1. Introduction
The widespread use of social media has revolutionized consumers’ fashion preferences and ways of expressing themselves through fashion. In the current landscape where the concept of “fast fashion” is prevalent, customers purchase fast-fashion products continuously to display their style. This causes a continuous cycle of fast-fashion consumption, leading to excessive depletion of resources and significant environmental consequences. In contrast, in reality, external factors limit outfit choices, restricting expression of personal identity and emotions. Advancements in digital virtual technology and the expansion of industrial digitalization have facilitated the development of “digital fashion” in recent years. This has transitioned from a tool utilized in traditional fashion retail and design to a digital product offered to consumers in virtual form.
Generation Z refers to individuals born between 1995 and 2010 and has emerged as a significant presence in China’s consumer market [1]. This generation has grown up in an environment closely linked to the rapid development of digital technology. Immersed in digital environments from a young age, they profoundly rely on new technologies [2]. Furthermore, they demonstrate profound insight and remarkable adaptability to the boundaries between the real and virtual worlds. Virtual clothes have emerged as a new platform for Generation Z to showcase their individuality and aesthetic preferences, allowing them to explore and express their fashion ideas without the constraints of the real world. This trend satisfies Generation Z’s pursuit of individuality and creativity and presents new avenues for development within the fashion industry.
Simultaneously, virtual clothes, which fulfill the requirements of being both fashionable and environmentally friendly, have attracted the attention and interest of academics concerned with sustainable fashion. DressX, the inaugural international digital fashion multi-brand retailer, asserts that its digital fashions are produced with a 97% reduction in carbon emissions compared to physical garments [3]. In an article published in Forbes magazine [3], Brooke Roberts-Islam, an authoritative writer in the field of fashion technology and sustainable development, noted that, given the inevitable environmental damage caused by the production and consumption of physical garments, digital fashion is increasingly favored by consumers as a choice for a sustainable lifestyle. However, despite the consensus among scholars that digital fashion holds significant advantages over physical fashion in terms of sustainability, there is a lack of empirical research to verify whether this sustainability truly impacts consumer behavior, prompting them to embrace digital garments as a novel means of fashion expression.
Furthermore, virtual clothes do not consider physical characteristics, such as coverage and warmth, compared to actual garments. Instead, they prioritize the fulfilment of consumers’ desires for emotional expression. Therefore, besides the widely explored attribute of sustainability, other affective characteristics of virtual clothes may significantly impact consumer behavior. To explore the affective characteristics of virtual clothes fully, this study introduces the emotional three-level theory to extract the features of virtual fashion clothes that can satisfy consumers’ emotional needs. The emotional three-level theory is a conceptual framework to analyze consumers’ emotional responses to products. It has been demonstrated that applying the emotional three-level theory in the product design and development process can improve the product’s attractiveness, usability, and emotional value, thus contributing to its success and commercial sustainability [4].
Previous researchers have focused on virtual fashion for virtual fashion shows, virtual fashion modeling, and virtual fitting and have discussed virtual technology within the humanities and philosophy. With the boom in virtual fashion businesses in recent years, many academics have acknowledged the need to study consumer motivation when buying virtual clothes. For instance, scholars have delved into the impact of avatar reality and fashion product realism on consumers’ attitudes toward acquiring virtual fashion items from a self-identity perspective [5], examined psychological factors affecting virtual garment purchases across brand categories [6], and employed theoretical frameworks such as Consumer Value Theory [7] and behavioral reasoning theory [8] to investigate the variables that affect consumers’ purchasing of virtual clothes.
As the virtual fashion industry advances, an increasing number of fashion enterprises recognize its development potential. They are exploring the possibility of establishing new avenues for profit growth within this emerging field to bolster their competitive edge. Thus, it is essential to understand how consumers perceive and accept digital fashion products. However, there is no research on public acceptance of virtual clothes. This study aims to fill this research gap and investigate consumer acceptance of virtual clothes. The Technology Acceptance Model (TAM) is a highly influential model widely used to examine the acceptance of technological innovations across various fields and is a favored theory for investigating customer attitudes and behaviors in virtual technology and digital products [9]. Therefore, this study adopts the TAM as the guiding framework.
This study integrates the Emotional Three-Level Theory and the Technology Acceptance Model to comprehensively investigate the emotional characteristics of virtual clothes and their impact on consumer acceptance, focusing specifically on Generation Z in China as the primary research subjects. Specifically, it examines how the attribute of sustainability shapes consumers’ perceptions of virtual clothes and influences their behavioral intentions. Consequently, this research provides a more comprehensive and in-depth perspective on consumer acceptance of and preference for virtual clothes, offering valuable insights into the sustainable development of the fashion industry.
2. Materials and Methods
2.1. Virtual Clothes
Virtual clothes represent the integration of information technology and the fashion industry, existing in a digital format through the simulation of fabrics using technologies such as virtual reality, computer graphics, and simulation techniques [10]. Nevertheless, in current academic discourse, “virtual clothes” encompasses various product categories. To delineate the scope of this study, this paper offers a classification of virtual clothes.
Virtual clothes are predominantly utilized in two major domains: fashion and finance. In the fashion industry, virtual clothes leverage virtual technology to attain realistic visual effects and cater to consumers’ desires for fashion and personalization. In contrast, in the finance sector, emphasis is placed on utilizing blockchain technology to address investors’ requirements for asset appreciation and collection. Significant differences exist between the two fields concerning product nature and objectives. This study categorizes virtual clothes into two types based on their associated industries: virtual clothes for the fashion industry and virtual clothes for the financial industry.
In the fashion industry, virtual clothes are utilized in both the virtual and real-world fashion industries. In the real fashion industry, virtual clothes serve as tools to aid in designing and producing physical apparel, expediting the design and production sampling process, and enhancing production efficiency and quality [11]. They can also assist consumers in making clothing purchases, such as via virtual try-on technology (VTO), or virtual clothes can be displayed via e-commerce platforms to provide a virtual display of the effect of clothing wear. In the virtual fashion industry, virtual clothes are typically presented in a non-physical format. Depending on the wearer, they can be used as the “skin” of a virtual avatar in a virtual platform or game [6]. Furthermore, virtual clothes can be worn by actual consumers, with this form of digital fashion primarily aimed at social media platforms. Typically, these products are marketed through videos or photos featuring virtual fashion items overlaid onto consumer images for social media promotion [6].
Another type of virtual clothing is utilized in the financial industry, essentially representing digital assets. Virtual clothes are one of the non-homogenized token collections released by clothing brands [12]. For example, in 2019, Dapper Labs, a pioneer in the NFT trend and the developer of the blockchain game Crypto Kitties, collaborated with The Fabricant to produce a virtual fashion item. Forbes referred to it as “the world’s first garment created solely in a virtual blockchain environment”, and this example of virtual fashion clothing was named “Iridescence”.
The virtual clothes examined in this study result from a combination of information technology and the fashion industry, novel products in the virtual fashion business, which utilizes virtual clothes as the end product. The virtual clothes studied in this paper mainly serve social media scenarios where virtual fashion clothes are displayed and sold by superimposing them on user photos or videos. In the subsequent discussion, we will use “virtual fashion clothes “ to distinguish them from other virtual clothes.
