & Gabbott, 2000). Significant positive relationships were found between trust and satisfaction on brand equity (Wang et al., 2009). Thus, based on the above arguments the authors proposed these hypotheses:

H4a: Trust has a positive impact on store brand equity.

3.2.2. Commitment and store brand equity

Commitment refers to “a consumer’s enduring desire to continue a relationship with a retailer accompanied by this consumer’s willingness to make efforts at maintaining it” (De Wulf et al., 2001, p. 37). Commitment can be categorized into three distinct dimensions: affective, calculative, and normative (Bansal et al., 2004). Calculative commitment derives from a cognitive assessment of the gains and losses that would be generated were the relationship to be terminated (Geyskens et al., 1996). Normative commitment refers to a relationship norm or a sense of obligation ((Bansal et al., 2004; Geyskens et al., 1996).

According to SET, people are highly goal oriented, and they are goal maximizers in relationships (Jeong & Oh, 2017). Calculative commitment reflects the aspect of rational assessment of benefits and results in a lack of choice and high switching costs (Ryu & Park, 2020). When a customer recognized that they receive more benefits from the relationship, it reduces the feeling of being locked into the relationship as a hostage (Verhoef et al., 2002). Normative commitment refers to partners staying in a relationship because they feel they ought to due to social or cultural reasons (Geyskens et al., 1996). In Confucian culture, righteousness (Yi) implies getting along with others, being reasonable in all dealings, showing reciprocity, and emphasizing mutual profitableness (Hsu, 2007) and an emphasis on the balancing benefits (Sun et al., 2016). Empirical evidence suggests a positive association between commitment and brand equity (Dwivedi & Johnson, 2013; Rego et al., 2009; Sierra et al., 2017). Hence, the authors proposed these hypotheses:

H4b: Commitment has a positive impact on store brand equity.

3.2.3. Satisfaction and store brand equity

Satisfaction refers to a customer’s cognitive or affective reaction to a single or prolonged set of service encounters with a retailer (Hu et al., 2009). Satisfaction occurs when customers perceive that their service encounter with a retailer has met or exceeded their expectations (Srivastava & Sharma, 2013).

The dedication mechanism based on SET refers to customer satisfaction with a retailer and them staying in a relationship with a retailer based on the benefits garnered and positive shopping experiences (Bendapudi & Berry, 1997). The level of satisfaction and motivation to remain in a relationship with a retailer is based on the theory of comparison levels. This theory posits that customers consider comparison levels as reference points to evaluate the “attractiveness” of the relationship or how satisfactory it is (Thibaut & Kelley, 1959). In the exchange relationship with a retailer, customers also invest their own resources, which are considered a cost. SET suggests that customers will only remain in the relationship when the continuum of satisfactory rewards exceed a minimum comparison level (Homans, 1958), and they are willing to develop an ongoing relationship with a brand when their expectations are met (Dwivedi, 2014). Brand equity derives from the fulfillment of consumer expectations (Jones, 2005), and customer satisfaction has a positive effect on brand equity (Iglesias et al., 2019; Rambocas et al., 2014; Torres & Tribó, 2011). Hence, we propose the following hypotheses:

H4c: Satisfaction has a positive impact on store brand equity.

Figure 1 illustrates the proposed model of this study.

Figure 1. The proposed model.

4. Methodology

4.1. Measurement

The authors carefully selected measurement scales that were previously adapted to retailing setting.

Preferential treatment (3 items) was measured with scales adopted from Huang (2015). Access convenience (4 items) was adapted from Moeller et al. (2009), and the scale was employed in retail setting. Store information transparency (07 items) was adapted from Liu et al.’s (2015) research. Trust (7 items) was borrowed from Y. Zhang et al. (2011). Commitment (6 items, including normative and calculative commitment) was adapted from (Roy et al., 2020), and the scale has been employed in retail setting. Satisfaction (5 items) was adapted from Gremler and Gwinner’s (2000) study.

Store brand equity scale, as a unidimensional construct, involves four items, as adopted from Hartman and Spiro (2005) and Yoo et al.’s (2000) study. In addition, this scale was applied in a retailing setting in Khaled et al.’s (2021) study.

