# The Purchase Intention for Agricultural Products of Regional Public Brands: Examining the Influences of Awareness, Perceived Quality, and Brand Trust

Authors: Yuling Sun; Yifan Huang; Xiang Fang; Feng Yan
Journal: Mathematical Problems in Engineering
 (2022)

---

## Abstract

Digital economy technologies such as big data, artificial intelligence, and 5G have brought significant changes to the operation and management of regional agricultural products. As a result, competition between agricultural enterprises turned to competition between brands. Recently, many regional brands of agricultural products have emerged, but most have low visibility, low influence, and significant homogeneity. Therefore, ways to rapidly improve public awareness of regional agricultural brands’ products have become an important issue in some regions. Against the background of regional brands and on the basis of 576 responses to a survey questionnaire, this study analyzes the direct and indirect influences of awareness and perceived quality on consumers’ purchase intention of agricultural products and the mediating influence of brand trust on consumer purchase intention. The results indicate that awareness has a significant positive effect on consumers’ purchase intention and that brand trust could strengthen the influence of awareness on consumers’ purchase intention. At the same time, brand trust can promote the positive influence of perceived quality on consumers’ purchase intention. This study extends the research on consumer behavior theory, reveals the influence mechanism of consumer purchase intention of the agricultural products of regional public brands, and provides a new perspective for further research on agricultural products in some regions. Additionally, we provide management implications for the operation of agricultural products of regional public brands.


---

## Body

## 1. Introduction

An agricultural regional public brand that is jointly owned by the government, enterprises, and farmers in a specific area, which is affected by natural and historical factors mainly, sells agricultural products that are grown locally [1]. Compared with ordinary brands, regional public agricultural product brands usually benefit from publicity and sociality, being a collection of products from a certain region, such as LiShuiShanGeng, which can include fruits, vegetables, meat, and other agricultural products. A highly valued regional public brand of agricultural products could be in the form of a city card for the regional agricultural industry. Such a format has very high brand content and can effectively promote the development of related industries, for example, increasing the brand value of regional public brands. For instance, the cumulative sales of the LiShuiShanGeng public brand reached CNY 13.52 billion by the end of 2021, with an average premium rate of more than 30% and a brand value of CNY 2.659 billion. Another high-value brand is the regional public brand TianFuHeTao, for which the brand premium rate of licensed products exceeded 30% and which had driven the overall premium of the city’s livestock products to 15% by January 2021. The agricultural brands have become an important driving force for regional economic development.Big data, artificial intelligence, and intelligent meteorology have been gradually applied in the supply chain of regional agriculture recently, greatly improving the level of agricultural industrialization. New media marketing modes, such as live streaming, WeChat marketing, and group buying, have simultaneously emerged. These new media marketing methods play an important role in product promotion. According to statistics, the online retail sales of agricultural products in China reached CNY 575 billion in 2020, representing an increase of 37.9% compared to 2019. At the same time, the digital economy has brought new challenges to regional agricultural products. For example, the risk of information and brand fraud has increased. WuChang Rice, Yangcheng Lake hairy crabs, West Lake Longjing Tea, and other well-known regional public brands of agricultural products have often been penetrated by impostors, detrimentally affecting consumers’ confidence in regional public brand products. Additionally, some regional brands have many similar varieties of the same product. For example, there are a lot of regional brand rice types in Jiangsu Province, such as Huaian, Sheyang, Xinghua, and Funing rice. However, most regional public brands of rice lack influence. In the context of the digital economy, it is a highly topical issue for regional public brands to analyze the key factors that influence consumers' purchase intention.Studies on consumers’ purchase intention are divided into three categories, with some scholars having focused their research on consumer purchase intention models. In 1963, the psychologist Fishbein [2] developed the multiattribute attitude model, the “Fishbein model,” also called the “consumers’ purchase intention model.” Kim et al. [3] and Chen et al. [4] used this model to verify the impact of consumer attitudes and other factors on consumers’ purchase intention. Other scholars are more concerned with measurement methods of consumers’ purchase intention. For example, Dennis et al. [5] developed a choice-based model to measure customers’ purchase intention. Huo and Zhang [6] analyzed the relationship between online reviews and purchase intention using data mining techniques. Wang and Xu [7] used an ensemble learning method (AdaBoost-FSVM) based on fuzzy support vector machines (FSVM) to predict consumers’ purchase intention. Other scholars concentrated on various factors influencing consumers’ purchase intention. Hong and Zhang [8], Lu et al. [9], and Shihab et al. [10], for example, studied the effects of perceived quality on consumers’ purchase intention, while Zhang and Lu [11], Saputra et al. [12], and others analyzed the effects of awareness on consumers' purchase intention. Besides, Zhao et al. [13], He and Li [14], Bashiru et al. [15], and other scholars have focused on the impact of brand trust on consumers’ purchase intention.Some scholars recently began to pay attention to research on agricultural brands in some regions. They mainly concentrated on the development modes and construction paths of these brands. For example, Fei and Du [16] put forward the idea of relying on geographical indications to build a regional brand of agricultural products. Chen [17] used a qualitative comparative analysis method to obtain the endogenous impetus of brand development from the perspective of quality heterogeneity. Huang and Geng [18] analyzed the strategy of brand selection based on empirical analysis and the Delphi method. In some regions, Li and Zhong [19] concluded that the improvement of farmers’ cooperatives is conducive to the establishment of agricultural brands. Yang [20] proposed a reconstruction strategy for Suzhou’s regional public brands. Scholars have begun to focus on analyzing the determinants of consumers’ purchase intention on agricultural brands of late. For example, Biondi [21] considered that prepackaging information has an impact on consumers’ purchase intention. Zhang and Lu [11] analyzed the impact of brand awareness, brand origin, brand premium, and purchase environment on the purchase intention of agricultural brands. Fan and Meng [22] studied the influence of regional image, regional cultural identity, and purchase behavior toward agricultural brands. In summary, the factors influencing the agricultural brands mainly focus on the image, environment, and price of agricultural products. However, few scholars have investigated the effects of brand awareness, perceived quality, and brand trust on the purchase intention regarding agricultural brands in some regions.At present, many agricultural brands that represent some Chinese regions have been established, but most are not influential. We therefore identified the key determinants of consumers’ purchase intention of agricultural brands in the context of the digital economy, which can help improve the operation efficiency in some regions. To this end, we investigated the impact factors by using the structural equation modeling (SEM) model, and we analyzed the impact of brand awareness and perceived quality on regional public brands, as well as the mediating role of brand trust.The contributions of this study are threefold: (1) it analyzes in some regions how both brand awareness and perceived quality affect consumers’ purchase intention of agricultural brands; (2) it determines how brand trust affects the relationship between brand awareness, perceived quality, and consumers’ purchase willingness; and (3) it suggests theoretical and managerial strategies that can improve the competitive advantage of regional public brands.