Recent advancements in graphic technology, virtual reality, and other virtual simulation techniques have significantly contributed to the expansion of the virtual fashion industry. Numerous luxury corporations have entered the field of virtual fashion, promoting an increasing number of virtual fashion brands specializing in producing virtual fashion clothes. As an illustration, luxury brand Louis Vuitton has collaborated multiple times with League of Legends (LOL) to create customized appearances for its in-game characters. NIKE’s Air Jordan brand has also bought RTFKT, a unique virtual fashion company, to improve its technology.
Some examples of virtual fashion brands are Tribute in London, Carlings in Norway, and The Fabricant in the Netherlands. The Fabricant, founded in 2018 and based in the Netherlands, is one of the most famous digital fashion companies. It has collaborated with several fashion companies, designers, and artists, displaying its virtual clothes at renowned fashion events and exhibitions worldwide, such as the Dutch Museum of Art Digital Fashion Exhibition. Therefore, this study selected The Fabricant as the research focus.
2.2. Emotional Three-Level Theory
Every user response to the three levels defined by Norman has the potential to evoke an emotional reaction, leading to either a positive or negative experience and ultimately establishing a satisfactory emotional connection with the product [13]. As outlined by Norman [8], user responses are categorized into three distinct levels: the visceral level (VL), the behavioral level (BL), and the reflective level (RL) [13].
Specifically, the visceral level of emotion is rooted in sensory experiences, such as sight, sound, touch, taste, and smell. Upon receiving a stimulus and providing a direct response, the user experiences a range of emotional responses [13]. Customers may experience a visceral level of emotion from the virtual fashion clothes’ color, substance, and style. The behavioral level of emotion is associated with usability, and the user’s response reflects the positive and negative experiences encountered while using the product [14]. The reflective level (RL) pertains to the semantic significance of the product, shaping the message and perception it communicates to the user. At this level, emotional connections can form and endure over time, distinguishing one product from the multitude available on the market and making it challenging for users to substitute one product for another.
Essentially, the design process considers three levels: the visceral level, which addresses the consumers’ desire for the product’s appearance; the behavioral level, which focuses on the product’s usability and how it makes the user feel; and the reflective level, which delves into the product’s semantics and meaning.
Academics have extensively utilized this theory to extract product features, guiding product design to significantly enhance consumer experience. For example, Zuo et al. [15] extended the application of the emotional three-level theory to virtual reality games. They built a user experience evaluation framework using this theory to enhance user experience in virtual games; Le, T. et al. [16] utilized the emotional three-level theory to enhance the user experience of health monitoring technology for the elderly by visualizing smart home sensor data. Similarly, Zheng et al. summarized the characteristics of public fitness equipment that evoke emotional experiences in consumers through the emotional three-level theory. They subsequently enhanced public fitness equipment design based on these characteristics [17].
Thus, this study employs the Three Levels of Emotion theory as an analytical tool to investigate the connection between virtual fashion clothing and consumers’ emotional needs. It is postulated that virtual fashion clothing is not only an emerging digital product but also a medium that can stimulate consumers’ emotional responses and satisfy their desire for personalized expression and their social needs. By applying the three-level theory of emotion to the field of virtual fashion, we can gain a more comprehensive understanding of consumers’ perceptions and preferences for virtual fashion garments. This provides theoretical support and practical guidance for the design of more attractive and market-competitive virtual fashion products.
2.3. Virtual Fashion Clothes’ Characteristics Extracted Based on Emotional Three-Level Theory
Virtual fashion clothes are emerging products in the virtual fashion industry, and the marketplace currently exhibits a degree of disarray. Thus, this paper studies the well-known virtual fashion clothes firm The Fabricant as a case study and identifies the distinct characteristics of virtual fashion clothes at the visceral, behavioral, and reflective levels.
At the visceral level, The Fabricant’s designers can create virtual fashion clothes without being constrained by physical features, enabling consumers to experience more exaggerated and distinctive design styles. Additionally, the designers at The Fabricant, a virtual fashion firm, utilize 3D design tools to produce virtual clothes that accurately replicate real-world fabric textures, the shine of metal fittings and draping effects, and enhance virtual fashion clothes’ realism, closely resembling the experience of wearing them on the human body. Therefore, virtual fashion clothes’ satisfaction at the visceral level of emotion is mainly reflected in their aesthetics and realism [18].
At the behavioral level, virtual fashion clothes offer advantages over physical clothing regarding production processes and modification. Unlike physical clothing, virtual fashion clothes do not require purchasing or sewing. Instead, virtual fashion clothes’ designers use computer programs to design and produce products, resulting in rapid product design. This level allows designers to highly customize and modify products to meet the personalized demands of consumers. The use of graphics technology and virtual reality (VR) is central to this process, enhancing the consumer’s interaction with virtual fashion. Graphics technology facilitates the creation of intricate designs and textures, ensuring that the digital garments closely mimic the aesthetics of real-world clothing. Meanwhile, VR provides an immersive platform for consumers to visualize and interact with these garments in three dimensions, simulating the drape, movement, and fit of the clothing. Once consumers have made their purchases of virtual fashion clothes, brands will utilize innovative technologies, like virtual simulation, to merge the virtual fashion products with photos or videos submitted by consumers. They will be sent to consumers as digital assets, allowing users to showcase the look of their “wearing” of virtual fashion clothes on different social platforms. Thus, virtual fashion clothes’ satisfaction at the behavioral level of emotion is mainly reflected in their personalization, novelty, and presentation.
At the reflective level, Michaela Lacrosse, Director of Strategic Communications at The Fabricant, emphasizes that “virtual fashion clothes accommodate different genders, body sizes, and ages to cater to diverse consumer groups expressing their individuality and fashion preferences”. Additionally, virtual fashion clothes emphasize being low-carbon and environmentally friendly; all aspects of virtual fashion clothes’ production, including resources, finished products, technology, and promotion, are in digital format, aligning with the criteria for digitally sustainable products [19], thereby minimizing resource wastage. This aspect elicits the interest of fashion aficionados while simultaneously engaging the cognizance of consumers committed to environmental sustainability.
Therefore, the satisfaction of virtual fashion clothes at the reflective level of emotion is mainly reflected in their inclusivity and sustainability. Figure 1 summarizes the characteristics of virtual fashion clothes’ characteristics.
3. Research Modeling and Hypothesis Deduction
3.1. Technology Acceptance Model
The Technology Acceptance Model (TAM), originating from Fishbein and Ajzen’s work and extending the Theory of Reasoned Action (TRA), was proposed by Davis and is centered on identifying cognitive and psychological factors influencing the acceptance of new technologies [20]. TAM posits that Behavioral Intention (BI) serves as the primary predictor of technology adoption and use, determined by Perceived Usefulness and Perceived Ease of Use, which are subsequently influenced by external variables. However, the TAM offers only general insights into the propensity for technology adoption and thus falls short of fully elucidating the specific motivations for technology use in particular contexts [21]. Therefore, the extensible framework of TAM permits researchers to augment its explanatory capacity by incorporating variables that can account for additional determinants of technology adoption [22].
As the application scope of TAM expands, researchers have discovered that the two key factors of TAM (perceived usefulness and perceived ease of use) solely emphasize the functional aspects of technology, neglecting the exploration of users’ psychological motivation. This limitation results in TAM’s inadequacy in fully explaining users’ intrinsic motivations and other specific phenomena. To address this limitation, subsequent studies have sought to enhance and expand upon the model by incorporating external and perceived variables [23].
