Investigating the Relationships Between Narrative Transportation, Consumer Brand Experience, Love and Loyalty in Storytelling Advertising, a Study Among the Young Generation in Ho Chi Mi
INTRODUCTION
Research background and statement of the problem
Vietnam has experienced remarkable growth in digital advertising, particularly in Ho Chi Minh City, which has emerged as a central hub for this expanding sector Statista forecasts that Vietnam's digital advertising market will reach an impressive US$1.201 billion by 2023, with Search Advertising expected to contribute US$489.70 million to this total.
In 2023, storytelling advertising has gained prominence as an effective strategy for enhancing brand engagement, supported by narrative transportation theory (NRT) This theory suggests that people experience a deep psychological immersion in stories, which can significantly influence their connection to a brand (Green & Brock, 2000).
While the concept of narrative transportation has been enriched to include elements such as emotion, attention, and imagery (Hamby et al., 2016; Green, Chatham, & Sestir,
Empirical studies have confirmed the effectiveness of emotional connections in enhancing brand experience, significantly influencing brand love and loyalty Research indicates that strong emotional bonds with brands can positively affect various dimensions of brand experience, ultimately leading to increased brand loyalty and affection.
Despite recent advancements, there is a notable lack of literature focusing on the youth of Ho Chi Minh City, a group with growing purchasing power and influence in shaping brand narratives in the digital age Existing research has not adequately addressed the long-term effects of storytelling advertising on brand love and loyalty within this demographic.
This study investigates the connections between narrative transportation, consumer brand experience, love, and loyalty in storytelling advertising, focusing on the young generation in Ho Chi Minh City By integrating narrative mobility and marketing impact variables, it aims to enhance understanding of storytelling advertising within this specific cultural and demographic context The anticipated findings will enrich existing knowledge and offer practical insights for marketers, scholars, and policymakers, highlighting how storytelling advertising influences consumer perceptions, cultivates brand love, and encourages both attitudinal and behavioral brand loyalty.
Research objectives
This research aims to explore the complex relationships between narrative transportation, consumer brand experience, love, and loyalty, and their combined effects on brand engagement among the youth in Ho Chi Minh City, Vietnam It seeks to understand how these elements contribute to psychological outcomes such as brand love and loyalty, and how these outcomes influence various dimensions of consumer engagement, including sensory, behavioral, intellectual, and emotional experiences.
A study in Ho Chi Minh City involving 385 young individuals actively engaged with brands reveals the significant role of storytelling advertising in enhancing brand engagement within Vietnam's digital landscape.
Research question
Narrative transportation plays a crucial role in storytelling advertising, particularly among the young generation in Ho Chi Minh City, Vietnam, by creating immersive consumer brand experiences that foster emotional connections This emotional engagement enhances brand love and loyalty, as consumers feel more invested in brands that resonate with their personal narratives Key factors contributing to the effectiveness of these narrative strategies include relatability, cultural relevance, and the ability to evoke strong emotions, which ultimately strengthen the bond between consumers and brands.
Research objects
Research subjects: Brand storytelling's influence on customer experience and the relationship between Consumer Brand Experience and Brand Love and Loyalty.
Participants: Young generations living, working, and studying in Ho Chi Minh City have awareness of Brand storytelling.
About space: This survey was conducted in Ho Chi Minh City, Vietnam.
Data was collected from October 1st to 25th, 2023, at various times throughout the day on both weekdays and weekends The studies and published results from the author's group were conducted between September 13th and November 15th, 2023.
Research method
This study employed both quantitative and qualitative research methods to explore the impact of narrative transportation on consumer brand experience, love, and loyalty It further examined how these factors collectively influence brand engagement among the youth in Ho Chi Minh City, Vietnam.
Qualitative research was conducted through individual interviews with a convenience sample of young adults aged 18 to 25 in Ho Chi Minh City Five respondents, representing diverse income levels and preferred brands across various product categories, were selected for the study Each interview, lasting between 60 to 90 minutes, was arranged via email The data collected was then coded to identify similarities and differences in responses, providing valuable insights for further adjustments to the research scale.
Quantitative research was conducted following the initial phase, involving a major survey and data analysis The survey was developed using Google Forms and shared across social media platforms, including Facebook, Zalo, and Instagram After data collection, the dataset was analyzed with SmartPLS 3.2.9, which included assessing measurement scales, testing for common method bias (CMB), and evaluating the structural model through hypothesis testing.
In the next phase, we utilized established measurement scales from prior research, translating them into Vietnamese to create a comprehensive questionnaire Our team engaged in extensive discussions and revisions to enhance clarity before distributing the final version.
Research structure
Chapter 02 - Literature review and hypothesis development
Chapter 04 - Data analysis and results
LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT
Narrative Transportation
Narrative transportation theory (NRT) posits that individuals become fully absorbed in a story, experiencing a sense of being "lost in the narrative" (Green & Brock, 2000) Throughout history, humans have been captivated by storytelling, with folklore and myths stimulating a desire for belief (Kelley, 2016) Brands often leverage this fascination by propagating their own myths (Holt and Thompson, 2004), a notion further supported by Teraiya et al (2023) and Yang.
Kang (2021) highlights the significant role of narrative transportation in advertising, demonstrating its impact on consumer experiences and brand equity As Hamby et al (2016) explain, narrative transportation immerses consumers in a rich blend of emotion, attention, and imagery, shaping their perceptions and behaviors when they return to reality Furthermore, Coker et al (2021) assert that narratives not only enhance persuasion but also foster positive attitudes toward advertisements and encourage social sharing behaviors, including word-of-mouth and promotional intentions, even in the context of digital engagement advertisements.
In the realm of brand storytelling, narrative transportation is a vital tool that engages consumers and shapes their perceptions and behaviors toward a brand This study emphasizes that brand narratives function as a strategic advertising approach, enhancing the overall brand experience and leading to persuasive outcomes (Roswinanto & Strutton, 2014) For instance, in the luxury hotel sector, a compelling narrative can foster a personal connection with guests, thereby enhancing the brand's credibility (Ryu et al., 2019).
Engaging storytelling, driven by strong narrative transportation, plays a crucial role in enhancing consumer brand engagement and shaping their intentions to use the brand and pay premium prices This study explores the impact of narrative transportation on consumer interactions with brands and its influence on brand-related outcomes such as brand love and loyalty.
Customer Brand Experience
Brand experience encompasses the subjective and internal responses of consumers, including sensations, feelings, and cognitive reactions, triggered by various brand stimuli such as design, identity, packaging, and communications (Brakus et al., 2009) This experience occurs throughout the entire customer journey, not just during product consumption, as it includes initial impressions, information searches, event participation, and discussions about the brand (Alloza et al., 2008; Ambler et al., 2002; Pina & Dias, 2020) Every interaction or touchpoint between the consumer and the brand contributes to this experience, making it an unavoidable aspect of brand engagement (Ong et al., 2018).
