The Mediating Role of Perceived Value in the Relationship Between Brand Image and Repurchase Intention: A Case Study of the Chinese Tea Market

This study is dedicated to exploring how brand image influences repurchase intention through perceived value in the Chinese tea market. Five randomly selected tea brands among the top twenty tea brands in Sichuan Province were chosen as the study sample. Corporate image, product image and user image were used to measure brand image; meanwhile, functional value, emotional value, social value and price value were used to assess perceived value; and repurchase intention was directly measured through questionnaires. Six hundred valid questionnaires from consumers of these five brands were collected through the Questionnaire Star platform and analyzed by structural equation modeling using SMARTPLS 4.0 software. The results show that brand image has a significant positive effect on perceived value and repurchase intention, and perceived value plays a significant mediating role between brand image and repurchase intention. These findings not only enrich the theoretical framework, but also provide practical strategic recommendations for brand management in the Chinese tea market, emphasizing the need to pay attention to the impact of brand image on consumer repurchase intention through perceived value in the process of brand image construction and management, so as to enhance consumer loyalty and promote sustained purchase behavior.


Introduction
In contemporary marketing theory and practice, brand image plays a crucial role in fostering repurchase intentions, as highlighted in the studies by Keller [1] and D. A. Aaker and Equity [2].This is especially true in the Chinese tea market, characterized by its unique cultural and consumption traits.With increasing consumer demand for healthy, organic, and high-quality tea, establishing a strong brand image has become essential for businesses to gain competitive advantages Zhao, Lee, and Copeland [3].This research, titled "The Mediating Role of Perceived Value in the Relationship between Brand Image and Repurchase Intention: A Case Study of the Chinese Tea Market," aims to delve into how brand image influences consumers' repurchase intentions through perceived value, with a focus on the case of the Chinese tea market.
Perceived value, encompassing factors such as product quality, price, social status, and personal emotions, serves as a vital bridge between brand image and repurchase intentions [4], [5], [6].In the Chinese tea market, tea is not just a beverage but also carries profound cultural significance, placing perceived value at the core of consumer decisionmaking.Through case analysis of the Chinese tea market, this study reveals the mechanism by which brand image enhances repurchase intentions by improving perceived value and provides strategic recommendations for tea companies to strengthen their market competitiveness.
The theoretical discussion and empirical research of this paper contribute not only to the academic fields of brand management and consumer behavior but also offer practical guidance for the tea industry facing challenges such as inadequate brand planning, upgraded tea consumption, and weak competitiveness [7].This research is significant as it deepens the understanding of the relationship between brand image, perceived value, and repurchase intention, and provides practical guidance for businesses operating in rapidly changing market environments, particularly in the Chinese tea market with its rich cultural heritage and vast market potential.
Research on repurchase intentions has highlighted its importance in marketing, especially its direct correlation with customer retention and long-term profitability.Fournier and Yao [11] emphasized repurchase as an important indicator of customer loyalty, and Reichheld and Schefter [9] showed that increasing repurchase rates can significantly increase profitability and reduce customer acquisition costs.Anderson & Sullivan [12] argued that repurchase rate is an effective tool to measure the market acceptance of a product or service, while Kotler and Keller [13] suggested that by analyzing repurchase patterns, firms can better understand their customers' needs.Zeithaml, Berry, and Parasuraman [14] stated that high repurchase rate is essential for building stable customer relationships and enhancing brand reputation and market position.In addition, the e-commerce environment, consumer behavioral psychology, the relationship between brand loyalty and customer satisfaction, and the impact of social media and digital marketing strategies on repurchase intentions are also important areas of research, such as the impact of social media, as explored by Kim and Johnson [15], and the psychological factors of consumers, as focused by Macdonald et al. [16].As a result, repurchase intentions have become a key metric for assessing customer loyalty, market performance, and long-term success.