We utilize TAM, widely recognized as a prominent model for predicting technology adoption and usage behavior [24], which has seen extensive application in examining customer attitudes and behaviors within the realms of virtual technologies and digital products [9]. Specifically, this study explores perceived enjoyment (a form of intrinsic motivation) by introducing it as a direct predictor of the intention to use virtual fashion products. Furthermore, this study extends TAM by incorporating considerations of external product attributes, such as aesthetics, authenticity, novelty, personalization, self-presentation, sustainability, and inclusiveness. These are regarded as crucial determinants of perceived usefulness, ease of use, and enjoyment. Perceived enjoyment encompasses the degree of pleasure and delight derived from engaging with a specific system or technology [25]. Research indicates that perceived enjoyment is a critical factor in gauging the effectiveness of virtual reality technologies [22] and augmented reality technology [26] and influences other determinants of the intention to use innovative technologies. Al-Adwan et al. have also demonstrated that perceived hedonicity is a psychological motivator for the behavioral intention of higher education students to adopt virtual reality technology for educational purposes. Academic consensus posits that the perception of VTO as enjoyable and fun drives consumers’ intention to use it [27,28]. While the enjoyment derived from digital fashion as an end product remains understudied, it is plausible that consumers derive pleasure from wearing such products, akin to the experience of a virtual try-on.
Aesthetics, authenticity, novelty, personalization, self-presentation, sustainability, and inclusiveness are external product features that represent the qualities of virtual fashion products that can attract consumers’ interest in using them. Perry’s research on smart virtual closets highlighted aesthetics as a pivotal product attribute and established its substantial impact on perceived ease of use and usefulness [29]. Similarly, Ross’s research demonstrated that design features are significant external variables in accepting augmented reality (AR) clothing technology [30]. This study delves deeper into utilizing product design features in virtual fashion, drawing from the framework of the three levels of emotion theory. Despite these features not being widely validated in the application of TAM, the methodology employed integrates the case study of virtual fashion brands with an in-depth analysis of the three levels of emotion theory, thereby offering a rational and systematic feature extraction approach. Consequently, there is ample justification to believe that these product features can offer fresh insights into the TAM. This could enhance its efficacy in elucidating users’ acceptance of virtual fashion products.
3.2. Hypothesis Deduction
3.2.1. Aesthetics
Aesthetics refers to a person’s assessment of a product’s visual appeal [31]; customers will consider aesthetic standards while assessing apparel because it serves as a significant medium for visual communication [32]. Aesthetic features in computer-guided virtual environments are important, especially for the younger population [33]. Products with visually appealing qualities are more inclined to capture consumers’ attention, providing them with sensory gratification and stimulation. The aesthetic pleasure from non-functional virtual assets, such as their visual appearance, voice effects, or movement, plays a crucial role in motivating consumer engagement and purchase behavior; video games that integrate a combination of visual, auditory, and haptic feedback can evoke emotional, behavioral, and cognitive responses, thus fostering affirmative attitudes towards the gaming experience [34]. Furthermore, products that possess aesthetic qualities have been shown to positively influence consumer emotional responses [31,35]. Many scholars have extended the Technology Acceptance Model (TAM) to include aesthetics as an external variable in the TAM to examine customer behaviors in the garment industry [36]. The deployment of digital technology in creating virtual fashion clothes offers substantial potential for aesthetic innovation, facilitating the emergence of novel design processes and visual representations. Consequently, this may engender increased emotional arousal and stimulation for consumers. Within the scope of this research, ‘aesthetics’ is defined as the visual appeal of virtual fashion clothes. Accordingly, the following hypotheses are proposed:
Aesthetics have a positive influence on Perceived Enjoyment.
Aesthetics have a positive influence on Perceived Usefulness.
Aesthetics have a positive influence on Perceived Ease of Use.
3.2.2. Reality
In the realm of an online sales platform, the stimulation of purchase intentions is facilitated through the orchestration of arousal and enjoyment. In conjunction with the synchronization of product presentations with consumers’ self-perception and with the enhancement of their aesthetic worth, this approach can effectively elicit emotional reactions from customers [37]. Moreover, individuals’ affective responses depend on whether they perceive themselves as interacting with a computer or a real person, and audiences develop more visceral emotional attachments when the objects they interact with exhibit more human-like characteristics [38]. Consequently, in order to replace physical clothing displays, virtual fashion clothing displays must accurately imitate the appearance of genuine clothes in terms of their outline, size, color, fabric, and other relevant aspects [39,40]. In the context of virtual fashion clothes, reality refers to the dependence on existing technologies, such as virtual simulation, which allows virtual fashion clothes to obtain realistic static and dynamic simulation effects. Accordingly, the following hypotheses are proposed:
Reality has a positive influence on Perceived Enjoyment.
Reality has a positive influence on Perceived Usefulness.
Reality has a positive influence on Perceived Ease of Use.
3.2.3. Novelty
Advanced technologies change consumers’ purchasing experience, prompting them to purchase virtual objects to satisfy their need to own and engage with these technologies [41]. British scholar Campbell argues that the primary motivation behind modern consumption is the constant search for new and novel experiences [42]. The distinction between traditional functional products further underscores this shift in consumer behavior because functional products emphasize the performance and utility of the product. In contrast, digital products, such as virtual fashion clothes, have functionality mainly reflected in technological advances and innovations [43]. Within the realm of e-commerce transactions, when consumers perceive the novelty of a new technology during online shopping, they develop a strong desire to try and understand it. They are more likely to focus on the experience [44]. The development of virtual fashion clothes represents a paradigmatic example of such novel products; significantly, Generation Z youth, as the primary consumers, have an intense curiosity and willingness to try new things. In this study, novelty refers to the fact that virtual fashion clothes and their associated technology are innovative compared to existing fashion products. Accordingly, the following hypotheses are proposed:
Novelty has a positive influence on Perceived Enjoyment.
Novelty has a positive influence on Perceived Usefulness.
Novelty has a positive influence on Perceived Ease of Use.
3.2.4. Personalization
Personalization is defined by enabling users to adjust the asset’s attributes to match their specific preferences [45]. The personalization of online shopping platforms is mainly reflected in the ability to understand the specific needs of each consumer based on their preferences and behaviors and then deliver efficient, valuable, and tailored services [46]. Notably, personalizing products garners consumers’ attention and fosters their inclination to procure virtual products [47]. In the context of this study, personalization refers to the capacity of virtual fashion clothes to cater to the specific requirements of diverse clients utilizing highly personalized services. Accordingly, the following hypotheses are proposed:
Personalization has a positive influence on Perceived Enjoyment.
Personalization has a positive influence on Perceived Usefulness.
Personalization has a positive influence on Perceived Ease of Use.
3.2.5. Presentation
Research emphasizes that presentation significantly motivates individuals to purchase digital items [47,48]. Furthermore, buying virtual fashion clothes enables individuals to display their sociability and willingness to embrace new trends and experiences [49]. Notably, a key motivation for individuals to purchase apparel and accessories stems from the wish to project a specific self-image [50,51]. The aspiration to exhibit oneself in a favorable light to others can be stimulated through items that cater to this aspiration [52]. Virtual fashion goods hold comparable significance as real-life apparel, serving as a crucial tool for users to display themselves in the virtual world [5]. Presentability in this paper refers to the fact that people can display their fashion preferences and personalities on social media through virtual fashion clothes. Accordingly, the following hypotheses are proposed:
Presentation has a positive influence on Perceived Enjoyment.
Presentation has a positive influence on Perceived Usefulness.
Presentation has a positive influence on Perceived Ease of Use.
