Brand image and customer loyalty: Transmitting roles of cognitive and affective brand trust

Main Article Content

Liang Huang
Muning Wang
Zhiling Chen
Benchi Deng
Wenfeng Huang
Cite this article:  Huang, L., Wang, M., Chen, Z., Deng, B., & Huang, W. (2020). Brand image and customer loyalty: Transmitting roles of cognitive and affective brand trust. Social Behavior and Personality: An international journal, 48(5), e9069.


Abstract
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In this study we explored the effect of brand trust on the relationship between brand image and customer loyalty. We took Procter & Gamble as the target brand and developed and tested a theoretical model regarding the relationships among brand image, brand trust (i.e., cognitive and affective), and customer loyalty (i.e., repurchase and advocacy intention) using path analysis and bias-corrected bootstrapping. Empirical results of data from 283 consumers revealed that brand image was positively related to both cognitive and affective brand trust. Brand image was indirectly correlated with both repurchase and advocacy intention through cognitive brand trust, and brand image was indirectly related to advocacy intention through affective brand trust. These findings provide a basis for enterprise marketing management to enhance customer loyalty by shaping the brand image.

The acceleration of global economic integration and fierce business competition has challenged the ways in which customer loyalty is established and maintained. This has encouraged enterprise management to pay increasing attention to these aspects of their business (Alhaddad, 2015). Many well-known multinational corporations, such as Procter & Gamble, rely on customer loyalty to survive, thrive, and excel in a competitive marketplace (Decker, 1998). Researchers have shown that customer loyalty can provide long-term benefits for business enterprises to sustain their competitiveness (Fernandes & Moreira, 2019). Given the growing salience of customer loyalty, researchers have identified factors that are conducive to customer loyalty enhancement, such as brand image, brand trust, brand affect, and customer satisfaction (Ahmed, Rizwan, Ahmad, & Haq, 2014; Alhaddad, 2015; Anwar, Gulzar, Sohail, & Akram, 2011; Fernandes & Moreira, 2019; Khamitov, Wang, & Thomson, 2019; Lin & Chuang, 2018).

Brand image refers to consumers’ perceptions and feelings about a brand, which generally determine their cognitive, emotional, and attitudinal outcomes regarding the brand (Cho, Fiore, & Russell, 2015). Previous findings have shown that brand image significantly affects consumer purchase intention (Chen, Chen, & Huang, 2012), and positively influences customer satisfaction, thereby fostering customer loyalty (Elsäßer & Wirtz, 2017). Although customer satisfaction is a necessary transmitter for brand image to generate customer loyalty, other factors can aid brand image in enhancing customer loyalty. These factors should be explored further to enrich the understanding of the transmitting mechanism between brand image and customer loyalty.

Trust plays a key role in achieving customer loyalty (Ahmed et al., 2014; Sun & Lin, 2010). Brand trust, which reflects the willingness of consumers to rely on the ability of the brand products to perform their stated function, is an important variable to improve the understanding of the brand–customer relationship (Menidjel, Benhabib, & Bilgihan, 2017). In general, researchers have paid insufficient attention to whether brand trust exerts a significant effect on the relationship between brand image and customer loyalty, and also to the roles of the different aspects of brand trust in this relationship. Although Alhaddad (2015) found positive relationships among brand image, brand trust, and brand loyalty, a theoretical explanation of these relationships remains unclarified. To address these research gaps, we examined the effects of the two aspects (cognitive and affective) of brand trust on the relationship between brand image and the two aspects (repurchase intention and advocacy intention) of customer loyalty, using Procter & Gamble as the target brand.

Literature Review and Hypothesis Development

Brand Image and Brand Trust

Brand image has been conceptualized in various ways, such as the representation of the tangible and intangible attributes and benefits of a brand (Cho et al., 2015). Dichter (1985) asserted that brand image describes the personal characteristics of a brand’s products and reflects consumers’ overall impression of the brand. Long, Sha, and Gan (2010) proposed that brand image is the integration of consumers’ perceptions and evaluation of, and associations with, a brand’s main characteristics, and their mental response to the brand’s essential elements. Long et al. developed a five-dimensional brand image model that comprised user, corporate, product, service, and visual image. They verified this model based on fast-moving consumer goods industry samples in China. As brand user image and brand personality are perceived to be somewhat transposable (Parker, 2009; Yang & Bolchini, 2014), and brand personality may be distinct from brand image (Hosany, Ekinci, & Uysal, 2007; Lau & Phau, 2007), researchers have debated if the brand image construct should include the user image dimension (Parker, 2009), which we did not include in this study. We mainly drew on Long et al.’s brand image definition to refine the conceptual definition of brand image.

