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Influence of Brand Trust, Perceived Value on Brand Preference and Purchase Intention

  • DAM, Tri Cuong (Lecturer, Faculty of Business Administration, Industrial University of Ho Chi Minh City)
  • Received : 2020.08.01
  • Accepted : 2020.09.10
  • Published : 2020.10.30

Abstract

The aim of this research was to empirical examine the influence of brand trust, perceived value on brand preference, and purchase intention for branded phones. The samples were gathered by a convenient sampling method. We collected data from 285 consumers who were visiting electronic supermarkets in Ho Chi Minh City, Vietnam. The measurement used a 5-point Likert scale ranging from 1=completely disagree, and 5=completely agree. PLS - Partial Least Squares method was performed to analyze the measurement model and the structural model. The study model was proposed from prior research. We had assessed the reliability of the scales through Cronbach's alpha and composite reliability. As well, we also had evaluated discriminant validity through the Fornell-Larcker criterion. The findings of the study demonstrated that brand trust had a significantly positive influence on brand preference. Likewise, the findings of the research also stated that brand trust had a positive impact on purchase intention. The results revealed that perceived value had a positive effect on brand preference. Furthermore, the outcomes show that perceived value had a positive influence on purchase intention as well. Furthermore, the findings of the research showed that brand preference had a positive effect on purchase intention.

Keywords

1. Introduction

Purchasing intention has been one of the principal topics examined in the marketing literature, and triggered the interest of marketing scholars on purchase intention coming from buying behavior. Besides, practitioners also have studied purchase intention to predict transactions of current and new goods/services. Purchase intention information could support practitioners in their marketing decisions linked to goods (new and current), market segmentation, and promotion plans (Tsiotsou, 2006). Therefore, how to get customers to purchase commodities has become essential to marketers because customers have more opportunities to choose the goods in a competitive and fluctuating business context recently (Choi et al., 2020).

Moreover, trust has been one of the essential elements of long-term and reliable connections between persons. Personal relationships were often employed as a comparison when describing the connection between the brand and the purchaser (Fournier, 1998). In this view, brand trust unveiled its vital importance in individual relationships and the building of a lasting connection between the brand and the purchaser (Aydin & Taskin, 2014). Some scholars said that brand trust was a precursor of brand preference (Afsar, 2014; Chinomona et al., 2013) and purchase intention (Aydin et al., 2014; Chae et al., 2020).

On the other hand, previous research revealed that perceived value was an antecedent of brand preference (Hellier et al., 2003; Muzakir & Damrus, 2018) and purchase intention (Calvo-Porral & Lévy-Mangin, 2017; Hu, 2011). Brand preference was the component that pushed consumers to buy the brand and to repeat this activity (Ebrahim et al., 2016; Soenyoto, 2015). Besides, some empirical studies confirmed that brand preference was a predictor of purchase intention (Chen & Chang, 2008; Emor & Pangemanan, 2015; Pool et al., 2018).

Prior studies involving phones brands such as Vazifehdoost el al. (2014) declared that brand experience, trust in brand, pleasure with brand, and symbolic brand value had direct effects on loyalty to brand (Vazifehdoost et al., 2014). Khundyz (2018) affirmed that brand image, customer satisfaction, brand trust, and promotion had direct impacts on brand loyalty (Khundyz, 2018). Surucu et al. (2020) disclosed that factors, such as brand trust and reference groups, affected the purchasing intention of young adults, in which the reference group was a key factor causing the purchasing intentions of young adults (Surucu et al., 2020). Other scholars examined the impact of attitudes on clients’ intention to participate in online fashion sharing (Won & Kim, 2020). In Vietnam, Wollenberg and Thuong (2014) disclosed that factors (advertising, word of mouth, perceived quality, price) had positive influences on brand perception. The authors also said that advertising, word of mouth, perceived quality, price, and brand perception had direct effects on customer purchasing decisions (Wollenberg & Thang, 2014). However, there have not been many scholars examining the impact of brand trust and perceived value on brand preference and purchase intention, especially in branded phones in Vietnam. Therefore, in this current empirical study, we analyze the influence of brand trust and perceived value on brand preference and purchase intention for branded phones.

