Corporate social marketing and brand equity – a case of dairy products in Vietnam

Abstract

The research conducted to study the impact of customers’ perceptions of corporate social marketing (CSM) on the multidimensions of brand equity in the case of dairy products in Vietnam. Research data was collected, through direct interviews, from 780 valid questionnaires responsed by customers living in Ho Chi Minh City and Ha Noi. The study found that CSM is an important factor in brand equity creation, and more effective than distribution intensity and advertising in building a dairy product brand. The results confirm that CSM initiatives positively effect on the five CBBE dimensions (brand awareness, brand associations, perceived quality, brand trust, and brand loyalty) and show causal order among the CBBE dimensions. Futhermore, the research findings enrich the theory of CSM and brand equity and support the Theory of Planned Behavior.

SUBJECTS:

• Work & Organizational Psychology
• Business, Management and Accounting
• Higher Education

Keywords:

• Corporate social marketing
• brand equity
• dairy products
• Vietnam

REVIEWING EDITOR:

• Kaouther Kooli, Bournemouth University, United Kingdom

Research background

Business organizations are operating in a quickly changing and unpredidictable environment. The change of business environment impacts their decisions and actions directly or indirectly. From a marketing perspective, changing customer attitudes and perceptions is a top concern. How to respond appropriately to change to achieve the desired results is a major challenge. Today, customers are more and more informed about health problem driven from food production, social issues, and environmental problems in the media. This requires business organizations engaged with social responsibility and toward social marketing to provide support for solving problems that customers are preoccupied with. Therefore, marketing should contribute to the formation of sustainable social behavior, and support sustainable economic development, or proactively implement corporate social marketing (CSM) as a sustainable marketing form (Emery, 2012; Gordon et al., 2011; Martin & Schouten, 2012). CSM refers to implementing firms’ responsibility for social issues such as economic, ethical, philanthropic responsibilities (Kotler, 2009, 2011).

CSM influences the perceptions and behaviors of target audiences (e.g. community, supplier, consumer) to form sustainable social behaviors; thereby it benefits both society and firms (Emery, 2012; Gordon et al., 2011; Lefebvre, 2012). Many empirical studies showed that consumer perception of environmental issues significantly affect their buying intention (Dilotsotlhe, 2021; Ellen et al., 1991; Kim & Choi, 2005; Li & Jaharuddin, 2021; Wheale & Hinton, 2007; Young et al., 2010). Consumers tend to buy products/services offered by reputable and socially responsible companies (Vo & Le, 2016). Numerous studies of corporate responsibility initiatives for social issues (education, public health, social security and welfare, etc.) found three positive outcomes of consumer perception toward corporate social responsibility: the increase of buying intention (Brown & Dacin, 1997; Lee et al., 2011; Sen & Bhattacharya, 2001; Thanh et al., 2021), customer loyalty (Barone et al., 2000; Bhattacharya & Sen, 2003; Lichtenstein et al., 2004), and consumer satisfaction (Luo & Bhattacharya, 2006). The relationship between CSM and brand equity represents an area that requires further investigation within the field of marketing. The purpose of CSM is to serve the interests of the public and their real needs, as well as to increase the common wellbeing of society (Hoeffler & Keller, 2002). One crucial research gap lies in understanding the mechanisms through which CSM activities influence brand equity. While it is widely acknowledged that corporate social responsibility initiatives can positively affect brand equity, there is a need for more empirical research to uncover the underlying processes and mechanisms involved. Specifically, exploring how different dimensions of CSM impact various aspects of brand equity (e.g. brand awareness, brand loyalty, perceived quality) can provide valuable insights for marketers and help them design effective CSM strategies that enhance brand equity. The second research gap is examining the impact of CSM on brand equity for businesses operating in specific industries or regions. Investigating the unique dynamics and challenges faced by these entities in implementing CSM initiatives and their subsequent impact on brand equity can provide valuable insights for a wider range of businesses. Moreover, there have been no empirical studies to assess the effectiveness of CSM initiatives based on consumer perspectives (Deshpande, 2016; Hoeffler et al., 2006; Inoue & Kent, 2014), and its association with brand equity. The research and experimental study of customer-based brand equity (CBBE) is an important issue for both scholars and marketers (Aaker, 1991, 1996; Kapferer, 2008; Kartono & Rao, 2009a; Keller, 2008; Keller & Lehmann, 2006). However, they continue to face challenges in broaden the perspective and empirical approach to CBBE, across different industries and in different countries (Bick, 2009; Christodoulides & De Chernatony, 2010; Hsieh, 2004; Koçak et al., 2007; Oliveira et al., 2015; Washburn & Plank, 2002). Therefore, studying how CSM impact on various aspects of CBBE in a specific industry in a country is essential.

The dairy industry has made important contributions to the economy, sustainable economic development, and human nutrition and health (FAO). Vietnamese dairy industry has grown rapidly with the average growth rate reached 12.6% per year, considered one of the industries with high and stable growth in the FMCG industry. The dairy industry has been contributed to the growth rate of livestock sector around 10% per year; therefore, considered as a potential dairy consumption market (VIRAC, 2019, VIRAC, 2020); and Vinamilk, Nutifood, IDP and Moc Chau Milk have been in the top 25 Vietnamese brand list in F&B industry, according to Vietnam (2022). The situation motivated us to conduct this study to measure the impact of CSM from the perception of consumers on CBBE components in Vietnamese dairy industry. The focusses of this study are on the effect of CSM on consumer perceptions towards dairy’ brands, and the relationships between CBBE dimensions. The following sections will be literature review, research hypothesis development and research model, data collection and processing, findings’ discussion, recommemdation, and limitations.

