This study aims to research the impact of brand ethnicity on consumers’ purchase intention and the psychological mechanism of native consumers under the stimulus of brand ethnicity in the context of domestic brand consumption.
Based on stimulus-organism-response theory, this research constructed a chain mediation model with brand ethnicity as the independent variable and conducted three empirical studies on Chinese consumers to explore the relationship between brand ethnicity and purchase intention.
The empirical results of three studies demonstrate that the five dimensions of brand ethnicity – domestic identity, political stance, national contribution, market performance and national culture – exert a significant and positive influence on Chinese consumers’ purchase intentions. Furthermore, brand attachment and brand trust play independent and chain mediating roles between brand ethnicity and purchase intention.
Consumers’ purchase intention is affected by many factors including brand symbolic meaning. Brand ethnicity is one emerging classification of brand symbolic meaning which can influence consumers’ purchase intention. To explore the mechanism, this study has constructed a chain mediation model with brand ethnicity as the independent variable.
1. Introduction
In the context of improving the quality and upgrading of Chinese consumption, Chinese consumers pay more attention to the value and cultural attributes of products. Their recognition of domestic brands is gradually increasing as well, which promotes the continuous expansion of domestic consumption. For instance, in 2021, the domestic brand Hongxing Erke donated 50 million yuan to assist with the Chinese flood disaster, which behavior met the psychological expectations of consumers for domestic brands. Thus, it greatly stimulated Chinese consumers’ purchasing desire for Hongxing Erke, causing the sales volume of it to increase by 52 times year-on-year within just 2 days. Brand ethnicity is consumers’ association and identity between the brand and the ethnic group (Li et al., 2013), reflecting the core value of brand identity and characteristics (Wang et al., 2024). It is one of the most suitable perspectives to classify the symbolic meaning of domestic brands, which is helpful in analyzing the relationship between domestic brands and local consumers’ purchase intention.
As an emerging concept, brand ethnicity has attracted the attention of scholars. Previous studies have focused on the concepts related to ethnic brands, such as ethnic elements in brands and ethnic brand identity (Chatzopoulou and Navazhylava, 2022; Li et al., 2023). The concept of brand ethnicity has been put forward in recent years, which includes many bands’ dimensions. For example, Cleveland and Bartikowski (2023) divided it into four dimensions – national identity, consumer cultural identity, cosmopolitanism and acculturation. Wang et al. (2024) also divided brand ethnicity into five dimensions in the Chinese context – domestic identity, political stance, national contribution, market performance and national culture. Since brand ethnicity is an emerging concept, our understanding of its impact on consumer purchase intention is still in its early stages. The most recent research by Wang et al. (2024) examined brand ethnicity’s influence on politically motivated purchase decisions. Building upon this foundation, this study extends the investigation into routine consumer contexts, exploring its effects on daily purchase intention and behavior. Moreover, the underlying mechanism between brand ethnicity and consumer purchase intention has not been fully studied. Therefore, based on the definition of brand ethnicity by Wang et al. (2024), this study attempts to further explore the relationship between brand ethnicity and purchase intention.
Previous studies have shown that brand attachment and brand trust play an important role in consumer consumption behavior (Bae and Kim, 2023; Choi et al., 2024). As a rational attitude, brand trust needs more external information and cognitive accumulation (Ling et al., 2023), while brand attachment can enhance brand credibility from the emotional level (Belaid and Temessek Behi, 2011). Thus, these two dimensions can appropriately analyze consumers’ psychology when they are exposed to the brands. What’s more, consumers’ psychology is exceedingly complex; combining these two dimensions is more beneficial to comprehensively measure consumers’ emotions and attitudes towards the brand. In addition, existing studies have not yet thoroughly explored the psychological proceeding mechanism through which brand ethnicity influences consumers’ purchase intentions. Meanwhile, although previous studies have demonstrated that brand attachment can impact brand trust (Aboulnasr and Tran, 2019; Yu and Yuan, 2019), studies usually select one of the dimensions to study the consumers’ psychology (Gul et al., 2021; Chand and Fei, 2021). Therefore, the chain mediating role of brand attachment and brand trust in the relationship between brand ethnicity and purchase intention is worthy of further exploration.
Stimulus-organism-response (SOR) theory proposed by Mehrabian and Russell (1974) can well explain the whole process that external stimuli affect an individual’s internal emotion and cognition and then affect individual behavior response, which is widely used to explore consumers’ purchase behavior (Laos-Espinoza et al., 2024; Yadav et al., 2024). Therefore, leveraging the SOR theory and the perspective of brand ethnicity, this research investigated consumers’ purchase intentions toward domestic brands in the Chinese context. Furthermore, this study explored the underlying mechanism between brand ethnicity and purchase intention by introducing brand attachment and brand trust to establish a chain-mediating framework. According to this, the study aimed to answer the following research questions.
Does brand ethnicity improve Chinese consumers’ purchase intention?
How do brand attachment and brand trust affect the relationship between brand ethnicity and Chinese consumers’ purchase intention?
The structure of this research is as follows. Following the introduction, Section 2 analyzes the SOR theory for framework development, as well as theoretical hypotheses. From Sections 3–5, we present three studies to examine the relationship between brand ethnicity and Chinese consumers’ purchase intention. Finally, conclusions and implications are reported in Section 6.
2. Research hypotheses
2.1 SOR theory
SOR theory shows that individuals will consciously process the valid information in the external stimuli they receive and make relevant behavioral decisions based on the processing results (Mehrabian and Russell, 1974). It is regarded as one of the most representative theories for studying consumer behavior and has been widely used (Chiles and McMackin, 1996). Based on the SOR theory, there are three necessary stages to make external factors stimulate consumers to produce purchasing behavior: firstly, the influence of external stimuli will make consumers connect the stimuli with their self-feelings. Secondly, consumers will generate different emotions after multiple internal processing stages. Finally, they will make a purchase decision relying on these emotions. Consequently, SOR theory can well analyze the psychological processing for consumers’ final purchase tendency or actual behavior.