3.2.6. Sustainability
Sustainability is essential for the strategic growth of a firm, particularly in industries like the garment industry that heavily rely on natural resources and labor [53]. Sustainability encompasses a spectrum of strategies and methodologies to mitigate adverse environmental effects, extend the life cycle of resources, and promote socio-economic well-being through a circular economy [54]. The survey emphasizes that the current younger generation is increasingly becoming more interested in sustainability and the concept of a circular economy, and these characteristics are increasingly critical strategic features and a possible means of gaining a competitive edge in the fashion sector over a lengthy period [55]. In this study, sustainability is defined as minimizing energy consumption, reducing pollution, and promoting resource recycling at every stage of the life cycle of virtual fashion clothes, including raw material acquisition, manufacture, usage, and disposal. Accordingly, the following hypotheses are proposed:
Sustainability has a positive influence on Perceived Enjoyment.
Sustainability has a positive influence on Perceived Usefulness.
Sustainability has a positive influence on Perceived Ease of Use.
3.2.7. Inclusivity
As defined by the British Standards Institution (2005), product inclusivity refers to creating mainstream products or services that a wide range of individuals can efficiently utilize without requiring specific modifications or specialized designs [56]. Inclusive design gives consumers more customized and attentive service, leading to higher happiness, loyalty, and a stronger positive perception and emotional bond with the brand [57]. In the fashion industry, inclusivity seeks to cater to the target consumer by lowering the importance of criteria regarding body shape, size, mobility, and other variables, stressing the importance of usefulness and aesthetic attractiveness, and enhancing the user’s experience of using the product in various situations [58]. Given its widespread acceptance, it is crucial to prioritize the inclusivity of clothes. Hence, we hypothesize:
Inclusivity has a positive influence on Perceived Enjoyment.
Inclusivity has a positive influence on Perceived Usefulness.
Inclusivity has a positive influence on Perceived Ease of Use.
3.2.8. Perceived Enjoyment
Enjoyment measures individuals’ perceptions of virtual fashion garments as enjoyable and exhilarating [59]. Previous research has emphasized the entertaining elements of various technologies, including sharing social media selfies [60] and immersing oneself in virtual reality [38]. Furthermore, digital fashion that utilizes superimposition and AR filters facilitates enjoyable self-expression on social media platforms [11]. Perceived Enjoyment (PE) substantially affects user adoption of the metaverse, owing to the potential of such systems to provide users with pleasure and delight [61]. Studies have also demonstrated that the experience of enjoyment has a positive effect on the likelihood of purchasing virtual environments [62,63]. Individuals may acquire virtual fashion garments to enrich their virtual experiences and derive enjoyment from them. Hence, we hypothesize:
Perceived enjoyment (PE) positively affects behavioral intentions (BI) to use virtual fashion clothes.
3.2.9. Perceived Usefulness
As defined by scholars, perceived usefulness indicates the degree to which an individual believes that employing a specific system will enhance job performance [20,36]. Perceived usefulness has a direct impact on users’ attitudes toward the adoption of technology. It is widely acknowledged as the primary variable determining individuals’ desire to use and embrace technology [64], and was evidenced in the context of solar apparel [65]. Within virtual fashion clothes, perceived usefulness is defined as the extent to which consumers believe virtual fashion apparel can help them with fashion expression. Therefore, the hypothesis is formulated:
Perceived usefulness (PU) positively affects behavioral intentions (BI) to use virtual fashion clothes.
3.2.10. Perceived Ease of Use
Perceived ease of use refers to the degree to which an individual perceives a particular system or product as easy to use [20]. Several studies have suggested that the perceived ease of use is a pivotal element influencing the acceptance of smart retail solutions [66]. Furthermore, perceived ease of use impacts perceived usefulness in the classical TAM [20]. The ease of use of virtual fashion clothes mainly refers to consumers finding, selecting, purchasing, and displaying virtual fashion clothes easily. The inclusivity of this paper is reflected in the design principle of virtual fashion products, which breaks through the limitations of traditional clothing, does not set any limitations on the consumer’s body size, age, or gender, and truly realizes wide acceptance and applicability to all users. Therefore, the hypothesis is formulated:
Perceived ease of use (PEOU) significantly and positively affects perceived usefulness (PU).
Perceived ease of use (PEOU) positively affects behavioral intentions (BI) to use virtual fashion clothes.
3.2.11. Behaviour Intention to Use
Behavior Intention to Use refers to the user’s planned or expected behavior in adopting and utilizing a specific technology, which is influenced by their positive or negative evaluations [67]. In the TAM, Behaviour Intention to Use is the focus of the study of consumer and user use behavior. Examining the Behaviour Intention to adopt new technologies can effectively identify the aspects that impact actual usage behavior. Furthermore, a higher willingness to use is more likely to encourage customers to adopt the new technology [64]. Figure 2 summarizes all the assumptions.
4. Research Methods
4.1. Data Collection
This study collected data through a questionnaire survey utilizing WENJUANXING, a specialized online survey platform in China. The primary respondents targeted for this research were predominantly Generation Z users, who were more familiar with the virtual environment.
Before completing the questionnaire, participants were instructed to review the preamble section to become familiar with the specifics of the virtual fashion clothes product. In the thesis, the preamble of the questionnaire was meticulously crafted to ensure a comprehensive introduction to virtual fashion and uniform understanding among respondents. Initially, we defined the fundamental concept of virtual fashion, elucidating its significant role and profound implications within the contemporary fashion realm. Subsequently, we provided an in-depth overview of the characteristics of virtual fashion apparel, such as Aesthetics, Reality, Personalization, Novelty, Presentability, Sustainability, and Inclusivity, detailing how these attributes are manifested in the product’s visual presentation, purchasing process, and perceived value. To enhance the respondents’ comprehension, we also included images of virtual fashion garments and furnished the official website link to The Fabricant brand, enabling interested consumers to delve deeper into and gain a thorough understanding of this burgeoning fashion trend.
Before distributing questionnaires, we implemented 150 preliminary assessments to refine our survey instrument, adjusting the questionnaire based on respondent feedback. This study amassed a total of 545 completed questionnaires. Following the exclusion of 42 responses deemed invalid, a final count of 503 valid questionnaires was retained for analysis. The demographic and characteristic analysis of the samples is presented in Table 1.
4.2. Variable Measurement
The survey consisted of 49 item questions. The respondents’ demographics were determined in the first section of the questionnaire using 4 item questions, including age, gender, and knowledge of virtual fashion clothes. The second part of the questionnaire consists of the indicators based on the extended TAM: Aesthetics, Reality, Personalization (PERS), Novelty, Presentation (PRES), Sustainability (SUS), Inclusivity, Perceived Enjoyment (PE), Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and Behaviour intention to use (IU), involving 11 latent variables. The questionnaire encompassed a series of statements to which respondents provided their level of agreement on a scale of one to five, with anchors at “completely disagree” and “completely agree”. A synthesis of the utilized measures and theoretical constructs can be found in Table 2. All constructs, except for “Inclusivity”, were derived from prior studies. The quantification of “Inclusivity” is derived from a scale derived from its definition.
5. Result
5.1. Reliability and Validity
The reliability of the measurements was assessed utilizing the SPSS 23.0 program. As depicted in Table 3, the Cronbach’s α coefficients for all underlying variables extended from 0.813 to 0.892, surpassing the threshold of 0.70 deemed acceptable and thus pointing to a robust reliability of the scales used.