Literature review

Theoretical background

To achieve the research objective mentioned above, the research model was developed from the two basic models - Theory Reasoned Action (TRA), and Theory Planned Behavior (TPB). The TRA Model (Fishbein & Ajzen, 1975) argues that attitude towards behavior and subjective norms are two basic groups of factors that form individual behavioral intention and actual behavior. Subjective norms elements belong to individual perception and influenced by society; attitude towards the behavior as elements belonging to the impact from the object (Bray, 2008). The TPB model (Ajzen (1985, 1991, 2019) argues that behavioral intention is explained by three groups of factors: attitude towards behavior, subjective norms, perceived behavioral control and actual behavior, but is regulated to a certain extent by variables of perceived behavioral control (Ajzen, 1991, 2019). To improve behavioral predictability in specific contexts, the TPB model is continuously adjusted by Ajzen (2011, 2019), namely, cognitive variables that control behavior not only directly impacting intentions but also regulating attitudes and subjective norms.

Corporate social marketing (CSM)

The social marketing concept was first introduced by Kotler and Zaltman (1971) as the design, ­implementation, and control of marketing programs with the main goal to achieve the success of an organization by balancing the short-term needs of individuals and the long-term benefits of society (Kotler, 1972). CSM is an extension of social marketing to a corporate context (Hoeffler et al., 2006; Kotler et al., 2012) to take on more social responsibility (Kotler, 2011). CSM applies marketing principles to better shape marketplace be more efficient and sustainable and increase people’s well-being and social welfare (Phils et al., 2008); and the fact that CSM has been constantly adjusted to the innovation of society (Lefebvre, 2012). CSM can be approached as a firm actively or voluntarily uses its business resources and/or its partners to develop, sponsor, conduct campaigns/programs to care for and improve education, public health, community well-being and/or social welfare; environmental protection; thereby it makes a change in perceptions and behaviors voluntarily of the target audience (local communities, partners, customers), and creates practical benefits for both society and company. Applying CSM has been an inevitable trend due to it connecting the social marketing purpose of a firm with the desired development of a society (Kotler et al., 2012). CSM aims to transform perception and voluntary behavior of target audiences, thereby it forms sustainable social behaviors to bring benefit to both society and business (Emery, 2012; Gordon et al., 2011; Lefebvre, 2011, 2012). Though, few empirical studies on CSM have focused on the perspective of consumers (Deshpande, 2016; Hoeffler et al., 2006; Inoue & Kent, 2014; Truong & Hall, 2016).

Customer–based brand equity (CBBE)

A brand can be thought of as a group of unique functional and emotional values and can provide customers with a favorable experience (De Chernatony et al., 2006). Branding promotes an increase in the customer’s perceived value of the product (Mizik & Jacobson, 2009). Brand as a competitive advantage, which is difficult for competitors to imitate or replace (Baldauf et al., 2003; Slotegraaf & Pauwels, 2006).

Brand equity (BE) is one of the popular and importanct concepts in marketing (Christodoulides & De Chernatony, 2010; Davcik et al., 2015; Keller, 1993, 2008), reflecting the added value a brand creates for its products, derived from brand marketing efforts to reach potential and/or target customers (Aaker, 1991, 1996; Anderson, 2007; Bick, 2009; Keller & Lehmann, 2006; Netemeyer et al., 2004). BE can be measured from three different aspects (Baalbaki & Guzmán, 2017; Keller & Lehmann, 2003, 2006): Consumer-level measures (e.g. Aaker & Joachimsthaler, 2000; Baker et al., 2005; Bendixen et al., 2004; Chen, 2001; Keller, 1993; Lassar et al., 1995; Shocker & Weitz, 1988; Tong & Hawley, 2009a, 2009b,…), Market-level measures (e.g. Cobb-Walgren et al., 1995; Doyle, 2001; Dyson et al., 1996; Farquhar et al., 1991; Kapferer, 1997; Kim et al., 2003), and Financial-level measures (e.g. Aaker & Jacobson, 1994; Barth et al., 1998; Simon & Sullivan, 1993). In addition, many authors have developed commercial asset measurement models that incorporate all these measurement systems (e.g. Epstein & Westbrook, 2001; Keller & Lehmann, 2006).

CBBE has been discussed by researchers; however, there is no consensus on its definition, or management (Keller, 1993, 2008; Oliveira et al., 2015; Vázquez et al., 2002) due to its two measurement approaches - financial and marketing (Christodoulides & De Chernatony, 2010; Hsieh, 2004). Some researchers assume that CBBE expresses selectively wills and emotions of consumers for the brand in a set of competing brands available in marketplace (Kartono & Rao, 2009b; Keller & Lehmann, 2006). Others believe that CBBE results from marketing efforts of a company to build positive awareness, attitude, behavior of consumers towards a brand (Bick, 2009; Hsieh, 2004; Keller, 2008) and create brand value based on increasing consumers’ buying intention for the brand (Keller, 2008).

Research hypothesis development and research model

The research hypotheses and research model were developed based on the TPB model adjusted by Ajzen (2011, 2019), and the selected empirical studies on CBBE such as Buil et al. (2013b) evaluated the effect of promotion and advertising on CBBE dimensions in the UK beverage, apparel, home appliances and car industries; Saydan (2013) assesses the impact of goods origin on CBBE components in the household electrical goods industry in the UK market; Su and Tong (2015) evaluated the impact of brand personality on CBBE components in the sportswear industry in the US market; Jafari Drabjerdi et al. (2016) evaluated the impact of advertising costs, attitudes towards advertising, money promotions, non-monetary promotions, product packaging and distribution intensity on CBBE components in dairy products in the Iranian market; Abril and Rodriguez-Cánovas (2016) evaluate the impact of distribution intensity, promotion and in-store communication on CBBE of private label - yogurt in the Spanish market, etc.