All items of the above scale were measured using a five-point Likert-type range from (1) strongly disagree to (5) strongly agree. The five-point Likert scale is also employed in consumer research in Vietnam context (Tho et al., 2016).

4.2. Measurement scale modification

The authors borrowed measures of research constructs in the hypothesized model from previous well-established scales in Western economies. The authors employed the back-translation technique (Brislin, 1970); we translated all scale items into Vietnamese using a professional translator to ensure language equivalence and clarity. The authors also made slight modifications to scale items to better fit the Vietnamese retailing context (Abdul-Latif & Abdul-Talib, 2017). This was done through conducting two qualitative focus group discussions—a method that enables participants to be open about their thoughts and views, and the researchers could obtain data from cohesive and natural discussions (Malhotra & Dash, 2010). A focus group discussion should ideally comprise 6 to 10 participants (C. R. Cooper & Schindler, 2008). All scheduled focus groups discussions were virtually conducted on Zoom in April 2021 in a relaxed and comfortable atmosphere. The first group discussion was conducted with five marketing professors and three retailer managers. The first group discussion sought to assess the face and content validity of all scale items and to recommend any complimentary scale items (if necessary; MacKenzie et al., 2011). The second focus group discussion was conducted to design a survey questionnaire (Krueger, 1998). This group discussion included 10 consumers above 18 years old, all frequent shoppers at retail stores in Ho Chi Minh City. All scale items from the first group discussion were screened for wording clarity, wording redundancy, and response format (DeVellis, 2003).

From the first group discussion result, two more items were added to the preferential treatment scale to better capture the high-power distance dimensions of Vietnam as a Confucian culture (Eng & Jin Kim, 2006). Thus, preferential treatment was recommended to reflect relevance with customer status such as “X usually places me higher on the priority list when dealing with other customers” and “The employees at X treat me better than other customers.”

From the result of the second discussion, the researchers identified 38 items that could be used to measure the research concepts. Table A in Appendix 1 presents all the measurement scales of this study.

4.3. Development of survey instrument

The main research objective is hypotheses testing, examining the statistical impact of several independent variables on the dependent variables, and generalizing research results about the population. Thus, a quantitative survey approach is appropriate (Indiani et al., 2021). Survey research aims to understand and capture the target population’s attitudes, perceptions, and opinions regarding store brand equity which is the study’s primary research interest (Chrysochou, ((2017).

Quantitative data for this study is collected by a survey using a questionnaire as the instrument. The first version of the draft questionnaire was pretested with a convenience sample of approximately 20 customers to identify any respondent difficulties (Malhotra, 2010) and avoid problems with ambiguous or complex items (Podsakoff et al., 2003). The questionnaire was then used to conduct pilot testing with 30 participants, as recommended by (Schriesheim et al., 1993). The reliability of all constructs was tested using Cronbach’s alpha coefficient and were found to be acceptable (i.e., > 0.7 as recommended by Hair et al., 2010).

4.4. Sampling and data collection process

Brand equity may vary depending on product type or the level of customer product involvement (Quester & Lim, 2003), thus we considered some common forms of retailers in the Vietnamese market (i.e., convenience store, retail store, and supermarket) to have a better representative sample. These retailers sell different kinds of goods from food to electronic, textile, and footwear and require different levels of interaction (low touch vs. high touch following the typology of Berry & Barnes, 1987). Ho Chi Minh City is an ideal place for data collection because it is the biggest commercial center in Vietnam, and the city concentrates 73% of the total convenience stores under different brand such as GS25, Family Mart, 7 Eleven. Further, 28% of supermarkets, such as Co.opmart, AEON, and LOTTE Mart, and retail stores chain such as VinMart and Bach Hoa Xanh, with thousands stores are located in the 19 district of Ho Chi Minh city (Mai, 2021).