Researchers have broken down brand experience into sensory, affective, behavioral, and intellectual dimensions, enhancing our understanding of consumer interactions with brands Studies by Ryu et al (2019) and Dessart (2018) explore these dimensions in contexts like luxury hotel branding and storytelling ads Brand experience is not just about passive reception; it is an interactive process where consumers shape their perceptions and attitudes In storytelling advertising, brand experience acts as a crucial mediator, transforming the emotional elements of narratives into measurable brand outcomes like loyalty and advocacy Therefore, understanding brand experience, particularly in the context of narrative transportation, is essential for crafting storytelling advertisements that effectively engage consumers and drive favorable brand results.
Behavioral Experience, often referred to as consumption experience, plays a vital role in brand engagement by encompassing the physical actions and emotional responses triggered by product use or brand interaction (Beig & Nika, 2019) This complex concept extends beyond mere transactions, exploring the emotional and hedonic aspects of the consumer journey (Holbrook and Hirschman, 1982).
Behavioral experience can lead to co-creation, allowing consumers to collaborate with brands by sharing ideas through interactions This engagement, particularly on online platforms, enables brands to anticipate consumer intentions and enhance brand values through co-creation (Wallace et al., 2021).
Behavioral experience is a vital metric for evaluating marketing effectiveness, as it encompasses sensations, feelings, fantasies, and enjoyment It connects the process of attracting target audiences with the development of brand loyalty, ultimately enhancing brand love This dimension, identified by Brakus and colleagues in 2009, is crucial for measuring the impact of various marketing strategies.
Recent research by Yang & Kang (2021) and Teraiya et al (2023) has examined the complexities of behavioral experience, revealing strategies to enhance brand love through effective narrative transportation By analyzing consumers' emotional and hedonic responses to brand interactions, these studies offer critical insights into the mechanisms of successful marketing campaigns Such findings can assist marketers in crafting experiences that resonate with consumers, fostering not only one-time purchases but also long-term brand loyalty.
The initial impression of target audiences significantly influences their willingness to explore brands and products further By utilizing narrative transportation across multiple channels, marketers can engage these audiences by appealing to their sensory experiences, which encompass the physical responses elicited by colors, sounds, scents, sights, tastes, touches, and phrases (Yang & Kang, 2021; Xie et al., 2017).
The sensory experience of a brand significantly influences how consumers engage with its products, allowing them to connect on a deeper level (Beig & Nika, 2019) This aspect not only enhances the appeal of the brand but also shapes consumer perceptions in a sensory context (Brakus et al., 2009) Research by Yang & Kang (2021) and Teraiya et al (2023) underscores the importance of Brand Sensory Experience, highlighting its critical role in fostering emotional connections and shaping consumer perceptions through effective brand storytelling and advertising.
Understanding the interplay between narrative transportation and brand sensory experience is crucial to unraveling the mechanisms by which storytelling advertising can shape consumer perceptions and promote brand love.
Intellectual experience, defined as a consumer's cognitive interaction with a brand, encompasses positive thinking and curiosity (Ong et al., 2018) It is one of the four key dimensions of brand experience, reflecting the cognitive responses triggered by various brand-related elements such as design, identity, packaging, communication, and brand environment (Brakus et al., 2009).
2009) Moreover, Yang and Kang (2021) claim that judgement of brand's functional benefits and performance of brand's problem-solving capabilities are related to brand intellectual experience
Research by Madeline and Sihombing (2019) indicates that customer experiences are often heightened when individuals encounter unfamiliar products This exposure fosters imaginative and analytical thinking, which is essential for a meaningful intellectual experience Specifically, it highlights the extent to which a brand can engage consumers' thought processes, spark their curiosity, and enhance their problem-solving skills, as noted by Brakus et al (2009).
Intellectual experiences are commonly associated with technological products, as leading brands frequently launch new items annually to stimulate customer engagement through cognitive and creative appeal This phenomenon is also evident in the retail and fashion industries Additionally, intellectual campaigns that incorporate collaborative elements, such as co-creating products or ideas with the brand, further enhance this experience (Mohd-Ramly & Omar, 2017).
Customers' emotions and sentiments play a crucial role in the affective dimension that brands create (Iglesias et al., 2019) The emotional attachment that customers develop towards a specific brand or store is referred to as brand affective experience, stemming from their identification with that brand or store (Allen and Meyer, 1990).
An empirical study by Walter et al (2014) reveals that brand equity is significantly enhanced by sensory, emotional, cognitive, behavioral, and relational experiences, with sensory and emotional factors having the most profound effect This indicates that strong customer relationships are primarily emotional, as companies that not only meet needs but also create enjoyable interactions foster loyalty, even amid mistakes (Iman Khalid A-Qader et al., 2016) Further research by Yang & Kang (2021) and Teraiya et al (2023) emphasizes the vital role of Brand Affective Experience in building emotional connections and promoting loyalty through effective brand storytelling and advertising.
Brand affective experience can evoke emotions in customers related to a product's purpose or name, leading to feelings that may be nostalgic, desirable, or joyful, as highlighted by Ghorbanzadeh and Rahehagh.
(2021), brands tend to attach consumers with positive emotion about their products.
Brand Love
Brand Love refers to the emotional attachment and affection consumers develop towards a brand, going beyond simple satisfaction or loyalty to include passion, commitment, and a long-term relationship This intricate concept is influenced by factors such as brand experience, trust, and personality For instance, sensory experiences like the feel of a luxury handbag or the fragrance of a perfume can foster brand love Ultimately, this multi-dimensional idea is shaped by consumer interactions and perceptions, resulting in a profound and lasting emotional connection.
Recent research by Bairrada, Coelho, and Lizanets (2019) enhances our understanding of brand love, previously examined by Huang (2017) and Zhang et al (2020) in terms of premium pricing and advocacy They highlight brand love as a multifaceted emotion influenced by various cognitive, affective, and behavioral experiences, categorizing it into seven dimensions such as passion-driven behaviors and self-brand integration This complexity underscores the irreplaceable nature of brand love and its significant effects on business outcomes, including customer loyalty and word-of-mouth promotion.
Joshi and Garg (2020) emphasize the significance of brand experience in developing brand love, asserting that immersive experiences are essential for creating an emotional connection between consumers and brands This view is supported by Yang & Kang (2021) and Teraiya et al (2023), who highlight that storytelling advertising facilitates narrative transportation, enhancing emotional ties and resonance with the brand, ultimately nurturing brand love.
The relationship between narrative transportation in storytelling advertising and brand love is crucial for marketers, highlighting the need to create stories that effectively communicate brand values while deeply connecting with consumers This connection is vital for building brand loyalty, especially in emotionally driven industries, where storytelling can evoke powerful emotional responses, ultimately enriching the brand experience and nurturing a lasting affection for the brand.