AMOS 26.0 was employed to execute confirmatory factor analysis, verifying the validity of each construct. As detailed in Table 3, the standardized factor loadings for each variable ranged from 0.705 to 0.808, surpassing the benchmark of 0.50. The combined reliability (CR) for all constructs exceeded the threshold of 0.80, indicating strong convergent validity. Additionally, the average variance extracted (AVE) for each variable was between 0.558 and 0.622, which is above the criterion of 0.50. Moreover, the square root of the AVE for each construct was greater than the Pearson correlations between the construct and others, as shown in Table 4, attesting to the high discriminant validity of each construct.
5.2. Model Fitting
Utilizing AMOS 26.0, the model’s fitness was evaluated through its goodness-of-fit indices. Table 5 outlines the statistical measures for the model’s fitness assessment. The CMIN/DF ratio was recorded at 1.136, aligning with the acceptable range between 1.0 and 3.0. The model’s CFI, IFI, TLI, and NFI indices were 0.988, 0.988, 0.986, and 0.914, respectively, each exceeding the benchmark of 0.90. Furthermore, the RMSEA index was 0.017, less than the threshold of 0.08, and the SRMR index was 0.034, below the cutoff of 0.05, indicating that the model exhibits a satisfactory fit.
5.3. Hypothesis Test
Based on the results shown in Table 6 and Figure 3, the relationship between aesthetics and perceived enjoyment (β = 0.118; CR = 2.016, p < 0.05) was accepted. Additionally, the relationship between reality and perceived enjoyment (β = 0.132; CR = 2.126, p < 0.05), the relationship between reality and perceived usefulness (β = 0.236; CR = 3.811, p < 0.001), and the relationship between reality and perceived ease of use (β = 0.184; CR = 2.799, p < 0.01) were accepted. Moreover, the relationship between Personalization and perceived usefulness (β = 0.115; CR = 2.074, p < 0.05) and the relationship between Personalization and perceived ease of use (β = 0.145; CR = 2.421, p < 0.05) were accepted. Furthermore, the relationship between novelty and perceived enjoyment (β = 0.128; CR = 2.333, p < 0.000) was accepted. Additionally, the relationship between presentation and perceived enjoyment (β = 0.168; CR = 2.545, p < 0.05), the relationship between presentation and perceived usefulness (β = 0.152; CR = 2.356, p < 0.05), and the relationship between presentation and perceived ease of use (β = 0.14; CR = 2.013, p < 0.05) were accepted. The relationship between sustainability and perceived enjoyment (β = 0.142; CR = 2.399, p < 0.05), the relationship between sustainability and perceived usefulness (β = 0.132; CR = 3.664, fap < 0.05), and the relationship between sustainability and perceived ease of use (β = 0.231; CR = 2.275, p < 0.001) were also accepted. Similarly, the relationship between inclusivity and perceived enjoyment (β = 0.130; CR = 2.139, p < 0.05) and the relationship between inclusivity and perceived ease of use (β = 0.085; CR = 00.127, p < 0.05) were accepted. Finally, the relationship between perceived enjoyment and intentions to use (β = 0.204; CR = 3.751, p < 0.000), the relationship between perceived usefulness and intentions to use (β = 0.224; CR = 3.807, p < 0.000), the relationship between perceived ease of use and perceived usefulness (β = 0.128; CR = 2.512, p < 0.05), and the relationship between perceived ease of use and intentions to use (β = 0.204; CR = 4.003, p < 0.000) were accepted.
Therefore, the impact relationships are summarized in Figure 4. The results support H1, H4, H5, H6, H8, H9, H10, H13, H14, H15, H16, H17, H18, H19, H21, H22, H23, H24, and H25, whereas H2, H3, H7, H11, H12, and H20 are invalid.
6. Discussion
6.1. Discussion of Technology Acceptance Models
This paper categorizes virtual fashion clothes and clearly defines the virtual fashion clothes that are studied in this research. It introduces the emotional three-level theory model to sort out the characteristics of virtual fashion clothes that can satisfy consumers’ emotional needs: aesthetics, reality, personalization, novelty, presentability, sustainability, and inclusivity. Extending the technology acceptance model, the characteristics of virtual fashion clothes, perceived enjoyment, perceived usefulness, perceived ease of use, and willingness to use are employed as the measurement items to establish the prediction model of consumers’ acceptance of virtual fashion clothes.
Perceived usefulness, perceived ease of use, and perceived enjoyment positively affect the willingness to accept virtual fashion clothes, and perceived ease of use positively affects consumers’ perceived usefulness. Perceived enjoyment (PE) was shown to have a significant positive effect on behavioral intention (BI) to use virtual fashion clothes. This suggests that satisfaction associated with virtual fashion clothes plays a significant role in influencing behavioral intention to accept virtual fashion clothes. This means that individuals are more likely to embrace new technologies if they are pleasant, satisfying, and enjoyable. This is consistent with the findings of previous research on the virtual industry [76]. To enhance players’ enjoyment, engagement, and enjoyment, virtual fashion clothes designers and practitioners should prioritize improving user experience scenarios. By focusing on the user, they can increase user engagement and contribute to the growth of the virtual fashion industry. Perceived Usefulness (PU) also significantly impacts Behavioral Intentions (BI) to use virtual fashion clothes. Prior scholarly work has recognized perceived utility as a paramount determinant of the behavioral intent to embrace and employ emerging technological advancements [77,78]. This implies that an enhancement in the perception of a technology’s utility is likely to escalate the willingness to adopt it, thereby boosting the uptake rate for the innovation. Additionally, perceived ease of use (PEOU) has been demonstrated to influence perceived usefulness (PU). This finding corroborates earlier research highlighting the linkage between PEOU and PU [20,79,80]. Meanwhile, TAM concluded that both PEOU and PU affect the establishment of good attitudes related to technology use and, when combined with PU, increase people’s willingness to use technology. In addition, PEOU is expected to positively influence users’ perceptions of their intention to use the technology [20]. Hence, organizations must formulate strategies to enhance awareness of its usefulness, improving the online shopping experience for virtual fashion clothes by providing visually attractive websites to enhance flexibility. This will enhance user satisfaction and happiness and encourage acceptance and sustained utilization.
At the visceral level, the aesthetics of virtual fashion clothes positively affect consumers’ perceived enjoyment, suggesting that the aesthetic design of virtual fashion clothes attracts consumers’ interest and leads to a positive emotional response. This is consistent with previous research on aesthetics [34,35]. Nevertheless, the hypothesis on the relationship of aesthetics with perceived usefulness and perceived ease of use was rejected. This is likely to be because, while virtual fashion clothes may offer consumers aesthetic pleasure, they do not inspire them to explore the idea of expressing their preferences through virtual fashion clothes products. This is consistent with research that says gamers only use skins for aesthetic enjoyment [33]; the characteristic of reality has a positive effect on consumers’ perceived enjoyment, usefulness, and ease of use. Reality has a strong positive effect on perceived usefulness, suggesting that, the more realistic the fabric, folds, and dynamic deformations of virtual fashion clothes are, the more consumers will be motivated to “wear” these virtual fashion clothes. This is consistent with previous research on authenticity [37].