In this study, the CBBE dimensions of milk products and marketing mix activities applying by dairy milk firms popularly were explored through the direct expert interview and focus group discussion based on Aaker’s CBBE model (Aaker, 1991, 1996); and resulted in five dimensions of CBBE: brand awareness, brand associations, perceived quality, brand loyalty, and brand trust. The interrelationship among these CBBE dimensions were discussed, the two most popular marketing mix activities - advertising and distribution intensity - were identified. Twenty research hypotheses with the research model were proposed and presented in Figure 1.

Figure 1. Proposed Research Model.

Brand awareness (AW) represents the ability of a (potential) buyer/user to recognize and recall a brand as an integral part of a particular product (Aaker, 1996; Keller, 2008). Brand awareness demonstrates the power of a brand existing in the minds of consumers (Hoang et al., 2010; Nguyen et al., 2011), plays an important role in purchasing and using decisions (Keller, 2008), helps consumers to distinguish a brand from a group of competing brands (Nguyen & Nguyen, 2011). Brand awareness is conceptualized as a component of CBBE demonstrated by many researchers such as Keller (2008), Buil et al. (2008, 2013a, 2013b), Tong and Hawley (2009b), Calvo-Porral et al. (2013), Ebeid (2014), Su and Tong (2015), and Shariq (2018). Milk (product) brand awareness mentions the ability of buyers/users to recognize and recall a dairy brand through the product’s appearance (packaging, logo, label), product characteristics (flavor, taste, nutritional content) and distinguishable from other competing brands of the same type (fresh milk and/or powdered milk) available on the market through characteristics such as natural origin, organic, processing technology. Brand associations (AS) is anything related to a brand that is associated in the consumer’s mind (Aaker, 1991). Brand associations include all the thoughts, feelings, perceptions, impressions, experiences, beliefs, and attitudes of consumers towards a brand (Keller, 2006). Brand associations is conceptualized as a component of CBBE demonstrated by many researchers such as Aaker (1996), Keller and Lehmann (2006), Atilgan et al. (2005, 2009), Buil et al. (2008, 2013a), Tong and Hawley (2009a, 2009b), Calvo-Porral et al. (2013), Ebeid (2014), Su and Tong (2015), Shariq (2018). Milk brand associations represent associations in the minds of consumers about a particular brand of milk (fresh and/or powdered) through its appearance (packaging, logo), internal characteristics (nutrition content, taste), and characteristics of dairy enterprises (constantly improving quality, caring – increasing social welfare and welfare). Perceived quality (QL) is considered as consumers’ unique perception of product quality (Netemeyer et al., 2004; Zeithaml, 1988), the subjective perception of the characteristics that a product brand gives them (Nguyen et al., 2011). Perceived quality is considered as a factor forming consumers’ beliefs about the brand (Cai et al., 2014; Kumar et al., 2013), is the basis for consumers to buy and use as well as compare brands (Nguyen & Nguyen, 2011), are reasons leading consumers to choose to buy a product brand (Hoang et al., 2010; Nguyen et al., 2011; Yoo et al., 2000). The perceived quality of a milk brand is considered as consumers’ subjective perception of a particular milk brand through the characteristics of a milk brand (eye-catching packaging, attractive taste, optimal nutritional content and of natural origin). Consumers perceive the quality of milk brand as superior (higher or best), that forms consumers’ beliefs, preferences, and choice (intentional decision) using the brand. Brand trust (BT) is defined as a consumer’s willingness to trust a brand’s performance (Chaudhuri & Holbrook, 2001), referring to the reasons consumers trust the brand that has the ability and intention to fulfill its promised requirements (Delgado-Ballester et al., 2003). Brand trust is derived from consumers’ experiences and interactions with the brand (Naggar & Bendary, 2017). It can affect branding performances directly (trial or usage) or indirectly (advertisement or word of mouth) (Keller, 1993; Krishnan, 1996), and can improve or destroy the brand-customer relationships (Keller, 2003). Brand loyalty (LO) implies that a particular product brand comes first in the consumers’ mind when they make a purchase decision (Gremler & Brow, 1996); indicates a consumer’s sympathy for the brand and will not intend to switch to another (expressed through the behavior of using, purchasing, or re-purchaing a specific product brand (Keller, 2008; Saydan, 2013). Brand loyalty should be considered in both cognitive and behavioral aspects because it represents a brand becoming the consumer’s first choice and this consequent leads to the brand being recognized and purchased again and agian (Keller, 2008), even when the brand changes in price or other product characteristics (Aaker, 1991; Chaudhuri & Holbrook, 2001).

Relationships between CSM and CBBE dimensions

Applying CSM is a clear trend because it connects the marketing purpose of the business with the practical requirements of the society (Andreasen, 1994, 2002; Kotler et al., 2012); CSM generates social and business benefits (Du et al., 2008); CSM increases the impression of businesses on consumers (Lichtenstein et al., 2004); CSM clearly demonstrates the moral function of the brand (Kapferer, 1997, 2008). CSM supports market development, increase sales or improve corporate impression (Bhattacharya et al., 2005; Bloom et al., 1997; Kotler & Lee, 2005); CSM differentiates businesses from competitors by forging both emotional and emotional connections with customers (Meyer, 1999); enhancing consumer confidence and loyalty (Inoue & Kent, 2012, 2014).