This study used the purposive sampling technique, which is frequently used in consumer studies in the retail industry (D. Cooper & Schindler, 2014). This approach ensures that the sample is aligned with the research purpose (Bernard, 2002). First, the gender ratio (48.60% of male and 51.40% of female) was set according to the result of Vietnam’s 2019 population and housing census figure (General Statistics Office of Vietnam, 2019). Second, according to recent statistics, the average monthly earnings of wage workers in the first quarter of 2021 were from 6.2 million to 11 million Vietnamese Dong (equal to US$270–480) (Report on labor force survey Quarter 1, 2020). Thus, these characteristics ensure that the sample in the study can capture an accurate and comprehensive picture of the consumer in the retail sector of Ho Chi Minh City.

The authors employed the mall-intercept survey technique (Bush & Hair, 1985) to collect quantitative data for the study. By adopting this approach, interviewers selected participants at the entrances of convenience stores, retail stores, and supermarkets in Ho Chi Minh City’s 19 districts. The Ho Chi Minh City Statistical Office trained the interviewers and supervised the data collection process. The interviewers only distributed the questionnaire to participants over 18 years. Each participant took about 20 min to complete the questionnaire. To increase the number of responses, the interviews gave out a small incentive, such as a pen or a mobile card, valued at US$0.5. Due to the issues of common method bias (CMB) via self-reported questionnaires and the data collected from a single source (customers), the authors employed several techniques to reduce method bias. First, the interviewers explained the survey’s purpose to the participants and informed them that the participants would remain anonymous. Second, the interviewers informed the participants that the study only focused on their opinions, and there were no right or wrong answers (Podsakoff et al., 2003), thus reducing the socially desirable responses tendency (Podsakoff & Organ, 1986). Third, the questionnaire was designed with a mix of independent and dependent variables, and it suggested no link between them (Podsakoff et al., 2003). The questionnaire also has a screening question to confirm whether the customers had visited a retail store at least twice a week.

The population in this study is customers of convenience stores, supermarkets, and retail stores in Ho Chi Minh City with a purchase-frequency at least twice a week.

The minimum sample size was calculated according to the 10:1 ratio (observation-to-items ratio) as suggested by Hair et al. (2010). This study uses of 38 items; therefore, ten times the number of items are 380 observations or samples. Thus, a total of 650 questionnaires were distributed, and after the data screening step, 456 valid responses (response rate 71.54%) were used for further analysis. A sample size of 456 fits the 10:1 ratio (Hair et al., 2010).

4.5. Data analysis techniques

The author used a two-step approach based of Anderson and Gerbing (1 recommendations 988). Firstly, explanatory factor analysis (EFA) was carried out with SPSS ver 24.0 to examine and determine the factor structure of scales.

Secondly, the Structural Equation Model (SEM) with AMOS 21.0 is employed to test the research hypotheses. SEM can be described as an analysis that combines factor analysis, structural model, and path analysis methods (Jihadi et al., 2021). This study employed CB-SEM, as this approach is appropriate for this research: theory testing and confirmation (Dash & Paul, 2021). CFA analysis is also performed to test the validity and reliability of the scale (Anderson & Gerbing, 1988).

5. Results

5.1. Demographic profiling of respondents

As shown in Table 1, more than half of the sample was female (51.40%). Adults between 18 and 49 years of age represented the highest distribution—almost 77.85% of the total sample as per the age ratio in The Vietnam Consumer Survey (Deloitte, 2020). Further, 52.47% of the respondents earn between 270 to 480 USD/month—approximately the average monthly earnings of wage workers. The majority of the respondents were in full-time employment (51.18%) and married (54.84%). In terms of shopping place, 37.85% of the participants were frequent customers of retail store chains in Ho Chi Minh city.

Table 1. Demographic profile of respondents

Items	Frequency	%
Gender
Male	226	48.60
Female	239	51.40
Age
From 18 to 29 years	125	26.88
From 30 to 39 years	128	27.53
From 40 to 49 years	109	23.44
Over 50 years	103	22.15
Income
Under 270 USD/month	91	19.57
From 270 to 480 USD/month	153	32.90
From 480 to 690 USD/month miliion	124	26.67
Over 690 USD/month	97	20.86
Professional Status
Students	47	10.11
Full-time employed	238	51.18
Part-time employed	103	22.15
Others	77	16.56
Education
Diploma	100	21.50
Intermediate	105	22.58
Bachelor or College	140	30.11
Master or above	120	25.81
Marital status
Single	210	45.16
Married	255	54.84
Shopping place
Convenience store	156	33.55
Super market	133	28.60
Retail store chain	176	37.85

5.2. Exploratory factor analysis (EFA)

The authors performed principal axis factoring (PAF) with the oblique rotation (Promax) technique, as per (Sun & Liang’s, 2020) study to identify the factor structure of the scales in the study using SPSS 24.