At the behavioral level, personalization positively impacts consumers’ perceived usefulness and ease of use. This implies that consumers will prioritize the ability to personalize virtual fashion clothes. That personalization will enhance the value of the product for consumers and make it easier to use the product. This is consistent with the findings of previous Personalization research [46,47]. Novelty positively affects consumers’ perceived enjoyment, but the hypothesized relationships between novelty and perceived usefulness and novelty and perceived ease of use are rejected, which is inconsistent with previous research that suggests that novelty hinders the usability and ease of use of products [8]. This may be because the main research object chosen for this paper is the youth of Generation Z. The current generation is accustomed to virtual technology and online shopping. While they find new technological advancements intriguing, they do not think it will make examining products more challenging. Additionally, although utilizing new technology, virtual fashion clothes differ from other products prioritizing technological experiences. Virtual fashion clothes primarily serve as a fashion product, allowing consumers to express their fashion preferences. The presentability of virtual fashion clothes positively affects perceived enjoyment, usefulness, and ease of use. This aligns with the idea that virtual fashion clothes are designed for social media users, who value the ability to present themselves in new and exciting ways. This result aligns with prior scholarly work regarding individuals’ inclination towards self-representation on digital platforms [47,49,50].
At the reflective level, the Inclusivity of virtual fashion clothes had a strong positive effect on consumers’ perceived ease of use, consistent with previous research suggesting that inclusivity in product design increases the efficiency of use across different groups of people [57]. Meanwhile, the sustainability features of virtual fashion clothes significantly impact consumers’ perceived enjoyment, use, and ease of use. In conclusion, the inclusivity and sustainability of virtual fashion clothes can elicit strong emotional reactions from consumers and foster their identification with the brand culture of virtual fashion clothes.
6.2. Discussion on the Sustainability of Virtual Fashion Clothes
The sustainability features of virtual fashion clothes significantly impacts consumers’ perceived enjoyment, use, and ease of use. This influence is evident in multiple facets: firstly, the perceived enjoyment of virtual fashion is closely intertwined with its sustainability aspects. The recognition that virtual fashion clothes minimize environmental impact fosters consumer satisfaction, aligning with their environmental and social responsibility values, which is supported by extant literature highlighting an escalating consumer focus on sustainability [53,54]. Second, concerning perceived use value, when virtual fashion clothes demonstrate their environmental benefits, consumers perceive these products as having a higher use value because they not only satisfy fashion needs but also reflect a commitment to social responsibility. Ultimately, the perceived ease of use for virtual fashion is heightened by the absence of physical storage needs, which in turn lessens carbon emissions in logistics and transportation. Furthermore, the accessibility of virtual fashion clothes through digital devices at any time and location introduces flexibility and convenience that substantially enriches the consumer experience.
The results of the questionnaire research on consumer attitudes towards the sustainability of virtual clothes revealed that item 3 (SUS3), “Virtual fashion clothes are more eco-friendly than physical fashion clothes,” exhibited a factor loading coefficient of 0.768. This indicates that the majority of consumers perceive virtual clothes to be more compatible with the concept of sustainability than physical clothes.
7. Conclusions
7.1. Theoretical Implications
This paper provides some academic implications. Firstly, the three-level theory of emotion has been integrated within the exploration of virtual fashion clothes’ features, categorizing consumers’ emotional needs into three levels: instinctive, behavioral, and reflective, thereby facilitating a more nuanced analysis of how virtual fashion clothes satisfy consumers’ emotional needs. The findings indicate that these emotional features can elicit various emotional responses from consumers, demonstrating the unique capacity of virtual fashion clothes to address consumers’ emotional needs, thus enabling researchers to better understand consumers’ genuine sentiments and motivations for purchasing virtual fashion clothes.
Furthermore, this study incorporates additional product attributes and perceived hedonic elements of virtual fashion clothes into the TAM for model enhancement, enabling a more precise examination of consumer acceptance behavior in virtual fashion. The study demonstrates that the features of aesthetics, realism, personalization, novelty, presentability, sustainability, and inclusivity identified herein exert varying influences on consumers’ perceived value, which suggests the suitability of TAM for the virtual fashion domain. This further offers a novel perspective for researchers examining the purchase motivations for other virtual domain products.
Concurrently, this paper delves into the influence of sustainability in virtual fashion apparel on consumer purchase intentions, revealing the capacity of virtual fashion as a sustainable business model to mitigate resource wastage within the fashion industry. The study’s findings offer a theoretical foundation for future research on consumer behavior in virtual fashion and supply empirical support for sustainability initiatives within the sector.
7.2. Practical Implications
This research elucidates the driving factors behind consumer adoption of virtual fashion clothes, offering valuable insights for designers, management, and other stakeholders in the virtual fashion sector. The findings of this research can assist traditional fashion brands in making well-informed decisions regarding potential entry into the virtual fashion market. The research indicates that consumers attach significant importance to the brand identity associated with virtual fashion clothes, utilizing these items as a means of self-expression on social media platforms. Additionally, consumers place equal emphasis on the visual appeal, realism, and personalized experience offered by virtual fashion clothes. This study also highlights the potential of virtual fashion clothes to promote sustainability and inclusivity within the fashion industry, providing valuable insights into the feasibility and durability of the industry’s environmental commitments.
At the visceral level, both the aesthetics and reality of virtual fashion clothes can contribute to consumers’ emotional connection with them. Still, the impact of authenticity is more diverse and stronger. As a result, virtual fashion designers or administrators can focus more on the design of virtual fashion clothes, web page layout, and other visual components to enhance the sensory experience for consumers. Simultaneously, it is crucial to focus on and actively investigate novel virtual technologies to raise the realism of the product and consequently improve the immersive experience for consumers.
At the behavioral level, virtual fashion designers can strategically emphasize the capacity of virtual fashion to exhibit individual fashion preferences, integrating this aspect into a pivotal marketing strategy aimed at capturing consumer attention. Additionally, by leveraging advanced data and text mining technologies, virtual fashion enterprises can glean insights into the unique requirements of their clientele across product development, purchasing decisions, and other pertinent stages, offering more precise and attentive personalized services. This approach not only holds the potential to broaden the market scope for virtual products but also to elevate satisfaction levels and foster loyalty among existing customers. Concurrently, virtual clothes brands are encouraged to prioritize innovation and diversification in product offerings, exploring novel modes of presentation beyond conventional photo and video formats. During the design phase, careful consideration should be given to cross-platform compatibility to ensure users can exhibit their virtual clothes imagery across major social media platforms in many inventive ways, thus enriching user experiences and bolstering brand perception.
At the reflective level, sustainability features give virtual fashion clothes a competitive advantage over traditional physical fashion. However, numerous virtual clothes businesses have not yet completely acknowledged the significance of these two cultural principles. Brands can use this opportunity to integrate sustainability into their marketing strategies and branding philosophies, infusing virtual clothes products with profound cultural significance.
7.3. Limitations and Future Research
There are still several limitations to this paper. First, although the variables derived from the Emotional Three-Level Theory showed statistical significance in our study, nevertheless the paths that were not supported, or exhibited low path coefficients, suggest that various complex psychological factors influence consumers’ willingness to accept virtual fashion. Future research endeavors could consider incorporating Grounded Theory to delve deeper into the consumer psyche. Through this approach, researchers may identify additional constructs that could refine the Emotional Three-Level Theory’s application and extend its explanatory power within consumer behavior studies.