The results of the case study by Hoeffler and Keller (2002) have shown that CSM initiatives can help build CBBE such as building brand awareness, enhancing brand image/associations, establishing brand credibility/trust, evoking brand feelings, creating a sense of brand commuity, and liciting brand commitment. Based on the above evidence from the literature, the following hypotheses H₁ was proposed:

H_1a: CSM has a significant effect on brand awareness.

H_1b: CSM has a significant effect on brand association.

H_1c: CSM has a significant effect on perceived quality.

H_1d: CSM has a significant effect on brand trust.

H_1e: CSM has a significant effect on brand loyalty.

Relationships between advertising and CBBE dimensions

Advertising is defined as any paid form of nonpersonal presentation and promotion of ideas, goods, or services by an identified sponsor via media (Kotler et al., 2021; Kotler & Keller, 2016). Advertising is a popular marketing communication tool, created to inform, remind or persuate the receiver to take some actions now or in the future (Buil et al., 2013b; Kotler et al., 2021; Kotler & Keller, 2016). Advertising perceived by consumers can depends on the amount of advertising investment (determined by how often the customer sees an advertisement), and the attitude towards the the advertisement (referring to the perception of the target audience of advertising messages) (Buil et al., 2013b; Kotler & Keller, 2016; Ramos & Franco, 2005).

Advertising has a positive relationship with brand recall, helping customers increase brand awareness (Deighton, 1984; Hoyer & Brown, 1990). Brand awareness created through marketing communications, especially advertising, is considered the main communication tool for products/services in the consumer goods market (Ailawadi et al., 2002; Ambler et al., 2002; Bravo et al., 2007; Rajh & Ozretić Došen, 2009).

Awareness of high ad spend helps develop higher brand awareness (Bravo et al., 2007, Buil et al., 2013b; Cobb-Walgren et al., 1995; Simon & Sullivan, 1993; Yoo et al., 2000). In other words, spending on brand advertising can increase brand exposure, and therefore, increased brand awareness (Keller, 2008). In addition, through fresh, innovative, and disruptive advertising messages, firms can attract more customers, leading to higher brand awareness (Aaker, 1991; Buil et al., 2013b).

Many research results show that the higher the advertising spend for the brand, the better associations will be formed in the customer’s mind (Bravo et al., 2007; Yoo et al., 2000). Furthermore, the company can develop strong, favorable, and unique brand associations through creative messaging (Aaker. 1991; Buil et al., 2013b). Several previous studies have shown a link between advertising and perceived quality (Aaker & Jacobson, 1994; Kirmani & Wright, 1989; Milgrom & Roberts, 1986). Spending ‘heavy’ on advertising demonstrates that an organization is investing in a brand, which creates a perceived superior quality (Kirmani & Wright, 1989; Ramos & Franco, 2005; Yoo et al., 2000).

In addition, companies can increase perceived quality through original, creative, and novel advertising messages (Aaker, 1991; Buil et al., 2013b); and subsequently, advertising helps support purchasing decisions by increasing brand equity (Karunanithy & Sivesan, 2013). Advertising increases the probability of a brand being selected from a pool of alternatives; thus, the decision-making process is simplified at the same time, as customer habits are created and lead to brand loyalty (Shimp, 1997; Yoo et al., 2000; and Ramos & Franco, 2005). Furthermore, the level of advertising spend increases the value of the product, supporting the purchase decision of the consumer (Archibald et al., 1983; Yoo et al., 2000).

Kirmani and Wright (1989) emphasized the direct positive effect of advertising on brand trust by focusing on the importance of spreading accurate and honest messages. Through advertising, people get a sense of ‘guaranteed’ for the brand being sold in the market; Once customers see the ad, they gain a sense of confidence and develop expectations and beliefs about the brand (Kotler et al., 2021). Based on the above evidence from the literature, we hypothesized H₂ as follows:

H_2a: Advertising has a positive effect on brand awareness.

H_2b: Advertising has a positive effect on brand associations.

H_2c: Advertising has a positive effect on perceived quality.

H_2d: Advertising has a positive effect on brand trust.

H_2e: Advertising has a positive effect on brand loyalty.

Relationships between distribution intensity and CBBE dimensions

In marketing (consumer goods), there are many studies showing that distribution channel expansion/development contributes to branding process, increasing brand equity (Dodds et al., 1991; Grewal et al., 1998; Kim & Hyun, 2011; Nguyen Viet & Nguyen Anh, 2021; Nguyen et al., 2011; Yoo et al., 2000). Distribution intensity refers to the number of outlets used by a producer in its commercial area; considered as a product that is available in a large number of stores to satisfy a customer’s purchase (Yoo et al., 2000). High distribution intensity has a positive effect on the increase of CBBE because it increases the probability of buying the brand wherever and whenever the consumer wants (Farris et al., 1989; Yoo et al., 2000, Kim & Hyun, 2011).

High distribution intensity enhances brand awareness and recognition (Ebeid, 2014; Nguyen et al., 2011; Srinivasan et al., 2005). The increase in distribution intensity reduces the effort of consumers in finding and buying the brand, they perceive the brand as more valuable, thereby increasing satisfaction and brand loyalty. Yoo et al., 2000). Increased distribution intensity leads to higher customer satisfaction, perceived quality and brand loyalty, and ultimately, higher brand equity (Heidarzadeh & Zarbi, 2008).

Several previous studies have shown that distribution intensity has a positive impact on perceived quality and brand loyalty (Ebeid, 2014; Kim & Hyun, 2011; Yoo et al., 2000). In addition, Huang and Sarigöllü (2012) found that increasing distribution intensity gives consumers repeated exposure to the product brand, which in turn leads to increased awareness and hence increased awareness. improve brand associations. It can be argued that distribution intensity has a positive effect on the formation and enhancement of brand associations.

