The digital transformation of the apparel sector has been driven by the development of virtual reality technology and the evolution of digital environments. According to Roberts-Islam (2020), virtual clothing (contactless cyber fashion and digital clothing), which exists only in digital environments and can be traded, has gradually become a hot topic as the core of the digital transformation of apparel. Beyond overcoming the physical limitations of traditional clothing, virtual clothing offers consumers a new fashion experience through advanced technologies like virtual reality, augmented reality, and blockchain (Baek et al., 2022). In 2018, Fabricant sold a virtual dress called Iridescence for USD 500, which marked the beginning of virtual clothing in the blockchain digital asset space (Roberts-Islam, 2019). As part of global digital fashion, virtual clothing is rapidly taking over the market in several digital domains, including gaming, virtual worlds, and social media (Y. Park et al., 2023). This development not only changes the ecology of the fashion industry but also marks the gradual penetration of virtual clothing into consumers’ lives. Therefore, the study of the drivers of virtual clothing consumers’ behavior will not only help to understand the acceptance of emerging digital products in the market but also provide theoretical and practical support for the digital transformation of the fashion industry.

 

The potential of the global virtual clothing market is gradually emerging. As a type of nonfungible token, virtual clothing utilizes blockchain technology to ensure its unique ownership attributes, allowing consumers to have exclusive digital assets in the virtual realm. Thus, virtual clothing not only provides users with new forms of fashion expression but also blurs the boundaries between reality and fantasy (Allaire, 2020). Many well-known apparel brands have entered the emerging virtual clothing sector to expand their digital presence. For example, luxury brands such as Gucci, Louis Vuitton, and Balenciaga have launched virtual clothing collections (Alexander & Bellandi, 2022; Joy et al., 2022) to prioritize their competitive advantage in the rapidly expanding digital fashion space. This trend suggests that virtual clothing is not only a tool for brands to innovate but also a key strategy to open new markets and attract digital natives.

 

Research on the factors that drive consumers’ intention to purchase is essential for facilitating the growth of the virtual clothing market and for making development decisions. Most existing research on virtual clothing has focused on the theoretical aspects of its nature (Baek et al., 2022; Meier et al., 2021), characteristics (H. Park & Lim, 2023), and design (M. Deng et al., 2023), with only a few studies exploring theoretical aspects of the more profound influences on consumers’ intention to purchase. For example, studies have found that the following variables have a positive impact on consumer purchase decisions: perceived value and quality (Lau & Ki, 2021; Reyes Robles et al., 2022), the connection between the creator and the brand (Mendis, 2021), personalization (Lau & Ki, 2021; Lin et al., 2025), interactivity (Lin et al., 2024), socialization (Lau & Ki, 2021; Saepudin et al., 2023), novelty (Lin et al., 2025; Saepudin et al., 2023), and aesthetics (Lin et al., 2024).

 

Although these studies provide important insights for understanding the factors influencing consumers’ willingness to purchase virtual clothing, most of them have focused on a single dimension, such as a specific design, functionality, or consumer interaction experience, which means they lack a systematic and comprehensive perspective. As a new and innovative product, particularly when it is not widely known to consumers, virtual clothing has not yet received enough attention in terms of its unique and essential features and the process of consumers’ evolving perception of the product. On the basis of market feedback and existing research, the adoption of virtual clothing primarily targets younger generations, particularly those with a strong interest in the metaverse and digital games (Khelladi et al., 2024). These young consumers are familiar with virtual environments and are keen to express their individuality and explore fashion trends through virtual platforms (D’Arpizio et al., 2020; Saepudin et al., 2023; Sheng, 2023).

 

However, virtual clothing has relatively low acceptance among other age and interest groups and has yet to be popularized in the mass market (Sheng, 2023). Therefore, there is a need to conduct in-depth analyses of the acceptance differences between different compatibility groups to better understand the market potential and consumer behavior. Since the virtual clothing market is in the early stages of development and consumers have limited knowledge about it, research into the relationship between virtual clothing cognition and the formation of intention to purchase will be of great significance in revealing the consumer purchase factors of virtual clothing and enhancing market acceptance. Consumers often go through a sequential reaction of cognition, affect, and conation in the process of accepting an innovative object (Qin et al., 2021). Cognition–affect–conation theory (Qin et al., 2021) provides a systematic framework for deep understanding of the whole process of consumption, from initial cognition to the formation of intention to purchase.