## 2. Theoretical Background and Hypotheses Development

### 2.1. Perceived Quality and Brand Trust

The concept of “brand trust” was put forward by Howard et al. [23] in 1969 and has two meanings: one is that the product has enough strength to influence consumer demand, and the other is that the product makes certain promises to the consumer. In 1972, Olson [24] defined perceived quality as the judgment and evaluation of product function and quality by consumers through subjective perception. Some studies have shown that the consumer-perceived quality of common brands has a positive effect on brand trust [25–27]. As for regional public brands, their agricultural products have unique natural ecological environments, and historical and cultural factors clearly confirm the perceived quality of regional agricultural products [28]. As such, perceived quality is consumers’ overall judgment of regional agricultural products; that is, consumers assess the quality of regional agricultural products and form an overall quality evaluation [29]. Therefore, product quality is a fundamental guarantee for winning consumers’ trust. When consumers compare the quality and commitment of agricultural brands in some regions with that of other brands, and the considered brand is better than others offering similar agricultural products, consumers will develop psychological dependence and, in the end, the psychological identity of the brand is formed. Therefore, the following hypothesis is proposed:H1: The perceived quality of regional agricultural products influences brand trust positively.


### 2.2. Awareness and Brand Trust

Awareness refers to consumers’ awareness of the function and ability of an object in addition to their brand awareness [30]. Some studies showed that, to a certain extent, brand awareness affects consumers’ brand trust. As an important part of brand equity, brand awareness is the direct reaction of consumers to agricultural brands’ marketing, and it can influence customers’ brand knowledge. Some scholars believe that brand awareness can increase consumer confidence [30–35]. Therefore, based on the above arguments, the following hypothesis was developed:H2: The public brand awareness of regional agricultural products positively influences brand trust.


### 2.3. Perceived Quality and Purchase Intention

Purchase intention refers to consumers’ attitudes toward a product or brand [36]. There are many factors that affect purchase intention, such as consumer-perceived quality, brand trust, and awareness. Product quality has always been an important factor for consumers to pay attention to. Consumers’ perceptions of quality influence their judgment of product quality. Through continuous evolution, brands have important value functions, such as product identification, service and quality commitment, consumer value recognition, and price premium. Agricultural brands in some regions have more stringent quality standards and quality assurance than ordinary brands [20]. As such, consumers are less likely to think about product quality and are more likely to buy such brands because of the region’s high levels of quality assurance. Some scholars believe that perceived quality positively influences purchase intention [8, 9, 37–42]. Therefore, the following hypothesis was developed:H3: The perceived quality of regional agricultural products positively influences the purchase intention.


### 2.4. Brand Trust and Purchase Intention

Howard [23] believed that brand trust is one of the determinants of purchase intention. Brand trust is also an important component of brand equity and an important determinant of consumers’ purchase intention [29]. When consumers are unfamiliar with a brand, trust will be an important factor that can influence their choice. Before consumers purchase regional public brand agricultural products, trust is mainly expressed as a psychological expectation and prediction. After the purchase has been made, the quality of the products will verify consumers’ expectations, and the results of the verification will form the expectation and prediction of the following purchase [28]. In other words, trust has a positive effect on consumer intention and behavior, and if consumers had high trust in private brands, they would be willing to buy private brand products [14]. Additionally, perceived high quality means that, through long-term brand-related experience, consumers recognize the differentiation and strengths of a brand, which generate a positive purchase intention [43]. Regarding the impact of brand trust on consumer behavior, domestic and foreign scholars have shown that consumer brand trust could influence consumer behavior positively [13, 14, 26, 44–47]. The following hypothesis was consequently developed:H4: The brand trust positively influences purchase intention.


### 2.5. Awareness and Purchase Intention

Brand awareness has the strongest impact on consumers’ purchasing decisions. Consumers may consider brand awareness an important factor in purchasing decisions [48]. The higher the brand awareness level is, the more likely a consumer will be to form a purchase intention. Consumers are willing to pay higher prices to buy products from high-profile brands because they are reliable and trustworthy [49]. Some studies have shown that awareness positively influences the purchase intention to a certain extent [11, 50, 51]. Therefore, the following hypothesis was formulated:H5: The public brand awareness of regional agricultural products positively influences the purchase intention.


