Cheng-Min Chao

Background: Mobile learning provides nurses with a flexible and convenient approach to continuing education and professional development. As nurses are required to continuously update their knowledge and skills, understanding the factors influencing their intention to adopt mobile learning is important for improving nursing education and management practices. Methods: This study developed an integrated research model based on the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2), the Information System Success Model, and individual psychological factors, including mobile self‐efficacy and technology anxiety. Data were collected from 173 nurses. Structural equation modeling was used to examine the determinants of nurses’ behavioral intention to adopt mobile learning. Results: The findings showed that attitude, facilitating conditions, and habit were significant positive determinants of behavioral intention, whereas effort expectancy had a negative effect on behavioral intention. Performance expectancy and mobile self‐efficacy were significant predictors of attitude. Effort expectancy and information quality had significant positive effects on performance expectancy, whereas mobile self‐efficacy and technology anxiety had negative effects on performance expectancy. In addition, system quality was identified as a key determinant of effort expectancy. Conclusion: The results indicate that nurses’ intention to adopt mobile learning is influenced by technological, psychological, and system‐related factors. In particular, attitude, facilitating conditions, habit, performance expectancy, information quality, and system quality play important roles in shaping acceptance of mobile learning. Implications for Nursing Management: Healthcare administrators and nursing managers should improve system quality, provide sufficient technical support, and strengthen nurses’ confidence and positive attitudes toward mobile learning. These strategies may enhance nurses’ acceptance of mobile learning and support more effective continuing nursing education.

Circular economy products are one of the solutions that can help solve the current environmental crisis and consequently achieve environmental sustainability. The theory of planned behavior (TPB) is the most important social psychological theory to explain individual purchasing behavior. However, the theory lacks a consideration of emotions, green altruism, and other factors. In order to address the research gap, this study proposes and tests a new theoretical model that incorporates variables such as emotions, green altruism, and the willingness to be environmentally friendly (WEF) into its extended model based on the TPB framework, in order to investigate the determinants that have an effect on Taiwanese consumers' purchase intention toward circular economy products. This study also uses multi‐group analysis (MGA) to analyze the moderating effects of WEF on its new theoretical model. It collected data from 387 Taiwanese consumers and analyzed the data using partial least squares (PLS). The research results showed (1) emotions, attitudes, green altruism, and perceived behavior control have a positive effect on consumer purchase intention toward circular economy products; (2) emotions have a positive effect on attitudes, green altruism, subjective norms, and perceived behavior control; and (3) groups with different levels of WEF have significant differences on consumer purchase intention toward circular economy products, in terms of emotions, attitudes, and green altruism. The results of this study can provide a reference for manufacturers and public policy makers to understand how consumers' emotions and green altruism can affect the decision‐making process to making purchase of circular economy products.

With the ease of using information technology tools, the explosive growth of smartphone applications (apps), and the rise of learning communities on social media, the acceptance of learning communities has become one of the most significant challenges for higher education institutions in Taiwan. In order to better understand teachers’ collaborative performance inlearning communities, this study employs the cognitive dimension (opportunism) andinternal tension dimension (e.g. rising expectation, relationship burden) as restrictive factors; on the other hand, it uses emotional support, sense of belonging, and interpersonal altruism as facilitating factors; and community interaction, relationship performance, and collaborative performance as endrogenous factors. With a cross-sectional survey method and a quantitative approach, this study further dives into the collaborative performance of professional learning communities. A total of 157 teachers (87 male and 70 female) were surveyed, and a structural equation modeling approach was used. It was found that social media learning communities have done better than previous courses of field learning in unrestraining learning styles and increasing the breadth of knowledge. Facilitating and restrictive factors led to the rearrangement of the entire knowledge contribution process, enabling new configurations of individuals, members, and community. Moreover, community interactions are important drivers of relationship and collaboration performance supported by empirical data. The findings offer guidelines for policymakers and educators who evaluate teachers’ collaborative performance and relationship performance to promote teaching efficiency and effectiveness by incorporating cyberethics in educational activities.

Followed by the fast developments in Internet of Things (IoT), artificial intelligence (AI) technologies, utilizing cloud architecture and big data, have been integrated into various aspects of our daily lives. Such an integration results in high levels of convenience, comfort, and energy savings. Deploying such new technologies benefits the elevator industry as well. Intelligent elevator with energy control schemes can improve the energy efficiency of eco-friendly applications. The purpose of this study is to examine the factors that affect the intelligent elevator adoption of Taiwanese people using the extended unified theory of acceptance and use of technology (UTAUT 2) model, which considers factors such as environmental consciousness, artificial intelligence optimism, attitude, and perceived quality. A well-structured face-to-face survey is performed to obtain data from the consumers living in central Taiwan. The data acquired are analyzed via structural equation modeling using the partial least squares method. The analysis results indicate that attitude, habit, performance expectancy, effort expectancy, and perceived quality are important factors that affect the behavioral intentions of consumers when adopting new technologies, such as an intelligent elevator. However, facilitating conditions adversely affect the behavioral intentions. In addition, environmental consciousness and artificial intelligence optimism are crucial factors that affect performance and effort expectancies, whereas the latter two contribute positively to attitude. The findings of this study supplement existing literature regarding the behavioral intentions for adopting intelligent elevators. Finally, the theoretical and practical significances of this research study are discussed.