Distribution intensity provides added value through a reduction in the costs consumers have to trade in order to obtain the product (Yoo et al., 2000). On the other hand, as De Chernatony and Cottam (2006) mentioned, trust acts as a tool to help reduce risk – helping to reassure customers. It can be argued that the wider the distribution channel (increasing the intensity), the greater the opportunity for consumers to recognize, interact with or come into contact with the brand, which can form brand trust, leading to purchase intention or repurchase. Based on the above evidence, the following hypothesis H₃ was proposed:

H_3a: Distribution intensity has a positive effect on brand awareness.

H_3b: Distribution intensity has a positive effect on brand associations.

H_3c: Distribution intensity has a positive i effect on perceived quality.

H_3d: Distribution intensity has a positive effect on brand trust.

H_3e: Distribution intensity has a positive effect on brand loyalty.

Relationships among CBBE dimensions

For consumers to have brand loyalty, the first things are that they must have brand knowledge, be able to aware or distinguish a particular brand from other brands (with the same product) present in the market (Aaker, 1991, 1996; Pappu et al., 2005). Brand associations are the key antecedent for consumers to make their purchasing decisions and create their loyalty to the brand (Aaker, 1991; Atilgan et al., 2005). Once consumers perceive a brand to be of higher quality than other brands (with the same product) available on the market, it will make them decide to buy or repurchase that product brand (Nguyen et al., 2011), leading to enhanced brand loyalty (Yoo et al., 2000; Buil et al., 2013b).

Brand trust is the trigger for consumers’ commitment to choose, use and repurchase a brand (Delgado-Ballester et al., 2003; Yannopoulou et al., 2011), an important element in creating successfully build and maintain the strong link between consumers and brands (Atilgan et al., 2009; Hiscock, 2001; LaBahn & Kohli, 1997). In other words, brand trust is an actecedent for increasing brand loyalty (Chaudhuri & Holbrook, 2001; Kumar et al., 2013; Power et al., 2008). In addition, some authors argue that once customers experience the more engaged with the brand, the better the perceived quality, the good experiences will form brand trust, thereby leading to brand loyalty (Kumar et al., 2013; Nguyen Viet & Nguyen Anh, 2021). The following hypotheses were summarized the arguments above:

H₄: Brand awareness has a significant effect on brand loyalty.

H₅: Brand association has a significant effect on brand loyalty.

H₆: Perceived quality has a significant effect on brand loyalty.

H₇: Brand trust has a significant effect on brand loyalty.

H₈: Perceived quality has a significant effect on brand trust.

In the research model, brand loyalty is customers’ behavioral intention influenced by the three groups of factors: (1) customers’ subjective norms – brand awareness and associations, (2) attitude towards behavior (perceived quality and brand trust), and (3) perceived behavioral control (marketing activities) that may impact directly or indirectly on CBBE components. The other control variables may impact significantly on customer perceptions and behavioral intention towards milk brands such as gender, income, age, geography, brand origin, and type of milk were also considered in this study.

Data collection and processing

The data used in this study collected from survey questionnaires; thereore, the development of the measurement scales of latent variables needed to be conducted. To develop the measurement scales of 8 latent variables in the research model, focus group and pilot test were conducted. Two focus group discussions with 13 customers who over 18 years old, and often purchase directly and use dairy products at popular shopping points in Ho Chi Minh City were conducted and resulted in 51 items (statements). To test the reliability of the measurement scales, the pilot test was carried out on 100 survey questionnaires by using exploratory factor analysis (EFA) and calculating Cronbach’ Alpha coefficient. Finally, 35 observable items were found which were used to develop the official survey questionnaire to collect data to test the twenty research hypotheses presented in the proposed research model.

According to reports by EVBN (EU-Vietnam Business Network) (2016) and Kanta WorldPanel (2016/2019), urban areas in Vietnam have about 3 times more spending on dairy products than rural areas; Ho Chi Minh City (HCMC) and Hanoi are the two largest consumption markets, with the total annual spending on dairy products accounting for more than 20% of the whole country, in which, the total expenditure on dairy products of Hanoi people are about 70% compared to HCMC.

The convenience sampling technique was applied. The participants of this study were consumers, both men and women over 18 years old, who have been living and working in two big cities in Vietnam (Ho Chi Minh and Hanoi), in 2020. The population was limited to only who directly and regularly purchase/use powdered milk and/or fresh milk brands from dairy companies in Vietnam. The face-to-face interviews took place at supermarkets, shops specializing in selling dairy products, and convenience stores. The entire research sample was conducted through the Vietnam Advertising Research and Training Institute (ARTI Vietnam). About 500 people (in HCMC) and 350 people (in Hanoi) were approached through direct interviewing by the survey questionnaires designed on 5-point Likert scale, and resulted in 780 valid questionnaires. Table 1 shows the characteristics of the research sample.

Table 1. Sample characteristics.