From the perspective of brand ethnicity, consumers will receive different dimensions of domestic brand ethnicity information. Then they will develop various emotions and attitudes towards brands by combining this information with their own preferences and purchase experiences and form consumer behaviors in the end.
2.2 Brand ethnicity and purchase intention
Research on brand ethnicity is currently underdeveloped in the marketing literature. From the perspective of culture, scholars defined brand ethnicity as the cultural association and perceived connection consumers form with a brand, arising from its linkage to a specific ethnic group’s culture (Li et al., 2013). However, this definition ignores the influence of political, social and economic attributes of a brand on consumers’ purchase intention. Wang et al. (2024) defined the concept of brand ethnicity by associating it with the social identity theory, holding that it is the social construction and mobilization of domestic consumers towards domestic brands in terms of blood, politics and culture, which reflected the existence or expectation of the common subjective consciousness of domestic consumers towards brands. It also was divided into five dimensions – domestic identity, political stance, national contribution, market performance and national culture. Domestic identity refers to the brand’s ownership, whether it belongs to China, including brand registration place, identity ownership and enterprise control ownership. Political stance means that domestic brands should have a clear and unified stance in both domestic and international markets, including actively aligning with Chinese policies and safeguarding Chinese interests on the global market. National contribution refers to the brand taking the initiative to undertake certain social responsibilities like promoting the country’s development, improving people’s livelihood and responding to disasters and emergencies. Market performance means that the brand should be in a leading position in both domestic and international markets. This implies that domestic consumers have a desire for the brand to have a high level of recognition in both domestic and international markets. National culture means that the brand’s core connotation embodies the national spirit and feelings of the country and the products reflect cultural characteristics. These definition and segmentation dimension are exceedingly accord with the Chinese context, which is conducive to research the relationship between brand ethnicity and consumers. Therefore, this study applies Wang et al.’s (2024) definition and dimensions of brand ethnicity.
Relevant research shows that each dimension of brand ethnicity will positively promote consumers’ purchase intention of domestic products. Brand ethnicity is proposed based on the country of origin of the brand (Phau and Prendergast, 2000), so domestic identity is the basis of brand ethnicity. According to the theory of the country of origin effect, the connection between brand and country can influence consumers’ purchase behavior through both perceptual and rational aspects (Herz and Diamantopoulos, 2013). Consumers’ strong positive or negative emotions towards a country will affect their product preferences (Josiassen et al., 2013). Based on political consumerism, consumers can express their political stances by buying or boycotting a certain brand (Georgios and Matt, 2022). The positive relationship between corporate social responsibility and consumers’ purchase intention has been confirmed by many empirical studies (Lyu et al., 2023; Ellen et al., 2006). In addition, considerable examples have shown that the social contributions of Chinese enterprises, such as White Elephant Instant Noodles employing a large number of disabled employees and Hongxing Erke donating to the disaster in Henan province, successfully stimulated consumers to make actual purchases. Consumers usually associate high reputation with high quality (Wang et al., 2021). Based on the theory of consumer behavior, brands with high market performance more easily get consumers’ attention and become the preferred object of consumers. Regarding cultural identity, consumers will have a positive attitude towards domestic brands because they are close to the symbolic meaning of domestic culture at the perceptual level (Aaker et al., 2001), which can improve the purchase intention of the brand (He and Wang, 2015). Depending on the theory of consumer purchase behavior, after identifying the five dimensions of brand ethnicity, consumers will judge and choose them and then generate purchase intention. Based on this, the following hypotheses are put forward:
Brand ethnicity positively affects consumers’ purchase intention of domestic products.
The brand’s domestic identity positively affects consumers’ purchase intention of domestic products.
The brand’s political stance positively affects consumers’ purchase intention of domestic products.
The brand’s market performance positively affects consumers’ purchase intention of domestic products.
The brand’s national contribution positively affects consumers’ purchase intention of domestic products.
The brand’s national culture positively affects consumers’ purchase intention of domestic products.
2.3 Mediating effect of brand attachment
Brand attachment has been one of the core research topics in brand studies in recent years (Sadat, 2022). Brand attachment is defined as an “ardent emotion,” which reflects the high degree of association and emotional connection between brands and consumers (Costa and Mccrae, 1992; Bidmon, 2017). The formation of brand attachment has aroused extensive discussion among many scholars. Thach and Olsen (2006) believed that brand attachment is the emotional connection between brands and consumers, which is derived from the brand image constructed by consumers’ brand perception. McManus et al. (2022) considered that the personality characteristics displayed by brands would promote the generation of brand attachment. Madadi et al. (2021) proposed that consumers’ feelings and perceptions of brands influence emotional connection and attachment formation. Liu et al. (2020) demonstrated a positive influence of consumers’ symbolic value perception on brand attachment in the hotel brands. The above studies show that a brand’s symbolic meaning shapes consumers’ psychological construction of the brand, which affects consumers’ brand attachment.
We propose that brand ethnicity influences consumers’ brand attachment across multiple dimensions. Regarding domestic identity, there is an inherent connection between domestic brands and native consumers because they are impacted by many common external factors including history and culture (Beverland et al., 2021). Liu et al. (2018) examined the impact of national identity in advertising within China, finding that such content positively influences Chinese consumers’ brand attitudes. Concerning political stance, research has indicated that political ideology can be positively related to brand attachment (Chan and Ilicic, 2019). Consumers choose brands that fit into and support their worldview; therefore, the political dimension of a brand may determine the nature of consumer–brand relationships and brand attachment (Flight and Coker, 2022). In terms of the brand’s market performance, empirical evidence has indicated that strong market performance can foster brand attachment. A strong brand is of paramount significance in competition for attracting customers (Foroudi, 2020). Simultaneously, as an important indicator of market performance (Mercedes et al., 2025), service innovation has been proven to significantly improve customers’ attitude towards the brand (Nguyen et al., 2024). Regarding national contribution, consumers develop emotional attachment when perceiving that a brand fulfills its social obligations. A brand’s substantive contributions to its nation can strengthen attachment to brands supporting national interests (Kim and Lee, 2006). In terms of national culture, Chinese consumers place high value on long history and rich cultural heritage (He and Wang, 2015). Thus, the brands with the elements of Chinese culture are more possibly chosen and loved by the Chinese consumers. Therefore, customers’ brand attachment will increase if enterprises’ each dimension of brand ethnicity is at a high level.