Brand Image
Brand image occupies a central place in modern marketing and consumer behavior, and is embodied in consumers' overall perceptions and emotions about a brand.This concept is not only about the consumer's direct knowledge and experience, but also about the emotional values and personality that the brand conveys Keller and Lehmann [17].With the rise of social media and digital marketing, the way in which brand image is constructed and communicated has undergone a transformation, with personal experience, online word-of-mouth, and socio-cultural factors becoming increasingly important to its impact Hollebeek, Glynn, and Brodie [18].
The composition of brand image is multidimensional and involves elements such as brand perception, personality, emotions and relationships.Brand perception reflects consumers' understanding of brand attributes and values, and is usually constructed from visual identities, slogans, and marketing messages [19].Brand personality describes the personality traits presented by the brand, such as sincerity, bravery, or luxury, which help to build an emotional connection with consumers [5].Brand emotion, on the other hand, is the consumer's emotional response to the brand, such as fondness, trust, or respect, which directly affects their loyalty and purchase decisions [20].Brand relationships emphasize long-term interactions between consumers and brands and reflect consumer commitment and trust [21].
Brand image has a profound effect on consumer behavior.A positive brand image enhances brand recognition and promotes purchase intention [19].Good brand personality deepens emotional connection and enhances loyalty [5].Brand emotions drive purchase and recommendation behavior [20].Strong brand relationships promote enduring loyalty and word-of-mouth communication [21].Brand image plays a decisive role in building and maintaining a brand's competitive advantage.Through effective brand management and innovative marketing strategies, companies are able to build a strong brand image, stand out in the fierce market competition and achieve long-term success.

Perceived Value
Perceived value refers to a consumer's overall evaluation of a product or service, which is based not only on price and quality, but also on multidimensional factors such as the product's functionality, emotional connection, and social value, etc. Zeithaml [14] first introduced this concept by emphasizing that consumers consider the overall value they bring to a product or service when evaluating it.When the perceived value of a product exceeds its market price, consumers' motivation to buy and the likelihood of repeat purchases increase significantly [22].In addition, a product or service that fits with a consumer's personal identity and values enhances his or her loyalty to the brand [23] [19], product innovation [24], corporate social responsibility (CSR) [25], and personalized service [26], can significantly influence consumers' perceived value.These factors increase perceived value by enhancing the uniqueness of the product, improving the consumer's emotional experience, or fulfilling socially responsible expectations, both online and offline, which are non-negligible factors influencing the consumer's decisionmaking process.

Research Framework and Hypotheses
In reviewing the literature, studies by [27], [28], [29] have shown that brand image is positively correlated with repurchase intention, Therefore, this study proposes Hypothesis 1: Brand image has a positive effect on repurchase.
Zeithaml [14] showed that a strong brand image significantly enhances the perceived quality and value of a product or service.Fournier [30] emphasized that brand image brings additional emotional value to consumers through emotional connection and identification with the brand's personality.Kaplan and Haenlein 31 pointed out the importance of social media and online marketing in enhancing the importance of social media and online marketing in enhancing the perceived emotional and social value of a brand.Holt [32] found that brand storytelling and digital content are crucial in shaping brand image and increasing perceived value.Kapferer and Bastien [33] noted that the impact of brand image on perceived value varies significantly across cultures and markets.Therefore, this study proposes Hypothesis 2: Brand image has an impact on perceived value.
Perceived value includes functional, emotional, social, and economic dimensions that together influence repurchase decisions [6].It is crucial for customer satisfaction, which in turn positively influences repurchase intentions [13].High perceived value also enhances brand loyalty and promotes repurchase [8].Positive social media interactions enhance perceived value and increase repurchase likelihood [34].The relationship between perceived value and repurchase intention varies across cultures and is influenced by cultural values and consumption habits [35].Therefore, Hypothesis 3 is proposed: perceived value has an effect on repurchase intention.Based on hypotheses 2 and 3, this study proposes hypothesis 4: brand image has an effect on repurchase intention through perceived value, and figure 1 below illustrates research framework used in this research.

Population and Sample
In terms of sample and data collection, the subjects of the study were consumers of five tea brands (Zhu ye qing; Meng ding gan lu; Mi cang shan; Longdu xiangming; Tian fu long ya) randomly selected from the top twenty tea brands in Sichuan Province.For each tea brand, 120 questionnaires were collected through Questionnaire Star, 600 valid questionnaires were received.