### 2.6. Brand Trust as a Mediating Variable

Based on the above assumptions, this study tested the following assumptions:H6a: Brand trust mediates the relationship between perceived quality and purchase intention.H6b: Brand trust mediates the relationship between awareness and purchase intention.Conceptual model of consumers’ purchase intention for agricultural products of regional public brands is shown in Figure1.Figure 1
Conceptual model of consumers’ purchase intention for agricultural products of regional public brands.Note. The solid lines represent the hypotheses with a direct effect, and the dashed lines represent the hypotheses with a mediating effect.


## 2.1. Perceived Quality and Brand Trust

The concept of “brand trust” was put forward by Howard et al. [23] in 1969 and has two meanings: one is that the product has enough strength to influence consumer demand, and the other is that the product makes certain promises to the consumer. In 1972, Olson [24] defined perceived quality as the judgment and evaluation of product function and quality by consumers through subjective perception. Some studies have shown that the consumer-perceived quality of common brands has a positive effect on brand trust [25–27]. As for regional public brands, their agricultural products have unique natural ecological environments, and historical and cultural factors clearly confirm the perceived quality of regional agricultural products [28]. As such, perceived quality is consumers’ overall judgment of regional agricultural products; that is, consumers assess the quality of regional agricultural products and form an overall quality evaluation [29]. Therefore, product quality is a fundamental guarantee for winning consumers’ trust. When consumers compare the quality and commitment of agricultural brands in some regions with that of other brands, and the considered brand is better than others offering similar agricultural products, consumers will develop psychological dependence and, in the end, the psychological identity of the brand is formed. Therefore, the following hypothesis is proposed:H1: The perceived quality of regional agricultural products influences brand trust positively.


## 2.2. Awareness and Brand Trust

Awareness refers to consumers’ awareness of the function and ability of an object in addition to their brand awareness [30]. Some studies showed that, to a certain extent, brand awareness affects consumers’ brand trust. As an important part of brand equity, brand awareness is the direct reaction of consumers to agricultural brands’ marketing, and it can influence customers’ brand knowledge. Some scholars believe that brand awareness can increase consumer confidence [30–35]. Therefore, based on the above arguments, the following hypothesis was developed:H2: The public brand awareness of regional agricultural products positively influences brand trust.


## 2.3. Perceived Quality and Purchase Intention

Purchase intention refers to consumers’ attitudes toward a product or brand [36]. There are many factors that affect purchase intention, such as consumer-perceived quality, brand trust, and awareness. Product quality has always been an important factor for consumers to pay attention to. Consumers’ perceptions of quality influence their judgment of product quality. Through continuous evolution, brands have important value functions, such as product identification, service and quality commitment, consumer value recognition, and price premium. Agricultural brands in some regions have more stringent quality standards and quality assurance than ordinary brands [20]. As such, consumers are less likely to think about product quality and are more likely to buy such brands because of the region’s high levels of quality assurance. Some scholars believe that perceived quality positively influences purchase intention [8, 9, 37–42]. Therefore, the following hypothesis was developed:H3: The perceived quality of regional agricultural products positively influences the purchase intention.


## 2.4. Brand Trust and Purchase Intention

Howard [23] believed that brand trust is one of the determinants of purchase intention. Brand trust is also an important component of brand equity and an important determinant of consumers’ purchase intention [29]. When consumers are unfamiliar with a brand, trust will be an important factor that can influence their choice. Before consumers purchase regional public brand agricultural products, trust is mainly expressed as a psychological expectation and prediction. After the purchase has been made, the quality of the products will verify consumers’ expectations, and the results of the verification will form the expectation and prediction of the following purchase [28]. In other words, trust has a positive effect on consumer intention and behavior, and if consumers had high trust in private brands, they would be willing to buy private brand products [14]. Additionally, perceived high quality means that, through long-term brand-related experience, consumers recognize the differentiation and strengths of a brand, which generate a positive purchase intention [43]. Regarding the impact of brand trust on consumer behavior, domestic and foreign scholars have shown that consumer brand trust could influence consumer behavior positively [13, 14, 26, 44–47]. The following hypothesis was consequently developed:H4: The brand trust positively influences purchase intention.


## 2.5. Awareness and Purchase Intention

Brand awareness has the strongest impact on consumers’ purchasing decisions. Consumers may consider brand awareness an important factor in purchasing decisions [48]. The higher the brand awareness level is, the more likely a consumer will be to form a purchase intention. Consumers are willing to pay higher prices to buy products from high-profile brands because they are reliable and trustworthy [49]. Some studies have shown that awareness positively influences the purchase intention to a certain extent [11, 50, 51]. Therefore, the following hypothesis was formulated:H5: The public brand awareness of regional agricultural products positively influences the purchase intention.


## 2.6. Brand Trust as a Mediating Variable

Based on the above assumptions, this study tested the following assumptions:H6a: Brand trust mediates the relationship between perceived quality and purchase intention.H6b: Brand trust mediates the relationship between awareness and purchase intention.Conceptual model of consumers’ purchase intention for agricultural products of regional public brands is shown in Figure1.Figure 1
Conceptual model of consumers’ purchase intention for agricultural products of regional public brands.Note. The solid lines represent the hypotheses with a direct effect, and the dashed lines represent the hypotheses with a mediating effect.