The Kaiser–Meyer–Olkin (KMO) test was performed, and KMO was valued at 0.948 > 0.6, as recommended by Hair et al. (2010). The Bartlett’s sphericity test (BTS) resulted in a significance of p < 0.01 (p = 0.000). Thus, the sample collected is sufficient and satisfactory for further analysis (Hair et al., 2010). The EFA resulted in a seven-factor solution with an eigenvalue >1.0 (Tabachnick & Fidell, 2007) and extracted 55.96% > 50%, as recommended by Hair et al. (2010). Further, all items were loaded into the intended constructs and all factor loadings were above 0.5 (Hair et al., 2010), as presented in Table 2.

Table 2. Reliability and convergence validity

Variable	Items	Factor loading	Cronbach alpha	Standardize factor loading	CR	AVE
Preferential treatment	PT1	0.743	0.880	0.754	0.880	0.595
	PT2	0.736		0.758
	PT3	0.776		0.788
	PT4	0.784		0.770
	PT5	0.770		0.786
Access convenience	AC1	0.756	0.829	0.813	0.831	0.533
	AC2	0.728		0.798
	AC3	0.627		0.649
	AC4	0.639		0.713
Store information transparency	RT4	0.778	0.822	0.754	0.823	0.538
	RT5	0.742		0.746
	RT6	0.720		0.737
	RT7	0.600		0.694
Trust	TRU1	0.632	0.888	0.745	0.888	0.533
	TRU2	0.674		0.726
	TRU3	0.749		0.748
	TRU4	0.824		0.760
	TRU5	0.806		0.732
	TRU6	0.532		0.676
	TRU7	0.582		0.718
Commitment	COM1	0.614	0.877	0.718	0.878	0.546
	COM2	0.773		0.790
	COM3	0.742		0.757
	COM4	0.740		0.730
	COM5	0.607		0.717
	COM6	0.585		0.718
Satisfaction	SAT1	0.595	0.869	0.730	0.870	0.574
	SAT2	0.690		0.778
	SAT3	0.777		0.752
	SAT4	0.769		0.786
	SAT5	0.528		0.739
Store brand equity	SBE1	0.572	0.820	0.770	0.822	0.606
	SBE2	0.826		0.791
	SBE3	0.628		0.774

5.3. Common method bias

The author employed Podsakoff et al.’s (2003) “single common method factor” to diagnose the potential of CMB. The total variance for a single factor result was 38.27%—less than 50% (Podsakoff et al., 2003). The results of the model with this single factor showed a significantly poor fit compared to the original model (χ2 = 3481.238; df = 629; χ2/df = 5.535 p < .000; TLI = 0.677; CFI = 0.694; RMSEA = 0.099). Therefore, CMB was unlikely to be a problem in this study.

5.4. Measurement model assessment

The skewness values (−0.601 to +0.077) and kurtosis values (−0.543 to 0.370) of all scale items were in an appropriate range (±2.58; Tabachnick & Fidell, 2007); thus, the authors concluded that they were normally distributed. Accordingly, applying maximum likelihood estimation is suitable.

The authors apply the two-step structural equation modelling (SEM) procedure followed Anderson and Gerbing (1988) to examined survey data. First, confirmatory factor analysis (CFA) was conducted with AMOS 24 to access all constructs in this study. The measurement model is satisfactory because goodness-of-fit indices, such as χ2 = 1002.093, df = 506, χ2/df = 1.980, p < .000, CFI = 0.942, TLI = 0.936, GFI = 0.887, and RMSEA = 0.046 fit the criteria such as χ2/df < 3; TLI > .90; CFI > .90; GFI > .80; RMSEA < .08 (Wu et al., 2017)

5.5. Construct reliability

Cronbach’s alpha for all the variables were above the threshold value of 0.7 (Hair et al., 2010). In addition, the composite reliability (CR) value ranged from 0.822 to 0.906, which exceeded the recommended value of 0.70 (Fornell & Larcker, 1981; Hair et al., 2010), thus confirming satisfactory reliability of scales.