Formation of the Questionnaire
Firstly, the questionnaire framework is devised based on the needs of the research.In this study, the brand image of tea is measured using Biel [36] three dimensions (corporate image, product image, and user image); perceived value is measured using Sweeney and Soutar [6] four dimensions (functional value, emotional value, social value, and price value).The researchers formulated the questionnaire questions based on relevant literature from [36], [37], [38], [39], and [40], [6].The questionnaire is divided into four sections: 1) Basic information 2) Tea brand image (15 items) 3) Perceived value (20 items) 4) Repurchase intention (3 items).Sections 2 to 4 are assessed using a Likert 5-point scale, ranging from 1 ("strongly disagree") to 5 ("strongly agree").
Subsequently, the researchers invited three experts to conduct a quality assessment verification of the draft questionnaire.The Item-Objective Consistency Index (IOC) ranged from 0.67 to 1.00, indicating that the questionnaire items are consistent with the research objectives and content, in accordance with the research methodology of Rovinelli and Hambleton [41].Modifications were made to address the issues identified in the questionnaire.
Finally, a pre-survey evaluation of the questionnaire was conducted, yielding 63 valid responses.The reliability of the questionnaire, as indicated by Cronbach's alpha coefficients, was greater than 0.985, confirming its validity.Minor modifications and adjustments were made to the questionnaire, resulting in the final survey instrument.

Questionnaire Collection
The researcher meticulously entered the questionnaire questions into Questionnaire Star, a specialized tool designed for creating survey URLs and QR codes.This process facilitated the seamless distribution of the questionnaires, ensuring that respondents could easily access and complete them online.To gather a diverse range of responses, the researcher partnered with five tea brand shops, strategically chosen for their varied customer bases.These shops displayed the QR codes prominently, inviting their patrons to participate in the survey.This method not only streamlined data collection but also enhanced the likelihood of obtaining a broad and representative sample of tea drinkers, thereby enriching the quality and reliability of the research findings.

Statistical Analysis
The study utilized SMARTPLS 4.0 software to analyze the collected data using Structural Equation Modeling (SEM).SEM was chosen due to its ability to examine complex relationships between latent variables, providing more accurate and reliable results.By employing SMARTPLS 4.0, researchers were able to efficiently identify and measure the pathways between variables, including assessing the validity and reliability of the constructs analyzed.The findings from this analysis are expected to offer deep insights into the patterns within the data, which can then be used to make practical and theoretical recommendations relevant to the research context.

Analysis of the Descriptive Statistics
In the basic information collection from 600 respondents, there were 292 male participants (48.67%) and 308 female participants (51.33%), with no significant gender differences observed in the behavior of purchasing tea.In terms of age distribution, the majority of respondents were concentrated in the 40-59 age group, totaling 352 individuals (58.67%).Regarding income levels, the largest group of respondents had a monthly income ranging from 4,001 to 8,000 RMB, accounting for 368 individuals (61.34%).The educational level was mainly distributed between high school/technical secondary school and junior college/bachelor's degree, with 455 individuals (75.83%).Additionally, all respondents indicated that they frequently purchase tea, totaling 600 individuals (100%), among whom 336 (56%) primarily buy tea for personal consumption.
It can be seen from the table 1 and figure 2 that the mean values of each Construct are between 3.357-3.586,which shows that the distribution is relatively balanced, and the standard deviation of each variable is between 1.018-1.287,indicating that the sample data has a small dispersion.Klein [42] believes that when the absolute value of the skewness of the sample data is <3 and the absolute value of the kurtosis is <10, the observed variables can be considered to basically conform to the normal distribution.Therefore, it can be considered that the shape of the large sample data basically conforms to the normal distribution, which meets the basic requirements of the analysis data of the research hypothesis of this article.