As important as brand equity, brand attachment plays a certain role in influencing consumers’ purchase behavior (Park et al., 2010). Plenty of studies have shown that brand attachment can have a positive impact on consumers’ purchasing behavior. Ahn and Back (2019) verified the promotion effect of brand attachment on purchase behavior in tourism consumption. In convenience products, Gul et al. (2021) demonstrated that brand attachment is an important criterion for improving consumers’ purchase intention. Moreover, when consumers form strong brand attachment, it is conducive to improving their willingness to maintain long-term relationships with brands (Chand and Fei, 2021; Vredeveld, 2018). Therefore, based on SOR theory, the following hypotheses are put forward:
Consumers’ brand attachment plays a mediating role between brand ethnicity and consumers’ purchase intention.
2.4 Mediating effect of brand trust
Brand trust is a kind of confidence attitude held by consumers towards products or services provided by a brand (Hsiao et al., 2016). In the field of brand research, scholars usually study the formation of brand trust from the viewpoint of consumers’ psychology (Ling et al., 2023). Amyx et al. (2016) found that the formation of brand trust comes from consumers’ perception of the brand. So when consumers think that the brand is safe and reliable, they will have high brand trust. Ling et al. (2023) argued that consumers’ perception of brand image can reduce unknown risks to brands and help to enhance consumers’ brand trust. In the process of knowing a brand, consumers can represent the brand through symbolic meanings such as brand image and characteristics. It’s beneficial for consumers to evaluate their own trust in the brand after forming a unique brand positioning. When consumers feel assured about the reliability and ethical conduct of the service provider, brand trust will gradually be generated (Morgan and Hunt, 1994). The above studies demonstrate that a brand’s symbolic meaning has an important role in the process of the formation of consumers’ brand trust.
We propose that brand ethnicity influences consumers’ brand trust across multiple dimensions. Concerning domestic identity, it has a pivotal impact on shaping consumers’ preferences for domestic products (Aguilar-Rodríguez and Arias-Bolzmann, 2021a). The origin of brand is important for consumers; for example, “Country-of-Origin” labeling introduced by the European Union is aimed at assuring food safety and promoting their trust (Miguel et al., 2023). Regarding political stance, the brands’ performance on a social or political issue is an opportunity for consumers to assess whether brands possesses a consistent moral stance with themselves (Mukherjee and Althuizen, 2020). According to market performance, it can be reflected by brands’ reputation, innovation ability and so on. Siau and Shen (2003) pointed out that enterprises’ reputation is the main factor that can affect the consumers’ brand trust. Krom (2015) demonstrated that innovation has a positive influence on brand trust. Regarding national contribution, Islam et al. (2021) found that shouldering the social responsibility is beneficial to build a trustworthy relationship between brands and consumers. In addition, firms’ corporate social responsibility has been a crucial instrument for constructing trust with consumers (Khan and Fatma, 2023). Concerning national culture, Amaral and Torelli (2018) demonstrated that brands can enjoy many benefits from the interaction with the consumers when they have a salient cultural identity. The five dimensions of brand ethnicity, including the above-mentioned elements, which play an important role in consumers’ brand trust, can be an evaluation perspective of brands’ reliability and level of moral. Thus, Chinese enterprises delivering their brand ethnicity can stimulate Chinese customers to form brand trust. Moreover, consumers’ brand trust is likely to be higher if they display a very high level of brand ethnicity in all dimensions.
Scholars have been actively exploring the underlying mechanisms within the relationship between brand trust and consumer behavior. Grazioli and Jarvenpaa (2000) believed that brand trust can directly or indirectly affect consumers’ purchase intention. In advertising products, Herbst et al. (2012) discovered that brand trust was the main reason that affected consumers’ purchase intention. Barjian et al. (2021) also believed that brand trust is closely related to consumers’ purchase decisions by researching automobile brands. From existing studies, it can be found that brand trust is a key factor affecting consumers’ purchase intention. Besides, brand trust is also considered an important part of maintaining long-term relationships with consumers (Morgan and Hunt, 1994). Therefore, based on SOR theory, the following hypothesis is put forward:
Consumers’ brand trust plays a mediating role between brand ethnicity and consumers’ purchase intention.
2.5 Chain mediating role of brand attachment and brand trust
In brand research, Chaudhuri and Holbrook (2001) divided brand trust and brand emotion into two independent concepts and believed that the two jointly determined the relationship between consumers and brands. Moreover, the relevant empirical studies also show that strong brand attachment can improve consumers’ brand trust. Bidmon (2016) pointed out that brand attachment can enhance brand trust. Roy et al. (2017) revealed that brand attachment contributed to restoring brand trust in the food safety scandal. Aboulnasr and Tran (2019) found that brand attachment can effectively decrease consumers’ perceived risk associated with the really new products and increased brand trust. Yu and Yuan (2019) discovered that brand attachment can play a positive role in brand trust when they researched the factors driving consumers’ social media brand experience. Based on this, the following hypotheses are put forward:
Brand attachment and brand trust play a chain-mediating role between brand ethnicity and consumers’ purchase intention.
Frgure 1 illustrates the relationships between the constructs and hypotheses presented earlier.