2. Literature Review and Hypotheses

2.1. Purchase Intention

Fishbein and Ajzen (1975) stated that purchase intention was the consumer’s real intention towards commoditizes (Fishbein & Ajzen, 1975). Purchase intention was considered as the mix of consumers’ concerns and the chance of buying the goods. Some previous research acknowledged that purchase intention related sharply to attitude and preference toward the brand or the product (Kim & Ko, 2012; Martín-Consuegra et al., 2018). Kotler (2003) demonstrated that purchase intention could also be affected by an individual’s perceptions and unforeseeable situations. An individual’s opinions related to private preference and unforeseen circumstances pointed to the conditions that change the purchase intention (Kotler, 2003). Furthermore, other scholars posited that buying intention was defined as the tendency of the consumers to purchase the goods. The more a customer would like to buy a product, the higher the purchase intention (Dodds et al., 1991; Schiffman & Kanuk, 2000).

2.2. Brand Trust

In the branding literature, the concept of brand trust is based on the perspective of a brand-consumer relationship (Zehir et al., 2011). There have been several concepts of brand trust in the current branding literature (Shin et al., 2019). Trust was considered as consumers’ confidence in the quality and trustworthiness of the products provided by the seller (Garbarino & Johnson, 1999). Chaudhuri and Holbrook (2001) revealed that brand trust was acknowledged as the clients’ readiness to rely on the sense of the brand to deliver its declared goal (Chaudhuri & Holbrook, 2001). Likewise, brand trust is an expression of believing while connecting with the brand relies on the thinking that the brand will continue to be reliable and satisfying the purchaser (Delgado-Ballester et al., 2003). The concept of trust is only proper in the circumstances of risk (e.g., in case of wider or smaller variety amongst brands). Accurately, trust declined in the situations where the buyer perceived the goods to be very unsafe as they knew they could rely on the trusted brand (Chaudhuri & Holbrook, 2001; Doney & Cannon, 1997). The brand trust also was defined as a purchaser’s willingness to depend on the brand from the viewpoint of uncertainty since anticipating that the brand will deliver positive outcomes (Lau & Lee, 1999).

Some scholars stated that, when consumers increased trust in a particular brand, repurchasing was likely to happen, starting to brand preference (Chinomona et al., 2013; Sheth & Parvatijar, 1995). Previous research demonstrated that brand trust was a predictor of brand preference (Afsar, 2014; Chinomona et al., 2013). Furthermore, there was an impact between brand trust and purchase intention, which indicates if brand trust has developed, then the rate of purchase intention will grow (Aydin et al., 2014; Sanny et al., 2020). Prior studies confirmed that brand trust had a positive effect on purchase intention (Aydin et al., 2014; Sanny et al., 2020). Therefore, we suggested the following hypotheses:

H1: Brand trust has a positive effect on brand preference.

H2: Brand trust has a significant influence on purchase intention.

2.3. Perceived Value

Perceived value was the concept that has been attracted researchers (Hanaysha, 2018; Zeithaml, 1988). Perceived value has been studied from four different angles. First, the value was the price. In other words, the value could be regarded the same as price. Second, the value was what I got for what I paid. Thirdly, the value was the trade-off between the quality of the goods and the price. The second and third meanings represented the fundamental role of value in the process of exchange and described the tradeoff between cost and benefit. Finally, the value was an overall evaluation of a target of subjective judgment with the attention of evaluation criteria (Pan & Kang, 2017; Zeithaml, 1988). Other scholars stated that the perceived value, in the narrowest sense, was the price paid for the product/service. More broadly, the perceived value was the sum that purchasers paid to get the benefits of having or utilizing the product/service (Kotler & Armstrong, 2016). Perceived value also was defined as consumers’ general evaluation of the product’s benefits with the expense and time that they gave to get the product (Hellier et al., 2003).