 

In this study we applied cognition–affect–conation theory and combined the technological frontier and market innovation characteristics of virtual clothing, focusing on three issues: First, from the cognition dimension, we analyzed whether consumers’ innovation identification and social influence of virtual clothing predicted their intention to purchase. Second, from the affect dimension, we examined whether perceived enjoyment and perceived sociability played a crucial role in predicting consumers’ intention to purchase, especially the emotional connection generated from social interaction and entertaining experiences. Third, we considered the differences in perception and acceptance of virtual clothing between familiar and unfamiliar groups, and whether this led to variations in the predictive effect of the mediators. Therefore, we introduced compatibility as a moderating variable and examined its effect on the mediating variables.

The cognition–affect–conation (CAC) framework is rooted in psychological research (B. Dai et al., 2020), and consists of three components: Cognition, which describes an individual’s beliefs about and evaluations of an object; affect, which is an emotional response based on cognition; and conation, which refers to a behavioral tendency based on both cognitive and affective factors (Xu, 2023). CAC theory suggests that cognition has a direct effect on affective outcomes, which, in turn, affects behavioral intentions (Huitt, 1999; Xu, 2023). As CAC theory provides a systematic framework for the mechanisms through which emotion is converted into behavioral intention, it has been widely applied in user behavior research areas such as social media information avoidance (B. Dai et al., 2020), persistent use of mobile augmented reality apps and purchase intentions (Qin et al., 2021), travel recommendations and revisit intentions (Ladhari & Souiden, 2020), and privacy disclosure intentions on social media (Wang et al., 2024).

The cognitive dimension focuses on the internal mechanisms by which consumers process external information (Hilgard, 1980). Given the nature of virtual clothing as a technologically innovative product, the core cognitive point is the identification of innovative features. Therefore, because consumers pay special attention to the degree of product innovation when processing such information (Rogers, 2003), we took the identification of innovation features of virtual clothing compared to traditional clothing as the primary cognitive variable. Information processing theory suggests that consumers’ cognitive processes are driven by external information inputs (Salancik & Pfeffer, 1978), and existing research also found that the behaviors and opinions of friends, relatives, or other social groups have a significant impact on consumers’ cognition (Amblee & Bui, 2011; X. Hu et al., 2019; Spears, 2021). This implies that the surrounding social environment profoundly influences consumers’ cognition of virtual clothing. Therefore, we also examined social influence as a variable within the cognitive dimension.

 

The diffusion of innovative products is crucial for gaining market share. Both the Bass model (Mahajan et al., 1990) and diffusion of innovation theory (Rogers, 2003) emphasize the important role of innovation information in this process, suggesting that user recommendations can effectively reduce uncertainty about new products. For example, existing research has suggested that enhanced social influence in social media accelerates the diffusion of innovation information (Kijek et al., 2020). Celebrity endorsements have a positive effect on intention to purchase (Shafiq et al., 2011), while opinion leaders play a key role in the diffusion of fashion innovations (H. M. Kim & Chakraborty, 2024). Thus, social influence may increase the visibility of innovations, fostering consumer attention and recognition. Therefore, we proposed the following hypothesis:

Hypothesis 1: Social influence will positively predict innovation identification.

On the basis of their cognition of virtual clothing products, consumers further develop emotions and feelings. Existing research has found that in the context of virtual clothing consumption, consumers primarily experience two subjective psychological responses: perceived enjoyment and perceived sociability (Khelladi et al., 2024; Lau & Ki, 2021; Saepudin et al., 2023). Perceived enjoyment refers to the level of consumer pleasure in the use of a particular product or service (Dhar & Wertenbroch, 2000). Perceived sociability focuses on interpersonal interactions and measures an individual’s effectiveness in maintaining and developing social relationships (H. Li et al., 2015) and promoting social connections (M. J. Kim et al., 2020). Unlike social influence, which involves external informational inputs and cognitive evaluation, perceived sociability places greater emphasis on emotional connections and relational bonds.

 

For virtual clothing, perceived sociability emphasizes the value consumers gain from interpersonal interactions in various social contexts (C.-B. Zhang et al., 2017), specifically in establishing and maintaining social relationships. Meanwhile, enjoyment measures the pleasure and entertainment experienced while using virtual clothing (Rauschnabel et al., 2017). Positive social interactions have been shown to predict mood and well-being (Roshanaei et al., 2024). Researchers have shown the importance of sociality, including online socialization (D. C. Li, 2011) and online gaming (Kaye & Bryce, 2012), in predicting the enjoyment experience of digital products. Therefore, we proposed the following hypothesis:

Hypothesis 2: Perceived sociability will positively predict perceived enjoyment.