## 3. Methodology

### 3.1. Research Design and Sampling

This study analyzes the key determinants of agricultural brands in some regions. To this end, each observed variable is given a score of 1 to 5, representing “strongly agree,” “agree,” “not necessarily,” “disagree,” and “strongly disagree,” respectively, for 13 topics. The model variables correspond to the questions in the survey questionnaire. The higher the score, the higher the consumer’s evaluation of the observed variable. Latent and observed variables are shown in Table1.Table 1
Latent and observed variables of consumers’ purchase intention.
Latent variablesObserved variablesSymbolic representationPurchase intentionIf required, you will consider purchasing products from the regional public brand of this agricultural productX1Your willingness to buy products from the regional public brand of agricultural products is strong and willing to try the brandX2Among similar agricultural product brands, you are highly likely to purchase the regional public brand of this agricultural productX3You will pay more attention to the products of the regional public brand of this agricultural productX4AwarenessYou often see advertisements for regional public brands of this productX5The advertisement of the regional public brand of agricultural products is very impressiveX6Brand trustYou will repeatedly purchase this agricultural product regional public brand agricultural productsX7The regional public brand of agricultural products is safe and reliableX8The regional public brand of agricultural products has the ability to protect the interests of customersX9The regional public brand of agricultural products can be trustedX10Perceived qualityThe regional public brand of agricultural products’ quality phase is goodX11The regional public brand of agricultural products tastes goodX12This agricultural product area public brand product is worth buyingX13The survey was conducted in two stages. The first stage was a preliminary investigation, and 83 questionnaires were collected with the help of a random network from April 10 to April 26, 2021. The questionnaire was revised based on an analysis of the presurvey results. In the second stage, 674 questionnaires were collected during May 1–18, 2021. After eliminating 98 invalid questionnaires due to incomplete or repeated answers, 576 valid responses were obtained, being an 85% response rate.


### 3.2. Reliability and Validity Analysis

IBM SPSS Statistics 26 and IBM SPSS AMOS 26 were used to test and analyze the questionnaire data. The specific analysis results are presented in Tables2—3. The reliability analysis showed that Cronbach’s α of all variables is 0.753, which is greater than 0.7. The reliability of the sample data was thus deemed satisfactory. Specifically, this means that each indicator has high internal consistency, and each variable has good reliability.Table 2
KMO and Bartlett sphere test results for the factors affecting consumers’ purchase intention.
TotalPurchase intentionAwarenessBrand trustPerceived qualityKMO sampling0.8990.8520.5000.7910.799Suitability BartlettQuantity chi-square12929.1231951.276890.7272050.8694927.737Spherical testDf786163Sig.0.0000.0000.0000.0000.000Table 3
Combination and convergence validity results.
PathUnstd.SEt-valuePStd.SMCCRAVEX1←Purchase intention1.000———0.8700.7570.9320.775X2←Purchase intention0.9870.03329.537∗∗∗0.8750.766X3←Purchase intention1.0490.03331.392∗∗∗0.9040.817X4←Purchase intention0.9930.03428.979∗∗∗0.8730.762X5←Awareness0.9570.03329.060∗∗∗0.9260.8570.9410.889X6←Awareness1.000———0.9590.920X7←Brand trust−0.5410.072−7.483∗∗∗−0.2990.0890.8380.690X8←Brand trust0.9830.02245.312∗∗∗0.9340.872X9←Brand trust0.9770.02049.079∗∗∗0.9520.906X10←Brand trust1.000———0.9440.891X11←Perceived quality1.0020.005189.265∗∗∗0.9960.9920.9970.992X12←Perceived quality1.000———0.9960.992X13←Perceived quality1.0070.005189.900∗∗∗0.9960.992Note. ∗∗∗Significance at the 0.001 level.According to the results of the validity Table2 analysis, the KMO (Kaiser–Meyer–Olkin) value of the total sample is 0.899, and the chi-square value of Bartlett’s sphericity is 12,929.123. The factor loading of each variable is greater than 0.5, which indicates that the sample data have good validity.Table 4
Differential validity results.
AwarenessPerceived qualityBrand trustPurchase intentionAwareness0.943———Perceived quality0.0000.996——Brand trust0.581−0.0980.831—Purchase intention0.601−0.0820.8260.881Additionally, to verify the relevance of the items in the same dimensions, confirmatory factor analysis (CFA) was performed. The results in Table3 indicate that the composite reliability (CR) is between 0.838 and 0.997, which is higher than the standard value of 0.7, and the average variance extracted (AVE) is between 0.690 and 0.992, which is higher than the standard value of 0.5. This means that the model has good internal consistency, combined validity, and convergent validity. All questions were significant because the P values of all variables were below 0.001.Finally, differential validity was performed to verify the differences between the different dimensions. As shown in Table4, the square root values of all variables are larger than those of related dimensions, indicating that each dimension is different, all variables are different and representative, and the validity Table 4 of the questionnaire is good.


## 3.1. Research Design and Sampling

This study analyzes the key determinants of agricultural brands in some regions. To this end, each observed variable is given a score of 1 to 5, representing “strongly agree,” “agree,” “not necessarily,” “disagree,” and “strongly disagree,” respectively, for 13 topics. The model variables correspond to the questions in the survey questionnaire. The higher the score, the higher the consumer’s evaluation of the observed variable. Latent and observed variables are shown in Table1.Table 1
Latent and observed variables of consumers’ purchase intention.
Latent variablesObserved variablesSymbolic representationPurchase intentionIf required, you will consider purchasing products from the regional public brand of this agricultural productX1Your willingness to buy products from the regional public brand of agricultural products is strong and willing to try the brandX2Among similar agricultural product brands, you are highly likely to purchase the regional public brand of this agricultural productX3You will pay more attention to the products of the regional public brand of this agricultural productX4AwarenessYou often see advertisements for regional public brands of this productX5The advertisement of the regional public brand of agricultural products is very impressiveX6Brand trustYou will repeatedly purchase this agricultural product regional public brand agricultural productsX7The regional public brand of agricultural products is safe and reliableX8The regional public brand of agricultural products has the ability to protect the interests of customersX9The regional public brand of agricultural products can be trustedX10Perceived qualityThe regional public brand of agricultural products’ quality phase is goodX11The regional public brand of agricultural products tastes goodX12This agricultural product area public brand product is worth buyingX13The survey was conducted in two stages. The first stage was a preliminary investigation, and 83 questionnaires were collected with the help of a random network from April 10 to April 26, 2021. The questionnaire was revised based on an analysis of the presurvey results. In the second stage, 674 questionnaires were collected during May 1–18, 2021. After eliminating 98 invalid questionnaires due to incomplete or repeated answers, 576 valid responses were obtained, being an 85% response rate.


