Examining the factors influencing brand equity in online to offline (o2o) e commerce a case study of the uniqlo brand Examining the factors influencing brand equity in online to offline (o2o) e commerce a case study of the uniqlo brand
Background of Study
Over the past decade, the business landscape has undergone substantial changes, primarily due to the rapid advancement and integration of digital technology This digital transformation has significantly altered corporate operations, customer interactions with brands, and the decision-making process for purchases (Putra, 2024).
The Covid-19 pandemic significantly accelerated the growth of online shopping, making it essential to modern consumer behavior In response, businesses have increasingly adopted the Online to Offline (O2O) strategy to enhance their visibility across various platforms (European Commission, 2020) Coined by Rampell (2010), O2O directs online consumers to physical retail locations, integrating traditional sales tactics with digital transformation This model improves customer accessibility, broadens market reach, and maximizes sales potential (Lee et al., 2022; Edelmann, 2013; Li et al., 2018) Consequently, O2O has become a compelling approach, attracting more consumers and representing a frontier in E-commerce with trillion-dollar market opportunities (Yang et al., 2020).
Research indicates that consumers are highly receptive to Online to Offline (O2O) services, as they prefer to view and experience products directly before making purchases (Zhang, 2015) Improving service quality is linked to increased customer satisfaction (Rust, 1996; Suthianto, 2023), while a positive brand experience can drive both initial purchases and repeat transactions (Kristoffer & Joel, 2013) Therefore, businesses must consider various factors that influence Brand Equity in O2O e-commerce.
In the realm of O2O E-commerce, understanding the factors that affect Brand Equity is essential Recognized as a vital intangible asset in marketing, Brand Equity significantly influences corporate success by affecting consumer purchase intentions and shaping the financial valuation of organizations (Chaudhuri & Holbrook, 2001; Oliver, 1999; Stahl et al., 2012).
Klarity Marketing highlights that while products are manufactured in factories, brands exist in the perceptions of consumers Consequently, modern marketers are focusing on creating communication strategies that enhance brand value in consumer minds (Kamboj et al., 2018; Yadav & Rahman, 2018).
Recent developments indicate a significant change in how businesses engage with customers Companies are moving beyond merely emphasizing the functionality of their products or services; they are now dedicated to crafting memorable and meaningful brand experiences that connect with consumers emotionally.
The O2O framework allows brands to create emotional connections and enhance engagement through consistent positive customer experiences in both online and offline channels This has led to increased interest in how a strong corporate image and positive customer-brand relationships can be utilized to boost profitability.
Companies across various sectors, particularly in retail and fashion, have acknowledged the critical role of Brand Equity in influencing consumer trust and purchasing behavior in the O2O environment The fashion industry, in particular, has adapted to O2O strategies by striving to provide integrated experiences across both digital and physical platforms A prime example is Uniqlo, a leading Japanese fashion retailer, which has successfully utilized its digital channels to enhance foot traffic to its physical stores while preserving a strong brand identity With over 26 direct sales branches in Vietnam and a comprehensive online sales network through its website and mobile app, Uniqlo offers customers the convenience of shopping anytime Over the last five years, the brand has not only expanded its physical footprint in Vietnam but has also seen a consistent increase in revenue.
Uniqlo has successfully established strong brand recognition in Vietnam by enhancing its presence across online and offline channels (NielsenIQ, 2024) The brand effectively utilizes digital platforms to expand its marketing efforts and improve the digital customer experience, known as e-brand experience These digital interactions create a direct communication channel with customers, fostering brand love and engagement Such strategies not only boost Uniqlo’s brand equity but also keep customers informed about new product launches, leading to increased sales (Tuổi Trẻ Online, 2023) Analyzing the factors that influence Uniqlo’s brand equity provides valuable insights for fashion retailers aiming to optimize brand performance in a rapidly changing digital landscape (Wenshan Li et al., 2020).
While practical examples like Uniqlo illustrate the success of O2O strategies in enhancing Brand Equity, academic research uncovers certain limitations Key factors influencing Brand Equity in O2O e-commerce include Brand Experience, Brand Love, and Brand Engagement Brand Experience encompasses the sensory, emotional, and behavioral responses to brand stimuli that shape consumer perceptions Brand Love reflects the emotional connections consumers form with brands, fostering loyalty and engagement Lastly, Brand Engagement measures the cognitive, emotional, and behavioral involvement consumers exhibit towards a brand.
Despite valuable contributions from existing studies, a notable research gap persists regarding the importance of E-Brand Experience This concept expands traditional Brand Experience into the digital space, which is crucial as consumer journeys increasingly start online in the O2O era The digital experience—encompassing website design, interactivity, personalization, and overall online engagement—has become as significant as offline experiences.