Prior research showed that perceived value was a crucial antecedent of brand preference (Ebrahim et al., 2016; Hellier et al., 2003; Muzakir & Damrus, 2018) and had a positive influence on brand preference (Ebrahim et al., 2016; Hellier et al., 2003; Muzakir & Damrus, 2018). Besides, some studies indicated that perceived value was a precursor of purchase intention (Calvo-Porral & Lévy-Mangin, 2017; Y. Hu, 2011). Prior empirical researches revealed that perceived value had a positive influence on purchase intention (Calvo-Porral & Lévy-Mangin, 2017; Hsieh, 2016; Hu, 2011). Therefore, we proposed the next hypotheses:

H3: Perceived value has a significant impact on brand preference.

H4: Perceived value has a positive influence on purchase intention.

2.4. Brand Preference

Brand preference is a notion that has interested scholars recently (Pool et al., 2018; Vongurai, 2020). Brand preference was defined as customers’ tendency towards certain brands that review their cognitive information processing towards brand stimuli. This concept highlighted the central control unit and the mental abilities of customers (Bettman et al., 1975; Ebrahim et al., 2016). Therefore, this indicated that a purchaser’s perception of brand attributes leads to preferences or attitudes, which impacts his/her intentions and brand choices (Bagozzi, 1982). The preference described a shifting phase between the inputs and outputs of the purchaser choice model. It was the link between information processing and the intention to purchase or choose (Bagozzi, 1983). Brand preference was considered as a behavioral propensity that reveals a purchaser’s attitude towards a brand (Ebrahim et al., 2016). Brand preference has been one of the customer judgment formed toward a brand. It was a state where the purchaser preferred a particular brand as they had positive feelings toward the brand. Brand preference usually happened in the alternative assessment step of customer decision making (Kotler & Keller, 2016).

Besides, some scholars suggested that brand preference was a crucial antecedent to purchase intention and had a positive influence on purchase intention (Chen & Chang, 2008; Emor & Pangemanan, 2015; Pool et al., 2018). Therefore, we suggested the following hypothesis:

H5: Brand preference has a positive impact on purchase intention.

Based on the research, literature review and hypotheses development, Figure 1 shows the proposed research model.

OTGHEU_2020_v7n10_939_f0001.png 이미지

Figure 1: The proposed research model

3. Research Methodology

3.1. Sample and Data Collection

The data was an analysis of consumers who drop by at electronic supermarkets and want to purchase branded phones in Ho Chi Minh, Vietnam. This research sample was conducted through convenience sampling with different groups of customers across gender and age in Ho Chi Minh City, Vietnam. We sent a total of 400 questionnaires; 347 questionnaires were returned, and 62 questionnaires were disregarded, as there was no adequate information. There were 285 questionnaires used for the last analysis. The sample was 121 male consumers (42.5%) and 164 female consumers (57.5%). Customers in the age group 18 to 25 made up 31.9% of the respondents, 30.9% were in the age group 26 to 35, 26,0%, in the age group 36 to 45, and 11.2% were older.

3.2. Measurements

The measurement items of the constructs from previous research were reviewed and adapted to suit the study circumstance. A 5-point Likert scale ranging from “1 = completely disagree” to “5 = completely agree” was performed. In this present research, we adapted four items of brand trust from Chaudhuri and Holbrook (2001); Lau and Lee (1999); four items of perceived value from So et al. (2013); Baek and King (2011); Baek and King (2011); four brand preference from Afsar (2014); Chinomona et al. (2013); and four items of purchase intention from Choi et al. (2020); Mathur (1999).

3.3. Analytical Method

The partial least squared (PLS) method was used in this research because this method is appropriate in any of the following contexts, such as (1) predicting the primary statistical objective of the study, (2) applying with small samples and non-normal distributions data, as was typical of social science and survey data, (3) studying includes many latent variables, (4) ability to assess complex models with many constructs and many indicators, (5) capacity to apply formative composite measures, (6) suitable for exploratory research predicting endogenous constructs, and (7) fitting with the latent variable measurement models are measured formatively (Hair et al., 2017; Manley et al., 2020). Besides, the PLS method has gained increasing popularity as a critical multivariate analysis method in different research fields such as marketing, operations management, and management information systems (Hair et al., 2017; Hair et al., 2013). We employed the partial least squared structural equation modeling (PLS-SEM) with SmartPLS software to measure the proposed research model and hypotheses. Testing the proposed research model and suggestions were taken through two stages: (1) evaluation of the measurement model and (2) evaluation of the structural model (PLSSEM) (Hair et al., 2017).