Characteristics		Frequency	%	Cumulative (%)
Gender	Male	265	34.0	34.0
	Female	515	66.0	100.0
Geography	Ho Chi Minh City	477	61.2	61.2
	Hanoi	303	38.8	100.0
Age	18 – 29 years old	232	29.7	29.7
	30 – 39 years old	286	36.7	66.4
	40 – 49 years old	167	21.4	87.8
	>50 years old	95	12.2	100.0
Income	<7 mil. VND per month	260	33.3	33.3
	7 – 12 mil. VND per month	241	30.9	64.2
	12 – 20 mil. Per month	169	21.7	85.9
	> 20 mil. Per month	110	14.1	100.0
Academic level	High school or equivalent	430	55.1	55.1
	Undergraduates	258	33.1	88.2
	Graduates	92	11.8	100.0
Types of milk	Fresh milk	397	50.9	50.9
	Powdered milk	383	49.1	100.0
Brand Origin	Local (6 brands)	462	59.2	59.2
	Foreign (4 brands)	318	40.8	100.0
Total		780	100.0

Data processing was carried out through 3 steps: data screening, measurement assessment, and evaluation of the structural model. As a preliminary step, the data screening process included visually inspecting data for identifying missing data and testing violations of normality statistical assumptions. The next step employed are Exploring Factor Analysis (EFA) and Confirm Factor Analysis (CFA) for measurement assessment.

The internal consistency of the items of each construct was measured using Cronbach’s α with minimum requirement of Cronbach’s α coefficients is 0.6 (Hair et al., 2010). The Cronbach’s α coefficients ranged from 0.815–0.897 in this study. The minimum requirement of composite reliability is 0.6 (Hair et al., 2010), and the value of the construct reliability ranged from 0.815–0.897. The minimum requirement of factor loading was 0.5 (Hair et al., 2010). The value of the factor loading ranged from 0.689–0.888 in this study. All indicators of composite reliability (CR), ranged from 0.815–0.897 in this study, are higher than minimum requirement of 0.6 (Hair et al., 2010). To test the validity of the measurements, we used average variance extracted (AVE) to evaluate the discriminant validity of the measurements (Fornell & Larcker, 1981). In this study, the average variance extracted (AVE) are greater than the criterion of 0.5 (Hair et al., 2010) for all constructs. The measurement scales meet the criteria of discriminant value, unidimensional, convergence value as shown in Table 2 and 3.

Table 2. Results of Exploring Factor Analysis (EFA).

Observable items	Factor loading
	1	2	3	4	5	6	7	8
AS2. I can quickly recall the symbol or logo of X.	0.837
AS1. Some characteristics of X come to my mind quickly	0.828
AS7. When I think of X, I immediately think that the product’s quality is always improving.	0.819
AS5. The company that makes X is very interested in contributing to the increase of social security and welfare.	0.804
AS3. I have no difficulty in imagining X in my mind.	0.800
AW2. I can recognize X among other (competing) brands.		0.857
AW3. I know X being a type (product) of natural origin.		0.826
AW1. I recognize the logo of X.		0.796
AW4. I am aware of X’s packaging.		0.758
AW6. I know the taste of X well.		0.746
AD1. X is heavily advertised.			0.888
AD6. The ads for X are very different from other competing brands.			0.875
AD4. The ads for X are ‘like no other’.			0.855
AD2. X is heavily advertised compared to other brands.			0.828
CSM5. The company producing X commits to use part of its profits to support non-profit organizations, Social Funds.				0.881
CSM7. The company producing X regularly sponsors or/and performs activities to improve social welfare.				0.877
CSM1. The company producing X always ensures the interests of buyers/consumers.				0.875
CSM3. The company producing X always shows its responsibility to protect the environment.				0.862
BT3. I believe the quality of X is always continuous and consistent.					0.797
BT2. The company that makes X always ensures the quality as promised.					0.774
BT5. I trust the company that makes X.					0.759
BT4. The company producing X ensures the quality (of X) as advertised.					0.753
BT1. I trust X fully.					0.689
DI4. I can buy X everywhere in HCMC (Hanoi).						0.867
DI3. X should be distributed in as many stores and supermarkets as possible.						0.838
DI2. Most stores and supermarkets sell X.						0.820
DI1. X is presented in more stores and supermarkets than other competing brands.						0.709
QL5. X is the best brand in its product group.							0.824
QL4. X possesses great features.							0.812
QL1. X is a very good quality product.							0.791
QL6. Compared to other brands (of product), X is of very high quality.							0.757
LO3. If X is not available, I will not buy other brands.								0.887
LO2. When buying milk products, X is my first choice.								0.807
LO1. I love X very much.								0.796
LO4. I consider myself to be loyal to X.								0.690
Eigenvalue	9,460	3,217	2,734	20,334	1,905	1,668	1,380	1,181
Total Variance Explained	9,967	9,498	8,932	80,875	8,640	7,713	7,623	6,977
Variance Extracted	9,967	19,465	28,397	37,272	45,912	53,624	61,247	68,224
KMO	0,905
Bartlett’s Test	Chi square		14199,913
	df		595
	Sig.		0,000

Table 3. Results of reliability, construct validity of research concepts.

Research variables	Code	Number of items	CA	CR	AVE
Brand Awareness	AW	5	0.863	0.864	0.560
Brand Associations	AS	5	0.880	0.880	0.595
Perceived Quality	QL	4	0.815	0.815	0.525
Brand Trust	BT	5	0.832	0.833	0.503
Brand Loyalty	LO	4	0.842	0.842	0.571
Advertising	AD	4	0.889	0.890	0.670
Distribution Intensity	DI	4	0.831	0.833	0.558
Corporate Social Marketing	CSM	4	0.897	0.897	0.685

CA: Cronbach’s Alpha, CR: Composite Reliability, AVE: Average variance extracted.

(Source: author’s data analysis).

Testing measurement model (CFA) resulted in that all criteria meet standards of the model good fit indicators (Chi-square χ2 = 1174.560 (p =.000); CMIN/df = 2.208 (< 5 (Schumacker & Lomax, 2004)), TLI =.948 (> 0.9 (Hair et al., 2010)), CFI =.954 (> 0.9 (Hu & Bentler, 1999), and RMSEA = .039 (< 0.07 (Hair et al., 2010)) are accepted (shown in Figure 2).