## 3.2. Reliability and Validity Analysis

IBM SPSS Statistics 26 and IBM SPSS AMOS 26 were used to test and analyze the questionnaire data. The specific analysis results are presented in Tables2—3. The reliability analysis showed that Cronbach’s α of all variables is 0.753, which is greater than 0.7. The reliability of the sample data was thus deemed satisfactory. Specifically, this means that each indicator has high internal consistency, and each variable has good reliability.Table 2
KMO and Bartlett sphere test results for the factors affecting consumers’ purchase intention.
TotalPurchase intentionAwarenessBrand trustPerceived qualityKMO sampling0.8990.8520.5000.7910.799Suitability BartlettQuantity chi-square12929.1231951.276890.7272050.8694927.737Spherical testDf786163Sig.0.0000.0000.0000.0000.000Table 3
Combination and convergence validity results.
PathUnstd.SEt-valuePStd.SMCCRAVEX1←Purchase intention1.000———0.8700.7570.9320.775X2←Purchase intention0.9870.03329.537∗∗∗0.8750.766X3←Purchase intention1.0490.03331.392∗∗∗0.9040.817X4←Purchase intention0.9930.03428.979∗∗∗0.8730.762X5←Awareness0.9570.03329.060∗∗∗0.9260.8570.9410.889X6←Awareness1.000———0.9590.920X7←Brand trust−0.5410.072−7.483∗∗∗−0.2990.0890.8380.690X8←Brand trust0.9830.02245.312∗∗∗0.9340.872X9←Brand trust0.9770.02049.079∗∗∗0.9520.906X10←Brand trust1.000———0.9440.891X11←Perceived quality1.0020.005189.265∗∗∗0.9960.9920.9970.992X12←Perceived quality1.000———0.9960.992X13←Perceived quality1.0070.005189.900∗∗∗0.9960.992Note. ∗∗∗Significance at the 0.001 level.According to the results of the validity Table2 analysis, the KMO (Kaiser–Meyer–Olkin) value of the total sample is 0.899, and the chi-square value of Bartlett’s sphericity is 12,929.123. The factor loading of each variable is greater than 0.5, which indicates that the sample data have good validity.Table 4
Differential validity results.
AwarenessPerceived qualityBrand trustPurchase intentionAwareness0.943———Perceived quality0.0000.996——Brand trust0.581−0.0980.831—Purchase intention0.601−0.0820.8260.881Additionally, to verify the relevance of the items in the same dimensions, confirmatory factor analysis (CFA) was performed. The results in Table3 indicate that the composite reliability (CR) is between 0.838 and 0.997, which is higher than the standard value of 0.7, and the average variance extracted (AVE) is between 0.690 and 0.992, which is higher than the standard value of 0.5. This means that the model has good internal consistency, combined validity, and convergent validity. All questions were significant because the P values of all variables were below 0.001.Finally, differential validity was performed to verify the differences between the different dimensions. As shown in Table4, the square root values of all variables are larger than those of related dimensions, indicating that each dimension is different, all variables are different and representative, and the validity Table 4 of the questionnaire is good.


## 4. Empirical Results

### 4.1. Descriptive Statistics

The descriptive statistics of the sample are reported in Table5. The respondents comprised both men (48.26%) and women (51.74%). Most respondents were under 45 years of age (86.46%). The monthly income levels reflect a fairly even distribution, with most respondents belonging to the middle and lower classes and 87.50% earning less than CNY 10,000 per month.Table 5
Sample characteristics.
VariableCategoryFrequency (%)GenderMale48.26Female51.74Age18–2945.1430–4541.3246–599.55>603.99Monthly income level<2,00022.922,001–6,00032.816,001–10,00023.9610,001–15,00012.50>15,0007.81


### 4.2. Model Fitness Analysis

This study used AMOS software to test the reliability and validity of the questionnaire data input theoretical model. The goodness of fit of the model is presented in Table6. The absolute fit index (χ2/df = 39.637; RMSEA = 0.259) and the relative fit index (GFI = 0.827; AGFI = 0.737) do not show a good fit [52–54]. Therefore, the above indices did not reach the required model fitness.Table 6
Model adaptation results before and after correction.
Fit indexPrerevision indexModified indexStandard valueCMIN/DF39.6374.0191–5GFI0.8270.950＞0.9AGFI0.7370.919＞0.9RMSEA0.2590.072＜0.08The initial model had to be modified to improve its goodness of fit. First, item X7 was deleted because the factor load coefficient on item X7 was not up to standard. Second, we made both factor e1 and factor e4 correlative. The prerevision and modified models are shown in Figures2 and 3, respectively.Figure 2
Prerevision model.Figure 3
Modified model.