Attitudinal Brand Loyalty
To establish brand loyalty, it is essential to consider both "attitude" and behavior, as emphasized by various academics Day (1976) was among the first to highlight this necessity, while Jacoby's (1971) concept of brand loyalty was further supported by Jacoby and Kyner (1973) They outlined six necessary conditions for brand loyalty: 1) a biased (nonrandom) 2) behavioral response (purchase), 3) occurring over time 4) by a decision-making unit, 5) concerning one or more alternative brands from a set, and 6) influenced by psychological processes involved in decision-making and evaluation.
Baldinger and Rubinson (1996) proposed a comprehensive definition of loyalty that encompasses both attitudes and behaviors to better explain brand loyalty They suggested that categorizing customers based on their behavioral loyalty patterns can reveal their underlying perceptions of brands Additionally, Rather et al (2022) described attitudinal loyalty as a key aspect of brand loyalty, characterized by positive brand-related word-of-mouth and recommendations to others.
Despite the growing demand for a comprehensive understanding of brand loyalty, its definition and operationalization remain unclear, particularly regarding the integration of attitudes alongside behaviors Day (1976) highlighted the importance of attitudes in defining loyalty but cautioned that emphasizing attitudinal criteria might limit the concept to brand-specific contexts, rather than allowing it to serve as a universal descriptor for product class behavior This perspective, while seemingly contradictory, enhances the generalizability of findings when similar attitudinal patterns emerge across various brands within a product category According to Wansink, Sonka, and Park (2001), product category loyalty pertains to switching between brands within the same category rather than within a single brand.
The design of the 1976 attitude scale lacked detailed clarification, leading to concerns about the accuracy of the research due to the constants being determined through trial and error Day himself recognized these limitations, expressing uncertainty regarding the significance of the relationship between attitude and behavior components in calculating loyalty scores.
Jacoby and Kyner (1973) attempted to define loyalty through a six-condition framework, but their understanding of attitudes remained ambiguous, lacking clarity on how they conceptualized and assessed them Despite claiming that their methodology ensured comparable evaluative judgments, they provided no details on attitude assessment Baldinger and Rubinson (1996) highlighted the importance of attitudes in evaluating loyalty and categorized individuals into “prospects” and “vulnerables” based on the strength of their attitudes and behaviors However, we argue that comparing two distinct concepts on the same scale may yield inaccurate data Furthermore, Baldinger and Rubinson (1996) failed to adequately describe their attitude scale or the criteria used to differentiate between low, moderate, and high attitudes.
Behavioral Brand Loyalty
Behavioral loyalty, or purchase loyalty, is defined as a customer's willingness to repeatedly buy a brand's products and services (Chaudhuri and Holbrook, 2001) According to Zhang et al (2020), it reflects a strong preference for a specific brand, indicating a customer's intention to make future purchases Furthermore, Yueh & Zheng (2019) highlight the role of storytelling in shaping purchase intentions, linking narrative processing with enhanced behavioral loyalty.
Previous studies have shown the importance of behavioral brand loyalty in consumer behavior (Dick & Basu, 1994) stress repeat purchase behavior, while (Oliver,
In 1999, research highlighted the importance of customer loyalty through repeat purchases, while Van Laer et al (2014) showed that narrative transportation significantly boosts consumer engagement and brand loyalty These insights underscore the necessity for brands to prioritize compelling storytelling and encourage repeat purchases to build lasting relationships with consumers.
Understanding the interplay between narrative transportation, consumer brand experience, emotional connection, and loyalty is essential for brands Compelling storytelling in advertising can immerse consumers in narratives that evoke strong emotions, enhancing their overall brand experience This study highlights the importance of storytelling in building behavioral brand loyalty, particularly among the youth in Ho Chi Minh City, Vietnam, which is key to achieving long-term success and growth for brands.
Prior relevant studies
Table 2.1 Relevant research on narrative transportation
Source Topic Independent variables Mediator Moderator Dependant
Variables Key rinding Research gap
Brand experience encompasses the sensations, emotions, thoughts, and actions associated with brand elements A unique four-dimensional scale, developed by the authors, measures this experience, setting it apart from other brand assessments This scale significantly influences consumer satisfaction and loyalty, with brand personality associations serving as a mediator in this relationship.
Further investigation is essential to understand how positively and negatively worded versions of the scale influence consumer behavior and their ability to predict specific behavioral outcomes Additionally, the study advocates for exploring the concept of brand experiences, emphasizing the need for research on the antecedents and long-term effects of these experiences on consumer interactions with brands.
Bu,akcio gill Ct al.
Antecedents and outcomes of brand love: rhe mediating role of brand loyalty
Self-congniity Brand Loyalty Brand Love; Positive
Brand experience significantly influences brand love, indicating that consumer interactions with a brand enhance their emotional attachment Additionally, self-congruity, a non-experience-based factor, plays a crucial role in fostering brand love.
The study's research model was conducted solely within one country, highlighting the need for replication across diverse geographies and timeframes to enhance external validity Furthermore, it overlooked critical aspects of brand loyalty, including both purchase and attitudinal loyalty, as well as various sub-dimensions of brand experience—namely sensory, emotional, behavioral, and intellectual factors—that could influence related variables Additionally, the research failed to consider the differences in market offerings between brands, which may also affect the outcomes.
The impacts of brand experiences on brand loyalty:
Brand Love Brand Trust; Brand Loyalty:
Sensory experience crucially drives brand love and trust, significantly shaping customer loyally, with both brand love
This research has limitations as it doesn’t follow the standards of multivariate normality Though brand love IS classified as a short-term
Mediators of brand love and trust.
Brand loyalty is influenced by brand experience through the mediating effects of brand love and trust However, this study highlights the need for further research to explore additional dimensions of brand loyalty, such as brand attachment, brand community, engagement, and product efficiency, as potential mediators Understanding these factors could provide deeper insights into the complex relationships that drive consumer loyalty.
Impact of brand experience on loyalty
Willingness to pay more; Word of mouth;
This study had tested empirically the influence of individual brand experience dimensions on individual loyalty dimensions There is at least one dimension of brand loyalty, namely Word of mouth
Willingness to pay more, and Repurchase Intentions are influenced by each dimension of brand experience.
The brand experience measurement developed by Brakus et al (2009) has primarily been assessed with Western consumers, indicating a need for future research to explore Eastern customer perspectives This study focused on small and medium-sized enterprises (SMEs) in the restaurant sector, utilizing intercept sampling; however, the findings may lack generalizability due to a higher response rate from female participants To enhance the model, further investigations should incorporate relevant mediating or moderating factors suitable for both goods and services research.
Do ads that tell a story always perform better?
The role of character identification and character type in storytelling ads
Storytelling ads especially those using animal characters, can reduce character identification, which results in an overall decrease in positive attitude toward the brand.
However, this effect is nuanced in the presence of joyful emotions.