4. Results and Discussion

4.1. Results

4.1.1. Evaluation of the Measurement Model: Construct Reliability and Validity

Table 1 presents the measurement scale of the construct’s research results. We applied Cronbach’s Alpha and composite reliability (CR) for assessing the reliability of the research. Cronbach’s alpha (α) values of the constructs should be higher than 0.70, and the CR values higher than 0.70, meaning there is enough internal consistency of the constructs (Hair et al., 2017). Table 1 illustrates that Cronbach’s alpha values of the independent variables were above 0.70. Therefore, these constructs have internal consistency reliability.

Table 1: Measurement items of the construct’s analysis results

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We applied the factor loading of all items values and the average variance extracted (AVE) to evaluate convergent validity. The factor loading and AVE should be higher than 0.50 (Bagozzi & Yi, 1988; Hair et al., 2017). In this current research, the factor loading of all items and the AVE values were above 0.50. Accordingly, the convergent validity of the constructs was fit.

Furthermore, we assessed discriminant validity through the Fornell-Larcker criterion (Fornell & Larcker, 1981). It depicted the square root of the AVE values with the latent variable. Specifically, the square root of the AVE should be higher than its highest correlation with any other concept. (Hair et al., 2017). Table 2 shows that the square root of AVE of reflective construct brand trust, perceived value, brand preference, and purchase intention was higher than the corresponding latent variables correlation. Hence, the discriminant validity of these constructs was good.

Table 2: Discriminant validity result​​​​​​​

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4.1.2. Assessment of the Structural Model and Hypotheses Testing

Evaluation of the model fit

Table 3 presents the model fit results. The results in Table 3 described that the Chi-square = 389.129 was significant at 0.05 level (p=0.00). SRMR (standardized root mean square residual) was a measure of the approximate model fit of the proposed research model. By convention, a model had a good model fit when SRMR was less than 0.08 (Hu & Bentler, 1998). The summary results in Table 3 exposed that this model had SRMR indices = 0.062 < 0.08. Hence, the suggested research model was appropriate well for investigation data. Furthermore, measuring of a multicollinearity issue revealed that all VIF values were below the threshold of 5. Consequently, there were no multicollinearity problems in the structural model (Hair et al., 2017).

Table 3: Model fit results​​​​​​​

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Hypotheses testing

Table 4 shows the hypotheses testing findings. Bootstrapping outcomes (with 5000 resamplings) for the association between the notions in the suggested study model demonstrated that the t-value of the H1, H2, H3, H4, H5 was higher than 1.96, and these hypotheses were meaningful at a 5% level. As a result, these hypotheses were supported.

Table 4: Hypotheses testing results​​​​​​​

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R2 (explained variance), f2 (effect size) and Q2 (predictive relevance)

The structural model is examined with the main evaluation metrics R2 (explained variance), f2 (effect size), and Q2 (predictive relevance) (Hair et al., 2017). The coefficient of determination (R2) was the overall effect extent measure for the structural model (Garson, 2016). The R2 value is between 0 to 1, with higher levels indicating more predictive accuracy. The R2 value of 0.19, 0.33, and 0.67 could be presented as weak, moderate, and substantial (Chin, 1998). The (f2) effect size enabled evaluating the independent variable contribution to the dependent variable. The f2 value 0.02 was small, 0.15 was medium, and 0.35 was high (Cohen, 1988). The Q2 value estimated the structural model's predictive relevance for each endogenous construct. The Q2 value should be over zero (Hair et al., 2017).

In this current study, the R2 value for the overall model was 0.580 (see Table 5), less than 0.67, regarded as a fairly substantial impact; we noticed that brand preference had the strongest influence (0.321), followed by the perceived value (0.288), and brand trust (0.250). Furthermore, brand trust and perceived value explained 53.1% of the variance on brand preference; we also unveiled that brand trust had a more substantial effect (0.402) than the perceived value (0.390).