Brand trust can be classified as either cognitive or affective (Chai, Malhotra, & Alpert, 2015; Johnson & Grayson, 2005). Cognitive brand trust refers to knowledge-driven trust in a brand, wherein consumers’ trust is based on good reasons for using the brand (Srivastava, Dash, & Mookerjee, 2015). Cognitive brand trust involves careful methodical thought to determine if a brand is trustworthy (Morrow, Hansen, & Pearson, 2004). Cognitive brand trust is thus derived from consumers’ evaluation of the expertise and performance of a brand provider in terms of competence, reliability, and credentials (Johnson & Grayson, 2005). The economic benefits associated with a brand and its related products and services shape consumers’ cognitive brand trust by reducing their risk perception and enhancing their performance expectations (Ali, Guo, Sherwani, & Ali, 2018; Banerjee, 2018; Cho et al., 2015).

Affective brand trust is defined as a consumer’s belief based on the level of care and concern displayed by the brand maker or provider (Srivastava et al., 2015). Affective brand trust is characterized as consumers’ feelings of security and perceptions regarding the strength of the brand–customer relationship (Johnson & Grayson, 2005). The sensory elements of brand image, which are significant factors in inducing consumers’ emotional pleasure and arousal, contribute to developing consumers’ affective brand trust by shaping their affection and love for the brand through their interaction with the brand (Cho et al., 2015; Cui, 2019). Therefore, we proposed the following hypotheses:
Hypothesis 1a: Brand image will be positively related to cognitive brand trust.
Hypothesis 1b: Brand image will be positively related to affective brand trust.

Brand Trust and Customer Loyalty

Customer loyalty is a sophisticated concept that comprises two dimensions (Chai et al., 2015), namely, instrumental (i.e., repurchase intention) and expressive (i.e., advocacy intention). Repurchase intention is an instrumental response that is aroused by self-interest and economic factors (Jones, Taylor, & Bansal, 2008) and is described as consumers’ judgment of repurchasing a brand (Chai et al., 2015). Advocacy intention, also known as word-of-mouth recommendation intention, is an expressive response that is promoted by affective factors, and refers to the likelihood that consumers will recommend a brand to others (Chai et al., 2015).

As consumers with strong cognitive brand trust have gained economic benefits from their brand interactions, they tend to rely on, and boost their relationship with, the brand in instrumental ways, thereby inducing strong repurchase intention. Cognitive brand trust also reduces the exchange uncertainty among consumers and strengthens the brand–consumer relationship (Ranganathan, Madupu, Sen, & Brooks, 2013), thereby increasing consumers’ affective brand attachment (Dessart, 2017). Consumers with strong cognitive brand trust may thus exhibit a strong tendency to promote the brand through word-of-mouth communication. Therefore, we proposed the following hypotheses:
Hypothesis 2a: Cognitive brand trust will be positively related to repurchase intention.
Hypothesis 2b: Cognitive brand trust will be positively related to advocacy intention.

Affective brand trust involves consumers’ emotional reliance on a brand (Srivastava et al., 2015). Those with significant emotional reliance on a brand derive substantial attachment and commitment from their strong affective brand trust. As this strengthens their awareness of their high-quality brand exchange relationship, these consumers exhibit strong motivation to maintain this valued relationship, thereby strengthening their tendency to repurchase the brand’s products (Chaudhuri & Holbrook, 2001). Further, as these consumers tend to receive various social benefits (e.g., fun and enjoyment) from their brand exchanges, and they tend to maintain and enhance the positive feelings derived from this interaction (Chai et al., 2015; Chiu, Wang, Fang, & Huang, 2014), they are thus motivated to recommend the brand to others. Therefore, we proposed the following hypotheses:
Hypothesis 3a: Affective brand trust will be positively related to repurchase intention.
Hypothesis 3b: Affective brand trust will be positively related to advocacy intention.