The conceptual research model is presented as a flow diagram with rectangular nodes and arrows indicating relationships. On the far left, a large rectangular node is labeled “Brand Ethnicity.” Below this label, five bullet points detail its components: “1. Domestic Identity, 2. Political Position, 3. National Contribution, 4. Market Performance, 5. National Culture.” From the “Brand Ethnicity” node, two horizontal arrows extend to the right: One arrow points to a rectangular node labeled “Brand Attachment.” This node is labeled “H 2” above it. Another arrow points to a rectangular node labeled “Brand Trust.” This node is labeled “H 3” below it. There is also an arrow originating from “Brand Ethnicity” and pointing directly to the “Purchase Intention” node (described below). This arrow is labeled “H 1 (a) to (e).” From “Brand Attachment,” a downward arrow points to “Brand Trust.” This arrow is labeled “H 4.” Finally, two arrows converge from “Brand Attachment” and “Brand Trust” to a single rectangular node on the far right labeled “Purchase Intention.”Framework of the research. Source(s): Created by the authors
The conceptual research model is presented as a flow diagram with rectangular nodes and arrows indicating relationships. On the far left, a large rectangular node is labeled “Brand Ethnicity.” Below this label, five bullet points detail its components: “1. Domestic Identity, 2. Political Position, 3. National Contribution, 4. Market Performance, 5. National Culture.” From the “Brand Ethnicity” node, two horizontal arrows extend to the right: One arrow points to a rectangular node labeled “Brand Attachment.” This node is labeled “H 2” above it. Another arrow points to a rectangular node labeled “Brand Trust.” This node is labeled “H 3” below it. There is also an arrow originating from “Brand Ethnicity” and pointing directly to the “Purchase Intention” node (described below). This arrow is labeled “H 1 (a) to (e).” From “Brand Attachment,” a downward arrow points to “Brand Trust.” This arrow is labeled “H 4.” Finally, two arrows converge from “Brand Attachment” and “Brand Trust” to a single rectangular node on the far right labeled “Purchase Intention.”Framework of the research. Source(s): Created by the authors
3. Study 1
To establish the relationship between brand ethnicity and consumers’ purchase intention, this study utilized a Chi-square test of independence. Data were compiled by scraping 474 movie reviews from Douyin and Maoyan, prominent Chinese movie review platforms, from January 29 to March 5, 2025. Brand ethnicity was evaluated based on textual content: reviews explicitly referencing or endorsing brand ethnicity dimensions were scored 1, while those lacking or opposing such elements were scored 0. Similarly, watching intention was coded as 1 if reviews expressed willingness to watch/purchase and 0 if indicating unwillingness or omitting such indication.
In Table 1, the Chi-square test results (χ2 = 51.747, p < 0.001) indicated a significant positive association between brand ethnicity and consumer intention, supporting Hypothesis 1. Specifically, reviews featuring brand ethnicity elicited a substantially higher willingness to watch (78.7%) compared to those without (44.9%). This finding aligns with the SOR model–brand ethnicity acts as an external stimulus that influences consumer behavioral intentions. The result lays the foundation for further investigation into how different dimensions of brand ethnicity differentially affect consumers.
Results of the chi-square test
| Value | df | Asymptotic sig. (2-sided) | Exact sig. (2-sided) | Exact sig. (1-sided) | |
|---|---|---|---|---|---|
| Pearson chi-square | 51.747 | 1 | 0 | ||
| Continuity correction | 50.376 | 1 | 0 | ||
| Likelihood ratio | 54.228 | 1 | 0 | ||
| Fisher’s exact test | 0 | 0 | |||
| Linear-by-linear association | 51.638 | 1 | 0 | ||
| N of valid cases | 474 |
4. Study 2
4.1 Data collection and analysis
This study took individuals who consumed domestic brands as survey subjects (Table 2). A total of 400 questionnaires were distributed offline and online, and 339 valid ones were collected after screening. Geographically, the sample covered 67 cities, including those in southeast coastal areas with large consumption markets and central and western regions with fast-growing consumption. Regarding gender, women made up 58.41% and men 41.59%. According to age, 37.17% were under 19 and 48.08% were 20–29. Concerning education, 81% had a bachelor’s degree or higher. For consumption frequency, 62.53% bought domestic brands several times a month.
Demographic characteristics
| Characteristics | n = 339 | % | Characteristics | n = 339 | % |
|---|---|---|---|---|---|
| Gender | Monthly Income (RMB) | ||||
| Male | 141 | 41.59% | <2,001 yuan | 168 | 49.56% |
| Female | 198 | 58.41% | 2,001–4,000 yuan | 94 | 27.73% |
| Education | 4,001–6,000 yuan | 30 | 8.85% | ||
| Middle/high school | 35 | 10.32% | 6,001–8,000 yuan | 18 | 5.31% |
| College | 35 | 10.32% | 8,001–10,000 yuan | 9 | 2.65% |
| University | 244 | 71.98% | >10,000 yuan | 20 | 5.90% |
| Graduate school | 25 | 7.37% | Area | ||
| Age | Northeast China | 12 | 3.54% | ||
| <20 | 126 | 37.17% | Hong Kong, Macao and Taiwan | 11 | 3.24% |
| 20–29 | 163 | 48.08% | North China | 28 | 8.26% |
| 30–39 | 16 | 4.72% | East China | 197 | 58.11% |
| 40–49 | 19 | 5.60% | Northwest China | 15 | 4.42% |
| 50–59 | 14 | 4.13% | Southwest China | 23 | 6.78% |
| >59 | 1 | 0.29% | Central and southern China | 53 | 15.63% |
| Occupation | Purchase frequency | ||||
| Office worker | 28 | 8.26% | Daily purchase | 16 | 4.72% |
| Institutional person | 14 | 4.13% | Weekly purchase | 53 | 15.63% |
| Student | 257 | 75.81% | Monthly purchase | 143 | 42.18% |
| Governmental personnel | 7 | 2.06% | Annual purchase | 127 | 37.46% |
| Professional | 22 | 6.49% | |||
| Other | 11 | 3.24% | |||
4.2 Measurement
The measure of brand ethnicity was based on Wang et al.’s (2024) study, with 16 items. The measure of brand trust was referred to the study of Morgan and Hunt (1994) study, including three items. The measure of brand attachment was combined the research of Thomson et al. (2005) and Keller (2001), with four items. The measure of purchase intention was based on the study of Dodds et al. (1991) and Schiffman and Kanuk (2000), including four items. The above measures were used on a five-level Likert scale. Besides, gender, age, educational background, occupation, region and income are selected as control variables.