### 4.3. Result Analysis

Based on the modified model, AMOS was used to verify the hypotheses. The results are presented in Table7 and indicate that the standardized path coefficients on the awareness of purchase intention and brand trust were 0.187 and 0.582, respectively. H2 and H5 are thus consistently supported. Awareness had a significant positive effect on purchase intention and brand trust and the highest impact on brand trust. The standardized path coefficient on brand trust to purchase intention was 0.709. H4 is thus supported as well. Brand trust had a significant and positive effect on purchase intention. The standardized path coefficient on perceived quality to brand trust was −0.085, meaning perceived quality had a significant negative effect on brand trust. H1 was therefore unsupported, as was H3. As the standardized path coefficient on perceived quality to purchase intention was −0.017, the perceived quality had a significant negative effect on purchase intention. As a mediating variable, brand trust could strengthen the influence of awareness on consumers’ purchase intention and reverse the influence of perceived quality on consumers’ purchase intention. In summary, H2, H4, and H5 were supported, and H1 and H3 were rejected.Table 7
Model path coefficient table.
AssumptionPathStd.Unstd.SEt-valuePConclusionH1Brand trust ←Perceived quality−0.085−0.0490.022−2.2160.027RejectedH2Brand trust ←Awareness0.5820.4870.03514.000∗∗∗SupportedH3Purchase intention ←Perceived quality−0.017−0.0100.016−0.6090.543RejectedH4Purchase intention ←Brand trust0.7090.6770.03618.911∗∗∗SupportedH5Purchase intention ←Awareness0.1870.1490.0295.120∗∗∗SupportedNote. ∗∗∗Significance at the 0.001 level.


### 4.4. Mediating Effect Test

The bootstrap trust interval method was used to study the mediating effects of brand trust on the relationship between brand awareness and perceived quality on purchase intention. The sample size was set to a 95% confidence interval of 5,000. The existence of a mediating effect was judged by whether 0 was included.The direct and indirect relationships among the variables are shown in Table8. The results revealed that brand trust plays a completely mediating role between perceived quality and purchase intention. When brand trust is a mediating variable on the path of perceived quality to purchase intention, the confidence interval of the bootstrap test of the total effect is [−0.077, −0.010], the indirect effect is [−0.06, −0.010], and the direct effect is [−0.033, 0.016]. This means that the direct effect is not significant, while the total and indirect effects are significant because the direct effect contains 0. Perceived quality can only influence the purchase intention through brand trust, and it cannot influence the purchase intention without brand trust as a mediating variable. Therefore, H1 and H3 were rejected. When brand trust is a mediating variable on the path from awareness to purchase intention, the confidence interval of the bootstrap test of the total effect is [0.410, 0.548], the indirect effect is [0.277, 0.389], and the direct effect is [0.090, 0.208]. These results show that brand trust plays a mediating role between brand awareness and purchase intention. Brand awareness can enhance the purchase intention through brand trust as a mediating variable, but it can also affect purchase intention directly without brand trust as a mediating variable. These findings support H2, H4, and H5.Table 8
Mediating effect test.
PathEffectPoint estimateSEZBias correctedLowerUpperPerceived quality ⟶Purchase intentionIndirect effect−0.0330.013−2.538−0.060−0.010Direct effect−0.0100.012−0.833−0.0330.016Total effect−0.0430.017−2.529−0.077−0.010Awareness ⟶ purchase intentionIndirect effect0.3300.02911.3790.2770.389Direct effect0.1490.0304.9670.0900.208Total effect0.4790.03414.0880.4100.548


## 4.1. Descriptive Statistics

The descriptive statistics of the sample are reported in Table5. The respondents comprised both men (48.26%) and women (51.74%). Most respondents were under 45 years of age (86.46%). The monthly income levels reflect a fairly even distribution, with most respondents belonging to the middle and lower classes and 87.50% earning less than CNY 10,000 per month.Table 5
Sample characteristics.
VariableCategoryFrequency (%)GenderMale48.26Female51.74Age18–2945.1430–4541.3246–599.55>603.99Monthly income level<2,00022.922,001–6,00032.816,001–10,00023.9610,001–15,00012.50>15,0007.81


## 4.2. Model Fitness Analysis

This study used AMOS software to test the reliability and validity of the questionnaire data input theoretical model. The goodness of fit of the model is presented in Table6. The absolute fit index (χ2/df = 39.637; RMSEA = 0.259) and the relative fit index (GFI = 0.827; AGFI = 0.737) do not show a good fit [52–54]. Therefore, the above indices did not reach the required model fitness.Table 6
Model adaptation results before and after correction.
Fit indexPrerevision indexModified indexStandard valueCMIN/DF39.6374.0191–5GFI0.8270.950＞0.9AGFI0.7370.919＞0.9RMSEA0.2590.072＜0.08The initial model had to be modified to improve its goodness of fit. First, item X7 was deleted because the factor load coefficient on item X7 was not up to standard. Second, we made both factor e1 and factor e4 correlative. The prerevision and modified models are shown in Figures2 and 3, respectively.Figure 2
Prerevision model.Figure 3
Modified model.