Second, given that this study focused on Generation Z to explore its acceptance and preferences for virtual fashion clothes, other age groups have received comparatively less research attention. Nevertheless, we realize that these groups are potential consumers that should not be ignored. Thus, future research can focus more deeply on their needs. Future research will investigate the effects of demographic characteristics, including age, gender, education level, and cultural background, on consumers’ acceptance and intention to use virtual fashion clothes. This multi-dimensional analysis can provide precise insights into the specific needs and preferences of various consumer groups, offering data that can inform market segmentation and customization strategies, thereby enabling targeted marketing of virtual fashion clothes.
In subsequent research, the principles of sustainability and inclusivity should be examined as essential dimensions of virtual fashion brand culture. Additionally, they deserve thorough scholarly exploration and theoretical analysis. Furthermore, considering the potential environmental implications of virtual fashion clothes, future studies should comprehensively assess their environmental footprint throughout the product life cycle, encompassing the stages of production, utilization, and disposal, which will facilitate the enhanced contribution of virtual fashion clothes toward sustainability objectives during their design, development, and marketing phases.
With the established connection between virtual fashion and technologies such as Virtual Reality (VR) and Augmented Reality (AR), these technologies’ ongoing integration and evolution within the fashion industry may significantly influence consumer perceptions and interactions with virtual fashion. Therefore, when researching virtual fashion, it is prudent to consider the newest developments in these technologies and explore their potential effects on consumer acceptance, fashion experiences, and purchasing behaviors.
In conclusion, these research methods are anticipated to establish a robust theoretical framework and offer strategic guidance for both academic research and practical applications in virtual fashion. Furthermore, they are poised to foster ongoing innovation and advancement in the field, while also contributing to the sustainable development of the fashion industry.
Y.D. collected and analyzed data and drafted the manuscript, and all co-authors conceived the original idea; H.S. and X.J. conducted the processing. All authors have read and agreed to the published version of the manuscript.
Ethical review and approval were waived for this study, as the data collected were anonymized and did not include participants’ names, which complies with the Measures for Ethical Review of Life Sciences and Medical Research Involving Humans issued by the People’s Republic of China in February 2023, specifically Article 32 of Chapter 3, regarding the exemption from ethical review.
Informed consent was obtained from all subjects involved in the study.
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the confidentiality assurance for each participant’s information.
The authors declare no conflicts of interest.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Enlarge this image.Figure 1. The characteristics of virtual fashion clothes are summarized based on the emotional three-level theory.
Enlarge this image.Figure 4. Summary of path relationships. Note: *** p < 0.001, ** p < 0.01, * p < 0.05.
Demographic characteristics of respondents.
| Sample | Category | Number | Percentage |
|---|---|---|---|
| Gender | Male | 262 | 52.1% |
| Female | 241 | 47.9% | |
| Age | 18–22 | 236 | 46.9% |
| 23–29 | 125 | 24.9% | |
| 30–43 | 103 | 20.5% | |
| Below 18 and above 43 | 39 | 7.8% | |
| Prior knowledge of virtual fashion clothes products | Yes | 168 | 33.4% |
| No | 335 | 66.5% |
Dimensions and measuring items.
| Items | Measure | Supporting References |
|---|---|---|
| Aesthetic | The virtual fashion clothes, e.g., the color, pattern, and texture presented in virtual fashion clothes, impressed me. | Wang [ |
| The design theme of virtual fashion clothes impressed me. | ||
| I was impressed by the technological elements, such as filters, materials, and effects, presented in virtual fashion clothes. | ||
| Virtual fashion clothes provided me with a rich sensory experience. | ||
| Reality | Simulating textures and materials similar to real-world scenes is crucial for virtual fashion clothes. | Fatma Baytar [ |
| High integration with the model’s body shape and movements is essential for virtual fashion clothes. | ||
| Showcasing dynamic wearing effects, like draping and wrinkles, akin to real-world scenes is important for virtual fashion clothes. | ||
| Realistic lighting and shadow effects in both dynamic and static states are important for virtual fashion clothes. | ||
| Personalization | Virtual fashion clothes’ designers need to tailor designs according to my preferences. | Juho Hamari [ |
| Adjusting virtual fashion clothes based on my “wearing” effect is crucial. | ||
| It is important to provide virtual fashion clothes designers with various forms of clothes (images, videos, etc.) based on my needs. | ||
| Virtual fashion practitioners must recommend clothes based on my needs. | ||
| Novelty | I would want to experience virtual fashion clothes because it’s a new way of expressing fashion. | Cambell [ |
| I want to experience the emerging technologies involved in virtual fashion clothes. | ||
| I want to learn about virtual fashion clothes because I’m curious about how they differ from other clothes (e.g., physical clothing, accessories, etc.). | ||
| Presentation | I want to show photos of me in my virtual fashion clothes on social media platforms. | Kim, Hee Woong [ |
| Virtual fashion companies must ensure cross-platform compatibility of their clothes for showcasing on social media. | ||
| Showing other people on social media platforms an image of me in virtual fashion clothes helps me attract the attention of other community members. | ||
| I want to differentiate myself from others on social media by wearing virtual fashion clothes. | ||
| Sustainability | The production and finishing of virtual fashion clothes reduce environmental pollution compared to physical fashion clothes. | Tai Ming Wut [ |
| Virtual fashion clothes reduce the consumption of resources (electricity, fuel, and other resources) compared to physical fashion clothes. | ||
| Virtual fashion clothes are more eco-friendly than physical fashion clothes. | ||
| The brand concept of virtual fashion clothes, which reduces environmental pollution by not using actual production materials, is correct. | ||
| Inclusivity | Virtual fashion clothes are gender-neutral, and the idea that both men and women can wear the same product is right. | British Standards Institution |
| Virtual fashion clothes can satisfy people with different fashion pursuits. | ||
| Virtual fashion clothes are right not to differentiate and limit consumer size. | ||
| Virtual fashion clothes are appropriate for not differentiating between clothes for different age groups. | ||
| Perceived | Virtual fashion clothes bring a lot of good experiences for me | Kowalczuk [ |
| Virtual fashion clothes are fun. | ||
| I think “wearing” virtual fashion clothes fulfills my imagination of living in a virtual world. | ||
| I find it stress-relieving and relaxing to learn information about virtual fashion clothes. | ||
| Experiencing virtual fashion clothes brings joy. | ||
| Perceived | Understanding the virtual fashion clothes process has generated a lot of thoughts for me. | Davis [ |
| I learned about many people and things while browsing for information about virtual fashion clothes. | ||
| “Wearing” virtual fashion clothes makes me feel fashionable. | ||
| Virtual fashion clothes can express my fashion preferences better than physical fashion clothes. | ||
| Perceived Ease of Use | I’ll soon learn how to buy and “wear” virtual fashion clothes. | Hwang [ |
| Buying and “wearing” virtual fashion clothes doesn’t require complex brain activity. | ||
| I have easily understood how virtual fashion clothes are purchased and used. | ||
| The actions required to purchase virtual fashion clothes were easy to understand. | ||
| It’s easier to express my fashion preferences virtually than with physical fashion clothes. | ||
| Intentions to use | I’d consider “wearing” virtual fashion clothes. | Ajzen [ |
| I would consider expressing my fashion attitude by showing photos of myself “wearing” virtual fashion clothes. | ||
| If and when I’m asked my opinion on a virtual fashion product, I’ll make a few points in favor of it. | ||
| I recommend virtual fashion clothes to others. |
Results of reliability analysis.