Human activities are important causal factors driving global warming and environmental degradation. Nowadays, consumers have become more aware that their consumption patterns are one of the main causes of environmental damage, bringing attention to various environmental issues. In this context, sustainable products (e.g., green products) are becoming increasingly popular. This study proposes an extended model of goal-directed behavior by including pollution avoidance intention and willingness to be environmentally friendly to offer a more comprehensive explanation of the decision making process of college students’ green purchase behavior. A structured questionnaire survey was made to gather data from 503 participants in Taiwan before partial least squares structural equation modeling was used to examine the sampled data and analyze the research hypotheses. The findings indicate that (1) anticipated emotions, perceived behavioral control subjective norms, attitudes, and are the key factors of forming desires, which, in turn, influence pollution avoidance intention; and (2) willingness to be environmentally friendly, perceived behavioral control, and pollution avoidance intention are crucial to college students’ green purchase behavior. Furthermore, desire serves as an essential mediator and has the strongest effect on pollution avoidance intention. The discoveries of this research are expected to bring better understanding of the decision-making processes behind college students’ green purchase behavior.

The purpose of this study was to develop and empirically test a model for predicting the key factors affecting nurses’ behavioral intention to use mobile learning (m-learning). We explored behavioral intention from users’ perspectives by applying an extended unified theory of acceptance and use of technology (UTAUT) model with the addition of information quality, system quality, technostress, and satisfaction. We conducted a survey of the district and regional hospitals in central Taiwan. Data were derived from 434 respondents. Structural equation modeling was applied to analyze the causal effects of 15 hypothesized predictive factors. We determined that satisfaction, social influence, performance expectancy, facilitating conditions, and effort expectancy positively impacted nurses’ behavioral intention to use m-learning. In addition, technostress was a negative antecedent of effort expectancy. Information quality and system quality had significantly positive effects on satisfaction, performance expectancy, and effort expectancy. This study provides hospital managers with a reference when assessing future developments and informs approaches to promote m-learning.

As social entrepreneurial intention has received increasing attention from scholars and practitioners, no clear conclusions have been drawn regarding antecedent or external factors that influence social entrepreneurial intention. This study aims to develop a structural model to shape the social entrepreneurial intention of business administration students, which involves the theory of planned behavior (i.e., attitudes, subjective norms), social capital, individual environmental responsibility, and individual absorptive capacity (i.e., potential absorptive capacity and realized absorptive capacity). Furthermore, this study regards potential absorptive capability as a multi-dimensional construct of a higher-order structure. The participants were students from business administration colleges/universities (including general universities and science and technology universities) in Taiwan. The empirical data from 969 participants were analyzed using Smart PLS 3.0 to obtain the results. The results revealed that: (1) social capital had a significant positive effect on attitudes and subjective norms; (2) attitudes, subjective norms, individual environmental responsibility, and realized absorptive capability had a positive effect on social entrepreneurial intention; however, social capital and potential absorptive capability had a negative effect. The results were discussed, and some specific recommendations for practitioners of business administration education were proposed.

This study developed and empirically tested a model to predict the factors affecting patients’ behavioral intentions to use a mobile health education website. It explored the behavioral intention to use a mobile health education website from the perspective of consumers by extending the Unified Theory of Acceptance and Use of Technology 2 model with the addition of mobile self-efficacy (M-SE), use motivation, and mobile literacy as moderators. For this purpose, variance-based structural equation modeling was used to analyze data collected from a sample of 1,649 patients at a hospital in Taoyuan, Taiwan. Partial least squares regression was used for model and hypothesis testing. The results revealed that (1) performance expectancy, effort expectancy, social influence, facilitating conditions, and habit were key predictors of the behavioral intentions of patients to use a mobile health education website; (2) M-SE had positive associations with effort expectancy; (3) use motivation was a significant determinant of both performance expectancy and effort expectancy; and (4) mobile literacy had a significantly negative moderating effect on the relationship between performance expectancy and behavioral intention. Our findings serve as a reference for the promotion of mobile health education in hospitals.

In recent years, online gaming and cyber pornography have become problematic activities among Internet users. When individuals immerse themselves in these activities, the experience of flow can negatively influence users’ physical and mental health and interpersonal relationships. Thus, this study analyzed the mediating roles of self-consciousness and peer relationships in the relationships between online gaming, cyber pornography, and physical and mental health. We obtained data from fifteen senior high schools in Taiwan (N = 1838 students; first year, 996 students, and second year, 842 students) by conducting a 2-year longitudinal survey. Statistical analyses were performed using structural equation modeling. The results indicated that adolescents’ online gaming was positively associated with their physical and mental health; however, it was negatively associated with their self-consciousness. In addition, when they became absorbed in cyber pornography, they lost track of time and lost self-consciousness, and it influenced their peer relationships. Self-consciousness and peer relationships mediated the relationships between cyber pornography and participants’ physical and mental health. We identified relationships between online gaming, cyber pornography, elements of flow, and physical and mental health. The findings of this research can offer guidelines for policy makers and educators who evaluate adolescents’ Internet use and behavior to provide proper access to Internet use and promote by building a healthy Internet environment in educational activities.