5.6. Convergence and discriminant validity

The authors accessed the convergent validity of all scales by assessing the standardized factor loadings (Hair et al., 2010). The result in Table 2 showed that all standardized factor loadings were significant and greater than 0.5 (Hair et al., 2010). After the screening process, three items with factor loading of less than 0.5 were removed (trans1, trans2, and trans3). In addition, the values of AVE were in the range of 0.533–0.763, and all exceeded the cut-off level of 0.50; and the CR value of all the constructs exceeds 0.70 (Hair et al., 2010). Thus, all scales achieved convergent validity.

The discriminant validity of the scales was assessed by the heterotrait–monotrait ratio of correlations (HTMT) because it is considered a superior criterion to the Fornell–Larcker criterion (Henseler et al., 2015). The discriminant validity of all constructs was established as presented in Table 3 because all HTMT ratios were lower than 0.85 (Henseler et al., 2015).

Table 3. Discriminant validity

Construct	1	2	3	4	5	6	7
1.TRU
2.PT	0.448
3.COM	0.751	0.465
4.AC	0.642	0.339	0.663
5.SAT	0.757	0.398	0.795	0.718
6.SBE	0.646	0.451	0.702	0.664	0.671
7.RT	0.617	0.397	0.630	0.660	0.685	0.533

Note: PT = preferential treatment; AC = access convenience; RT = store information transparency; TRU = trust; COM = commitment; SAT = satisfaction; SBE = store brand equity

5.7. Structural equation model

The overall model fitness indices including χ2 = 1136.908, df = 512, χ2/df = 2.221, CFI = .927, TLI = .921, GFI = 0.871, and RMSEA = .051 exceed the recommended threshold and indicated that the data fits well with the structural model as suggested by Wu et al. (2017).

All research hypotheses are accepted based on the results presented in Table 4.

Table 4. Hypothesis testing

Hypothesis	Relationships			Estimate standardized	Estimate Unstandardized	S.E	C.R.	P	Result
H1a	TRU	<—	AC	.503	.452	.058	7.788	***	S
H1b	COM	<—	AC	.525	.469	.056	8.335	***	S
H1c	SAT	<—	AC	.567	.495	.055	9.047	***	S
H2a	TRU	<—	RT	.221	.233	.067	3.492	***	S
H2b	COM	<—	RT	.231	.241	.065	3.734	***	S
H2c	SAT	<—	RT	.284	.290	.062	4.650	***	S
H3a	TRU	<—	PT	.213	.218	.045	4.804	***	S
H3b	COM	<—	PT	.213	.217	.044	4.955	***	S
H3c	SAT	<—	PT	.120	.119	.041	2.923	.003	S
H4a	SBE	<—	TRU	.206	.195	.060	3.253	.001	S
H4b	SBE	<—	COM	.388	.371	.065	5.687	***	S
H4c	SBE	<—	SAT	.245	.239	.067	3.570	***	S

Note: S = Supported

The results revealed that access conveniences had a significant positive effect on trust (β = 0.503, p = .000) and supported H1a. Access conveniences had a significant positive effect on commitment (β = 0.525, p = .000) and supported H1b. Access conveniences had a significant positive effect on satisfaction (β = 0.567, p = .000) and supported H1c.

Store information transparency directly and significantly affected trust (β = 0.221, p = .000), thus, H2a was supported. Store information transparency directly and significantly affected commitment (β = 0.231, p = .000), which supported H2b. Store information transparency directly and significantly affected satisfaction (β = 0.284, p = .000), which supports H2c.

Preferential treatment was established as a significant driver of trust (β = 0.213, p = .000), thus we accepted H3a. Preferential treatment was established as a significant driver of commitment (β = 0.213, p = .000), thus we accepted H3b. Preferential treatment was established as a significant driver of satisfaction (β = 0.120, p = .005), thus we accepted H3c.