| Factors | Code | Loading | AVE | CR | Cronbach’s α |
|---|---|---|---|---|---|
| Aesthetic | A1 | 0.742 | 0.560 | 0.836 | 0.826 |
| A2 | 0.728 | ||||
| A3 | 0.745 | ||||
| A4 | 0.778 | ||||
| Reality | R1 | 0.769 | 0.576 | 0.844 | 0.821 |
| R2 | 0.754 | ||||
| R3 | 0.758 | ||||
| R4 | 0.755 | ||||
| Personalization | PERS1 | 0.705 | 0.594 | 0.853 | 0.834 |
| PERS2 | 0.781 | ||||
| PERS3 | 0.785 | ||||
| PERS4 | 0.808 | ||||
| Novelty | N1 | 0.801 | 0.618 | 0.830 | 0.829 |
| N2 | 0.754 | ||||
| N3 | 0.804 | ||||
| Presentation | PRES1 | 0.791 | 0.589 | 0.870 | 0.851 |
| PRES2 | 0.742 | ||||
| PRES3 | 0.770 | ||||
| PRES4 | 0.765 | ||||
| Sustainability | SUS1 | 0.755 | 0.584 | 0.849 | 0.813 |
| SUS 2 | 0.775 | ||||
| SUS 3 | 0.768 | ||||
| SUS 4 | 0.759 | ||||
| Inclusivity | I1 | 0.792 | 0.608 | 0.861 | 0.862 |
| I2 | 0.778 | ||||
| I3 | 0.787 | ||||
| I4 | 0.763 | ||||
| Perceived Enjoyment | PE1 | 0.776 | 0.558 | 0.863 | 0.824 |
| PE2 | 0.746 | ||||
| PE3 | 0.744 | ||||
| PE4 | 0.734 | ||||
| PE5 | 0.737 | ||||
| Perceived Usefulness | PU1 | 0.751 | 0.565 | 0.839 | 0.841 |
| PU2 | 0.753 | ||||
| PU3 | 0.743 | ||||
| PU4 | 0.761 | ||||
| Perceived Ease of Use | PEOU1 | 0.798 | 0.622 | 0.891 | 0.892 |
| PEOU2 | 0.774 | ||||
| PEOU3 | 0.782 | ||||
| PEOU4 | 0.787 | ||||
| PEOU5 | 0.804 | ||||
| Intentions to use | IU1 | 0.761 | 0.574 | 0.843 | 0.845 |
| IU2 | 0.759 | ||||
| IU3 | 0.763 | ||||
| IU4 | 0.749 |
Correlation matrix and AVE.
| Factors | Inclusivity | SUS | PRES | Novelty | PERS | Reality | Aesthetic | PU | PEOU | IU | PE |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Inclusivity | 0.780 | ||||||||||
| SUS | 0.504 | 0.764 | |||||||||
| PRES | 0.503 | 0.478 | 0.767 | ||||||||
| Novelty | 0.429 | 0.409 | 0.477 | 0.786 | |||||||
| PERS | 0.386 | 0.390 | 0.536 | 0.449 | 0.771 | ||||||
| Reality | 0.492 | 0.469 | 0.451 | 0.427 | 0.442 | 0.759 | |||||
| Aesthetic | 0.480 | 0.435 | 0.491 | 0.403 | 0.394 | 0.492 | 0.748 | ||||
| PU | 0.484 | 0.473 | 0.503 | 0.398 | 0.450 | 0.533 | 0.445 | 0.752 | |||
| PEOU | 0.435 | 0.491 | 0.470 | 0.390 | 0.438 | 0.473 | 0.407 | 0.400 | 0.789 | ||
| IU | 0.267 | 0.280 | 0.283 | 0.229 | 0.258 | 0.292 | 0.247 | 0.411 | 0.401 | 0.758 | |
| PE | 0.464 | 0.455 | 0.486 | 0.433 | 0.379 | 0.455 | 0.445 | 0.394 | 0.371 | 0.222 | 0.747 |
Leading indicators of model fit test.
| Model Fit Indices | Evaluation Index (Acceptable Level) | Values of the Model |
|---|---|---|
| CMIN/DF | 1.0 < CMIN/DF < 3.0 | 1.136 |
| CFI | >0.90 | 0.988 |
| IFI | >0.90 | 0.988 |
| TLI | >0.90 | 0.986 |
| NFI | >0.90 | 0.914 |
| SRMR | <0.05 | 0.034 |
| RMSEA | <0.08 | 0.017 |
Hypothesis testing.
| Hypotheses & Path | Estimate | Std. Estimate | CR | p | Conclusion | |||
|---|---|---|---|---|---|---|---|---|
| H1 | PE | ← | Aesthetic | 0.118 | 0.119 | 2.016 | 0.044 | Supported |
| H2 | PU | ← | Aesthetic | 0.071 | 0.073 | 1.243 | 0.214 | Rejected |
| H3 | PEOU | ← | Aesthetic | 0.06 | 0.056 | 0.963 | 0.335 | Rejected |
| H4 | PE | ← | Reality | 0.132 | 0.128 | 2.126 | 0.034 | Supported |
| H5 | PU | ← | Reality | 0.236 | 0.234 | 3.811 | *** | Supported |
| H6 | PEOU | ← | Reality | 0.184 | 0.166 | 2.799 | 0.005 | Supported |
| H7 | PE | ← | Personalization | 0.026 | 0.027 | 0.467 | 0.641 | Rejected |
| H8 | PU | ← | Personalization | 0.115 | 0.120 | 2.074 | 0.038 | Supported |
| H9 | PEOU | ← | Personalization | 0.145 | 0.138 | 2.421 | 0.015 | Supported |
| H10 | PE | ← | Novelty | 0.128 | 0.133 | 2.333 | 0.020 | Supported |
| H11 | PU | ← | Novelty | 0.026 | 0.028 | 0.487 | 0.626 | Rejected |
| H12 | PEOU | ← | Novelty | 0.053 | 0.051 | 0.918 | 0.359 | Rejected |
| H13 | PE | ← | Presentation | 0.168 | 0.164 | 2.545 | 0.011 | Supported |
| H14 | PU | ← | Presentation | 0.152 | 0.152 | 2.356 | 0.018 | Supported |
| H15 | PEOU | ← | Presentation | 0.14 | 0.127 | 2.013 | 0.044 | Supported |
| H16 | PE | ← | Sustainability | 0.142 | 0.140 | 2.399 | 0.016 | Supported |
| H17 | PU | ← | Sustainability | 0.132 | 0.212 | 3.664 | *** | Supported |
| H18 | PEOU | ← | Sustainability | 0.231 | 0.133 | 2.275 | 0.023 | Supported |
| H19 | PE | ← | Inclusivity | 0.13 | 0.129 | 2.139 | 0.032 | Supported |
| H20 | PU | ← | Inclusivity | 0.125 | 0.079 | 1.334 | 0.182 | Rejected |
| H21 | PEOU | ← | Inclusivity | 0.085 | 0.127 | 2.100 | 0.036 | Supported |
| H22 | IU | ← | PE | 0.204 | 0.210 | 3.751 | *** | Supported |
| H23 | IU | ← | PU | 0.224 | 0.227 | 3.807 | *** | Supported |
| H24 | PU | ← | PEOU | 0.128 | 0.141 | 2.512 | 0.012 | Supported |
| H25 | IU | ← | PEOU | 0.204 | 0.227 | 4.003 | *** | Supported |
Note: *** means the p-value is less than 0.001. The arrow ‘←’ in the table indicates the hypothesized direction of the relationship, where the variable to the right is expected to influence the variable on the left.
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