ABSTRACT. This study investigates the impact of AI-empowered co-creation, compared to traditional (non-AI) co-creation, on consumers’ willingness-to-pay (WTP). We examine this effect through the mediating roles of psychological ownership and perceived price fairness, with self-efficacy serving as a moderator. Utilizing multi-scenario experiments involving T-shirts,eco-bags,and shoes. We simulate real-world co-creation contexts to test these relationships. Our findings are expected to offer valuable insights for companies, highlighting how AI-empowered co-creation shapes consumer perceptions of fairness.

ABSTRACT. This study examines how the transparency of AI recommendation systems (trade-off AI transparency: high vs. low) affects consumers’ intention to use such systems, with a focus on the mediating role of procedural justice and the moderating effect of brand status (high vs. low). Drawing on procedural justice theory, this research proposes that high transparency can enhance perceived fairness in decision-making processes, thereby increasing users’ intention to use the system. Furthermore, it is expected that the positive effect of transparency on using intention via procedural justice will be stronger for high-status brands. This research highlights the importance of transparency and brand context in building trust and acceptance of AI systems.

ABSTRACT. Measuring CX is complicated because each individual experiences interactions with a brand, product, or service differently, because personal factors significantly influence how we perceive the world around us (Gorgoglione & Panniello, 2018). In the context of AR experiences and retail, several researchers, including Kumar (2022), have emphasized the need of investigating personal factors. One of these individual characteristics are the cognitive styles, also referred to as thinking styles (Kim et al., 2023). These are relatively stable strategies, preferences, and attitudes that determine an individual's typical modes of perception, memory, and problem-solving, as well as how consistently they encode and retrieve information (Tsianos et al., 2009). Consequently, the thinking style of individuals can influence how they perceive their environment and interact with it, thereby impacting their perceived CX. Various authors use different terminology and scales to describe and measure the thinking style of an individual, such as wholist-analytic, verbalizer-imager (Riding & Cheema, 1991), analytic-holistic (Choi et al., 2007), or field-dependent/independent (Witkin & Goodenough, 1977). However, field independent and field dependent thinking styles are analogous to the holistic (or wholistic) and analytic thinking styles. Analytic thinkers perceive objects as separate from their surroundings, excel in thinking restructuring and creativity, focus on individualism, and tend to show fewer negative emotions with mixed-quality services, while holistic thinkers view the world as interconnected, consider contexts, excel in interpersonal tasks, and rely more on external influences and emotional openness (Choi et al., 2007; Goodenough & Witkin, 1977; Kim et al., 2023; Miller, 2007).

ABSTRACT. With the rise of the internet and social media, brand communities have become essential for fostering engagement between brands and customers. While extensively studied in B2C (business-to-consumer) contexts, brand communities are also gaining traction in B2B (business-to-business) environments, particularly in IT sectors where they facilitate knowledge-sharing and networking. However, most B2B brand community research relies on B2C models, overlooking key B2B-specific factors. This study aims to compare participation intention in B2C and B2B brand communities and to figure out the difference between these. Using the Uses and Gratifications (U&G) framework (Katz et al., 1973), it examines motivational drivers and perceived values for community participation by using Multi-group SEM.

ABSTRACT. The advent of Industry 5.0 emphasizes human-centricity, sustainability, and resilience, leveraging advanced technologies such as collaborative robots, digital twins, and extended reality. While its theoretical benefits are well-documented, empirical methods to measure Industry 5.0 adoption remain underdeveloped. This study addresses this gap by introducing an Industry 5.0 score to quantify firms' alignment with its principles, including sustainability, human-centric innovation, and resilience. Additionally, it explores the impact of Industry 5.0 adoption on Myopic Marketing Management (MMM) behaviors, which prioritize short-term financial outcomes over long-term investments. The moderating role of CEO leadership styles, particularly regulatory focus and regulatory mode complementarity is examined to understand their influence on balancing short- and long-term strategic priorities. Employing text mining techniques and financial data, this research provides a robust framework for understanding how leadership dynamics and strategic orientations influence firms' ability to transition toward sustainable industrial practices.

ABSTRACT. This study empirically investigates the effects of influencer-generated content characteristics (creativity, informativeness, and entertainment) on purchase intention by considering the information processing method (vicarious expression) and parasocial relationship (PSR). A questionnaire from 598 followers was analyzed using partial least squares structural equation modeling (PLS-SEM). Various content characteristics affect purchase intention, vicarious expression, and PSR differently. The result considers how content processing (method and characteristics) facilitates the construction of relationships. The relationship shows a mediation role between content characteristics and purchase intention, emphasizing the strong persuasive effect in influencer marketing.