Trust had a positive effect on store brand equity (β = 0.206, p = .005), which supported H4ba. Commitment had a positive effect on store brand equity (β = 0.388, p = .000) and supported H4b. Satisfaction had a positive effect on store brand equity (β = 0.245, p = .000), which supported H4c.

5.8. Variance explained in the model

The findings shown in Figure 2 revealed that 70.00% of the variance (R²) in satisfaction, 64.80% of the variance in commitment, and 60.02% of the variance in trust is explained by access conveniences, preferential treatment, and store information transparency. In addition, 54.50% of the variance in store brand equity is explained by relationship quality (trust, commitment, and satisfaction). The R² values of .01, .09, and .25 indicate small, medium, and large effects, respectively, in behavioral sciences as per the recommendations of Cohen (1988). The value of R² > .25 implies that the model largely captured the effects of exogenous variables on the endogenous variables and possesses good predictive power (Hair et al., 2010).

Figure 2. Standardized coefficients and R-squares.

Note: Numbers in bold are R-squares values

6. Discussion

This study was conducted in the context of the retailing industry in emerging markets of Vietnam to expand the application of the S-O-R framework and further understand the concept of store brand equity in this market. Overall, all the proposed hypotheses and the research models were supported by empirical data.

The findings showed that store brand equity directly affected by trust (β = 0.206), commitment (β = 0.388) and satisfaction (β = 0.245). These figures indicated that relationship quality dimensions such as commitment and satisfaction are important factors in storing brand equity in retail. These findings align with previous research examining the positive link between satisfaction, trust, commitment, and brand equity (Marquardt, 2013; Morgan & Hunt, 1994).

In addition, access convenience (β = 0.525), store information transparency (β = 0.231) and preferential treatment (β = 0.213) in that order were significant driver of commitment. The study’s finding emphasizes the contribution role of store information transparency on commitment in the Vietnam retail market. In addition, the result of this study confirmed the positive link between preferential treatment and commitment, which is consistent with the result presented in the previous study (S. Chou & Chen, 2018; Gwinner et al., 1998; Lacey et al., 2007; Ma et al., 2018).

Further more, access conveniences (β = 0.567), store information transparency (β = 0.284), preferential treatment (β = 0.120) has positive association with satisfaction. These findings are in line with the previous study, which has proved that the accessibility of service providers has a link to satisfaction (Dai & Salam, 2014; Kaura et al., 2015; Seiders et al., 2007), store information transparency resulted in satisfaction (Kang & Hustvedt, 2014; Spena et al., 2012) and preferential treatment also resulted in consumer’s satisfaction (Yen & Gwinner, 2003).

Finally, among the three relationship marketing tactics, preferential treatment has the least importance compared to other stimuli components in the S-O-R framework (i.e., access convenience and store information transparency).

7. Conclusion

Information transparency is an important issue in emerging markets such as Vietnam. To the best of our knowledge, only a limited number of studies have considered store information transparency as an S-O-R framework stimuli in the Vietnamese retail setting. This study also explores the role of relationship quality in store brand equity. The SEM results, based on the data set collected from 465 customers in the Vietnamese retail setting, reveal that store information transparency constitutes the “stimuli” components, store brand equity constitutes the “response,” and relationship quality constitutes the “organism” in the S-O-R framework within the Vietnam retail industry. The present study found a significant and positive impact of relationship marketing tactics such as preferential treatment, access convenience, and store information transparency on relationship quality with three distinct constructs such as trust, commitment, and satisfaction. Relationship quality was found to enhance store brand equity in the Vietnamese retail market. The study findings offer a number of theoretical and managerial implications.

8. Implications

8.1. Theoretical implications

This study makes four theoretical contributions:

First, the study expands the application of the S-O-R framework in examining the concept of store brand equity. Within the framework, relationship marketing tactics such as access convenience, preferential treatment, and store transparency policy were confirmed as the “stimuli” relationship quality; three distinct constructs: trust, commitment, and satisfaction as the “organism” (Cattapan et al., 2022; Izogo et al., 2017; M. Zhang et al., 2018); and store brand equity as the “response” (Loureiro & Sarmento, 2018) in the S-O-R framework in the Vietnamese retailing industry.