Positive brand experiences, especially those delivered via digital platforms, greatly influence consumers' perceptions of quality and their loyalty to online shopping sites Additionally, recent research indicates that combining digital and physical brand experiences boosts Brand Equity by creating strong brand associations, enhancing brand love, and promoting deeper customer engagement.
Seamless integration of digital and physical brand experiences is crucial for fashion retailers like Uniqlo, which utilizes AI-driven virtual try-ons, real-time stock checks, and personalized recommendations to enhance its online presence This digital strategy is complemented by consistent physical store design and technology, such as interactive fitting rooms, ensuring a superior offline experience When digital and physical elements align, customers form stronger emotional connections and trust in the brand, leading to increased engagement and loyalty—key components of Brand Equity Additionally, Brand Love and Brand Engagement are vital, as Brand Love creates emotional ties that enhance loyalty, while Brand Engagement involves consumers' cognitive, emotional, and behavioral investment, strengthening relationships and advocacy Understanding the interplay of these factors in an O2O context is essential for fashion retailers aiming to build sustainable Brand Equity and maintain a competitive edge.
Sohaib et al (2022) conducted a case study on the Apple brand to investigate the factors affecting its Brand Equity Their research highlighted a significant gap in existing literature, which has primarily concentrated on Brand Experience, Brand Love, and Brand Engagement, while neglecting the critical role of E-Brand Experience In the context of the growing importance of O2O commerce, where digital interactions frequently serve as the initial contact point, E-Brand Experience is shown to have an impact comparable to that of traditional brand experiences, thereby playing a crucial role in shaping a company's brand equity.
This study aims to address the gap in existing research by integrating E-Brand Experience with established factors such as Brand Experience, Brand Love, and Brand Engagement By doing so, it provides a deeper insight into how brands can enhance their performance and bolster their Brand Equity in the evolving realm of O2O E-commerce.
Contribution of Study
This study explores the factors that impact brand equity in Online to Offline (O2O) e-commerce, using Uniqlo as a case study to offer practical insights for similar businesses The main goal is to understand how Brand Experience, E-Brand Experience, Brand Love, and Brand Engagement contribute to building strong brand equity in the O2O context The research aims to answer the question: How do these factors influence Brand Equity in O2O e-commerce?
It specifically pertains to the fulfillment of the following objectives:
1 Describing the consumer’s profile as designated by:
- Online product search and access platform
2 Exploring the significant difference between the consumers’ perception and their profile.
3 Analyze the correlation among the elements of brand experience (both offline and online), Brand love and Brand Engagement in connection to Brand Equity.
4 Propose effective strategies to enhance and cultivate Brand Equity among customers.
This study evaluates the influence of various factors on Brand Equity as perceived by young consumers in the O2O context, with a specific focus on the Uniqlo brand It addresses a gap in existing literature and builds on prior research that identified three key dependent variables: Brand Experience, Brand Love, and Brand Engagement Notably, this research is one of the few to explore the positive relationship between Online Brand Experience (EB) and Brand Equity.
This study evaluates the influence of various factors on Brand Equity as perceived by young consumers in the O2O context, with a specific focus on the Uniqlo brand It addresses a gap in existing literature and builds on prior research that identified three key dependent variables: Brand Experience, Brand Love, and Brand Engagement Notably, this research is one of the few to explore the positive relationship between Online Brand Experience and Brand Equity.
The study reveals essential factors that impact brand equity in the O2O context, offering strategic insights for enhancing omnichannel marketing and fostering offline consumer loyalty It emphasizes the significance of consumer experience, brand love, and engagement across digital and physical platforms, urging companies like Uniqlo to optimize their digital interfaces and improve in-store interactions The findings underscore the role of brand equity and brand love in shaping consumer perceptions, suggesting that maintaining product quality, leveraging user feedback, and ensuring transparent communication can strengthen long-term customer relationships Additionally, the study outlines practical implications for digital marketing strategies, demonstrating how personalized engagement, social media influence, and targeted promotions can boost offline sales and reinforce brand positioning From a comprehensive business viewpoint, these insights can inform retail development strategies, enabling companies to optimize resource allocation and enhance consumer engagement By applying these findings, businesses in the O2O marketplace can achieve a competitive edge through improved omnichannel experiences that elevate customer satisfaction and brand equity, ultimately contributing to sustainable success in the digital retail landscape.
There are 10 keys steps during the process of investigating in this research.
Step 1: Conduct document analysis to refine and specify the study subject.
Step 2: Examine the theoretical framework to discover research gaps.
Step 3: Define research objectives, delineate study scope, choose model, and determine research techniques.
Step 4: Formulate a theoretical research model
Step 5: Develop the survey and develop a questionnaire informed by prior research Step 6: Distribute questionnaire and begin data collecting
Step 7: Conduct a preliminary study to assess the reliability of the scale and perform determinant analysis to mitigate multicollinearity when utilizing multiplicative factors.