Figure 2. Testing CFA results.

Notes: Cmin/df < 5 (Schumacker & Lomax, 2004), TLI > 0.90 (Hair et al., 2010), CFI > 0.90 (Hu & Bentler, 1999), RMSEA < 0.07 (Hair et al., 2010).

The results of the linear structure analysis (SEM) presented in Figure 3 show that the model is compatible with market data because of Chi-square χ2 = 1715,519, degrees of freedom df = 540 (p - value = 0.000), Cmin/df = 3.177 (< 5), TLI = 0.906 (> 0.9), CFI = 0.915 (> 0.9), and RMSEA = 0.053 (< 0.07).

Figure 3. The results of testing the research model.

The results of testing research hypotheses

Testing the research hypotheses (Table 4) showed that the relationship between AD and LO is not accepted at the significance level of 0.05 (P-value = 0.151). Hypothesis H2d assumes the relationship between AD and BT is accepted at 10% significance level (P = 0.062). The remaining 18 hypotheses are accepted at 5% significance level.

Table 4. Results of testing research hypotheses.

Relationship			Unstandardized regression estimate	Standardized regression estimate	S.E	C.R	P-value	Conclusion
AW	←	CSM	0.232	0.278	0.034	6.896	***	H1a accepted
AS	←	CSM	0.184	0.227	0.032	5.685	***	H1b accepted
QL	←	CSM	0.087	0.232	0.016	5.552	***	H1c accepted
BT	←	CSM	0.060	0.156	0.015	4.001	***	H1d accepted
LO	←	CSM	0.081	0.101	0.030	2.662	0.008	H1e accepted
AW	←	AD	0.065	0.080	0.031	2.060	0.039	H2a accepted
AS	←	AD	0.081	0.102	0.031	2.619	0.009	H2b accepted
QL	←	AD	0.048	0.132	0.015	3.227	0.001	H2c accepted
BT	←	AD	0.026	0.070	0.014	1.867	0.062	H2d accepted
LO	←	AD	0.038	0.049	0.027	1.437	0.151	H2e rejected
AW	←	DI	0.163	0.199	0.033	4.904	***	H3a accepted
AS	←	DI	0.112	0.142	0.032	3.512	***	H3b accepted
QL	←	DI	0.034	0.094	0.015	2.233	0.026	H3c accepted
BT	←	DI	0.040	0.107	0.014	2.784	0.005	H3d accepted
LO	←	DI	0.077	0.098	0.028	2.700	0.007	H3e accepted
LO	←	AW	0.201	0.210	0.036	5.538	***	H4 accepted
LO	←	AS	0.329	0.333	0.038	8.634	***	H5 accepted
LO	←	BT	0.492	0.235	0.096	5.120	***	H6 accepted
LO	←	QL	0.558	0.260	0.097	5.731	***	H7 accepted
BT	←	QL	0.472	0.462	0.049	9.615	***	H8 accepted

Notes: S.E. – standard error; C.R. – critical ratio; (***) – p value < 0.001.

Multigroup analysis for difference

To test the differences between groups, multigroup analysis was used, including variable and partial invariant models. In the variable method, the estimated parameters in each model of the groups are not constrained. In the partial invariant method, the measurement components are not constrained, but the relationships between the concepts in the research model are fixed to be the same for all groups. Chi-squared test was used to compare the two models. If the chi-square test shows that there is no difference between the invariant and the variable model (p-value > 0.05), the invariant model will be chosen because it has higher degrees of freedom. Conversely, if the Chi-square difference is significant (p - value < 0.05), the variable model is chosen because of its higher compatibility (Nguyen & Nguyen, 2009, 2011). The results of testing the difference of compatibility criteria (Table 5) showed that there is no difference between the invariant (partial) and variable models (P - value > 0.05) or confirmed that the impacts of CSM, distribution intensity and advertising on CBBE components are not affected by different consumer groups in purchasing different categories milk with different brand origin.

Table 5. Analysis results for difference between groups.

	χ^2	Df	p-value	CFI	TLI	RMSEA
Sex
Invariant (Partial)	1.936,599	1.100	0,000	0,938	0,933	0,031
Variant	1.928,643	1.080	0,000	0,937	0,931	0,032
Difference	7,956	20	0,992	0,001	0,002	0,001
Income
Invariant (Partial)	2.940,425	1.660	0,000	0,908	0,901	0,31
Variant	2.910,644	1.620	0,000	0,907	0,898	0,32
Difference	29,781	40	0,881	0,001	0,003	0,01
Age
Invariant (Partial)	2.321,014	1.100	0,000	0,912	0,905	0,38
Variant	2.295,593	1.082	0,000	0,912	0,903	0,38
Difference	25,475	18	0,112	0,000	0,002	0,00
Region
Invariant (Partial)	1.873,405	1.100	0,000	0,942	0,938	0,03
Variant	1.860,454	1.080	0,000	0,942	0,936	0,03
Difference	12,951	20	0,879	0,000	0,002	0,00
Milk types
Invariant (Partial)	2.218,161	1.099	0,000	0,919	0,912	0,36
Variant	2.205,989	1.082	0,000	0,918	0,910	0,37
Difference	12,172	17	0,790	0,001	0,002	0,01
Brand Origin
Invariant (Partial)	1.865,557	1.100	0,000	0,943	0,938	0,03
Variant	1.853,532	1.080	0,000	0,942	0,936	0,03
Difference	12,025	20	0,915	0,001	0,002	0,00