Intention to purchase is a consumer’s psychological tendency or plan to purchase a product or service (X. Li et al., 2021; J. Zhou et al., 2023), based on their cognitive and affective responses. We aimed to verify whether consumers’ intentions regarding learning about virtual clothing will translate into intention to purchase after having cognitive and affective experiences.

Alonso-García et al. (2023) indicated that innovative characteristics significantly enhance users’ positive emotional responses, particularly in terms of interest and desirability. In the field of virtual product consumption, although research on the relationship between innovativeness identification and perceived value has differed across contexts, the positive impact of innovative features on perceived value has been validated. For example, technological innovation can enhance perceived pleasure in a culturally creative virtual brand community (Chen et al., 2022), and the novelty and interactivity of virtual clothing can enhance perceived value (Lin et al., 2024). Virtual word-of-mouth significantly increases the perceived hedonic value of innovative products and enhances their social applicability through interaction and information sharing (Kunja et al., 2022). Therefore, innovative identification may enhance users’ perceived enjoyment along with their perceived sociability through social interactions. Chen et al. (2022) further found that social interactions in a virtual community can enhance perceived enjoyment and social belonging, and Joy et al. (2022) noted that consumers present themselves through digital products, such as virtual fashion and nonfungible tokens, thereby significantly enhancing their social presence and identity in the group. Therefore, we proposed the following hypotheses:

Hypothesis 3: Innovation identification will positively predict perceived enjoyment.

Hypothesis 4: Innovation identification will positively predict perceived sociability.

Hypothesis 5: Social influence will positively predict perceived enjoyment.

Hypothesis 6: Social influence will positively predict perceived sociability.

In the virtual digital domain, the positive association of perceived enjoyment and perceived sociability with consumer adoption intention is well established. For example, perceived enjoyment has been found to predict nonfungible token purchases (L. Zhang & Phang, 2024), virtual clothing displays (S. Dai et al., 2024), and virtual reality adoption (Y. Deng et al., 2024), while perceived sociability has been found to predict intention to purchase (Kautish et al., 2023), driven by both interpersonal and human–computer interactions (Khelladi et al., 2024; Lin et al., 2025). Therefore, we proposed the following hypotheses:

Hypothesis 7: Perceived enjoyment will positively predict intention to purchase.

Hypothesis 8: Perceived sociability will positively predict intention to purchase.

The positive impact of innovation identification and social influence on consumer intention to purchase has been shown in the domain of virtual digital products. For example, Brandtzaeg and Følstad (2017) demonstrated that innovative technologies can promote consumer adoption of chatbots. In addition, Khelladi et al. (2024) found a positive effect of the novelty dimension of innovativeness on consumers’ willingness to purchase virtual clothing, and T. Zhou (2019) found social influence plays a critical role in purchasing decisions within virtual online environments. Under strong informational social influence (Lee et al., 2011), consumers often rely on recommendations from social networks (Duan et al., 2008), which can trigger purchasing behavior (X. Hu, 2019). Therefore, we proposed the following hypotheses:

Hypothesis 9: Innovation identification will positively predict intention to purchase.

Hypothesis 10: Social influence will positively predict intention to purchase.

Although most previous research using CAC theory has focused on the direct predictive effects of the cognitive and affect dimensions of conation, as well as the progressive enhancement of their predictive effects, the mediating role of the affective dimension between cognition and conation has been gradually receiving more attention from scholars (Kowalczuk et al., 2021). Meanwhile, the mediating role of perceived value (social value, hedonic value, enjoyment value) within the affect dimension has been extensively demonstrated in consumer behavior studies across different contexts (see, e.g., S. Dai et al., 2024; Guo & Li, 2021; Zeng & Kim, 2025). Therefore, we proposed the following hypotheses:

Hypothesis 11: Perceived enjoyment will mediate the relationship between innovation identification and intention to purchase.

Hypothesis 12: Perceived sociability will mediate the relationship between innovation identification and intention to purchase.

Hypothesis 13: Perceived enjoyment will mediate the relationship between social influence and intention to purchase.

Hypothesis 14: Perceived sociability will mediate the relationship between social influence and intention to purchase.