4.3 Common method bias test
Since all questionnaire items were filled by the same respondents, common method bias may exist. Using Harman’s single factor test, the first factor’s cumulative variance explanation rate without rotation was 31.995%, less than 40%. The total variance explained was 63.712%, indicating a single factor could not explain most variation. Thus, this study’s data did not have serious common method bias.
4.4 Reliability and validity analysis
Table 3 shows the measurement model’s reliability and validity analysis. Each variable’s Cronbach’s α ranged from 0.831 to 0.878 (>0.7), indicating strong internal consistency. The Kaiser–Meyer–Olkin (KMO) values ranged from 0.721 to 0.870 (>0.7), with significance levels less than 0.001, suggesting valid data suitable for factor analysis. Additionally, in Table 4, confirmatory factor results show that the model’s incremental fit index (IFI), comparative fit index (CFI) and Tucker–Lewis index (TLI) values all exceeded 0.8, while the root mean square error of approximation (RMSEA) value was less than 0.08, indicating a good model fit.
4.5 Descriptive statistics and correlation analysis
Table 5 shows the mean value (MV), standard deviation (SD) and correlation coefficient of all control variables and scale dimensions. Except for domestic identity, other dimensions of brand ethnicity had significantly positive correlations with purchase intention and brand attachment. Similarly, except for political stance, brand trust was highly correlated with other dimensions of brand ethnicity. For the control variables, gender had a significant impact on purchase intention; females were more willing to consume domestic products than males.
Means, standard deviation and correlation coefficients of variables
| MV | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Gender | 1.58 | 0.49 | 1 | |||||||||||||
| Age | 1.92 | 1.03 | 0.07 | 1 | ||||||||||||
| Education | 2.76 | 0.73 | 0.14* | −0.25** | 1 | |||||||||||
| Occupation | 1.65 | 1.37 | −0.12* | 0.51** | −0.30** | 1 | ||||||||||
| Area | 4.40 | 1.45 | −0.13* | −0.16** | −0.03 | −0.12* | 1 | |||||||||
| Income | 2.01 | 1.41 | −0.04 | 0.47** | −0.11* | 0.55** | −0.13* | 1 | ||||||||
| Domestic identity | 3.72 | 0.80 | 0.12* | −0.01 | 0.03 | −0.05 | 0.01 | 0.04 | 1 | |||||||
| Political position | 4.48 | 0.66 | 0.13* | −0.20** | 0.10 | −0.22** | 0.11* | −0.11* | 0.35** | 1 | ||||||
| National contribution | 4.31 | 0.74 | 0.14* | −0.12* | 0.01 | −0.13* | −0.03 | −0.12* | 0.28** | 0.56** | 1 | |||||
| Market performance | 3.94 | 0.73 | 0.11* | −0.07 | 0.01 | −0.06 | −0.03 | −0.08 | 0.30** | 0.34** | 0.56** | 1 | ||||
| National culture | 4.21 | 0.72 | 0.06 | −0.10 | −0.05 | −0.09 | −0.03 | −0.13* | 0.28** | 0.49** | 0.62** | 0.56** | 1 | |||
| Brand attachment | 3.96 | 0.74 | 0.02 | 0.01 | −0.14* | 0.05 | −0.09 | 0.04 | 0.20** | 0.26** | 0.39** | 0.46** | 0.33** | 1 | ||
| Brand trust | 3.39 | 0.81 | −0.01 | 0.13* | −0.17** | 0.15** | −0.10 | 0.12* | 0.12* | 0.09 | 0.29** | 0.41** | 0.36** | 0.54** | 1 | |
| Purchase intention | 3.87 | 0.73 | 0.12* | 0.09 | −0.07 | 0.03 | −0.08 | 0.06 | 0.24** | 0.32** | 0.43** | 0.49** | 0.39** | 0.56** | 0.50** | 1 |
4.6 Regression analysis
The effect of brand ethnicity on purchase intention was tested by regression analysis. In Table 6, all dimensions of brand ethnicity–domestic identity (β = 0.236), political stance (β = 0.318), national culture (β = 0.427), market performance (β = 0.495) and national contribution (β = 0.385) – significantly and positively affected purchase intention (P < 0.001), supporting H1a–H1e. Among them, national culture and market performance had stronger impacts (β > 0.4).
Regression analysis
| Dependent variable | Independent variable | Standardization coefficient | F | R2 | Adjusted R2 |
|---|---|---|---|---|---|
| Purchase intention | Domestic identity | 0.236*** | 19.871*** | 0.056 | 0.053 |
| Political position | 0.318*** | 37.831*** | 0.101 | 0.098 | |
| National contribution | 0.427*** | 75.082*** | 0.182 | 0.180 | |
| Market performance | 0.495*** | 109.269*** | 0.245 | 0.243 | |
| National culture | 0.385*** | 58.817*** | 0.149 | 0.146 |
4.7 Mediating effect test of brand attachment and brand trust
The chain-mediating effect of brand attachment and brand trust was tested by the Bootstrap mediating effect test, taking gender, age, education, occupation and location as covariates. Table 7 exhibits that brand attachment played a significant mediating role between brand ethnicity and purchase intention (β = 0.157, SE = 0.045, 95% CI: [0.078, 0.253]). Brand trust also played a significant mediating role between them (β = 0.170, SE = 0.047, 95% CI: [0.086, 0.270]). Moreover, the chain mediating effect of brand attachment and brand trust was significant (β = 0.091, SE = 0.022, 95% CI: [0.051, 0.137]). The above confidence intervals did not include 0, so H2, H3 and H4 were supported.