Transmitting Roles of Cognitive and Affective Brand Trust

A good brand image can impress consumers with its tangible and functional attributes (Long et al., 2010). This can increase consumers’ economic benefits through their exchange with the brand, thereby developing their cognitive brand trust, which can subsequently motivate consumers to enhance and commit to the brand–customer relationship in terms of both instrumental and expressive loyalty (i.e., repurchase and advocacy intention). In addition, an effective brand image has emotional characteristics that can provide consumers with social gains, and thereby cultivate their affective brand trust (Long et al., 2010), which can further drive consumers to value the brand–consumer relationship and to maintain positive feelings toward the brand. These feelings are manifested as strong repurchase and advocacy intention toward the brand. Therefore, we proposed the following hypotheses:
Hypothesis 4a: Brand image will have a positive indirect relationship with repurchase intention through cognitive brand trust.
Hypothesis 4b: Brand image will have a positive indirect relationship with advocacy intention through cognitive brand trust.
Hypothesis 5a: Brand image will have a positive indirect relationship with repurchase intention through affective brand trust.
Hypothesis 5b: Brand image will have a positive indirect relationship with advocacy intention through affective brand trust.

The theoretical model is shown in Figure 1.

Table/Figure

Figure 1. Theoretical model.

Method

Participants and Procedure

We chose Procter & Gamble brands as they are popular international brands, and attract a wide range of users in China. As they also have a considerable number of subbrands, we could easily obtain representative samples. We randomly selected 10 consumers to participate in the pilot test and to offer feedback to improve the quality of the survey items prior to the formal investigation. After considering this feedback, we transformed the wording of reverse-scored items in both the cognitive and affective brand trust scales, to express them in a positive tone. Subsequently, one author electronically distributed the survey to 308 consumers in China, using the snowball sampling method, with help from her friends and relatives. Participants were informed of the purpose of the study and were guaranteed that their responses would be used for academic purposes only, and that their private information was confidential. Further, we assured participants that their participation was voluntary, and they were informed that there was no remuneration.

We received valid responses from 283 participants, who had the following demographic characteristics: Regarding gender, the percentages of men and women were 43.11% and 56.89%, respectively. In terms of age, the percentage of participants under 18 years was 0.71%, and 43.82% were aged from 18 to 25, 40.28% were aged from 26 to 30, 12.01% were aged from 31 to 40, and 3.18% were 41 years old and older. Regarding education, the percentage of participants who had a junior high school education or below = 0.35%, high school education or special secondary school education = 5.30%, college degree = 24.03% bachelor’s degree = 66.43%, and master’s degree and above = 3.89%. Regarding occupation, the percentage of homemakers = 2.12%, enterprise or institution employees = 50.53%, merchants = 7.07%, students = 35.69%, and other occupations = 4.59%. Regarding monthly income, the percentage of participants with income below RMB 2,500 (USD 352) = 36.75%, RMB 2,500–3,499 (US493) = 18.02%, RMB 3,500–4,499 (US634) = 19.08%, RMB 4,500–5,499 (US775) = 12.37%, RMB 5,500–6,499 (US916) = 7.42%, RMB 6,500–7,499 (US1057) = 3.89%, and equal to and above 7,500 RMB = 2.47%. Regarding the monthly expenditure on fast-moving consumer goods, the percentage of participants who spent RMB 149 (US21) and below = 13.78%, RMB 150–349 (US50) = 25.09%, RMB 350–549 (US78) = 21.20%, RMB 550–749 (US106) = 19.43%, RMB 750–949 (US134) = 9.19%, RMB 950–1,199 (US169) = 6.01%, and equal to and above 1,200 RMB = 5.30%.

Measures

All the measures were rated on a 5-point Likert scale that ranged from 1 = totally disagree to 5 = totally agree. Except for brand image, we used Brislin’s (1980) translation/back-translation procedure to guarantee semantic equivalence of the original English measures. Management and linguistic professors (including one author) partook in and completed the procedure.