Compatibility pertains to how well a product innovation aligns with consumers’ established sociocultural values, convictions, and prior experiences (Rogers, 2003), and it also refers to the extent to which an innovation matches consumers’ existing feelings, cognitions, and behaviors (Kaabachi et al., 2019). Previous studies have demonstrated that compatibility positively moderates the relationship between different objects and behavioral intentions (Groß, 2018; Islam, 2016). However, according to diffusion of innovations theory (Rogers, 2003) and related studies (Wani & Ali, 2015), compatibility does not always lead to positive outcomes. Excessive compatibility may cause consumers to underestimate a product’s innovativeness and distinct features, thereby reducing interest in the product (Xie et al., 2022). Moreover, the familiarity effect suggests that overly familiar products may attract less attention from consumers, leading to reduced depth of information processing (Johnson & Russo, 1984; Lynch & Srull, 1982). Thus, the predictive effect of compatibility on consumer behavioral intentions may vary in different contexts.

 

On the basis of the proposed research model (see Figure 1), we explored the possible moderating effect of compatibility on the relationships between cognition subdomains (social influence, innovation identification), affect subdomains (perceived sociability, perceived enjoyment), and conation subdomains (intention to purchase).

This study was approved by the Ethics Committee of Shaanxi University of Science and Technology. Participants provided informed consent and completed the survey anonymously through a Chinese platform called PowerCX (https://www.powercx.com). We collected 429 questionnaires between June and August 2024 and excluded 27 invalid surveys with too-brief completion times or identical responses, leaving 402 (93.71%) valid forms. The demographic characteristics of the respondents are displayed in Table 1.

We divided the questionnaire into three parts. The first part involved participants’ sociodemographic information; the second part required participants to watch a 2-minute video introducing the concept of virtual clothing, its methods of use, and forms of interaction; and the third part assessed the research constructs through participant responses. The measures in the third part were based on existing literature and adjusted to fit the unique attributes of virtual clothing and consumers’ perceived experiences. To enhance clarity and accuracy, the scale items were first translated into Chinese and then back-translated into English by two bilingual experts familiar with the research topic. Three industry experts reviewed the initial 18-item version of the questionnaire to evaluate its structure, validity, and relevance, and we then revised the items and tested them on a pilot sample of 50 participants with diverse ages, social backgrounds, and cultural settings. After reliability and validity tests, we confirmed the final version of the questionnaire. Each dimension was measured using three items (see Table 2). Respondents rated the items on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). 

We used Amos 24.0 to apply structural equation modeling, and employed SPSS 26.0 and Amos 24.0 for data analysis.

Given the gender imbalance in the sample, we conducted independent samples t tests, and the results showed that gender had no significant impact on the key variables (ps > .05). Therefore, gender is unlikely to have significantly affected the study results.

 

We evaluated the reliability and validity of the measurement model using four key parameters: standardized factor loadings, Cronbach’s alpha, convergent validity, and discriminant validity (Hair et al., 2021). First, we assessed factor loadings for reliability, with all exceeding the recommended threshold of .60. Then, we employed Cronbach’s alpha and composite reliability to assess the internal consistency of the scales, with all constructs exceeding the standard threshold of .70 (see Table 3).

We used average variance extracted (AVE) values to assess convergent and discriminant validity, where values greater than .50 indicate strong convergent validity, and discriminant validity is confirmed if the square root of the AVE of a construct is greater than its correlations with other constructs (Fornell & Larcker, 1981). In this study all constructs had AVE values exceeding .50 (see Table 3), and the square root of the AVE for each latent variable was greater than its correlations with other latent variables (see Table 4). This confirms that the measurement model met the established criteria for both convergent and discriminant validity.

Following the recommendations of Hair et al. (2021) and L. Hu and Bentler (1999), a model is considered to have a good fit to the data if the following criteria are met: χ²/df < 3, goodness-of-fit index (GFI) > .90, Tucker–Lewis index (TLI) > .90, comparative fit index (CFI) > .90, root-mean-square error of approximation (RMSEA) < .08. In this research, structural equation modeling confirmed a good fit for the model, χ²/df = 2.178, GFI = .947, TLI = .972, CFI = .979, RMSEA = .054. Table 5 presents the results of the hypothesis testing, with Hypotheses 1, 2, 3, 4, 5, 6, 7, 8, and 10 being supported, but Hypothesis 9 not receiving support. The validated research structural model is shown in Figure 2.