Step 9: Analyze the gathered findings
This article has five chapters: an introduction, a literature review and hypothesis formulation, a methodology section, a findings and discussion section, and a conclusions and recommendations part.
The beginning section includes the study's history, objectives, contributions, research flowchart, structure, and word definition.
The literature review chapter presents an overview of Social Exchange Theory, Attribution Theory, Brand Equity, Brand Engagement, Brand Love, Brand Experience, and E-Brand Experience from the customers' perspective.
The research methodology chapter outlines the procedures utilized in this study, detailing the operational definitions of research variables, measurement design, pilot testing, sample size determination, types of data, data collection methods, and data analysis techniques The findings from this analysis will be examined in greater detail in Chapter IV.
The Results and Discussion chapter establishes data related to descriptive analysis, mean comparison, reliability analysis, measurement model, and structural equation model.
The Conclusions and Recommendations chapter will provide a detailed overview of the study's findings and their significance, along with actionable recommendations for businesses based on the analysis Additionally, the research will highlight its limitations and encourage further investigations.
Theoretical Framework
In 1958, Homans introduced the Social Exchange Theory, proposing that social behavior is driven by an exchange process in which individuals aim to maximize benefits and minimize costs.
In 1976, Emerson's research reinforced the theory of brand-consumer relationships, highlighting that consumers assess their interactions with brands based on perceived rewards and costs, which influence their engagement and loyalty (Cook et al., 2013) Studies show that brands providing high-value experiences foster positive consumer behaviors, such as increased engagement and advocacy (Groening & Binnewies, 2019) Additionally, in Online-to-Offline (O2O) commerce, the seamless integration of digital and in-store interactions enhances perceived brand value, strengthening brand equity (Verhoef et al., 2015).
This study utilizes the Self-Expansion Theory (SET) to elucidate consumer motivations for brand engagement (BE) and brand love (BL) The model posits that when consumers perceive high value and low cost in Brand Experience (EX) and E-Brand Experience (EB), they respond with greater engagement and emotional attachment, thereby boosting Brand Equity (EQ).
Attribution Theory explores how individuals interpret events and how these interpretations shape their attitudes and behaviors (Homans, 1958; Kelley, 1967) Research by Hollebeek et al (2014) shows that consumer perceptions of brand authenticity and quality, influenced by their experiences, significantly affect brand engagement and equity Positive brand experiences, linked to a company's competence and consumer-centric approach, foster stronger consumer-brand relationships, resulting in brand love and commitment (Batra et al., 2012) This attribution process is especially important in O2O commerce, where consumer trust in digital platforms plays a crucial role in offline purchasing decisions (Kim & Ko, 2012).
Contemporary research has refined the applicability of theoretical frameworks within the digital landscape, highlighting the significance of e-brand experience as a key factor in consumer engagement and brand relationships Studies by Brakus et al (2009) and Khan et al (2016) reveal that sensory, affective, and behavioral interactions in online brand environments are crucial for fostering consumer trust and brand equity Additionally, Schivinski et al (2016) found that online brand interactions within the O2O paradigm significantly impact offline brand perceptions, enhancing overall brand resonance.
The integration of brand love into consumer-brand relationship theories provides valuable insights into emotional connections Batra et al (2012) found that brand love, defined as passionate consumer attachment, mediates the relationship between brand experience and brand equity Consumers with strong emotional ties to brands are more likely to engage in positive word-of-mouth and are less affected by negative information (Carroll & Ahuvia, 2006; France et al., 2016) In the online-to-offline (O2O) context, emotional engagement in digital spaces significantly influences real-world purchasing behaviors (Hudson et al., 2015).
In today's market, consumers seamlessly navigate between online and offline brand interactions, making it crucial to integrate these experiences into a unified theoretical model Research shows that an effective online-to-offline (O2O) strategy fosters cohesive and immersive brand experiences, leading to increased consumer engagement and brand equity Additionally, studies highlight that digital engagement strategies, especially those that include personalized interactions, social media involvement, and smooth omnichannel experiences, have a significant positive effect on brand equity.
Uniqlo's O2O strategy exemplifies the application of theoretical insights by enhancing brand equity through seamless and personalized experiences across both digital and physical channels The mobile application significantly improves the e-brand experience, while social media engagement caters to consumers' preferences for digital interactions that seamlessly transition into offline experiences.
Brand Equity
Brand equity, a term that gained prominence in the late 1990s, has become essential in marketing, influencing both theoretical frameworks and practical business applications.
Brand equity can be viewed from two main perspectives: the corporate perspective, which evaluates a brand's financial value as an indicator of company performance, and the consumer perspective, which focuses on the relationship between the brand and its customers.