Second, this study includes store information transparency and expands the stimuli component of the S-O-R framework. In a developing country such as Vietnam, information transparency is important. This study shows a positive association between store information transparency and commitment, which has limited empirical study in a retail setting. Information transparency signals the retailer’s goodwill (Liu et al., 2015). Thus, customers will positively judge a retailer’s motivation. In Confucianism-rooted culture, such as Vietnam, customers will support retailers who follow the ideal ethical standard of traditional Confucianism (Cheung & Yeo-chi King, 2004). In addition, in a long-term oriented society, people place an emphasis on honesty, integrity, and fairness, which prevents them from engaging in opportunistic behavior. This is the foundation of the relationship and customer satisfaction in Confucian culture (Ndubisi & Nataraajan, 2018). This explains why customers will exert more effort to maintain a relationship with a retailer in the Vietnamese retail industry that shares their cultural norms. Store information transparency is critical to customer satisfaction (Merlo et al., 2018). When customers have more knowledge about a retailer’s offering, they can form a more reasonable expectation because customer satisfaction is the result of what the customer hopes for and expects from an appealing product and/or service or exchange relationship (Ndubisi & Nataraajan, 2018).

Third, in the Vietnamese retailing industry, the performance of the access convenience dimension is crucial for retailers—consumers should be able to get to the stores quickly and easily (Troiville et al., 2019). The contribution of this dimension to customer satisfaction and commitment is very high. Due to the specific demands of a large segment of the consumer population in Ho Chi Minh city and the characteristic busy lifestyle in a big city, customers have limited time, and they prefer a conveniently located retailer (Cadilhon et al., 2006). The more convenient a retailer or a brand the more time customers save, which enhances their satisfaction and results in a high store brand equity (Yoo et al., 2000).

Fourth, store brand equity serves as a shortcut in customers’ minds to the most satisfactory shopping experiences, impacting their behavioral intentions (Allaway et al., 2011). Herein, the results emphasize the central role of commitment and satisfaction on store brand equity in the context of Vietnam. When customers receive more benefits from their relationship with a retailer, they will feel locked into the relationship (Verhoef et al., 2002). In addition, based on the country’s characteristic Confucian culture, customers will have a favorable attitude toward retailers who place a higher emphasis on consumers’ interests (Eng & Jin Kim, 2006). Owing to the Confucian culture in Vietnam, customer will feel that they ought to commit to retailer due to the norm of reciprocity and the mutual profitability of the relationship (Hsu, 2007). Finally, the commitment leads to favorable store brand equity (Dwivedi & Johnson, 2013; Rego et al., 2009; Sierra et al., 2017). With reference to the dedication mechanism of SET (Blau, 1964), customer satisfaction serves as the “attractiveness” of the relationship (Thibaut & Kelley, 1959). Thus, customers are willing to develop an ongoing relationship with a retailer or a brand that fulfill their expectation (Dwivedi, 2014), resulting in positive store brand equity (Iglesias et al., 2019; Rambocas et al., 2014; Torres & Tribó, 2011).

8.2. Managerial implications

Building a strong brand equity link to a store is an important consideration in Vietnam, where retailers have not recognized the importance of brands and branding (Nguyen et al., 2011). This study offers three managerial implications.

First, the importance of store brand equity must be considered because it can provide more value to consumers while creating and sustaining market awareness (Troiville et al., 2019). In the Vietnamese retail market, convenient access provides customers with benefits because it helps them save time and effort when making purchases (Seiders et al., 2007). Thus, retailers must focus on building their own competitive advantages by setting up reasonable store locations, opening hours, parking facilities, etc.

Second, the role of information transparency must be considered because it can enhance relationship quality, especially through improved customer satisfaction and commitment. Managers should invest greater effort into building a transparency policy and setting up different communication channels. This provides helpful information about its services and for designing effective platforms or websites, allowing for the most updated information about promotions. These facilitate customers’ access to information about services in a convenient manner while ensuring that all information provided clear and easily understandable.