We tested the mediating effects of perceived enjoyment and perceived sociability using the bootstrapping method with 5,000 resamples. A mediating effect is considered significant if the bootstrapped 95% confidence interval does not include zero (Preacher & Hayes, 2004). The results in Table 6 show that Hypotheses 11, 12, 13, and 14 were all supported.

We conducted moderation effect analyses using Models 7, 14, 83, and 87 of the PROCESS macro (Hayes, 2022) to examine the stage-specific moderating effects of compatibility across distinct mediation pathways. The direct effect of innovation identification on intention to purchase was nonsignificant, so there was no need to test for the potential moderating effect of compatibility. In the social influence → intention to purchase path, the interaction between social influence and compatibility did not significantly predict intention to purchase, β = –.035, p = .109.

 

The moderated mediation effects are detailed in Table 7. In the innovation identification → perceived sociability  → intention to purchase path, the interaction term of innovation identification and compatibility did not significantly predict perceived sociability, β = –.019, p = .571. However, the interaction term of perceived sociability and compatibility significantly and negatively predicted intention to purchase, β = –.063, p = .002, weakening the indirect effect of perceived sociability. Likewise, in innovation identification → perceived enjoyment → intention to purchase, the interaction term of innovation identification and compatibility did not significantly predict perceived enjoyment, β = –.014, p = .667. However, the interaction term of perceived enjoyment and compatibility significantly and negatively predicted intention to purchase, β = –.041, p = .023, weakening the indirect effect of perceived enjoyment. In the social influence → perceived sociability → intention to purchase path, the interaction term of social influence and compatibility significantly and positively predicted perceived sociability, β = .057, p = .015, enhancing the indirect effect of perceived sociability. By contrast, the interaction term of perceived sociability and compatibility significantly and negatively predicted intention to purchase, β = –.069, p < .001, weakening the indirect effect of perceived sociability. In the social influence → perceived enjoyment → intention to purchase path, the interaction term of social influence and compatibility did not significantly predict perceived enjoyment, β = –.023, p = .304, whereas the interaction term of perceived enjoyment and compatibility significantly and negatively predicted intention to purchase, β = –.046, p = .007, weakening the indirect effect of perceived enjoyment. In the innovation identification → perceived sociability → perceived enjoyment → intention to purchase pathway, the interaction term between innovation identification and compatibility did not significantly predict perceived sociability, β = .019, p = .571. However, the interaction term between perceived enjoyment and compatibility significantly and negatively predicted intention to purchase, β = –.050, p = .003, weakening the indirect effect from perceived sociability to perceived enjoyment. In the social influence → perceived sociability → perceived enjoyment → intention to purchase pathway, the interaction term between social influence and compatibility significantly and positively predicted perceived sociability, β = .057, p = .015, thus enhancing the indirect effect from perceived sociability to perceived enjoyment. However, the interaction term between perceived enjoyment and compatibility significantly and negatively predicted intention to purchase, β = –.053, p = .002, weakening the indirect effect from perceived sociability to perceived enjoyment.

Next, we used further simple slope plots to examine how compatibility moderated the mediating effects of social influence on perceived sociability, perceived enjoyment on intention to purchase, and perceived sociability on intention to purchase. The results showed that at lower levels of compatibility (M – 1 SD), social influence significantly predicted perceived sociability, β = .393, p < .001, while at higher levels of compatibility (M + 1 SD), this effect was amplified, β = .541, p < .001 (see Figure 3a). Perceived enjoyment positively predicted intention to purchase at lower compatibility, β = .689, p < .001, but showed a slight attenuation at higher compatibility, β = .582, p < .001 (see Figure 3b). Similarly, perceived sociability positively predicted intention to purchase at lower compatibility, β = .589, p < .001, but this effect was attenuated at higher compatibility, β = .428, p < .001 (see Figure 3c).

This study deepens understanding of the role of social influence in promoting consumers’ intention to purchase virtual clothing. First, we found that social influence positively predicted virtual clothing consumers’ intention to purchase, which is consistent with previous research findings for other types of virtual products (Sambe & Haryanto, 2021; T. Zhou, 2019). Second, social influence indirectly predicted consumers’ intention to purchase through the mediators of perceived enjoyment and perceived sociability. This result is in line with the recent trend of socially driven consumer behavior regarding virtual products (Nivedhitha, 2023), further supporting the critical position of social influence in digital consumption environments and revealing its far-reaching role in shaping consumers’ emotional experiences.