The two main theoretical frameworks in brand equity research are established by Aaker (1991) and Keller (1993) Aaker defines brand equity as the collection of brand assets and liabilities associated with a specific brand, which can influence its value to both the firm and its customers His framework identifies five key elements of brand equity: brand awareness, brand associations, perceived quality, brand loyalty, and other distinctive brand assets However, marketing research often overlooks the last element due to its limited impact on consumer perceptions of the brand (Yoo & Donthu, 2001).
Keller (1993) examines brand equity by highlighting how brand knowledge influences consumer reactions to marketing efforts, underscoring the variations in customer perceptions and behaviors associated with high-value brands.
This study builds upon established theoretical foundations by incorporating four key elements from Aaker's model (1991): brand recognition, brand association, perceived quality, and brand loyalty These components are frequently utilized in prior research on brand equity (Emari et al., 2012; Ertemel et al., 2021; Soenyoto, 2015).
Recent studies highlight the importance of integrating brand equity into corporate marketing strategies to maintain a competitive edge Key factors such as brand engagement, brand love, brand experience, and e-brand experience significantly influence consumer perception, brand loyalty, and purchase intentions These elements collectively determine a brand's strength and value, underscoring the necessity for businesses to strategically manage and enhance them for optimal long-term brand performance.
Brand equity is a vital asset for businesses, representing the value a brand holds beyond its physical assets In the Online-to-Offline (O2O) context, it significantly influences consumer engagement, loyalty, and purchase decisions The integration of online and offline experiences is essential for effective O2O strategies, as studies indicate that both types of brand experiences enhance brand equity by promoting customer satisfaction and loyalty Research by Shehab and Dinana (2023) and Zhao et al (2022) underscores the advantages of combining online and offline channels, such as search convenience and direct product experiences, in shaping consumer-perceived value and brand relationships Consistent interaction across these channels is crucial for maintaining a strong brand image and equity.
The Online-to-Offline (O2O) business trend is revolutionizing the fashion industry by merging digital and physical shopping experiences This model allows consumers to easily switch between online platforms and physical stores, enhancing their overall shopping journey Research by Cai (2023) highlights the growing importance of the O2O model in fashion, as digital engagement becomes essential to consumer behavior By integrating online and offline channels, fashion brands can offer a cohesive shopping experience, enabling customers to browse products online and purchase them in-store, or vice versa This approach is particularly effective in fashion, where the need for tactile experiences and immediate satisfaction is paramount.
This study investigates the influence of critical factors on brand equity in the Online-to-Offline (O2O) business model, using Uniqlo as a case study By exploring Uniqlo's strategic methods, the research reveals how O2O integration affects brand perception, consumer engagement, and overall brand equity in today's retail environment.
Brand Experience
The concept of "brand experience," introduced by Holbrook and Hirschman in 1982, has become essential in marketing, influencing both academic research and practical applications (Amoroso et al., 2021) As marketing has evolved, frameworks like experiential marketing (Schmitt, 1999) and customer experience management (Schmitt, 2010) have emerged, providing strategies for brand differentiation Pine and Gilmore (1999) defined consumer experience as a memorable interaction with a brand, while Brakus et al (2009) described brand experience as a consumer's internal response—encompassing emotions, cognitive reactions, and behaviors—triggered by brand elements such as design, identity, packaging, communication, and environment These experiences can vary in intensity and impact consumer behavior significantly, whether positive or negative.
Brand experience is a unique concept that is associated with various brand-related elements such as brand attachment, involvement, and attitude Despite these connections, it maintains its distinct identity within the realm of brand studies.
To maintain customer engagement and enhance brand equity, brands must cultivate meaningful connections with consumers, thereby reducing the likelihood of switching to competitors (Akoglu & ệzbek, 2021) Establishing a strong brand experience is essential for building long-term relationships, as it involves complex interactions that add emotional and affective value at every consumer touchpoint (Neumeier, 2009) Marketers focus on ensuring that customers have positive experiences with their products and services, which helps associate desired thoughts, emotions, and perceptions—such as brand love and brand engagement—with the brand (Keller, 2010).
Research indicates that positive brand experiences are crucial for fostering brand love, which signifies a strong emotional connection between consumers and brands Key elements such as innovative product design and seamless user experiences enhance this emotional bond Satisfying brand experiences lead to increased consumer loyalty, emotional attachment, and a deeper connection with the brand By prioritizing meaningful and engaging experiences, brands can reinforce their identity and cultivate long-term relationships with consumers Brand experiences provide opportunities for consumers to engage, establishing a significant relationship between them and the brand.
A deeper emotional connection can enhance brand equity and strengthen brand trust Research indicates that sensory and affective experiences significantly influence all dimensions of brand equity To better understand these branding factors, several hypotheses have been proposed.