## 4.3. Result Analysis

Based on the modified model, AMOS was used to verify the hypotheses. The results are presented in Table7 and indicate that the standardized path coefficients on the awareness of purchase intention and brand trust were 0.187 and 0.582, respectively. H2 and H5 are thus consistently supported. Awareness had a significant positive effect on purchase intention and brand trust and the highest impact on brand trust. The standardized path coefficient on brand trust to purchase intention was 0.709. H4 is thus supported as well. Brand trust had a significant and positive effect on purchase intention. The standardized path coefficient on perceived quality to brand trust was −0.085, meaning perceived quality had a significant negative effect on brand trust. H1 was therefore unsupported, as was H3. As the standardized path coefficient on perceived quality to purchase intention was −0.017, the perceived quality had a significant negative effect on purchase intention. As a mediating variable, brand trust could strengthen the influence of awareness on consumers’ purchase intention and reverse the influence of perceived quality on consumers’ purchase intention. In summary, H2, H4, and H5 were supported, and H1 and H3 were rejected.Table 7
Model path coefficient table.
AssumptionPathStd.Unstd.SEt-valuePConclusionH1Brand trust ←Perceived quality−0.085−0.0490.022−2.2160.027RejectedH2Brand trust ←Awareness0.5820.4870.03514.000∗∗∗SupportedH3Purchase intention ←Perceived quality−0.017−0.0100.016−0.6090.543RejectedH4Purchase intention ←Brand trust0.7090.6770.03618.911∗∗∗SupportedH5Purchase intention ←Awareness0.1870.1490.0295.120∗∗∗SupportedNote. ∗∗∗Significance at the 0.001 level.


## 4.4. Mediating Effect Test

The bootstrap trust interval method was used to study the mediating effects of brand trust on the relationship between brand awareness and perceived quality on purchase intention. The sample size was set to a 95% confidence interval of 5,000. The existence of a mediating effect was judged by whether 0 was included.The direct and indirect relationships among the variables are shown in Table8. The results revealed that brand trust plays a completely mediating role between perceived quality and purchase intention. When brand trust is a mediating variable on the path of perceived quality to purchase intention, the confidence interval of the bootstrap test of the total effect is [−0.077, −0.010], the indirect effect is [−0.06, −0.010], and the direct effect is [−0.033, 0.016]. This means that the direct effect is not significant, while the total and indirect effects are significant because the direct effect contains 0. Perceived quality can only influence the purchase intention through brand trust, and it cannot influence the purchase intention without brand trust as a mediating variable. Therefore, H1 and H3 were rejected. When brand trust is a mediating variable on the path from awareness to purchase intention, the confidence interval of the bootstrap test of the total effect is [0.410, 0.548], the indirect effect is [0.277, 0.389], and the direct effect is [0.090, 0.208]. These results show that brand trust plays a mediating role between brand awareness and purchase intention. Brand awareness can enhance the purchase intention through brand trust as a mediating variable, but it can also affect purchase intention directly without brand trust as a mediating variable. These findings support H2, H4, and H5.Table 8
Mediating effect test.
PathEffectPoint estimateSEZBias correctedLowerUpperPerceived quality ⟶Purchase intentionIndirect effect−0.0330.013−2.538−0.060−0.010Direct effect−0.0100.012−0.833−0.0330.016Total effect−0.0430.017−2.529−0.077−0.010Awareness ⟶ purchase intentionIndirect effect0.3300.02911.3790.2770.389Direct effect0.1490.0304.9670.0900.208Total effect0.4790.03414.0880.4100.548


## 5. Main Conclusions and Implications

### 5.1. Main Conclusions

Based on the analysis of determinants of consumers’ purchase intention on agricultural brands in some regions, this study constructed an SEM of purchase intention, awareness, brand trust, and perceived quality, subsequently arriving at the following three conclusions:Both awareness and brand trust positively influence consumers’ purchase intention. Compared with awareness, brand trust can influence consumers’ purchase intention more significantly. The results show that consumers’ trust is more likely to induce consumers to buy agricultural products from regional public brands because such agricultural products are safe and reliable. Additionally, awareness can push consumers to purchase agricultural products from a regional public brand, which means that the brand has a higher status in people’s minds than other brands. However, if agricultural products in some regions have low visibility, consumers cannot measure the difference between regular and branded produce clearly and distinguish the quality of their products. Therefore, consumers will have a wait-and-see attitude toward the products of regional public brands of agricultural products. These findings indicate that perceived quality has a negative effect on consumers’ purchase intention. Consumers who have already bought such products will still buy them as usual, while those who have not yet bought them will hesitate.Awareness has a significant positive effect on brand trust, while perceived quality has almost no effect on it. In a network, consumers usually search for various items of information related to products through all types of channels before making purchase decisions. Our research results show that awareness can improve consumers’ trust in the agricultural products of regional public brands. Perceived quality had little effect on brand trust. Consumers do not have blind trust because most agricultural products of regional public brands are less well known.Brand trust, as a mediating variable, can significantly enhance the impact of awareness of consumers’ purchase intention and can promote perceived quality to have a positive impact on their intention. When brand trust is used as a mediating variable, the factor loading coefficient of awareness to consumers’ purchase intention increases from 0.15 to 0.68, and the factor loading coefficient of perceived quality to consumers’ purchase intention increases from −0.01 to 0.68. This means that awareness of regional public brands will further enhance consumers’ purchase intention if consumers have a certain degree of trust in regional public brands of agricultural products. This also means that improving product quality would promote consumers’ purchase intention if they had a certain degree of trust in a regional public brand of agricultural products. Consumers’ trust in a brand is also the brand operator’s commitment to the consumer. With the brand trust as an endorsement, perceived quality of agricultural products can promote consumers’ purchase intention toward agricultural products in some regions.