ABSTRACT. Will high-yield luxury tourism contribute to sustainable development? Assuming that luxury tourism experiences can be integrated into rural tourism environments, this study aims to divide the high-income luxury tourist market based on the degree of emphasis placed on various aspects of luxury tourism experiences in the context of rural tourism. It will further explore the attributes that tourist destinations need to meet the demands of the tourism niche market. In doing so, unique models of tourism destination development may be developed which effectively target and satisfy each of these segments. This study adopts three mixed methods, including three stages. Develop a scale for luxury tourism experience in Phase 1. The second phase will collaborate with luxury tourism operators in Australia and China to measure the tourist experience and satisfaction of tourist destinations through quantitative surveys. Structural equation modeling analysis was used for data analysis in the first and second stages. In the third stage, cluster analysis is used to rate the importance of the data from the second stage. Then analyze the significant and valuable attributes of each segmented market, sort and analyze them, and develop a prototype rural tourism destination model.

ABSTRACT. In recent years, with the rise of social media platforms and the evolution of content ecosystems, the Creator Economy has rapidly emerged as an important driver of the global digital economy. In this system, individual creators build a new value distribution network by creating, disseminating, and monetizing content through platforms. At the same time, Generative AI, as a new generation of core technology, is profoundly changing the operating logic and content production model of the creator economy with its breakthrough capabilities in the generation of multimodal content such as text, images, and videos. In the fashion industry, generative AI is widely applied in trend prediction, design generation, personalized recommendations, and virtual influencers, driving brands to transition from traditional marketing to a new paradigm of intelligent marketing centered on data-driven and human-machine collaboration. Meanwhile, the interaction patterns between creators, platforms, and consumers are also undergoing profound changes. However, the academic community is still in the early stages of exploring the mechanism of generative AI in the creator economy, especially lacking systematic research on the consumer perception path and brand value construction mechanism in the application scenario of the fashion industry. On the one hand, existing literature mostly focuses on AI technology itself or the platform perspective, with little in-depth discussion of how generative AI influences consumer brand perception, attitudes, and behavioral responses through content generation and interaction mechanisms. On the other hand, the types of perceived value and trust formation mechanisms of consumers when faced with AI-generated content, as well as their driving paths for brand equity and word-of-mouth communication, are not yet clear. Additionally, in the context of highly algorithmic content and the virtualization of creator identities, how consumers discern content sources and establish authentic emotional connections with brands poses challenges to traditional marketing theories. Therefore, this study takes generative AI as the core variable, focuses on its application pathways in the creator economy, and explores its comprehensive impact on fashion brand marketing, consumer participation, and value cognition. This study takes “how generative AI reshapes the value logic of the creator economy” as its core question and analyzes its typical applications in the fashion industry to reveal its impact on brand content marketing and consumer participation mechanisms. The study adopts an exploratory sequential mixed methods approach and is divided into two phases. Study 1 involves expert interviews to identify the core application pathways and influence mechanisms of generative AI. Study 2 designs consumer questionnaires and conduct empirical validation based on the findings from study 1. Study 1 conducted in-depth interviews with 20 experts and practitioners from the fields of AI technology, fashion marketing, and the creator economy. The aim was to identify the core application areas of Generative AI in the creator economy, understand its functional characteristics, value impact, and potential limitations in practical applications, with a particular focus on its specific implementation pathways in the fashion industry. The study focused on examining the mechanisms by which generative AI reshapes the relationship between creators, consumers, and platforms in the creator economy. Study 1’s results confirmed that generative AI has significantly lowered the technical threshold for content creation, enabling more people without professional backgrounds to participate in content creation and dissemination, forming a new trend of “everyone is a creator.” Professional creators have used generative AI to improve their creative efficiency, achieving multimodal content output, style control, and batch generation. In the fashion industry, generative AI not only assists in designing sketches and trend charts, but also promotes the high realism of visual content and product images, improving the integration efficiency of creation and marketing. From the consumer's perspective, the application of generative AI has, to a certain extent, improved the efficiency and consistency of the user experience in accessing content, especially in terms of personalized recommendations, matching suggestions, and brand interaction, bringing new value perceptions. However, interviews show that some consumers have doubts about the authenticity, interpretability, and emotional resonance of AI-generated content. Especially in situations involving brand personas, emotional expression, and creator relationships, this “non-human” source of content has led to trust barriers and a sense of psychological distance. When faced with AI-generated brand stories or fashion content, consumers tend to question the authenticity of the values behind them, which affects their attitude toward the brand and their willingness to engage. Meanwhile, platforms have further consolidated their dominant position in traffic allocation and value capture through AI algorithms, gradually forming a new content ecosystem centered on “human-machine co-creation.”