Analysis of Measurement Model
The data were analyzed using SMARTPLS software.The selection of the structural equation modeling-partial least squares (SEM-PLS) approach was based on the PLS method's ability to maximize explained variance [43].Literature review revealed that studies on brand image influencing repurchase intentions through perceived value, specifically utilizing tea as the research subject, are rare.Therefore, employing the PLS structural equation model for analysis is particularly appropriate [43], [44].Based on this, the current study conducted structural equation modeling analysis using SMARTPLS 4.0 software.

Validity and Reliability
Cronbach's Alpha and composite reliability were used to measure the reliability of the structure.Table 2 in the measurement model showed that Cronbach's Alpha coefficients for the individual observed variables range from 0.897 to 0.906, and composite reliability values range from 0.924 to 0.930; Table 3 showed that Cronbach's Alpha coefficients for the three latent variables range from 0.732 to 0.813, and composite reliability values range from 0.849 to 0.877.the Cronbach's values for both Alpha and composite reliability were above the recommended threshold of 0.70, indicating acceptability [45].Therefore, the structure in the research model is acceptable [46].In the assessment of discriminant validity among constructs, the HTMT ratio was considered a relatively new and effective method.According to the study by Henseler, Ringle, and Sarstedt [47], an HTMT ratio below 0.85 was indicative of good discriminant validity among the constructs within the model.In certain cases, a more stringent criterion of 0.90 was applied, depending on the specific conditions and conventions of the research field, as noted by [48].The results reported in table 4 showed that the HTMT ratios for the examined dimensions ranged from 0.298 to 0.623, all significantly below the threshold of 0.85.Therefore, these findings indicated that each measured dimension had clear statistical discriminant validity, and each construct effectively reflected its unique phenomena or attributes, as established by [47].The data in table 5 showed that the square root of the AVE for each construct exceeded the correlation coefficients between it and all other related constructs, thereby meeting the Fornell-Larcker criterion.Hence, it was inferred that the constructs within the model had appropriate discriminant validity among each other, and each construct effectively captured the unique phenomena or attributes it was intended to reflect, as established by [45].

Collinearity Indicators
In the structural equation modeling (SEM), the Variance Inflation Factor (VIF) was used as a key statistical indicator to measure multicollinearity.VIF provided a method to quantify the degree of interdependence among the predictive variables, thereby assisting researchers in identifying and addressing collinearity issues, as noted by [49].In table 6, the reported VIF values for the Outer model (external model) indicated the level of multicollinearity among the observed variables.It was considered that multicollinearity was acceptable when VIF values were below 5, as suggested by [50].The table showed that all VIF values were less than 3, indicating that the problem of collinearity among the predictive variables was not significant.Therefore, it could be concluded that these variables were statistically reasonable.In table 7, the values of each observed variable are all less than 2, which is far below the threshold of 5, indicating that there is no significant multicollinearity problem with these observed variables in the model [50].In the analysis of SEM, the coefficient of determination (R-square, R²) is a key indicator used to measure how the independent variables in the model explain the variation in the dependent variable.Table 8 shown the R² values for each observed variable.The higher the R² values, the greater the extent of variance in the data explained by the model.Generally, an R² value greater than 0.10 was considered to indicate the minimum acceptable explanatory power of a model, as suggested by [50].According to table 8, the R² values for each observed variable exceeded 0.60, demonstrating excellent performance in explaining the variance of their respective constructs.Additionally, table 9 revealed that latent variables such as Perceived Value and repurchase intention had R² values over 0.220, indicating a high overall explanatory degree of brand image on Perceived Value and repurchase intention.These results suggested that the proposed model was statistically reasonable and capable of effectively explaining the observed data variability, as indicated by [50].