H1a: Brand Expercience is positively related to Brand Love
H1b: Brand Expercience is positively related to Brand Engagement
H1c: Brand Expercience is positively related to Brand Equity.
E- Brand Experience
E-Brand Experience emphasizes digital interactions that occur through online platforms like mobile apps, websites, and social media These experiences often involve interface usability, personalized content, and real-time responsiveness (Rose et al., 2012, Van Noort et al., 2012, Luo et al., 2011).
E-brand experience in the online environment has become a focus of research for both academics and marketers, with many studies analyzing the influencing factors and outcomes in many different contexts In particular, the shopping experience and the product and service selection process play a key role in shaping customer satisfaction, increasing brand equity (Valmohammadi et al., 2025; Suthianto, 2023). Morgan-Thomas and Veloutsou (2013) define e-brand experience as a person's subjective reaction during online interactions with brands Ha and Perks (2005) examine the "web-based brand experience" to assess customer behavior within the digital marketing context According to them, this experience includes both proactive factors, such as users participating in online communities or events, and cognitive factors, including the attractiveness of cookies, the variety, uniqueness of the website interface, as well as the value it brings to customers.
Brands leverage their online presence to foster connections and relationships with customers (Quan et al., 2020) Emotional responses and brand attachment are often triggered by brand experiences (Kang et al., 2017) Research by Khan et al (2020) indicates that brand engagement is influenced by online experiences and serves as a mediator between these experiences and brand equity Therefore, marketers should develop strategies for online brand engagement and experiences that enhance customer trust and commitment, ultimately boosting brand loyalty (Khan et al., 2020).
Recent research by Roy et al (2013) and Bıỗakcıoğlu et al (2018) highlights that a positive brand experience can cultivate brand love Studies by Zollo et al (2020) and Koay et al (2020) further emphasize the importance of social media marketing in improving e-brand experience (EB) In the realm of e-commerce, the relationship between brand experience and brand love is being increasingly clarified through works by Mulyawati et al (2020), Khamwon & Masri (2020), Kumar & Kaushik (2020), Coelho et al (2020), and Singh et al (2021) As online social media continues to evolve, prioritizing brand experience is essential for enhancing consumer trust and fostering brand love.
Recent research by Zollo et al (2020), Coelho et al (2020), and Koay et al (2020) highlights the critical role of social media marketing in improving e-brand experiences and boosting brand equity.
In 2020, a positive brand experience significantly enhances customers' appreciation of the brand image and their perception of brand equity This highlights the critical role of e-brand experience in fostering brand equity and driving overall success Thus, it can be hypothesized that e-brand experience is essential for promoting brand equity.
H2a: E-Brand Expercience is positively related to Brand Love
H2b: E-Brand Expercience is positively related to Brand Engagement
H2c: E-Brand Expercience is positively related to Brand Equity.
Brand Love
Brand love is a profound emotional connection that consumers develop with a brand, distinct from mere satisfaction, liking, or trust Defined as "the degree of passionate, emotional attachment a satisfied consumer has for a particular trade name" (Carroll & Ahuvia, 2006), brand love signifies a robust consumer-brand relationship shaped by experiences with the brand's products (Ghorbanzadeh & Rahehagh, 2020) This emotional attachment leads to increased customer engagement, loyalty, and repeat purchases (Karjaluoto et al., 2016) Positive outcomes of brand love include stronger brand associations and heightened engagement (Kang, 2015), fostering long-term consumer-brand relationships and affective brand commitment (Albert & Valette-Florence, 2010), as well as a willingness to pay premium prices (Albert et al., 2010) Furthermore, consumers who cultivate brand love are more likely to maintain long-term engagement with the brand (Ahuvia, 2005) Recent studies emphasize the importance of brand love in shaping consumer attitudes and behaviors, ultimately benefiting organizations, with a particular focus on engagement (Palusuk et al., 2019; Trivedi & Sama, 2021; Sarkar & Sreejesh, 2014).
Brand love refers to the emotional connection that enhances the relationship between consumers and a brand (Samekto et al., 2023) This emotional bond not only fosters customer loyalty but also boosts brand equity (Karjaluoto et al., 2016) However, the effect of brand love on brand equity can vary, influenced by consumer satisfaction and the brand's ability to fulfill expectations (Thomson et al., 2005) To thrive in competitive markets, brands must prioritize the cultivation of customer loyalty through brand love, a strategy that Uniqlo should embrace.
As technology advances, businesses are prioritizing social media marketing to enhance online consumer experiences through strategic promotions, which helps build trust and attract potential customers, fostering brand love (Saununu et al., 2024; Tubalawony, 2023) By combining engaging online interactions with real-life experiences, brands can strengthen emotional connections and trust, encouraging consumer attachment Research by Mayasari et al (2023) highlights the importance of social media marketing in the O2O (Online-to-Offline) context, particularly in the fashion industry and among millennials, in cultivating and deepening brand love.