Table 5: R2 , f2 , and Q2 results​​​​​​​

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Table 5 shows the f2 effect sizes. The medium f2 effect size happened for the relationship of brand trust → brand preference (0.181), and perceived value → brand preference (0.170). The medium-weak f2 effect size occurred for the link of brand preference → purchase intention (0.115). The small f2 effect size happened for the connection perceived value → purchase intention (0.088), and brand trust → purchase intention (0.066).

Table 5 also shows that the Q2 values of two endogenous variables were over zero. Precisely, brand preference had Q2 values (0.281), and purchase intention had Q2 values (0.362). These results confirmed the model’s predictive power is suited for the endogenous latent variables.

4.2. Discussion

This present research’s contribution was to examined and measured the influence of brand trust and perceived value on brand preference and purchase intention for branded phones in a different circumstance from previous research. Most of the prior studies focus on these impacts for the various industries, and this current study demonstrated these effects in the Vietnam electronic supermarket market.

The current study results show that the five hypotheses in the research model were supported. The research results illustrate that brand trust had a positive impact on brand preference. Brand trust was an antecedent to brand preference. The f2 impact size of the relationship between brand trust and brand preference was moderate (0.181). The prior empirical research reinforced the findings of this study (Afsar, 2014). The research findings also showed that brand trust had a significant positive effect on purchase intention. Brand trust was a precursor of purchase intention. The f2 effect size of the link between brand trust and purchase intention was small (0.066). The previous empirical studies confirmed the results of this research (Aydin et al., 2014; Sanny et al., 2020).

Besides, the study results also pointed out that perceived value had a positive impact on brand preference. Perceived value was a predecessor of brand preference, and the f2 effect size of the connection of the perceived value and brand preference was medium (0.170). The previous empirical investigations confirmed the results of this research (Ebrahim et al., 2016; Hellier et al., 2003; Muzakir & Damrus, 2018). Likewise, the study outcomes also noted that perceived value had a positive influence on purchase intention. Perceived value was an antecedent of purchase intention, and the f2 effect size of the link of the perceived value and purchase intention was small (0.088). The prior empirical studies reinforced the results of this research (Calvo-Porral & LévyMangin, 2017; Hsieh, 2016; Hu, 2011).

Moreover, the findings also reveal that brand preference had a positive effect on purchase intention. Brand preference was a precursor of purchase intention, and the f2 effect size of the tie of brand preference and purchase intention was medium-weak (0.115). The earlier empirical research verified the outcomes of this research (Chen & Chang, 2008; Emor & Pangemanan, 2015; Pool et al., 2018).

5. Conclusions and limitations

In line with the prior studies, this current study documents the influence of brand trust, perceived value on brand preference, and purchase intention for branded phones. Thus, practitioners should focus on strategies that improve the consumer’s perception of brand trust, perceived value, and brand preference to increase purchase intention. Managers also should note brand trust has a more essential role in brand preference than perceived value. The study results illustrated that brand trust was a predictor of brand preference and purchase intention. The research will help electronic supermarket managers to recognize the significance of brand trust on brand preference and purchase intention. Therefore, managers should build strategies to increase customers’ brand trust. If consumers trust the product brand, consumers have express a positive tendency for brand preference and purchase intention. Likewise, the findings demonstrated that perceived value was an antecedent to brand preference and purchase intention. The research will help practitioners to understand the importance of perceived value on brand preference and purchase intention. Therefore, managers should build strategies to increase clients’ perceived value, such as to improve good value for the price in the context of the price competition. If clients’ perceived value increases, clients will increase brand preference and purchase intention. Finally, the results also revealed that brand preference was an antecedent of purchase intention. Therefore, managers should create marketing programs to improve brand preference, in turn, which leads to enhance purchase intention.

Though this current research has made an essential contribution to the literature and practice, it has some limitations. First, this ongoing research may not be generalizable to all other industries, so future research should focus on other sectors such as fashion, computers, etc. Second, this study looks only on the effect of brand trust and perceived value on brand preference and purchase intention for branded phones; therefore, future studies should focus on other influential factors such as brand image, brand awareness, brand love, etc.

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