Future research should focus on storytelling in advertising across diverse media, incorporating participants who may not favor online commercial content to mitigate audience bias Additionally, studies should investigate the effects of storytelling ads that prominently showcase products in use, examining how direct representation of products affects brand relationships and enhances consumer engagement.
Scale Development and Model Evaluation
The study formulated and validated a construct to gauge storytelling effectiveness in agricultural marketing, comprising a 13-item scale with four subscales: narrative processing, affect, brand attitude, and purchase intention
The findings affirmed a well- structured model across the four dimensions.
Further investigation is essential to understand narrative persuasion and its influence on consumer behavior in agricultural marketing This research should focus on aspects of narrative processing, its effects, and how it shapes brand attitudes Future studies ought to target primary buyers of agricultural products and examine the effectiveness of different storytelling appeals in marketing strategies.
Effect of a brand story structure on narrative transportation and perceived brand image of luxury hotels
A well-structured brand story can improve brand image by influencing consumers' narrative transportation, which involves cognitive absorption, imagery, and emotional immersion in the story's events.
Future research should examine how the structure of brand stories affects perceived brand image, brand attitude, and purchase intentions, as these factors may significantly influence financial performance Furthermore, analyzing the role of storytelling across different channels and the impact of servicescape in luxury hotels will enhance our understanding of storytelling's effectiveness in branding.
Impact of Brand Experience on
Online Shopping Portals: A Study of Select
The study presents empirical evidence indicating that brand experience plays a crucial role in enhancing brand equity Furthermore, it suggests that leveraging brand experience can effectively influence customer emotions and perceptions, making it a valuable strategy for businesses.
The study highlights significant research gaps stemming from the limited generalizability of its findings, emphasizing the need for a larger sample size to extend conclusions across all online shopping platforms Additionally, conducting comparative analyses across various regions and demographic groups could enhance the understanding of brand impact in the online shopping landscape.
Sites in the State of Jammu and Kashmir efficient and cost-effective route to achieve brand success in the online shopping marketplace. experience on brand equity in online shopping
The impact of brand personality on consumer behavior The role of brand love
Loyalty Positive Word-of- Mouth
Brand personality plays a crucial role in fostering brand love, which subsequently enhances consumer behaviors such as loyalty, word-of-mouth promotion, resistance to negative information, willingness to pay a premium, self-disclosure, and active engagement However, it's important to note that brand personality does not directly correlate with brand loyalty, word-of-mouth, premium pricing willingness, or active engagement on its own.
The study acknowledges the need for further exploration of brand personality by testing additional variables Future research should focus on identifying the antecedents of brand personality and analyzing it at a dimensional level to establish relevant personality traits Additionally, investigating these variables across various product categories could provide deeper insights into brand personality development.
Longitudinal studies are suggested to provide a better understanding of these relationships.
Brand Love, and Brand Loyalty for Tablet PCs:
Expressive brand relationship predicts brand trust and loyally, influences brand love, and indirectly mediates brand loyalty through trust and love
Future research must utilize a longitudinal design to investigate long-term brand loyalty among tablet customers, integrating both qualitative and quantitative methods to assess brand love, trust, and loyalty Additionally, it is essential to examine the impact of brand communities and service-dominant logic on brand management, as well as the effects of social media, community engagement, and social identity theory on brand relationships.
Role of brand experience in shaping brand love
Recent research highlights that Brand Love, Loyalty Intention, and Brand Engagement are essential concepts in modern marketing Furthermore, Brand Trust and Brand Image significantly influence the development of Brand Love, serving as key drivers in fostering deeper customer relationships.
Research framework and Hypothesis development
2.7.1 The relationship between Narrative Transportation and Consumer Brand Experience
Hamby (2016) identifies three key elements—emotion, attention, and imagery—that facilitate narrative transportation, allowing customers to immerse themselves in a fictional world This deep engagement with brand narratives leads to significant subjective and behavioral changes, as highlighted by Brakus et al (2009), who emphasize that emotional responses, sensory perceptions, and cognitive involvement drive this transformation.
The resonance of customers with a brand's narrative messaging is crucial for fostering a brand behavioral experience (Yang & Kang, 2021) However, achieving narrative transportation can be difficult due to the diverse ways audiences interpret messages, influenced by their perceptions of authenticity Authentic brand perceptions can enhance customer engagement and create interactive, co-creative experiences (Morhart et al., 2014) Many brands have adopted this approach in their marketing strategies to encourage customer participation and co-production, which helps reduce uncertainty and boosts satisfaction and self-connection, as suggested by the theory of self-service bias (Etgar, 2007).
People are naturally inclined to seek sensory stimulation, which plays a crucial role in enhancing the overall customer experience in retail environments The vibrant aesthetics of a store and an appealing brand name contribute significantly to this experience However, the impact of these sensory elements largely depends on the brand's ability to create engaging narratives In the tourism sector, sensory experiences are vital for a destination's popularity, as travelers are drawn to locations that offer captivating sights, delicious food, intriguing stories, and legendary myths.
Third, intellectual stimulation helps people avoid boredom (Cacioppo and Petty,
Boredom often stems from repetitiveness and a lack of creativity, making experiences feel tedious This concept applies to brands as well; to remain prominent in consumers' minds, they must consistently update their offerings, launch new products, and create innovative marketing campaigns In addition to fresh innovations, brands need a compelling narrative to attract and persuade customers, especially in a competitive landscape filled with diverse stories and product innovations By effectively utilizing narrative transportation, brands can spark curiosity, provoke thoughtful engagement, and encourage customers to explore new products with the latest features.
Understanding the mood, emotions, and feelings of customers is crucial in shaping their perception of brands, highlighting the significance of affective responses in brand marketing strategies (Iman Khalid A-Qader et al., 2016; Zhang et al., 2020) Positive emotional experiences directly enhance consumer satisfaction, fostering feelings of connection and contentment with brands (Shekhar Kumar et al., 2013) Research by Zarantonello and Schmitt (2010) indicates that affective and sensory experiences appeal to hedonistic consumers seeking emotional gratification To effectively engage these customers, brands should focus on narrative transportation that strengthens emotional bonds, as such attachments significantly influence customer behavior, including repeat purchases and a willingness to invest resources, ultimately driving brand loyalty (Lee and Workman, 2014; Thomson et al., 2005).
Based on the arguments above, we propose:
Hl The level of narrative transportation positively predicts consumer brand experience.
Hla A high level of narrative transportation will lead to higher brand behavioral experience.
Hlb A high level of narrative transportation will lead to higher brand sensory experience.
Hlc A high level of narrative transportation will lead to higher brand in tellectua I experien ce.
Hid A high level of narrative transportation will lead to higher brand affective experience.