Therefore, it can be hypothesized as follow:
H3a: Brand Love is positively related to Brand Engagement
H3B: Brand Love is positively related to Brand Equity.
Brand Engagement
Brand engagement has become a focal point for marketers and researchers due to its significant impact on brands and consumer behavior It is defined as the alignment between an organization's promises and individuals' intrinsic motivations, whether as employees or customers Research indicates that brand engagement is an experiential state resulting from interactions with a brand, linking consumers' flow experiences to their self-brand connections Hollebeek et al (2014) further defined brand engagement as a blend of cognitive activity, emotional attachment, and positive behavioral responses during brand interactions The level of an individual's involvement and connection with a brand's offerings is a crucial indicator of engagement.
Brand engagement is significantly shaped by customer experience and brand love, as highlighted by Syamsuddin & Fadhilla (2024) Research indicates that both brand love and engagement are essential for building brand equity (Pinto Borges et al., 2016; Seo et al., 2017; Wallace et al., 2014) Engagement is a key factor in consumer decision-making, fostering long-term relationships and brand loyalty, which are vital for effective brand management (Buckingham, 2007) Elevated levels of engagement reflect stronger emotional ties, prompting customers to cultivate enduring relationships with the brand and ultimately boosting brand equity (Zainol et al., 2016).
The O2O (Online-to-Offline) model highlights the significant impact of digital media in enhancing consumer interactions with products These interactions extend beyond mere physical engagement, offering consumers valuable brand-related knowledge.
Research across multiple industries underscores the significant role of brand engagement in enhancing brand equity In the banking sector, Prentice et al (2020) revealed that brand engagement has a profound impact on brand equity Similarly, Sohaib et al (2022) analyzed Apple's brand engagement strategy within the technology industry, confirming its effectiveness Furthermore, Vo Minh et al (2022) demonstrated that in the fashion industry, brand engagement directly boosts brand equity through online experiences on social media platforms.
Therefore, it can be hypothesized as follow:
H4: Brand Engagement is positively related to Brand Equity
Figure 1: The proposed research model
Figure 1 presents the proposal research model that is structured to evaluate the relationship between factors affecting to Brand Equity in terms of EX, EB, BL, andBE.
The Operational Definition and Measurement Design
In Structural Equation Modeling (SEM), variables are categorized as exogenous or endogenous Exogenous variables are those that are not influenced by other factors within the model, while endogenous variables are determined by one or more other variables This research provides an operational definition of these variables.
This study examines the relationships between brand love, brand engagement, and brand equity, utilizing a five-point Likert Scale for assessment The findings reveal significant insights into how these endogenous variables interact and influence consumer perceptions.
Table 1: Dimensions and indicators of Brand Equity
No Variable Items Indicators Sources
1 Brand Equity EQ1 Even if another brand’s products offer the same features as Uniqlo,
I would still use Uniqlo products.
EQ2 If there were other brands as good as this Uniqlo, I would still use Uniqlo products.
EQ3 It makes sense to buy Uniqlo instead of any other brand, even if they are the same.
EQ4 It makes sense to use this Uniqlo product instead of any other similar brand.
Table 2: Dimensions and indicators of Brand Engagement
No Variable Items Indicators Sources
BE1 Using Uniqlo products gets me to think about the Uniqlo brand.
Hollebeek et al., 2014 BE2 I feel very positive when I use
Uniqlo products BE3 Whenever I’m using Uniqlo products (such as t-shirts, shirts, trousers, pajamas, towels, accessories, etc.), I usually use Uniqlo products.
BE4 Uniqlo is one of the brands I often use when buying fashion products (such as t-shirts, shirts, trousers, pajamas, towels, accessories, etc.).
Table 3: Dimensions and indicators of Brand Love
No Variable Items Indicators Sources
3 Brand Love BL1 I love Uniqlo Brand Wang et al.,
BL2 Uniqlo products help to make me happy.
BL3 I have an excellent attachment to the quality of Uniqlo products.
BL4 I am passionate to get Uniqlo products.
Exogenous in this research includes EX and EB The measurements for each variable are shown in Table 4:
Table 4: Dimensions and indicators of Brand Experience and E – Brand
No Variable Items Indicators Sources
EX1 This brand offers a comfortable, flexible experience for the body.
EX2 The outcome of using Uniqlo products is a physical experience.
EX3 In my opinion, Uniqlo products positively impact my visual senses.
EX4 I engage in a lot of thinking when
EB1 The layout of this e- brand website is appealing.
EB2 This e-brand’s website is easy to navigate.
EB3 The results of this e-brand’s website are always up-to-date.
EB4 Accurate search results are always returned when browsing this e-brand’s website.