 

We also found that innovation identification did not directly predict intention to purchase, which is inconsistent with existing research findings on physical clothing (Kaur et al., 2024). The result that innovation identification predicted intention to purchase only indirectly through enhanced perceived enjoyment and perceived sociability emphasizes that relying on innovativeness alone is not sufficient to motivate the emergence of consumer behaviors in virtual clothing consumption; rather, it requires a deeper connection with consumers through emotional and social experiences (B. Dai et al., 2020).

 

By analyzing the moderating effect of compatibility on the mediating role of affect, this study has provided a new perspective on virtual apparel consumer behavior and, at the same time, enriched cognition–affect–conation theory by enhancing understanding of the role of affect in consumer behavior intention. The study showed that the moderating effect of compatibility on the mediating role of affect dimensions (perceived sociability, perceived enjoyment) varied at different stages. In particular, when moderating the relationship between cognition (social influence) and affect (perceived sociability), higher, compared to lower, compatibility enhanced the mediating effect of affect reflections, thus contributing to intention to purchase. However, when moderating the relationship between affect (perceived sociability, perceived enjoyment) and conation (intention to purchase), high compatibility instead suppressed the mediating effect of perceived sociability and perceived enjoyment, suggesting that the influence of affect factors on intention to purchase was weakened in the high compatibility condition.

Our study found that the emotional dimension was the core factor driving consumers’ intention to purchase virtual clothing, with perceived enjoyment playing the strongest role. Therefore, brands and designers should focus on enhancing the emotional experience of virtual clothing by increasing interactivity, fun, and personalized design to strengthen consumers’ sense of enjoyment and entertainment. Additionally, by emphasizing the product’s social attributes and leveraging channels such as social media and virtual social platforms, brands can enhance consumers’ perception of social value, thereby effectively stimulating their intention to purchase.

 

Virtual apparel companies need to focus on the moderating effect of compatibility on consumers’ affect dimensions at different stages and find a balance between compatibility and affect factors. Our results lead us to believe that in the early stage of marketing, the high compatibility context, wherein consumers feel a fit with the virtual clothing product, the mediating effect of affect is strengthened. This can be enhanced through online communities, virtual events, and celebrity endorsements to enhance consumers’ social engagement and sense of belonging, which could lead to a positive affect response (perceived sociability) and influence their intention to purchase. In the later stages of formation of consumers’ behavior intention, the mediating role of affect factors may decrease in high-compatibility contexts, implying that consumers may turn to more rational factors, such as price, compatibility with the virtual environment, and compatibility with their needs. Thus, firms should pay attention to the actual value of their virtual apparel products. Companies need to carefully balance affect and rationality to ensure that their marketing strategies effectively combine the needs of both.

This research focused on cognition, affect, and conation variables and their interactions. However, other factors like price perception, ease of technology use, privacy, and security may also impact the formation of intention to purchase virtual clothing. Future research could introduce further relevant variables and construct more complex models to reveal the multidimensional factors affecting intention to purchase virtual clothing and improve the theoretical framework.

 

This study initially explored the moderated mediating effect of compatibility on perceived sociability and perceived enjoyment, focusing on segmental identification of the location and direction of the moderated mediation effect; however, we did not verify the synergistic effect of the moderated mediation effect through the integrated model. Compatibility may exhibit different mechanisms of action at the front end and back end of the mediating effect, suggesting that contextual factors or individual differences may influence the moderated mediation effect of compatibility. Meanwhile, the moderated mediation effect of compatibility on the overall pathway may also be affected by differences in the front-end and back-end moderated effects. Future research could explore these synergistic moderating effects at both points in combination with specific contextual variables (e.g., cultural background, work environment) or individual differences (e.g., personality traits, values) and adopt an integrated model to comprehensively test the overall moderated mediation effect and further reveal the moderated mediation mechanism of compatibility, so as to provide more prosperous theoretical foundations and empirical support for practical applications.

 

With the rapid development of technologies such as virtual reality and augmented reality, the design, functionality, and user experience of virtual clothing will continue to evolve. Future research could explore how technological advances affect consumer perceptions, emotions, and intentions and update theoretical models to adapt to changing market conditions and technological environments, providing more forward-looking theoretical support for companies to develop innovative product strategies and marketing programs.

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