### 5.2. Implications

In view of the above conclusions, the following recommendations are put forward.First, the manager of a regional public brand should broaden sales channels to improve awareness. For example, the manager could establish flagship stores on a large-scale, third-party, e-commerce platform, such as Amazon or Alibaba. Constructing a related WeChat applet is also a good idea to improve awareness of regional public brands, to which live streaming could be added, to improve the awareness of regional public brands. Additionally, managers can build online-to-offline (O2O) smart experience stores or create new retail virtual reality experience and other high-technology stores.Second, managers should build trust in the regional agricultural products’ public brand. Based on the consumer's decision-making process, they can improve consumers’ trust in the regional public brand. During the search phase, managers should use digital economy technology to communicate brand values to consumers. During the potential purchase phase, managers can provide consumers with a value-adding trying/tasting service so that consumers can have zero-distance contact with the agricultural products and can assess their quality first-hand. During the after-sales phase, the manager can provide periodic return visits for consumers and a quick response to complaints about defective quality.Third, managers should continue to improve the quality of the agricultural products of regional public brands. To this end, they can formulate brand production standards and food processing standards by reaching out to experts and scholars from brand industry associations or product industry associations. At the same time, managers can build science and technology demonstration parks, such as the Industrial Integration Development Demonstration Park and the Science and Technology Demonstration Park, by relying on the Internet, big data, blockchain, artificial intelligence, and other emerging technologies.


## 5.1. Main Conclusions

Based on the analysis of determinants of consumers’ purchase intention on agricultural brands in some regions, this study constructed an SEM of purchase intention, awareness, brand trust, and perceived quality, subsequently arriving at the following three conclusions:Both awareness and brand trust positively influence consumers’ purchase intention. Compared with awareness, brand trust can influence consumers’ purchase intention more significantly. The results show that consumers’ trust is more likely to induce consumers to buy agricultural products from regional public brands because such agricultural products are safe and reliable. Additionally, awareness can push consumers to purchase agricultural products from a regional public brand, which means that the brand has a higher status in people’s minds than other brands. However, if agricultural products in some regions have low visibility, consumers cannot measure the difference between regular and branded produce clearly and distinguish the quality of their products. Therefore, consumers will have a wait-and-see attitude toward the products of regional public brands of agricultural products. These findings indicate that perceived quality has a negative effect on consumers’ purchase intention. Consumers who have already bought such products will still buy them as usual, while those who have not yet bought them will hesitate.Awareness has a significant positive effect on brand trust, while perceived quality has almost no effect on it. In a network, consumers usually search for various items of information related to products through all types of channels before making purchase decisions. Our research results show that awareness can improve consumers’ trust in the agricultural products of regional public brands. Perceived quality had little effect on brand trust. Consumers do not have blind trust because most agricultural products of regional public brands are less well known.Brand trust, as a mediating variable, can significantly enhance the impact of awareness of consumers’ purchase intention and can promote perceived quality to have a positive impact on their intention. When brand trust is used as a mediating variable, the factor loading coefficient of awareness to consumers’ purchase intention increases from 0.15 to 0.68, and the factor loading coefficient of perceived quality to consumers’ purchase intention increases from −0.01 to 0.68. This means that awareness of regional public brands will further enhance consumers’ purchase intention if consumers have a certain degree of trust in regional public brands of agricultural products. This also means that improving product quality would promote consumers’ purchase intention if they had a certain degree of trust in a regional public brand of agricultural products. Consumers’ trust in a brand is also the brand operator’s commitment to the consumer. With the brand trust as an endorsement, perceived quality of agricultural products can promote consumers’ purchase intention toward agricultural products in some regions.


## 5.2. Implications

In view of the above conclusions, the following recommendations are put forward.First, the manager of a regional public brand should broaden sales channels to improve awareness. For example, the manager could establish flagship stores on a large-scale, third-party, e-commerce platform, such as Amazon or Alibaba. Constructing a related WeChat applet is also a good idea to improve awareness of regional public brands, to which live streaming could be added, to improve the awareness of regional public brands. Additionally, managers can build online-to-offline (O2O) smart experience stores or create new retail virtual reality experience and other high-technology stores.Second, managers should build trust in the regional agricultural products’ public brand. Based on the consumer's decision-making process, they can improve consumers’ trust in the regional public brand. During the search phase, managers should use digital economy technology to communicate brand values to consumers. During the potential purchase phase, managers can provide consumers with a value-adding trying/tasting service so that consumers can have zero-distance contact with the agricultural products and can assess their quality first-hand. During the after-sales phase, the manager can provide periodic return visits for consumers and a quick response to complaints about defective quality.Third, managers should continue to improve the quality of the agricultural products of regional public brands. To this end, they can formulate brand production standards and food processing standards by reaching out to experts and scholars from brand industry associations or product industry associations. At the same time, managers can build science and technology demonstration parks, such as the Industrial Integration Development Demonstration Park and the Science and Technology Demonstration Park, by relying on the Internet, big data, blockchain, artificial intelligence, and other emerging technologies.


## 6. Research Outlook

This study explored the key determinants of the purchase intention of regional public brand consumers. The empirical results show that consumers’ purchase intention is positively influenced by brand trust and awareness. Brand trust can therefore enhance the impact of brand awareness and perceived quality on consumers' purchase intention.The contributions of this study are as follows: First, it expands the research on consumer behavior and offers suggestions on ways to stimulate the purchase intention of consumers of regional public brands of agricultural products. Second, it provides experimental proof of how awareness significantly affects consumers’ purchase intention as well as a new theoretical explanation for the influence of awareness. Finally, it extends the research on consumers’ purchase intention in regional public brands. Our results show that brand trust plays an important mediating role because brand trust not only causes the perceived quality to affect consumers’ purchase intention positively but also enhances the impact of brand awareness on consumers’ purchase intention.Future studies could use experimental methods to explore the relationship between trust and sustainable development of regional agricultural product brands. It will be also interesting to examine more determinants, such as fairness, brand preference, and opinion leaders of social networks.



---

*Source: 4991059-2022-04-26.xml*