Chain mediation analysis
| Path | Indirect effect | SE | 95% confidence interval | |
|---|---|---|---|---|
| Upper limit | Lower limit | |||
| Brand ethnicity → Brand attachment → Purchase intention | 0.157 | 0.045 | 0.078 | 0.253 |
| Brand ethnicity → Brand trust → Purchase intention | 0.170 | 0.047 | 0.086 | 0.270 |
| Brand ethnicity → Brand attachment → Brand trust → Purchase intention | 0.091 | 0.022 | 0.051 | 0.137 |
4.8 Structural equation model
The influence of brand ethnicity on consumers’ purchase intention is constrained by various complex factors, making it challenging to directly identify its primary drivers and mechanisms. Therefore, to enhance the stability and accuracy of the research results, this study employed structural equation modeling (SEM) to analyze measurement errors through a set of latent variables.
After modeling 339 questionnaires using SmartPLS software, the path coefficients and fit values of the model are shown in Figure 2.
From left to right, the main constructs are: “Brand Ethnicity”: Represented by a large blue circle on the left. An arrow labeled “1.000” points from a yellow rectangle “A” to this construct. “Brand Trust”: A blue circle at the top center, with “0.375” inside. Three arrows from this circle (“0.864,” “0.860,” and “0.862”) are pointing upward to three yellow rectangles (B 1, B 2, B 3), respectively. “Brand Attachment”: A blue circle at the bottom center, with “0.125” inside. Four arrows from this circle (“0.825,” “0.826,” “0.796,” and “0.806”) are pointing downward to four yellow rectangles (C 1, C 2, C 3, C 4), respectively. “Purchase Intention”: A blue circle on the far right, with “0.435” inside. Four arrows from this circle (“0.833,” “0.837,” “0.827,” and “0.813”) are pointing right to four yellow rectangles (D 1, D 2, D 3, D 4), respectively. Arrows indicating relationships and their standardized path coefficients connect the latent constructs: From “Brand Ethnicity” to “Brand Trust”: “0.275.” From “Brand Ethnicity” to “Brand Attachment”: “0.353.” From “Brand Ethnicity” to “Purchase Intention”: “0.280.” From “Brand Trust” to “Purchase Intention”: “0.299.” From “Brand Attachment” to “Purchase Intention”: “0.249.” From “Brand Attachment” to “Brand Trust”: “0.459.”Path coefficient diagram of the structural equation model. Source(s): Created by the authors
From left to right, the main constructs are: “Brand Ethnicity”: Represented by a large blue circle on the left. An arrow labeled “1.000” points from a yellow rectangle “A” to this construct. “Brand Trust”: A blue circle at the top center, with “0.375” inside. Three arrows from this circle (“0.864,” “0.860,” and “0.862”) are pointing upward to three yellow rectangles (B 1, B 2, B 3), respectively. “Brand Attachment”: A blue circle at the bottom center, with “0.125” inside. Four arrows from this circle (“0.825,” “0.826,” “0.796,” and “0.806”) are pointing downward to four yellow rectangles (C 1, C 2, C 3, C 4), respectively. “Purchase Intention”: A blue circle on the far right, with “0.435” inside. Four arrows from this circle (“0.833,” “0.837,” “0.827,” and “0.813”) are pointing right to four yellow rectangles (D 1, D 2, D 3, D 4), respectively. Arrows indicating relationships and their standardized path coefficients connect the latent constructs: From “Brand Ethnicity” to “Brand Trust”: “0.275.” From “Brand Ethnicity” to “Brand Attachment”: “0.353.” From “Brand Ethnicity” to “Purchase Intention”: “0.280.” From “Brand Trust” to “Purchase Intention”: “0.299.” From “Brand Attachment” to “Purchase Intention”: “0.249.” From “Brand Attachment” to “Brand Trust”: “0.459.”Path coefficient diagram of the structural equation model. Source(s): Created by the authors
4.8.1 Standardized root mean square residual
In this study, the SRMR is 0.074, which is below the threshold of 0.08, suggesting that the model has a good fit. The model effectively explains the observed data, with minimal differences between the predicted and actual data.
4.8.2 Coefficient of determination
The Table 8 presents the R2 and adjusted R2 values for each endogenous. The model had the strongest explanatory power for purchase intention (R2 = 0.435, adjusted R2 = 0.430), indicating that brand attachment, brand ethnicity and brand trust effectively predict consumers’ purchase intention. The explanatory power for brand trust was also at a moderate level (R2 = 0.375, adjusted R2 = 0.371), suggesting that brand ethnicity was a significant influencing factor for brand trust. However, the explanatory power for brand attachment was relatively weak (R2 = 0.125, adjusted R2 = 0.122), implying that the formation of brand attachment may be influenced by additional factors not included in the model, which future studies could further explore.
4.8.3 Path analysis
In Table 9, path analysis using SmartPLS 3.0 and Bootstrap confirmed that brand attachment significantly and positively influences both brand trust and purchase intention. Brand ethnicity also has significant positive effects on brand attachment, brand trust and purchase intention, playing a key role in strengthening consumer attachment and trust, which further promotes purchase intention. Additionally, brand trust can significantly boost purchase intention. All results were statistically significant and aligned with the hypothesized directions, indicating that the model has strong explanatory power and a good fit.
Path analysis results
| Path coefficient | Original sample | Sample mean | Standard deviation | T statistic | p value |
|---|---|---|---|---|---|
| Brand attachment → Purchase intention | 0.248 | 0.252 | 0.056 | 4.421 | 0.000 |
| Brand ethnicity → Brand attachment | 0.134 | 0.134 | 0.059 | 2.275 | 0.023 |
| Brand ethnicity → Brand trust | 0.437 | 0.436 | 0.057 | 7.669 | 0.000 |
| Brand ethnicity → Purchase intention | 0.28 | 0.278 | 0.054 | 5.153 | 0.000 |
| Brand trust → Brand attachment | 0.496 | 0.499 | 0.056 | 8.806 | 0.000 |
| Brand trust → Purchase intention | 0.299 | 0.299 | 0.061 | 4.87 | 0.000 |
4.9 Results
Based on consumer purchasing behavior theory and SOR theory, this study investigated how brand ethnicity influences Chinese consumers’ purchase intention through brand attachment and brand trust as chain mediators.