2.7.2 The relationship between different types of Brand Experience and Consumer Brand Love
2.7.2.1 Brand Behavioral Experience and Consumer Brand Love
Brand behavioral experience, as outlined by Holbrook and Hirschman (1982), encompasses all interactions a consumer has with a brand, from initial engagement to product usage This experience is vital in shaping consumer perceptions and fostering emotional connections, with a positive brand experience linked to higher consumer satisfaction and emotional ties (Fog et al., 2011) Consequently, a strong emotional attachment enhances customers’ intentions to repurchase, demonstrating their loyalty and affection for the brand (Biẹakcioglu et al., 2016).
Research indicates a strong link between brand behavioral experience and brand love, underscoring the importance of consumer satisfaction and trust Yang & Kang (2021) emphasize that authentic brand narratives foster behavioral experiences that resonate with consumer expectations Consistent delivery of positive experiences enhances trust and satisfaction, which are crucial for developing brand love (Huang, 2017) Consumers' emotional and behavioral investments, driven by these positive experiences, cultivate a loving relationship with the brand, marked by emotional attachment and loyalty (Thomson et al., 2005) Thus, we propose the following hypothesis:
H2 Brand behavioral experience positively influences consumer brand love.
2.7.2.2 Brand Sensory Experience and Consumer Brand Love
Brand sensory experience encompasses the various sensory cues—visual, auditory, tactile, and olfactory—that consumers interact with when engaging with a brand (Brakus et al., 2009) These sensory elements play a crucial role in eliciting specific emotional responses from consumers, enhancing their overall connection with the brand.
& Kang, 2021) For example, the vibrant aesthetics of a retail store or the pleasing texture of a product can elicit positive emotions and enhance the overall consumer experience (Chapman, 2010; Roswinanto, 2011).
Sensory experiences play a crucial role in developing brand love by creating memorable moments that resonate emotionally with consumers (Zhang et al., 2020) Effective use of sensory cues immerses consumers in a brand’s narrative, enhancing emotional resonance and connection (Teraiya et al., 2023) When sensory experiences align with consumer expectations and desires, they amplify the brand's emotional appeal, fostering deeper connections and affection towards the brand (Ryu et al., 2019) This emotional bond, characterized by positive feelings, often leads to brand love, resulting in increased loyalty and advocacy among consumers (Lee and Workman, 2014).
H3 Brand sensory experience positively influences consumer brand love.
2.7.2.3 Brand Intellectual Experience and Consumer Brand Love
Brand engagement is significantly influenced by consumers' cognitive responses to various elements such as design, identity, packaging, and communications These factors stimulate curiosity, positive thinking, and problem-solving abilities (Brakus et al., 2009; Ong et al., 2018) This aspect of brand experience plays a crucial role in shaping consumers' assessments of a brand's functional benefits and its innovative potential (Yang & Kang, 2021).
Intellectual engagement plays a crucial role when consumers encounter new product categories or innovative ideas, stimulating both imaginative and analytical thinking (Madeline & Sihombing, 2019) This phenomenon is particularly observable in the technology sector, where annual product launches are designed to captivate consumers' cognitive and creative abilities Furthermore, this intellectual appeal transcends technology, influencing fashion and retail industries through campaigns that foster collaborative creativity, including co-creation of products and concepts (Mohd-Ramly & Omar, 2017).
In light of this, we posit the following hypothesis:
H4 Brand intellectual experience positively influences consumer brand love.
2.7.2.4 Brand Affective Experience and Consumer Brand Love
The emotional aspect of brand experience plays a crucial role in shaping consumer feelings towards a brand, creating a profound emotional bond that goes beyond simple identification Research by Walter et al (2014) highlights that both sensory and emotional experiences greatly enhance brand equity, indicating that strong emotional connections are the key drivers of customer loyalty.
Emotional experiences play a crucial role in consumer-brand relationships, as they can create connections to a product's purpose and evoke feelings of nostalgia or desire linked to its name (Ghorbanzadeh & Rahchagh, 2020) Brands that effectively cultivate positive emotions around their products build stronger customer loyalty, enabling them to maintain these ties even during challenging times (Iman Khalid A-Qader et al., 2016).
Moreover, the harmonization of affective experiences with consumer expectations and desires is indispensable for cultivating and maintaining brand love (Ryu et al.,
2019) When the emotional experiences consumers have with a brand are in sync with their expectations, it amplifies the emotional allure of the brand, promoting brand love and loyalty (Dessart, 2018).
Thus, based on the emotional depth of affective experiences, we propose:
H5 Brand affective experience positively influences consumer brand love.
2.7.3 The relationship between Brand Love and Brand Loyalty
Brand love is a deep emotional attachment that goes beyond consumer satisfaction and loyalty, incorporating passion, commitment, and a long-term relationship with the brand This connection is formed through multi-dimensional experiences, including sensory, affective, behavioral, and intellectual encounters These rich experiences create a passionate and enduring bond, encouraging consumers to advocate for the brand and pay premium prices.
Brand love is a crucial element of attitudinal brand loyalty, reflecting the emotional attachment and commitment consumers have towards a brand This deep emotional connection not only signifies loyalty but also acts as a precursor to stronger attitudinal loyalty When consumers truly love a brand, they demonstrate unwavering commitment and belief in its offerings, showcasing their loyalty through a profound psychological bond.
Summary
This chapter delves into the complex interplay between narrative transportation, consumer brand experience, brand love, and brand loyalty, utilizing the Narrative Transportation Theory and relevant research It highlights how the four dimensions of brand experience—Behavioral, Sensory, Intellectual, and Affective—fulfill diverse consumer needs, including Emotional Resonance, Cognitive Stimulation, and Sensory Appeal.
This article proposes that fulfilling emotional, cognitive, and sensory needs through brand experiences enhances Brand Love and Attitudinal Brand Loyalty It explores the impact of narrative transportation on consumer brand experiences and its significance in cultivating brand love, particularly among the youth in Ho Chi Minh City, Vietnam The findings presented lay a solid theoretical groundwork for the empirical research that will follow in subsequent chapters.
RESEARCH METHODOLOGY
Research design
This research is conducted based on two main stages: (1) preliminary research and
(2) official research A summary of the research phases carried out is as follows:
Step Type Method Technique Sample Time Location
Qualitative In-depth interview 5 09/2023 HCMC
2 Formal research Quantitative Direct survey 385 11/2023 HCMC
The preliminary research phase involves evaluating the theoretical foundation of the study and refining the proposed research model and scale The author conducted qualitative interviews with five marketing experts to gather insights, which informed adjustments to the initial scale Following this, a quantitative assessment was performed with 100 survey samples using the revised questionnaire, leading to the creation of a final version During this quantitative phase, the author applied Cronbach’s Alpha test and analyzed factor loading coefficients, removing any factors that did not meet statistical standards and further refining the scale Ultimately, a finalized questionnaire was prepared for the official quantitative research phase.
The formal research phase aims to quantify the impact of narrative transportation, consumer brand experience, love, and loyalty in storytelling advertising Data was gathered through an official survey utilizing a non-probability sampling method and convenience sampling The survey results were compiled, stored, and coded in Microsoft Excel, with subsequent analysis performed using SPSS and SmartPLS software.