Brand image. We measured brand image with an 18-item scale that was developed by Long et al. (2010) in China. The scale comprises four dimensions, namely, corporate image, product image, service image, and visual image. Sample items are “The company is an industry leader” (corporate image), “The products of this brand work well” (product image), “The services of this brand has advantages in the industry” (service image), and “The visual image of this brand identity is superior” (visual image).

Cognitive brand trust. Cognitive brand trust was measured with a three-item scale developed by Srivastava et al. (2015). A sample item is “I can confidently depend on this brand since it does not adversely affect me by functioning carelessly.”

Affective brand trust. Affective brand trust was measured with four items developed by Srivastava et al. (2015). A sample item is “This brand isn't only interested in selling products.”

Advocacy intention. Advocacy intention was measured with four items from Chai et al. (2015). A sample item is “I will say positive things about this brand to other people.”

Repurchase intention. We measured repurchase intention with three items from Chai et al.’s (2015) scale. A sample item is “I will probably use this brand again.”

As shown in Table 2, Cronbach’s alpha for the five constructs ranged from .80 to .94, all of which were of acceptable reliability.

Control variables. We treated brand familiarity, customer satisfaction, gender, age, and education as control variables in the path analysis model, according to previous research on antecedents of customer loyalty (e.g., Anić, Piri Rajh, & Rajh, 2014; Elsäßer & Wirtz, 2017).

We adopted the brand familiarity questionnaire survey (four items; Mieres, Martín, & Gutiérrez, 2006). A sample item is “I have plenty of experience in using this brand.” We also used the customer satisfaction questionnaire survey (three items; Lee & Back, 2009). A sample item is “Overall, I am satisfied with this brand.” Cronbach’s alpha for these measures were .86 and .82, respectively, both indicative of acceptable reliability.

Hypothesis Testing Method

We used path analysis and bias-corrected bootstrapping with 5,000 resampling replications to test our hypotheses. We employed Mplus 6.12 to obtain the empirical results.

Results

Confirmatory Factor Analysis

We conducted confirmatory factor analysis using the indices of comparative fit index (CFI), Tucker–Lewis index (TLI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR) to verify the construct validity of the study variables, using AMOS 22. The results, as shown in Table 1, reveal that the five-factor model yielded a better fit to the data than the other nested models (i.e., all the Δχ2 were significant at the .001 level), namely, the best fit four-, three-, two-, and one-factor models. The CFI and TLI of the five-factor model were greater than .90, and the RMSEA and SRMR were lower than .08. Moreover, in the five-factor model, all average variance extracted (AVE) values of latent variables, ranging from .55 to .68, were greater than .50, and all the factor loadings of latent variables were greater than .64 and significantly positive. In summary, the key variables exhibited acceptable construct validity.

Table 1. Results of Confirmatory Factor Analysis

Table/Figure

Note. BI = brand image, ABT = affective brand trust, CBT = cognitive brand trust, RI = repurchase intention, AI = advocacy intention, CFI = comparative fit index, TLI = Tucker–Lewis index, RMSEA = root mean square error of approximation, SRMR = standardized root mean square residual. Models 2 to 4 are the best fit of the four-, three-, and two-factor models.
*** p < .001.

Hypothesis Testing

As shown in Table 2, the correlations of brand image with both cognitive and affective brand trust, of cognitive brand trust with both advocacy and repurchase intention, and of emotional brand trust with both advocacy and repurchase intention were all significantly positive. Thus, the results provided preliminary support for our assumptions. The empirical results of all the hypotheses indicated that the model depicted in Figure 2 was a saturated model with a perfect fit, χ2(0) = 0, CFI = 1.00, TLI = 1.00, RMSEA = .00, SRMR = .00. The significant positive relationships between brand image and cognitive brand trust (β = .86, SE = 0.10, t = 9.09, p < .001), and between brand image and affective brand trust (β = .91, SE = 0.09, t = 10.72, p < .001) are shown in Figure 2. Hypotheses 1a and 1b were thus supported. There was a positive relationship between cognitive brand trust and repurchase intention (β = .18, SE = 0.07, t = 2.68, p < .01), and between cognitive brand trust and advocacy intention (β = .18, SE = 0.07, t = 2.65, p < .01). Therefore, Hypotheses 2a and 2b were supported. In addition, there was a significant positive relationship between affective brand trust and advocacy intention (β = .37, SE = 0.07, t = 5.02, p < .001), but the relationship between affective brand trust and repurchase intention was not significant (β = .08, SE = 0.09, t = 0.95, ns). Therefore, Hypothesis 3a was not supported, but Hypothesis 3b was supported.

