In recent years, the rapid advancement of artificial intelligence (AI) in the video sector has captured widespread attention. Despite the proliferation of AI video generation tools targeted at general consumers, there remains a gap in addressing the specialized requirements and advanced functionalities sought by industry professionals. This study aims to identify and overcome the barriers hindering the adoption of AI video tools in the Chinese video industry, thereby facilitating their seamless integration. The research unfolded in two phases employing a comprehensive methodology. Initially, we delineated the industry’s video usage standards, drawing upon both established norms and insights gleaned from seasoned industry experts through focus group interviews. These insights informed the formulation of semi-structured interview questions. Subsequently, in-depth semi-structured interviews were conducted with ten Chinese industry experts, leading to the identification of eight primary adoption barriers: innovation, market demand, technological maturity, cross-disciplinary collaboration, ethics and privacy, public acceptance, data security and copyright, and global perspectives and localization. In the second phase, a detailed questionnaire survey involving 401 Chinese industry practitioners validated these factors. A data analysis underscored the significant impact of these eight factors on industry adoption, particularly emphasizing technological maturity. Furthermore, exhaustive examinations and discussions were undertaken for each identified barrier. The findings of this study theoretically bridge the gaps in understanding the impediments to the application of AI video generation tools in the video industry. They offer valuable insights into the current application landscape and furnish pertinent suggestions for advancing technology promotion and development in the future. Ultimately, this research aspires to augment the integration and utilization of AI technology within the Chinese video production industry, thereby propelling its progress and development forward.

In recent years, research and applications related to the metaverse have garnered widespread attention in the field of online education. However, enhancing user experiences in metaverse learning remains a challenging issue. This study aims to explore how gamification enhances the metaverse learning experience by boosting learning motivation. In the first phase of the research, the relationship between gamification, learning motivation, and user learning satisfaction was examined. The results indicated higher user satisfaction with gamified metaverse learning experiences, with intrinsic and external regulations serving as mediating factors between gamification and learning satisfaction. In the second phase of the study, the five elements of gamification (challenge, reward, feedback, PBL, social interaction) were further validated for their role in enhancing learning motivation and, consequently, improving learning satisfaction. Notably, the rewarding element emerged as the most significant factor. These research findings hold practical significance for providers of metaverse learning experiences and the application of gamification in metaverse learning. They provide valuable insights for future research and practical implementation in this evolving field.

Poor medication adherence among older adults is a widespread problem worldwide. As the population ages, the design of smartphone medication management apps is critical to improving medication adherence among older adults. Taking the design of an elderly medication reminder APP as an example, this study proposes a sustainable design research method that integrates the KANO model, Analytic Hierarchy Process (AHP), Quality Function Deployment (QFD), and PUGH decision matrix. The method collects user demands through in-depth interviews, and applies the KANO model to classify these demands. The hierarchical structure of user needs is established by using AHP, and the priority is sorted according to the weight and importance determined by the judgment matrix. QFD is used to translate user needs into design requirements, and the house of quality matrix identifies key design requirements. Finally, design alternatives are evaluated using Pugh’s concept selection method. The results of this study demonstrate that the integration of KANO-AHP-QFD-PUGH can be effective as a sustainable optimal design approach for the user experience of a medication reminder application for the elderly. This integrated method not only facilitates innovative optimization and sustainability of application design methods but also provides valuable theoretical and practical insights for future drug-assisted design for elderly users.

With the rise of the metaverse, digital transformation is profoundly affecting the field of art exhibitions. Museums and galleries are actively adopting metaverse technologies to present artworks through virtual platforms, providing audiences with novel opportunities for immersive engagement and art experiences and shaping high-quality user experiences. However, the factors influencing user engagement in the metaverse art exhibition platform (MeAEP) remain unclear in the current research. This research combines the information systems success model (ISSM) and the hedonic motivation system adoption model (HMSAM) to construct a theoretical model that provides insights into the factors influencing MeAEP users’ intention to engage and their immersion behavior, with a focus on the sustainability of the art exhibition. We quantitatively analyzed 370 users that experienced MeAEP and analyzed the data and measurement model using SPSS 27 and partial least squares structural equation modeling (PLS-SEM). The results showed that information quality (IQ), system quality (SQ), and perceived ease of use (PEOU) significantly and positively influenced perceived usefulness (PU), curiosity (CUR), joy (JOY), and control (CON). PU, JOY, and CON have a positive and significant effect on Immersion (IM). Finally, PU, CUR, JOY, and CON had a positive effect on behavioral intention (BI). In conclusion, only one of the twenty hypotheses was not supported. The research findings not only enrich the academic and managerial theories related to the metaverse and art exhibition platforms, but also provide practical insights for administrators, developers, and MeAEP designers to create higher-quality and more immersive art content, as well as provide constructive ideas for the sustainability of art exhibitions to further enhance user experience.

In recent years, despite the widespread success of artificial intelligence (AI) across various domains, its full potential in the field of education, particularly in filmmaking education, remains largely untapped. The purpose of this study is to explore the application of AI-generated programs in filmmaking education to address existing shortcomings in curriculum design. We employed a comprehensive approach, starting with an extensive review of existing filmmaking courses and AI-recommended courses. Subsequently, two rounds of in-depth interviews were conducted, involving both experts and students, to gain profound insights. We utilized user journey maps to visualize the participants’ experiences and feedback, complemented by a mixed-methods analysis approach for a comprehensive data assessment. The study revealed that both the experts and the students derived positive benefits from AI-recommended courses. This research not only provides a fresh perspective on the practical applications of AI in filmmaking education but also offers insights for innovation in the field of education. Theoretically, this study establishes a new foundation for the application of AI in education. In practice, it opens up new possibilities for filmmaking education and promotes the development of cutting-edge teaching methods. Despite limitations in sample size and geographical scope, this study underscores the immense potential of AI in filmmaking education. It provides directions for future research to deepen our understanding of AI’s impact on education.

In the context of globalization, cross-cultural research is essential for understanding behaviors and values across different cultural backgrounds. The way audiences from diverse cultures interpret and accept film content significantly impacts the international dissemination and market performance of films. This study, grounded in Hofstede’s six cultural dimensions—power distance index (PDI), individualism vs. collectivism (IDV), uncertainty avoidance (UAI), masculinity vs. femininity (MAS), long-term vs. short-term orientation (LTO), and indulgence vs. restraint (IVR)—incorporates additional variables such as visual aesthetic appeal (VAA), narrative complexity (NCI), viewing motivation (VM), behavioral intentions (BIs), and brand loyalty (BL) to construct a multidimensional research framework. This framework aims to comprehensively examine the acceptance of American animated films among Chinese audiences and the cultural differences influencing such acceptance. Using structural equation modeling (SEM), this study analyzed the interrelationships between variables based on a sample of 507 participants with prior viewing experience. The findings reveal that different cultural dimensions significantly impact VM. PDI, UAI, and IDV exert significant negative influences on VM, with PDI being the most influential. Conversely, LTO and IVR do not demonstrate significant negative effects. In contrast, MAS, VAA, and NCI exhibit significant positive impacts on VM. Additionally, VM strongly influences audience acceptance, which, in turn, promotes the formation of BIs and repeated VM. This study extends the application of Hofstede’s cultural dimensions to the domain of cross-cultural media consumption, enriching the theoretical framework with additional dimensions and offering a novel perspective for cross-cultural research. Furthermore, the study uncovers the intricate interactions between cultural context and film content, proposing strategies to enhance the acceptance of cross-cultural films. These findings not only provide valuable insights for the production and marketing of animated films but also offer strategic guidance for filmmakers in diverse markets.