In this stage, the author employs the PLS-SEM method for data analysis, which serves as a robust alternative to OLS regression and other analytical techniques PLS-SEM effectively addresses complex research issues, including unobservable variables and interactions among different variables (Giao & Vuong, 2020) According to Lowry and Gaskin (2014), this method significantly enhances causal analysis in behavioral research, particularly in scenarios involving small sample sizes or limited theoretical frameworks The PLS approach comprises two key phases: first, evaluating the measurement model's appropriateness by testing the reliability and validity of constructs; second, assessing the structural model's suitability through multicollinearity checks, structural path coefficients, and R² values, along with overall composite coverage of the construct.
To ensure the scientific nature of the topic, the author designed the research process as follows:
Step 1 - Determine the research object!ve/research question: This step is done to state the reason for choosing the topic and provide the research context Determine the objectives, objects and scope of the research.
Step 2 - Systematize the theoretical basis: Systematize the theoretical basis and research concepts related to the topic Summary of previous research related to the topic Thereby building the proposed research model Thereby building a preliminary research scale.
Step 3 - Preliminary qualitative/quantitative research: At this step, the author conducts in-depth interviews to evaluate the concepts and scales used in the research Thereby building a preliminary scale used in research The author conducted in-depth interviews with lecturers in the field of marketing, the specific list is in Appendix A In addition, the author measured scale reliability and factor loading coefficients with the quantitative method The preliminary quantity has a sample size of 100 This serves as a basis for calibrating the scale in the next step.
Step 4 - Calibrate the scale: After conducting qualitative and quantitative research, the author calibrates the scale to suit the research situation Finally, the official measurement scale used in quantitative research is completed.
Step 5 - Official quantitative research: The author conducted a survey with 385 respondents, conducted in Ho Chi Minh City; in addition, the surveys were also posted online on forums and social networks.
Step 6 - Testing the scale: At this step, the author tests the reliability of the scale, analyzes factor loading coefficients, convergent value, and discriminant value using Smartpls software From there, we can confirm the suitability of the data set in this study and determine the necessary adjustments in statistics.
Step 7 - Model testing: After evaluating the appropriateness of the scale, the author proceeds to test the model and hypotheses using tests such as testing the SEM model on Smartpls, testing multicollinearity, Testing direct and indirect relationships, testing coefficients R2, Q2, f2, analyzing regression models, etc From those results, the author draws conclusions for the research.
Step 8 - Hypothesis testing: From data analysis, the author relies on the standardized regression equation and p-value coefficient to evaluate and test the hypotheses in the study.
Step 9 - Conclusion and proposed implications: From the research results, the author proposes appropriate management implications to develop factors as well as increase Brand Love In addition, the author also presents some limitations of the topic and future research directions based on these limitations.
Research Methodology
3.3.1 The Partial Least Squares Structural Equation Modeling (PLS-SEM)
This study utilizes Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the complex relationships among narrative transportation, consumer brand experience, brand love, and brand loyalty, particularly among the youth in Ho Chi Minh City, Vietnam PLS-SEM is chosen for its effectiveness in handling intricate models and its suitability for exploratory research, allowing for simultaneous evaluation of both measurement and structural models The research investigates various dimensions of brand experience—behavioral, sensory, intellectual, and affective—that are intricately linked to narrative transportation and brand love This analytical approach facilitates a thorough examination of how storytelling in advertising, bolstered by strong narrative transportation, influences consumer perceptions and brand experiences, providing valuable insights for enhancing brand engagement and loyalty in Vietnam's dynamic advertising environment.
The aim of qualitative research is to delve deeper into the elements of Storytelling Advertising and related theories, while also tailoring the research model to align with the characteristics of the young generation in Ho Chi Minh City Consequently, the author proposes a refined research model and calibration scale to facilitate the subsequent stages of the research process.
3.3.2.2 Methods of conducting qualitative research
Sixteen questions were developed for in-depth individual interviews to explore the connection between narrative transportation and personal brand experiences Open-ended questions such as “Is there a brand that has made you think deeply or sparked your curiosity?” and “What specific attributes or experiences make you say you ‘love’ a particular brand?” aimed to uncover insights into respondents' emotional connections with their favorite brands across different product categories.
All individual interviews were recorded and transcribed, allowing for the classification of responses into similar or different categories These responses were then coded using a quantitative scale The next phase involved deriving insights and calibrating the scale to create a comprehensive measurement tool To validate the qualitative adjustments, a pilot test was conducted with a sample size of 100, ensuring that the methodology would function effectively in subsequent larger-scale testing.
Table 3.2 In-depth interviewee characteristics
In-depth interviews with a diverse group of individuals yielded valuable qualitative insights, reinforcing the reliability of the current measurement scales As a result, it was decided to retain these scales without any modifications.
The findings validated essential elements of the theoretical frameworks supporting our scales, particularly highlighting that the Narrative Transportation scale effectively reflected participants' emotional engagement with brand stories.
Interviewees' descriptions of their brand experiences mirrored the constructs of the Brand Love and Brand Loyalty scales, reinforcing their relevance and applicability.
Participants of different ages, genders, and occupations demonstrated a consistent perception and interaction with storytelling in advertising, highlighting the universal relevance of current measurement scales in this context.
The uniform responses, especially regarding emotional and intellectual engagement with brands, validated the scales' ability to capture a wide range of consumer experiences.
Participants shared in-depth insights into their emotional and sensory interactions with brands, emphasizing the intricate nature of consumer-brand relationships This complexity was effectively captured in the existing scales, reinforcing their thoroughness.
The depth of engagement expressed by interviewees, especially regarding narrative transportation and brand loyalty, further validated the existing scales.
Analysis revealed no gaps in what the scales measured and the participants* experiences Even nuanced aspects of consumer-brand interactions were effectively captured by the existing scales.
This lack of gaps in measurement implies that the scales are sufficiently comprehensive, leaving no need for modification or addition of new variables.
After conducting extensive interviews and analyzing the data, we found that no modifications were necessary for our measurement scales Despite receiving valuable feedback that enhanced our understanding, the existing scales, established and validated by prior research, proved to be effective and comprehensive in measuring the key factors of our study.
Based on qualitative research findings, the author refined the survey and transitioned to a quantitative research approach The preliminary quantitative phase aims to assess the clarity of the survey content for respondents and evaluate its effectiveness through data analysis (Buschle et al., 2021) This process will provide a solid quantitative foundation to address the research problem, propose solutions, and standardize the survey scale, ultimately creating a more effective official questionnaire that reduces potential errors in data collection.
3.3.3.2 Methods of conducting quantitative research a) Research sample and sample selection method
In this study, a non-probability sampling method, specifically convenience sampling, was utilized to select participants due to its accessibility and cost-effectiveness This approach is particularly beneficial when time and resources are constrained, making it ideal for exploratory research aimed at assessing the significance of a research problem Convenience sampling also allows for preliminary evaluations and pre-testing of questionnaires Given the limited time and funding available for this specific research, the author opted for this method to efficiently gather relevant data.