First, all brand ethnicity dimensions positively affect purchase intention. National culture and market performance exert stronger effects than domestic identity, aligning with growing Chinese cultural confidence and “Made-in-China” support, extending the research of Wang et al. (2024).
Second, brand ethnicity positively affects purchase intention through brand attachment. The emotional bond encourages long-term domestic brand choice. SEM analysis confirmed brand attachment’s significant mediating role, enriching the conclusion of Thomson et al. (2005) in the Chinese context.
Third, brand ethnicity positively influences purchase intention through brand trust. Brand trust emerges from consumers’ psychological processing of brand ethnicity information, consistent with the research of Davoud et al. (2022) while focusing on domestic brands.
Finally, empirical analysis verifies brand attachment’s positive effect on brand trust. SEM analysis demonstrates that brand ethnicity significantly influences purchase intention through both mediators. The model shows strong explanatory power, indicating that positive brand ethnicity enables consumer consensus on domestic brands at perceptual and rational levels, enhancing purchase intention and solidifying brand–consumer relationships.
5. Study 3
To further prove the practical value of the chain mediation model with brand ethnicity being the independent variable constructed in this paper, a study was conducted on the purchasing intention of Generation Z (born between 1995 and 2009) in China’s Yangtze River Delta region for the Chinese daily chemical product brands.
5.1 Data collection and analysis
According to the proportion of permanent population in the four provinces of China’s Yangtze River Delta region, this investigation used the method of the stratified sampling design to collect the data. In total, 1,000 copies were actually distributed, and 980 copies were recovered. After excluding invalid questionnaires, a total of 843 valid questionnaires were collected.
5.2 Measurement
In the survey design, based on the chain mediation model with brand ethnicity as the independent variable set up in this study, the realistic context of Chinese daily chemical products was added to the questions. Besides, concerning the survey scope, Generation Z in the Yangtze River Delta region, the study adjusted the division criteria of control variables including age, education, occupation and region. Regarding the data, the ratio of female to male is equal (female: 52.67%, male: 47.33%); the main age group is 2000–2005 (1995–1999:31.8%, 2000–2004:60.5%, 2005–2009:7.7%); more than 60% of the population has received higher education (high school or below: 17.9%, junior college: 19.9%, bachelor’s degree: 54.6%, master’s degree or above: 7.6%); the majority of occupations are enterprise employees and students (enterprise employees: 41.5%, public institution personnel: 14.1%, students: 26.2%, government personnel: 9.7%, freelancers: 8.3%, others: 0.1%); the income of 4,001–8,000 yuan is close to 60% (below 2000 yuan: 17.3%, 2001–4,000 yuan: 12.9%, 4,001–6,000 yuan: 31.2%, 6001–8000 yuan: 25.5%, 8,001–10000 yuan: 10.2%, 10,001 and above: 2.8%).
5.3 Findings
5.3.1 Reliability and validity analysis
In Table 10, the overall scale had good reliability (Cronbach’s α = 0.903), with each variable’s Cronbach’s α ranging from 0.714 to 0.929, indicating strong internal consistency and reasonable scale design. The overall KMO value was 0.931, with each variable’s KMO exceeded 0.7, confirming suitability for exploratory factor analysis. In Table 11, model fit indices (IFI, CFI, TLI > 0.9; RMSEA < 0.08) met ideal standards, indicating good model fit.
Reliability test and validity test in the realistic context
| Factors | Number | Cronbach’s α | KMO | Ave | cr | |
|---|---|---|---|---|---|---|
| Brand ethnicity | Domestic identity | 3 | 0.791 | 0.890 | 0.532 | 0.947 |
| Political position | 4 | 0.929 | ||||
| Market performance | 3 | 0.714 | ||||
| National contribution | 3 | 0.816 | ||||
| National culture | 3 | 0.915 | ||||
| Brand attachment | 4 | 0.897 | 0.847 | 0.541 | 0.825 | |
| Brand trust | 3 | 0.801 | 0.712 | 0.549 | 0.785 | |
| Purchase intention | 4 | 0.825 | 0.810 | 0.542 | 0.825 | |
5.3.2 Regression analysis
Through the method of hierarchical regression, the analysis results of the influence of brand ethnicity on consumers’ purchase intention are shown in the Table 12. Comparing model 1 and model 2, except for national culture, other dimensions of brand ethnicity have significant positive effects on the purchase intention of Generation Z consumers.
Regression analysis in the realistic context
| Factors | Purchase intention(Y) | Consumers’ brand psychology(M) | ||||||
|---|---|---|---|---|---|---|---|---|
| Brand trust | Brand attachment | |||||||
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 | Model 8 | |
| Gender | 0.021 | 0.000 | −0.011 | −0.013 | 0.041 | 0.019 | 0.032 | −0.002 |
| Age | 0.05 | 0.034 | 0.029 | 0.03 | 0.02 | 0.008 | −0.188 | 0.008 |
| Education | 0.055 | −0.044 | 0 | −0.03 | 0.068 | −0.034* | −0.011* | −0.066 |
| Occupation | −0.031 | 0.018 | −0.014 | 0.003 | −0.023 | 0.03 | −0.075 | 0.044 |
| Area | −0.032 | 0.003 | −0.015 | −0.004 | −0.022 | 0.012 | −0.038 | 0.009 |
| Income | −0.043 | 0.012 | 0.012 | 0.032 | −0.074 | −0.012 | −0.158* | 0.102 |
| Domestic identity | 0.275*** | 0.085** | 0.291*** | −0.022 | ||||
| Political position | 0.13** | 0.072* | 0.171*** | 0.451*** | ||||
| National culture | −0.076 | 0.017 | −0.095* | 0.289*** | ||||
| Market performance | 0.228*** | 0.085** | 0.232*** | 0.055 | ||||
| National contribution | 0.26*** | 0.121*** | 0.233*** | 0.096* | ||||
| Brand attachment | 0.811*** | 0.643*** | ||||||
| Brand trust | −0.026 | −0.114*** | ||||||
Using the same method, the mediating effects of brand trust and brand attachment are tested. The model 3 revealed that brand trust played a full mediation role and that brand ethnicity can enhance brand trust and then improve purchase intention of Generation Z consumers. The mediating effect of brand attachment on the relationship between brand ethnicity and Generation Z consumers’ purchase intention is statistically non-significant.