Table 2. Means, Standard Deviations, and Correlations Among Study Variables

Table/Figure

Note. N = 283. Cronbach’s α for corresponding constructs are shown on the diagonal.
*** p < .001.

Table/Figure

Figure 2. Path coefficients. Solid line denotes significant path, and dotted line denotes nonsignificant path.
** p < .01, *** p < .001.

We tested the transmitting roles of brand trust using bias-corrected bootstrapping (see Table 3). The transmitting effect of cognitive brand trust on the correlation between brand image and repurchase intention and between brand image and advocacy intention was significant. Thus, Hypotheses 4a and 4b were supported. The transmitting effect of affective brand trust on the correlation between brand image and advocacy intention was significant, but the effect on the relationship between brand image and repurchase intention was not significant. Thus, Hypothesis 5b was supported, whereas Hypothesis 5a was not supported.

Table 3. Results of Transmitting Effects Testing

Table/Figure

Note. BI = brand image, CBT = cognitive brand trust, ABT = affective brand trust, AI = advocacy intention, RI = repurchase intention.

Discussion

We developed a theoretical model to investigate the relationships among brand image, brand trust (i.e., cognitive and affective), and customer loyalty (i.e., repurchase and advocacy intention) and obtained the following empirical results: First, brand image was positively correlated with cognitive and affective brand trust. Previous researchers have traditionally treated brand trust as a construct comprising two aspects that indicate consumers’ belief in the competence of the brand (brand reliability), and the positive intention toward consumers (brand intention; Munuera-Alemán, Delgado-Ballester, & Yagüe-Guillén, 2003; Wottrich, Verlegh, & Smit, 2017). These researchers primarily focused on the cognitive aspect of consumers’ brand trust, but, as they failed to capture its emotional aspect, this may not comprehensively explain the brand image and brand trust relationship. We have provided a more comprehensive view to account for the cognitive and emotional process between consumers’ brand image and cognitive and affective brand trust. Thus, we have enhanced theoretical understanding of the brand image–brand trust relationship.

Second, cognitive brand trust played a transmitting role in the relationships between brand image and advocacy intention, and between brand image and repurchase intention. Affective brand trust, however, played a transmitting role only in the relationship between brand image and advocacy intention. Previous researchers have focused on the relationship between brand image and customer loyalty (e.g., Anwar et al., 2011; Lin & Chuang, 2018) and have found that customer satisfaction mediated that relationship (Bloemer & de Ruyter, 1998; Kandampully & Suhartanto, 2000). Correlations were also found among brand image, brand trust, and brand loyalty (Alhaddad, 2015). However, scholarly knowledge about the unique role of brand trust in the relationship between brand image and customer loyalty was vague. We based this study on the differentiation of the two forms of brand trust and the two divergent aspects of customer loyalty and, by controlling for the effect of the previously highlighted customer satisfaction, we confirmed that cognitive and emotional brand trust exerted distinct transmitting effects on the relationships between brand image and repurchase intention, and between brand image and advocacy intention. Thus, our results contribute to the understanding of the relationship between brand image and customer loyalty from the perspective of brand trust, and the cognitive and emotional process within the brand image–customer loyalty relationship.