In quantitative analysis involving small sample sizes, researchers typically rely on their experience to determine the appropriate sample size According to Hair et al (2014), a commonly accepted observation ratio is 5:1, indicating that at least five observed variables are required for every measured variable However, some experts advocate for a more favorable ratio of 10:1, while others suggest an even higher ratio of 20:1 for optimal results.
However, in this study, the author selected the sample without determining the overall size Therefore, the research sample will be selected using the following formula:
In there: n: sample size z: distribution value corresponding to the selected confidence (if the confidence is
95%, the z value is 1.96) p: estimated percentage of the population To maximize the product p(l - pf we choose p = 0.5 q = I-p e: tolerance Among them, the most common level is ±0.05
Accordingly, the sample size is calculated as follows:
The study determined a sample size of 385 observable variables and aimed to gather responses from 500 participants to ensure accurate PLS-SEM analysis results The research team utilized social media platforms such as Facebook, Instagram, Zalo, and Messenger to distribute a Google Form link, ultimately collecting a total of 443 responses The survey was conducted from October 1st to October 25th, 2023.
The PLS-SEM technique is chosen as the primary data analysis tool in this study due to its significant advantages over CB-SEM Notably, PLS-SEM provides a higher variance explained in dependent variables, making it ideal for researchers focused on predictive power (Hair et al., 2017; Hcnsclcr Ct al., 2009) Additionally, it does not require normally distributed datasets and is resilient to multicollinearity issues (Hair et al., 2018) PLS-SEM also allows for the simultaneous assessment of models with multiple latent variables, including those measured by higher-order variables (Hair et al., 2017) Furthermore, this technique estimates both the measurement and structural models concurrently, reducing the risk of biased or inappropriate estimates (Hair et al., 2018).
SmartPLS 3.2.9 is used for evaluating the accuracy of the scales, R2, Q2 and f2 values using the PLS method (PLS algorithm) To test the importance of the path coefficients, the bootstrapping approach was used.
Data analysis process
Before starting data analysis, it's essential to summarize the information using Google Forms and conduct thorough checks to prevent errors, resulting in a final sample of 386 The features of the study sample were defined using SmartPLS 3.2.9 for descriptive statistics analysis Subsequently, the research model was evaluated through two approaches: Effect Indicator (Reflective Measurement Models) and Composite Indicator (Formative Measurement Models) as outlined by Henseler & Chin (2010).
The reliability and validity of the measurement model are critically evaluated, with reliability assessed through metrics like Cronbach's Alpha and the Composite Reliability (CR) coefficient Validity, encompassing both convergent and discriminant aspects, is determined using the Cross Loading coefficient, Average Variance Extracted (AVE), and the correlation matrix among the research variables.
Cronbach's alpha, introduced by Cronbach in 1951, is a method for assessing internal consistency reliability through the correlation of observable variables It operates under the assumption that all observable variables possess equal reliability, also known as outer loading However, it is important to note that the Cronbach's alpha coefficient can be influenced by the number of observable variables within each scale, often leading to an underestimation of the true internal consistency dependability.
Where: a: Cronbachs Alpha Coefficient k: Number of items in the scale of: the variance for all items on the scale of: the variance of individual item i
Cronbach's Alpha coefficient is a measure of reliability that ranges from 0 to 1, with values above 0.70 generally indicating acceptable reliability, while higher values closer to 1 are preferred This article outlines the various ranges of Cronbach’s Alpha coefficients and offers guidance on interpreting these values in the context of reliability research.
Cronbach’ s Alpha value range Interpretation a > 0.90 Excellent a 0.80-0.89 Good a 0.70-0.79 Acceptable a 0.60 - 0.69 Debatable a 0.50 - 0.59 Poor a < 0.50 Not acceptable
The formula calculates composite reliability (CR), which takes into account varied outer loadings of the observable variables (Hair et al., 2018).
The equation (^iO)2 + Eivar(ei) represents the relationship between the standardized loading of an observable variable (i) and a latent variable (e^), incorporating the measurement error of the observable variable The variance of this measurement error, denoted as var(ef), is calculated as 1 — I2, with the requirement that the Composite Reliability (CR) is 0.6 or greater.
Convergent validity is essential for evaluating the validity of measurement constructs, primarily determined through the average variance extracted (AVE) from each construct by analyzing the outer loadings of indicators For a construct to demonstrate convergent validity, the square of its outer loadings should exceed 0.708, ensuring that it accounts for at least 50% of the variance of the variable (Henseler et al., 2015) The AVE, a key convergence indicator, is calculated by subtracting the variance of all items loading on a specific construct, with a benchmark of greater than 0.50 indicating satisfactory convergence, meaning the construct score explains over half of the indicator variance (Hair et al., 2010; Hair et al., 2017) Additionally, all AVE indices should meet or exceed 0.5 to confirm the scale's convergence; any index below this threshold suggests that error variance exceeds the explained variance (Hock & Ringle, 2010; Fornell & Larcker, 1981).
Discriminant validity is a crucial aspect alongside convergent validity, ensuring that a measurement scale accurately distinguishes between different latent variables To establish discriminant validity, the square root of the Average Variance Extracted (AVE) must exceed the variance of any other latent variable, as outlined by Fornell and Larcker.
In the standard table by Fornell and Larcker, the diagonal cells represent the square root of the Average Variance Extracted (AVE), while the correlations between variables are displayed below To confirm discriminant validity, the absolute value of the square root of the AVE must be greater than any correlation coefficient in its respective column and row (Giao & Vuong, 2020).
Heterotrait-Monotrait Ratio Index (HTMT)
Discriminant validity, as defined by Henseler et al (2009), emphasizes the necessity for distinct constructs to show significant differentiation, indicating that their combined indicators should not be unidimensional In the realm of PLS path modeling, several measures have been proposed to evaluate discriminant validity, with the Fornell-Larcker criterion and cross loadings being the most notable The Fornell-Larcker criterion, established by Fornell and Larcker (1981), asserts that a latent variable must account for more variance with its corresponding indicators than with any other latent variable.
The Heterotrait-Monotrait Ratio Index (HTMT) is a crucial tool for assessing discriminant validity, as defined by Giao & Vuong (2020) It is calculated as the geometric mean of correlations between measurement items from different constructs, normalized by the average correlations of items within the same construct Henseler et al (2015) demonstrated through simulation studies that the HTMT index is more effective in measuring discriminant validity A HTMT value of less than 0.9 indicates meaningful discriminant validity, with a stricter threshold set at 0.85 (Hair et al., 2017; Kline, 2015).