Third, preferential treatment also contributes significantly to relationship quality. However, its contribution is quite limited when compared to convenient access and transparent store information. This does not mean that this marketing tactic it not important. Managers should maintain this tactic among their loyal customer segments.

8.3. Future research avenue

The study has some limitations which can be regarded as avenues for future research: (i) the sample in the study is limited to consumers in Ho Chi Minh City, so it does not represent the entire population, (ii) further studies should verify the relationship chain in different contexts and services to generalize the result, and (iii) the stimuli dimensions can be expand to other variables such as store reputation, store image and store price.

Acknowledgements

Prof. Dr. Si Van Nguyen is a senior lecturer at University of Economics Ho Chi Minh City (UEH). His research focuses on tourism, consumer behavior, marketing and statistic. He has authored and co-authored of several articles in Scopus journals. [email protected], https://orcid.org/0000-0003-0294-7831. Affiliation: UEH school of Economic Mathematics – Statistics, University of Economics Ho Chi Minh City (UEH).

Minh Duy Vo is a PhD in process at University of Economics Ho Chi Minh City (UEH). His research interests include consumer behavior and marketing. [email protected], https://orcid.org/0000-0001-8507-4487. Affiliation: UEH school of Economic Mathematics – Statistics, University of Economics Ho Chi Minh City (UEH).

Disclosure statement

The authors report there are no competing interests to declare.

Additional information

Funding

The authors received no direct funding for this research.

APPENDIX 1

Table A. Measurement scale

Construct	Author	Items
Access convenience	Moeller et al. (2009)	AC1: It is easy to reach X.
		AC2: It takes little time to get access to the store of X.
		AC3: X offers convenient parking facilities.
		AC4: X offers convenient opening hours.
Preferential treatment	Huang (2015)	PT1: X makes greater efforts for regular customers than for non-regular customers.
		PT2: X offers better service to regular customers than to non-regular customers.
		PT3: X does more for regular customers than for non-regular customers.
	Focus group	PT4: X usually places me higher on the priority list when dealing with other customers.
		PT5: The employees at X treat me better than other customers.
Store information transparency	Liu et al. (2015)	RT1: X offers access to other customers’ comments or ratings of its service.
		RT2: X compares the pros and cons of its services versus competitor offerings.
		RT3: X openly shares customer reviews about its services.
		RT4: X provides helpful information about its services.
		RT5: Information provided by X about its services is easily to access.
		RT6: Information provided by X about its services is easily understood.
		RT7: X regularly updates information about its promotions.
Trust	Y. Zhang et al. (2011)	TRU1: I believe that X is consistent in quality and service.
		TRU2: I believe that X is keen to fulfill my needs and wants.
		TRU3: I believe that X is honest.
		TRU4: I believe that X wants to be known as one that keeps promises.
		TRU5: I believe that X has my best interests in mind.
		TRU6: I believe that X is trustworthy.
		TRU7: I believe that X has high integrity.
Commitment	Normative (Roy et al., 2020)	COM1: My attachment to X is mainly based on similarity of our values.
		COM2: Because of the values X stands for, being a customer feels the right thing to do.
		COM3: I prefer X to others because it stands for values important to me .
	Economic (Roy et al., 2020)	COM4: It pays off economically to be a customer of X.
		COM5: I would suffer economically if the relationship were broken.
		COM6: The economic benefit of dealing with X exceeds the costs.
Satisfaction	Gremler and Gwinner (2000)	SAT1: Based on all of my experience with X, I am very satisfied with the services it provides.
		SAT2: My choice to use X was a wise one.
		SAT3: Overall, I am satisfied with the decision to use X.
		SAT4: I think I did the right thing when I decided to use X for my needs.
		SAT5: My overall evaluation of the services provided by X is very good.
Store Brand Equity	Hartman and Spiro (2005); Yoo et al. (2000)	SBE1: It makes sense to buy store brand X instead of others available in the market.
		SBE2: Even if other brands had characteristics that were similar to brand X, I would buy store brand X.
		SBE3: Although there were other store brands as good as X, I would rather buy the brand X.
		SBE4: If another brands is not different from X in any way, it seems smarter to purchase in store brand X.