Third, as the relationship between affective brand trust and repurchase intention was not significant, this result showed that brand image was not indirectly related to repurchase intention through affective brand trust. This result could be because affective brand trust is based on emotional factors, such as fondness for the brand, whereas repurchase intention is motivated by economic factors, such as cost benefit evaluation of the brand (Chai et al., 2015). As the emotional factors that serve as the basis of affective brand trust may be irrational, it is reasonable to suggest that affective brand trust is not related to the rational aspect of consumer loyalty (i.e., repurchase intention). This leads to a nonsignificant indirect connection between brand image and repurchase decision through affective brand trust. This result indicates a significant gap between the emotional aspect of brand trust and the rational aspect of customer loyalty. Thus, the indirect link of brand image to repurchase intention through an emotional process was not significant. Moreover, the situation of the relationship between affective brand trust and repurchase intention, and the indirect link between brand image and repurchase intention through affective brand trust, both being positive, seems to be understudied. In particular, consumers’ analytical thinking, which is characterized as a rational, conscious, and reflective cognitive style (Evans, 2008), may be a potential facilitator for ensuring that the relationship between affective brand trust and repurchase intention is positive, and thereby also ensuring the significant indirect effect between brand image and repurchase intention through affective brand trust. Because strong analytical thinking can provide consumers with rational ways to evaluate and react to their liking for a brand, this cognitive style can make consumers with affective brand trust generate rational intention toward their favorite brand (i.e., repurchase intention). This inference merits future examination.

Our findings also have important implications for enterprise marketing management personnel. They should pay attention to the brand image construction of their businesses, particularly in the construction of their visual, corporate, product, and service images, because, according to our findings, brand image was indirectly related to different aspects of customer loyalty through emotional and cognitive processes. First, additional personalized products should be offered to consumers according to their diverse needs, to enhance their visual image of a brand. Second, to help consumers establish emotional connections with a brand, managers should engage in activities based on corporate social responsibility, which demonstrate humanistic care, thereby improving the corporate image associated with the brand. Third, managers should continually work to improve product quality and provide quality-assured products to consumers, thereby strengthening the product image of the brand. Fourth, managers should constantly improve the service quality of the company, to strengthen the brand’s service image. Further, we selected as our target brand, Procter & Gamble, the successful experiences of which in brand image creation keep it grounded in its deep-rooted purpose, values, and principles. Such practices provide a model from which local company managers in China selling brands of fast-moving consumer goods can learn, such as a precise understanding of the preferences of consumers in different segments, the establishment of long-lasting connections with innovators worldwide to solve the problems that deter firms from better meeting consumers’ diverse needs, and the provision of distinctive and innovative products preferred by consumers.

There are several limitations in this study. First, Procter & Gamble was the only sample that we empirically examined, and we electronically surveyed Chinese consumers. Therefore, our evidence may not be sufficient to be generalized to other brands. Future researchers can verify our results by including other brands and investigating additional diverse samples. Second, as our results were drawn from cross-sectional data, this does not satisfy causal inference requirements. Therefore, future researchers should use an experimental design or collect multisource survey data at multiple time points to accurately verify our results. Third, we disregarded any moderator in our brand image–brand trust–customer loyalty process analysis. Future researchers can thus explore potential boundary conditions of consumers’ individual differences (e.g., Big Five personality traits) in the relationship to improve the generality of our results. For example, future researchers can explore if consumer agreeableness can enhance the relationship between brand image and brand trust, and consequently facilitate the brand image–brand trust–customer loyalty process.

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Table/Figure

Figure 1. Theoretical model.


Table 1. Results of Confirmatory Factor Analysis

Table/Figure

Note. BI = brand image, ABT = affective brand trust, CBT = cognitive brand trust, RI = repurchase intention, AI = advocacy intention, CFI = comparative fit index, TLI = Tucker–Lewis index, RMSEA = root mean square error of approximation, SRMR = standardized root mean square residual. Models 2 to 4 are the best fit of the four-, three-, and two-factor models.
*** p < .001.


Table 2. Means, Standard Deviations, and Correlations Among Study Variables

Table/Figure

Note. N = 283. Cronbach’s α for corresponding constructs are shown on the diagonal.
*** p < .001.


Table/Figure

Figure 2. Path coefficients. Solid line denotes significant path, and dotted line denotes nonsignificant path.
** p < .01, *** p < .001.


Table 3. Results of Transmitting Effects Testing

Table/Figure

Note. BI = brand image, CBT = cognitive brand trust, ABT = affective brand trust, AI = advocacy intention, RI = repurchase intention.


Wenfeng Huang, International Business School, Guangdong University of Finance and Economics, Foshan 528100, People’s Republic of China. Email: [email protected]

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