Scale of study
This research focuses on Uniqlo customers who have engaged with the brand's online-to-offline (O2O) shopping experience All participants are adults over the age of 18, capable of perceiving and managing their purchasing behaviors.
Data Gathering Procedure
The following steps will be used to acquire primary data from survey participants: Phase 1: The survey questionnaire serves as the primary research tool for this study.
The study has been revised based on prior research and the advisor's suggestions to enhance the reliability and effectiveness of the data collection instrument, making it suitable for the study's subject matter.
Phase 2: The survey questionnaire is given to the respondents together with an introduction letter, instructions, and a cover letter indicating the amount of time required to complete the form.
Phase 3: The researcher distributes the survey questionnaire online to collect responses using the convenience sampling method.
Population, Sample size and Sampling Techniques
This study involves 317 customers who engaged with Uniqlo's online to offline (O2O) shopping model The primary data collected for this research is sourced from these participating customers.
In order to determine the appropriate size of the sample, the following formula was utilized: n = 6 * m
Where n represents the size of the population and m is the number of questions that were included in the survey.
Given that m is equal to 27, the sample size for this investigation is calculated as follows: n = 6 * 27 = 162
This study requires data from at least 162 respondents to ensure reliability The researcher found that the information gathered from this sample reflects the experiences of individuals who have engaged with the online to offline purchasing model of the Uniqlo apparel brand in Vietnam Ultimately, data was collected from 317 customers who participated in the research.
Data Collection Technique
The data collection process aims to gather essential information needed to achieve the research goals Although the objectives are framed as hypotheses addressing the research questions, empirical verification is required to establish the answers, necessitating comprehensive data gathering.
Data collection is conducted using specific methods aligned with its objectives, necessitating various techniques during the gathering process One effective strategy for obtaining consumer insights is through questionnaires In this study, the researcher implemented a two-part survey to gather primary data from respondents familiar with the online to offline (O2O) purchasing model employed by Uniqlo.
The initial section of the survey addresses the factors affecting UNIQLO's brand equity in the context of online to offline (O2O) e-commerce, with key insights derived from the theoretical framework presented in Chapter II.
The second section provides detailed insights into the respondent's profile, covering key demographics such as gender, age, monthly income, and occupation, as well as their preferred sources for information regarding Uniqlo products.
Data was collected using a five-point Likert scale to assess respondents' perceptions This scale included five levels: Strongly Disagree, Disagree, Neutral, Agree, and Strongly Agree.
Data Analysis Technique
The data obtained from the surveys will undergo a coding, capturing, and editing process For data analysis, the study will utilize the Statistical Package for Social Sciences (SPSS) version 26 and Partial Least Squares (Smart PLS version 4.0).
This study utilizes SPSS and SmartPLS to enhance analytical depth and reliability SPSS handles fundamental statistical tasks such as descriptive analysis, T-tests, ANOVA, and multicollinearity checks, while SmartPLS is employed for PLS-SEM, making it suitable for complex models and non-normally distributed data This approach allows for thorough evaluation of both the measurement model and the structural model, thereby reinforcing the analytical rigor and academic value of the research.
Following is a breakdown of the process of data analysis as well as the methods that will be utilized:
Descriptive statistics, as noted by Lind et al (2005), encompass various methods used to organize, summarize, and present data effectively, providing valuable insights Raw data, such as population censuses or the weekly salaries of computer programmers, often lacks inherent value By applying statistical techniques, this data can be systematically organized, improving its clarity and usefulness.
Descriptive statistics are essential for analyzing a sample to draw conclusions about a larger population This method involves summarizing and interpreting data to identify patterns and trends, providing a clear understanding of the overall population.
The analysis utilizes data collected from responses to distributed questionnaires, which can be presented through various formats such as tables, graphs, pie charts, pictograms, and statistical measures including mode, mean, median, percentiles, average, standard deviation, and percentage calculations These diverse methods enable researchers to effectively analyze the data and draw meaningful conclusions from the identified trends.
3.6.2 Reliability and Content Validity Analysis
Evaluating the reliability of a measuring scale is crucial for ensuring consistent data collection Cronbach’s alpha serves as a key statistical tool for assessing the internal consistency of questionnaire items A robust reliability analysis is indicated by a high intercoder agreement, with a kappa value greater than 0.70, reflecting coder consistency (Spence, 2004) Such a high level of agreement signifies a reliable coding process, reducing the risk of biases or inaccuracies.
A Cronbach’s α value between 0.5 and 0.7 indicates satisfactory internal consistency, though further enhancement may be necessary Items with a Cronbach’s α below 0.35 should be eliminated due to their inadequate contribution to the scale's overall reliability (Hair et al., 2010).