Finding discussion, recommendations, and limitation

Firstly, the research results show that CSM activities have a positive impact on consumers’ perception, attitude, and intention - behavior. The results imply that, nowadays consumers using dairy products identify and differentiate forms of CSM; they have been very interested in CSM, supporting brands. The results support the recommendation on CSM from the perspective of consumer perception and behavior of many authors (e.g. Deshpande, 2016; Hoeffler et al., 2006; Inoue & Kent, 2014; Truong & Hall, 2016). The results reinforced the conclusions of many authors such as CSM is increasingly widely applied (Drumwright, 1996; Drumwright & Murphy, 2001); the tendency to use CSM is increasing (Hoeffler & Keller, 2002; Truong & Hall, 2013, 2016); application of CSM is a clear trend because it connects the marketing activities of the business with the practical requirements of society (Andreasen, 1994, 2002; Kotler et al., 2012); CSM generates social benefits and business profits (Du et al., 2008); CSM increases both emotional and mental association with customers (Meyer, 1999), and impressions (associations) of businesses (Lichtenstein et al., 2004), etc.

Secondly, the positive impact of CSM, advertising, and distribution density on CBBE components imply that brand marketing program of dairy businesses should combine CSM programs with traditional marketing activites such as advertising and distribution density to incresase the effect of marketing activities on CBBE, due to the impact of CSM on CBBE components is stronger than that of advertising and distribution density supported by standardized beta coefficient (see Table 4). This result encourages dairy businesses to invest more in CSM initiatives/programs – consistent with the assertions – CSM of a business can create advantages to brand to win the heart and mind of skeptical consumers in hypercompetitive marketplace (Hoeffler et al., 2006, p. 55); CSM supports market development, increase sales or improve corporate impression (Bhattacharya et al., 2005; Bloom et al., 1997; Kotler & Lee, 2005); CSM differentiates a business from its competitors by forging emotional and spiritual bonds with consumers (Meyer, 1999); enhance credibility (perception and belief about attributes or characteristics of the business) and consumer loyalty towards the business (Inoue & Kent, 2012, 2014).

Thirdly, for dairy industry in Vietnam market, brand loyalty is directly affected by 04 other components of CBBE: brand awareness, brand association, perceived quality, brand trust implies that customers are loyal with milk brands having superior quality; good taste, beautiful, and eye-catching packaging. Their loyalty will increase the CBBE of that dairy product.

The concept of brand trust is first tested in the dairy industry in Vietnam, and exists in the perception of Vietnamese consumers (Nielsen, 2017), because it is closely related to the success of brands and businesses (Interbrand, 2018), and creates an opportunity for businesses to develop their brands (Bainbridge, 1997); as a mean to build, maintain and upgrade the perception of consumers to brand equity (Atilgan et al., 2009; Hiscock, 2001; Keller, 2003; LaBahn & Kohli, 1997); and then impact on consumption behavior (Keller, 1993; Krishnan, 1996).

The study findings contribute to some of the theorical implications. This study adds to the existing literature in several ways: (1) propose a research model to evaluate the impact of marketing on five dimensions of CBBE based on the perspective of Cognitive Consumer Behavior, namely the TPB model (Ajzen, 1985, 1991, 2019), (2) identify factors building CBBE which represents a key priority for academics and marketers (Baldauf et al., 2009). From practical perspective, this study confirmed to role of CSM in building the dairy brand by investigating how CSM initiatives, one of the effective sustainable marketing strategies for boosting firms’s concerns and consumers engagement, affects towards CBBE dimensions. The study finds the five dimensions of CBBE and the causal relationships among these dimensions, which provides useful insights in the brand marketing tasks of companies (Buil et al., 2013b; Lehmann et al., 2008).

The research’ results have supplemented and reinforced the findings and comments from previous studies; thereby, the empirical evidence of the impact of CSM based on consumer perception on CBBE in dairy industry in a transition market like Vietnam has been found, however, the generalizability of the research’s findings may be low because the study was conducted in a specific industry. Further research suggested should be a comparative study between different industries in the same country, or between different countries with the same industry. It is expected that the further research’s findings will bring more insights into the role of CSM in company branding.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Thi Quy Vo

Thi Quy Vo, School of Business, International University, Vietnam National University, HCM, Quarter 6, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam. She is working for International University being university member of Vietnam National University Ho Chi Minh (VNUHCM) as a senior lecturer. Currently, she is the Director of Academic Programme and key trainer of SMEI Vietnam for training professional certification in Sales & Marketing International in Vietnam. She completed her master’s and Ph.D. Degrees from the Asian Institute ofTechnology (AIT) specialized in International Business. She was promoted to associate professor in 2012. She has been the holder of CME® - Certified Marketing Executive® from 2011 to the present. She has published more than 50 publications in both international journals and domestic journals. Her scientific articles focus on firm performance, bank efficiency, and customer behavior. She also wrote business cases book in Vietnamese published by VNU Press (2019), a domestic prestigious publisher and they have been used to teach students specialized in business administration major.

Tuan Nguyen-Anh

Tuan Nguyen-Anh, Marketing Faculty, University of Finance – Marketing, Ho Cho Minh City, Vietnam; He have been working for University of Finance – Marketing (UFM) as a lecturer in field marketing from 2004 to now. He completed his MBA (in 2004) and degree of Ph.D in Management (in 2021) from the University of Economics, HCM. He is actively involved in research, particularly in the field of marketing, suatainable marketing, brand management and public relations. He has published many research papers in various journals of National and International repute. He is co-author Marketing Management book in Vietnamese published by VNU Press (2016), and they have been used to teach students specialized in marketing major, UFM.