Measurement Model's f² Values
In the analysis of SEM, the effect size (f²) was used to measure the relative impact of one variable on another.According to Hair et al. [20], f² values of 0.02, 0.15, and 0.35 represented small, medium, and large effects, respectively [51].In table 10, the f² value of brand image on Perceived Value was 0.296, indicating a medium to large effect, while its effect on repurchase intention was 0.041, suggesting a smaller effect.The f² value of Perceived Value on repurchase intention was 0.112, indicating a small to medium effect.These results provided quantitative indicators of the importance of relationships between variables in the model.The path coefficient from BI to RI is 0.202, demonstrating a strong positive effect of BI in enhancing RI.Its T-statistic is4.751, indicating the effect's substantial significance, with a corresponding P-value of 0.000 [50].The path coefficient from PEV to RI is 0.339, signifying a notable positive impact of PEV on RI.The T-statistic is 8.358, also denoting a highly significant result, with the P-value similarly being 0.000 [50.
In table 12, each path coefficient is detailed with Original Sample Estimates (O), Sample Means (M), and the 95% Confidence Interval bounds-lower (2.5%) and upper (97.5%).According to Cumming (2014), a path coefficient is statistically significant if its confidence interval does not include zero.For the path from BI to PEV, the confidence interval is between0.414and 0.542.In the path from BI to RI, the interval ranges from 0.117 to 0.286.Similarly, for the path from PEVto RI, the interval extends from 0.259 to 0.419.These intervals indicate significant statistical effects in each case.In table 14, the 95% confidence interval for the impact path from BI through PEV to RI ranges from 0.120 to 0.212, with the lower bound at the 2.5% confidence interval being 0.099 and the upper bound at the 97.5% confidence interval being 0.179.This range, entirely above zero, indicates the statistical significance of these path coefficients, thereby substantiating the hypothesis that Brand Image influences RI through PEV, as pr the analytical framework suggested by [52].Vol.

Hypothesis Testing
The results from tables 11 and 13 reveal significant effects of brand image on repurchase intention (β = 0.202, p = 0.000), brand image on Perceived Value (β = 0. 478, p = 0.000), Perceived Value on repurchase intention (β = 0.339, p = 0.000), and the mediating role of customer engagement in the relationship between brand image and repurchase intention (β = 0.162, p = 0.000).Accordingly, all four hypotheses of this study are supported, with detailed data presented in table 15 and illustrates in figure 3.

The Impact of Brand Image on Repurchase Intentions
In this study, we explored how the brand image of tea influences repurchase intentions and thus confirmed Research Hypothesis 1.The results show that a positive tea brand image significantly enhances consumers' intention to repurchase.This research utilized Biel [36], three-dimensional model of brand image (corporate image, product image, and user image) to comprehensively measure the tea brand image.In assessing corporate image, the study evaluated the company's strength, reputation, trustworthiness, social responsibility, and growth potential through five key questions, considering these factors crucial in enhancing consumer trust and brand loyalty.Regarding product image, the study assessed aspects such as packaging, freshness, quality, cultural elements, and value for money, emphasizing their significant impact on consumer satisfaction and repurchase intention.In terms of user image, the study examined the congruence between the brand and the consumer's income, cultural cultivation, lifestyle, and social status, reflecting the brand as a mirror of the consumer's social identity and lifestyle.
Furthermore, this study directly measured consumer repurchase intention through three questions, highlighting the significant role of tea brand image in encouraging consumers to choose the brand again.The findings of [53], [54], [29], align with the results of this study, further substantiating the crucial role of tea brand image in influencing consumer repurchase intentions.Vol.The findings substantiate that a positive tea brand image significantly enhances perceived value.The research scope encompassed factors such as the strength, reputation, consumer trust, social responsibility, and growth potential of tea companies.The assessment of tea product image included aesthetics of packaging, product freshness, quality, representation of tea culture, and cost-effectiveness.The evaluation of user image focused on the congruence between the brand and consumers in terms of income, cultural literacy, lifestyle, social status, and symbolic recognition.Perceived value was comprehensively assessed through functional value (quality assurance, expression of tea culture, sensory perfection, health benefits, efficacy), emotional value (pleasure, dependency, emotional resonance, fond memories, associations with tea culture), social value (alignment of the brand with consumers' social status, projection of a positive and healthy self-image, cultural cultivation, alignment of values, sense of social responsibility), and price value (reasonableness of price, value for money, quality-price correlation, market competitiveness, correctness of purchasing decisions).The outcomes of this research align with findings from scholars such as Solomon [55], and Ilahi and Syaefulloh [56], further enriching the theoretical and practical domains of brand management and consumer behavior.