Assessing Structural Model
The initial phase of structural model analysis involves assessing multicollinearity using the variance inflation factor (VIF) or tolerance This assessment is crucial to ensure that the path coefficients derived from the regression of the endogenous variable and the additional exogenous variable are aligned Elevated multicollinearity levels diminish the research's capacity to evaluate the relative significance of independent variables in comparison to others (Giao & Vuong, 2020).
Multicollinearity is indicated when the tolerance is below 0.2 or the variance inflation factor (VIF) exceeds 5, although some researchers adopt stricter thresholds of tolerance < 0.25 or VIF > 4 Since the VIF is the inverse of tolerance, both metrics convey the same information regarding multicollinearity, allowing the use of either for confirmation Tolerance is derived from the formula 1.0 - R², and multicollinearity is unlikely to occur if R² is less than 0.8.
When facing multicollinearity issues in a study, it is essential to evaluate whether highly correlated constructs should be combined or if one should be removed Constructs must be preserved in the model if they distinctly measure different aspects and are theoretically interconnected (Giao & Vuong, 2020).
Structural path coefficient (standardized Beta coefficient)
Structural path coefficients represent the weights that are interconnected within a model's framework When data is standardized, beta coefficients typically range from 0 to 1, with statistically significant values indicating meaningful relationships A higher beta value signifies a stronger connection in the structure While it is possible to save or delete less significant paths, doing so may impact the overall interpretation of the model's routes (Giao & Vuong, 2020).
The non-parametric bootstrapping (Davison & Hinkley, 2003; Henseler et al.,
In 2009, a procedure was introduced for PLS sampling paths that enables the creation of confidence intervals for all parameter estimates, establishing a foundation for statistical inference This method involves generating bootstrap samples by randomly selecting cases with replacement from the original dataset Each bootstrap sample is used to estimate a path model, resulting in path model coefficients that create a bootstrap distribution, which serves as an approximation of the sampling distribution.
R2 is also known as the coefficient of determination, which is an index that measures the total impact of the structural model (Giao & Vuong, 2020) According to Hock & Ringle (2010):
- If R2 value > 0.67, the model is strongly explained
- If the value 0.33 < R2 < 0.67, the model is moderately explained
- If the value 0.19 < R2 < 0.33, the model is weakly explained
Wetzels et al (2009) have proposed the following thresholds for evaluating the f2 index:
- Greater than 0.26 indicates a large influence
The predictive capacity of the structural model is assessed using Stone-Ọ2 Geisser’s criterion, a widely recognized measure of predictive relevance that employs blindfolding techniques This criterion emphasizes that the model should effectively predict the indicators of the endogenous latent variable By integrating cross-validation and function fitting in a single step, this method highlights the significance of predicting observable variables over merely estimating often misleading construct parameters, as noted by Chin (1998).
Measurement Scale
The research utilized a 7-point scale to score papers, following established literature, and translated them into Vietnamese for the current study context Three key variables for Narrative Transportation were identified: engagement, authenticity, and humanity (Yang & Kang, 2021) Additionally, based on prior work by Yang & Kang (2021) and Teraiya et al (2023), Consumer Brand Experience was evaluated through behavioral, sensory, intellectual, and affective experiences, each comprising multiple items Furthermore, Brand Love was assessed using four observed variables, while Attitudinal and Behavioral Brand Loyalty were measured through two observations each A Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree) was employed for these assessments.
1 This ad makes me feel human again
2 This ad is authentic (NT2) Yang & Kang (2021)
3 This ad is engaging (NT3) Yang & Kang (2021)
1.1 engage in physical actions and behaviors when I use this brand's products and services (BBE1)
2 This brand results in bodily experiences (BBE2) Yang & Kang (2021)
3 This brand is action-oriented (BBE3) Yang & Kang (2021)
1 The brand in the ad (henceforth, this brand) makes a strong impression on my visual senses or other senses (BSE1)
2.1 find this brand interesting in a sensory way (BSE2) Yang & Kang (2021)
3 This brand appeals to my senses
1.1 engage in a lot of thinking when I encounter this brand (BIEI) Yang & Kang(2021)
2 This brand make me think (BIE2) Yang & Kang(2021)
3 This brand stimulates my curiosity and problem-solving skills (BIE3) Yang & Kang (2021)
1.1 found the advertisement for this brand interesting (BAE1) Teraiya et al (2023)
Source: Compiled and edited by the authors
2.1 noticed the advertising about this brand (BAE2) Teraiya et al (2023)
3.1 want to watch this ad again (BAE3) Teraiya et al (2023)
4 This brand advertisement made me want to learn more about the brand (BAE4)
1 This brand makes me very happy
2.1 love this brand (BL2) Yang & Kang (2021)
3.1 am passionate about this brand
1.1 am willing to pay a higher price to buy this brand’s products and services (ABL1)
2 If this brand is out of stock, I will wait and refuse any substitute (ABL2) Yang & Kang (2021)
1.1 will tell other people how good this brand is (BBL1) Yang & Kang (2021)
2.1 will recommend this brand to other people (BBL2) Yang & Kang (2021)
Quantitative research results (preliminary)
3.7.1 Assess the quality of preliminary observed variables
To ensure the scale of research, the author conducted an evaluation of the results of 209 samples collected from preliminary research The results are shown as follows:
Table 3.4 Results of analyzing the preliminary scale’s outer loading coefficients
ABL BAE \ BBE 1 BBL BIE BL \ BSE
The analysis reveals that all loading coefficients for the observed variables in the preliminary scale exceed 0.708, indicating their high quality Consequently, no variables have been eliminated, allowing for their continued use in the main quantitative analysis without the need for adjustments.
3.7 2 Assess the reliability and convergent validity of the preliminary scale
In this analysis, the author chose to evaluate the CR index instead of CA because the reliability can be more suitable for the PLS model (Giao & Vuong, 2020).
Table 3.5 Reliability results of the preliminary scale
The combined reliability (CR) results for all constructs exceed 0.8, indicating that the scale is reliable for use in official research Additionally, each construct has an Average Variance Extracted (AVE) index greater than 0.5, and the external loading coefficients of the observed variables also surpass 0.5, confirming the scale's convergent validity.
Summary
In Chapter 3, the author outlines the comprehensive research process, detailing the systematic organization of research objectives and theoretical foundations to develop a research model This model serves as the basis for constructing a preliminary scale, which is subsequently refined into an official measurement scale The chapter further discusses the selection of a survey sample, the collection and analysis of data through descriptive statistics, and the validation of scales It culminates in hypothesis testing to derive conclusions and propose practical implications.
This chapter outlines the preliminary quantitative research process, emphasizing the analysis of 209 observation samples The outcomes are measured using a model consisting of 23 questions based on 8 research concepts Importantly, the final research model and scale align with the originally proposed framework.
The author explores data processing methodologies, focusing on statistical sample description through the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach This analysis is performed using SmartPLS 3.2.9 software, highlighting the study's dedication to employing advanced and reliable data analysis techniques.