Ensuring the validity of an instrument is essential for accurately measuring the intended construct, as defined by Malhotra (2002) as the degree to which scores reflect true variations rather than errors Validity testing verifies that the instrument aligns with the theoretical constructs it aims to measure Content validity is evaluated by how well an empirical measurement represents a specific domain, necessitating careful design to match each conceptual dimension Reliability and validity analyses are crucial for assessing the three research models in this study, ensuring measurement precision and consistency.
Statistical comparisons of means are commonly performed using Student’s T-test and Analysis of Variance (ANOVA) The Student's T-test is utilized to assess significant differences between the means of two independent groups, particularly in analyzing demographic characteristics and customer responses In contrast, ANOVA is employed to identify significant differences among the means of three or more independent groups, helping researchers discern whether observed data variances are due to actual group differences or random chance This method assesses the proportion of variance between group means in relation to the overall variance within groups.
2014) A one-way ANOVA was employed to examine possible significant differences between demographic characteristics and customer responses.
In 2009, (Henseler et al., 2009), et al performed an extensive analysis of reflecting measurement models, highlighting the need of evaluating both reliability and validity.
In measurement theory, composite reliability is used to assess internal consistency reliability, providing a more comprehensive evaluation of construct reliability compared to Cronbach’s alpha (Coelho et al., 2020).
CR ratings range from 0 to 1, with higher values indicating greater reliability A composite dependability index is considered acceptable when it falls between 0.70 and 0.95 In social sciences, a CR value of 0.70 is generally acceptable, while values exceeding 0.80 or 0.90 reflect good to excellent reliability (Ye & Wen, 2011) This range suggests that the items are sufficiently related to measure the same concept while reducing redundancy (Peterson & Kim).
A well-calibrated Composite Reliability (CR) value ensures that measurement items accurately reflect the intended construct while minimizing excessive similarity, thereby improving the reliability and validity of the model CR values exceeding 0.95 may indicate substantial duplication among indicators, potentially jeopardizing construct validity In contrast, CR values below 0.60 signal insufficient internal consistency, which can undermine the overall integrity of the measurement model.
Validity evaluation consists of two main dimensions: convergent validity and discriminant validity Convergent validity is established when a set of indicators effectively represents a single theoretical concept Henseler et al (2009) introduced the average variance extracted (AVE) as a key metric for assessing convergent validity in structural equation modeling (SEM) AVE measures the average of the squared factor loadings of a construct's indicators, reflecting the proportion of variance attributed to the underlying construct rather than measurement error This ensures that the construct is reliably represented by its indicators within the model.
An Average Variance Extracted (AVE) benchmark of 0.50 indicates that at least 50% of the variance in observed variables must be explained by the construct for it to be considered valid (dos Santos & Cirillo, 2023) Values below this threshold suggest that the indicators may not adequately represent the construct, potentially undermining the validity of the measurement model Therefore, AVE is a crucial metric for evaluating the quality of constructs in Structural Equation Modeling (SEM) applications.
Indicator reliability is a crucial aspect of measurement quality, reflecting how well a construct corresponds to its indicators To ensure strong measurement reliability, standardized outside loadings should ideally exceed 0.70 Loadings between 0.40 and 0.70 require careful evaluation regarding their effect on content validity, as some indicators may hold theoretical significance despite lower loadings However, indicators with outer loadings below 0.40 should be removed, as they do not contribute meaningfully to construct assessment (Hair et al., 2010).
Descriptive Analysis and Mean Comparison
This research utilized data gathered from structured questionnaires designed according to a practical consumer profile The frequency distribution of sample characteristics is presented in Table 5, highlighting the general attributes of the participants.
Online product search and access platform
Source: Data processed by SPSS 29
Gender Rely on result from table 5 There was a significant difference between women and men respondent percentages, with women (64%) greatly outnumbering men (36%).
Age The largest age group was 18-28 years old (46.4%), followed by 29-44 years old (35%), 45-60 years old (15.5%) and customers over 60 years old (3.2%).
Income Income representation is divided unevenly across income levels: income 10-
20 million VND (30.6%), under 10 million VND (35.6%), 20-30 million VND (23.7%), 30-50 million VND (3.2%) and over 50 million VND (6.9%).
Occupation The research participants were mostly of Businessmen (3.2%), Student (12.6%), Service Professional (18.3%), Freelancer/Homemaker (28.4%) and above Office worker (37.5%).
Independent sample T-test and one way Anova were used to compare mean between different demographic characteristics and consumers’ responses.
Table 6: T-test results by gender
Demographic Characteristics N Mean Std t p -value
This table 6 clearly shows that, there is a significant difference in green purchase intention between male (N4, M=3.6294, SD=1.00289) and female (N 3,
M=3.8768, SD=0.81954), Df 17, t=-2.377, p-value=0.0260.05) and Occupation (0.843>0.05) exceeded the p value threshold.
Meanwhile, the values: Income (1.3735E-18