The Impact of Perceived Value on Repurchase Intentions
This study investigated the impact of perceived value on repurchase intentions, thereby confirming Research Hypothesis 3. The results indicate that perceived value significantly enhances repurchase intentions.The research comprehensively assessed functional value (quality assurance, expression of tea culture, sensory experience, health benefits, efficacy), emotional value (pleasure, dependency, emotional resonance, fond memories, connection with tea culture), social value (alignment of the brand with consumers' social status, projection of a positive and healthy selfimage, cultural cultivation, alignment of values, sense of social responsibility), and price value (reasonableness of price, value for money, quality-price relationship, market competitiveness, correctness of purchasing decisions).Repurchase intentions were directly measured through three questions: "If I could choose again, I would repurchase this tea brand," "I plan to continue purchasing tea from this brand," and "If I need tea, this brand will be my first choice."The findings of this study are in line with the research of Cipto and Erdiansyah [57],Ubogbram Gideon Chukwengwem [58], further validating the significant role of perceived value in influencing consumer repurchase intentions.

The Impact of Brand Image on Repurchase Intentions through Perceived Value
This study explored the mediating role of perceived value, specifically how tea brand image influences repurchase intentions, thereby validating Research Hypothesis 4. The results confirmed that perceived value significantly mediates the relationship between tea brand image and repurchase intentions.The study comprehensively evaluated factors such as the strength, reputation, consumer trust, social responsibility, and growth potential of tea companies, as well as the aesthetics of packaging, freshness, overall quality, cultural representation, and cost-effectiveness of tea products.The assessment of user image considered the alignment between the brand and consumers in terms of income, cultural literacy, lifestyle, social status, and peer recognition.Perceived value was assessed across four dimensions: functional value, emotional value, social value, and price value.Repurchase intentions were directly measured through three specific questions.
This research unveiled the mechanism by which tea brand image enhances perceived value, thereby affecting repurchase behavior.It offers a new perspective on how to enhance the mediating role of perceived value within tea brand image to influence consumer behavior, enriching the theoretical and practical domains of tea brand management and consumer behavior.

Figure 2 .
Figure 2. Measurement Model of the study

Figure 3 .
Figure 3. Structural model of this study

Table 1 .
Statistics the mean, standard deviation, skewness and kurtosis

Table 2 .
Consistency Indicators of Observational Variables

Table 3 .
Consistency Indicators of Latent Variables

Table 4 .
HTMT of the observed variables

Table 8 .
R² of Each Observed Variable

Table 9 .
R² of Each Latent Variable

Table 10 .
[50]alues of the Measurement ModelBased on the measurement of various indicators, the measurement model of this study demonstrated good statistical properties, supporting the hypotheses of the study.4.3.Analysis of Structural Model4.3.1.Direct Effects Between VariablesAs can be seen in table11, the path coefficient from Brand Image (BI) to Perceived Value (PEV) is 0.478, indicating a positive influence of BI on PEV.The path's T-statistic is 14.553, substantially surpassing the common critical value (e.g., 1.96), with a corresponding P-value of 0.000, signifying this result's high statistical significance[50].

Table 11 .
Direct Effects between Variables

Table 12 .
[20]ct Impact Metrics Between Variables Within Confidence Intervals table 13, the path coefficient from BI through PEV to RI has an O of 0.162.The M is 0.163, demonstrating exceptional stability of this path coefficient across bootstrap samples.The Standard Deviation (STDEV) is 0.023, reflecting the variability of the path coefficient within the bootstrap samples.The T-statistic (|O/STDEV|) is 7.067, significantly exceeding the commonly used critical values, indicating the high statistical significance of the path from BI through PEV to RI.The P-value is 0.000, further emphasizing the strong significance of this path coefficient[20]. In

Table 13 .
Indirect Effects Between Variables

Table 14 .
Indirect Effects Metrics Between Variables Within Confidence Intervals

Table 15 .
The results of hypothesis testing The Impact of Brand Image on Perceived ValueThis study delved into the impact of tea brand image on perceived value, thereby confirming Research Hypothesis 2.