5.3.3 The chain mediating role of brand attachment and brand trust
In Table 13, with gender, age, education, occupation and location used as covariates, the chain mediation effect of brand attachment and brand trust was tested by using the method of Bootstrap. According to Table 6, the chain mediation effect of brand attachment and brand trust was significant (β = −0.2205, SE = 0.0217, 95% confidence interval (CI): [−0.2645, −0.1800]). The CI that did not include 0 indicated that the path was well fitted as well. Meanwhile, brand attachment played a significant mediating role in the relationship between brand ethnicity and purchase intention (β = −0.1082, SE = 0.0220, 95% CI: [−0.1541, −0.0666]). This result supplemented the hierarchical regression results of brand attachment and revealed that the indirect effect through brand attachment was significantly negative. It may be because the consumption values of Generation Z consumers tend to be rational. Brand attachment tends to be emotional; therefore, the promoting effect of brand attachment is not applicable to Generation Z consumers' samples.
Chain mediation analysis in the realistic context
| Path | Indirect effect | SE | 95% confidence interval | |
|---|---|---|---|---|
| Upper limit | Lower limit | |||
| Brand ethnicity → Brand attachment → Purchase intention | −0.1082 | 0.0220 | −0.1541 | −0.0666 |
| Brand ethnicity → Brand trust → Purchase intention | 0.6676 | 0.0410 | 0.5846 | 0.7464 |
| Brand ethnicity → Brand attachment → Brand trust → Purchase intention | −0.2205 | 0.0217 | −0.2645 | −0.1800 |
6. Conclusion and implications
6.1 Conclusion
This research combines secondary data analysis with two contextualized questionnaire studies to explore the relationship between brand ethnicity and consumer purchase intention. In the secondary data analysis, brand ethnicity has a positive relationship with consumer purchase intention. In addition, the results of two contextualized questionnaire studies show that the five dimensions of brand ethnicity – domestic identity, political stance, national contribution, market performance and national culture – have significant and positive influences on Chinese consumers’ purchase intentions. Furthermore, brand attachment and brand trust play independent and chain-mediating roles in the relationship between brand ethnicity and Chinese consumers’ purchase intention.
6.2 Theoretical implications
Our findings have several theoretical implications. First, this study explored the relationship between brand ethnicity and consumers’ purchase intention for domestic products. Brand ethnicity, as an emerging research topic, has been unexplored. Domestic scholars have mainly discussed brand ethnicity’s influence on political consumption intention (Wang et al., 2024), while this research has broadened the discussion extent by using the classic purchase intention scale of Dodds et al. (1991) and Schiffman and Kanuk (2000), enriching the understanding of brand ethnicity’s mechanism on consumer behavior.
Second, while brand ethnicity includes brand behavior and symbolic meaning, its five dimensions vary in influencing purchase intentions. Notably, national culture and market expression dimensions have a stronger impact, supplementing the influence mechanism of brand ethnicity.
Third, the research has established chain-mediating mechanisms involving brand attachment and brand trust. Unlike previous cognitive-focused studies (Zhang et al., 2023; Xiaoxian and Rini, 2023), our approach considered emotional attitudes. Brand attachment emphasizing emotion and brand trust emphasizing rationality stem from complex psychological processes, explaining long-term brand preference. Hence, this study deeply explored the mediating role of consumers’ affective attitude towards brand between brand ethnicity and consumers’ purchase intention, which could help clarify the influence mechanism of brand ethnicity on purchase intention at the perceptual level.
6.3 Practical implications
First, domestic brands should recognize brand ethnicity’s role in fostering lasting consumer relationships. Given its five dimensions’ positive impact on purchase intentions, brands should highlight their domestic identity and political stance in promotions, actively promoting Chinese culture and enhancing product quality and innovation to build a strong brand image.
Second, domestic brands need to value the emotional interaction with consumers. Leveraging their rich histories, domestic brands can use their brand stories to foster brand attachment and encourage consumption. Enhancing emotional interaction during purchases can also provide high emotional value, strengthening brand attachment and long-term consumer relationships.
Third, domestic brands need to strengthen consumers’ trust, a key to lasting relationships. Brand ethnicity can clearly convey the signal of Chinese brands to consumers, linking the brand to the nation and consumers. This connection fosters initial trust, encouraging purchases. Over time, the maintenance of brand ethnicity and positive experiences from repeated purchases cultivate high brand trust, solidifying long-term consumer relationships.
6.4 Limitations and future research
This study has several limitations. First, the discussion on the domestic brand ethnicity remains relatively broad. Since this study did not classify specific product categories or individual brands, participants showed biases in their ethnic perceptions of different brands. Future research could focus on specific brands to deeply examine Chinese consumers’ brand ethnicity perceptions and related purchasing behaviors across product categories.
Second, this study’s examination of brand trust among Chinese consumers is limited in depth. Given that brand trust develops over time, the cross-sectional approach used here cannot fully capture its developmental nature. Future research could employ longitudinal tracking to measure how brand trust evolves as a mediating variable, obtaining more accurate data through multi-phase assessments.
Third, this study focused on mediating mechanisms between brand ethnicity and consumers’ purchase intention. While these mechanisms are critical to understanding brand ethnicity, the influence of moderating factors is not examined. Future research could identify relevant contextual conditions to determine how specific circumstances moderate the effects of brand ethnicity on purchase intention.
