Virtual reality (VR) tourism can become a game-changer in tourism industry. It has been recognized as an effective way to manage tourist load and preserve the ecological balance at environmentally fragile destinations. As the “digital generation”, Generation Z members provide a huge market for VR tourism. However, the behavioral outcomes of Generation Z in the context of VR tourism have been scarcely explored, especially from a perspective of perceived value. Thus, this research particularly focuses on Generation Z. A conceptual model is developed based on Consumption Value Theory (CVT) to investigate the determinants behind user satisfaction and its impact on word-of-mouth (WOM) and continuance intentions. Furthermore, this study explores the moderating role of technology optimism in the relationship between perceived value and user satisfaction. Through the analysis of 509 samples, this research indicates that functional value (immersive presence and convenience), emotional value (enjoyment), epistemic value (curiosity and novelty), social value (online social interaction), and conditional value (the overcrowded form of tourism) are positively related to user satisfaction with VR tourism. In addition, user satisfaction is a predictor of WOM and continuance intentions. Moreover, technology optimism greatly moderates the influences of functional value, social value, and conditional value on user satisfaction. The findings in this research expand the theoretical application of CVT and provide a new perspective to explore tourists’ behavioral outcomes in the context of VR tourism. In addition, this research expands the research boundary of technology optimism and provides valuable insights for designers and managers to focus on influential values.

AI-based chatbot, a typical product of human–computer interaction (HCI), is widely employed by tourism service providers. However, there is a lack of research on the determinants that explain why customers continuously use chatbots for tourism. Based on the Unified Theory of Adoption and Use of Technology 2 (UTAUT2), the Theory of Perceived Risk (TPR), anthropomorphism, and personalization, this research developed an integrated model to investigate the determinants behind customers’ continuance intention to use chatbots for tourism. In addition, the moderating role of gender differences in the relationships between determinants and continuance intention was tested. The analysis based on a sample of 613 users highlighted the positive effects of performance expectancy, social influence, habit, anthropomorphism, and personalization. However, the findings showed that time risk and privacy risk have negative influences. Although the moderating test did find two differences due to gender, many other relationships showed no differences between male and female.

The global spread of COVID-19 has caused a huge number of confirmed cases and deaths, which in return leads to a plethora of mental disorders across the world. In order to address citizens’ psychological problems, government agencies in many countries have employed AI-based chatbots to provide mental health services. However, there is a limited understanding of the determinants affecting citizens’ user experience and user satisfaction when mental health services supported by chatbots are provided. Thus, based on the Theory of Consumption Values (TCV), this study proposes an analytical framework to investigate the factors that are important to citizens’ user experience and user satisfaction when they interact with mental health chatbots. Analysis of data collected from 295 chatbot users in Wuhan and Chongqing reveals that personalization, enjoyment, learning, and condition are positively related to user experience and user satisfaction. However, voice interaction fails to devote to citizens’ user experience and user satisfaction. Thus, government agencies and their AI service contractors should enhance the functions and systems of mental health chatbots to ensure citizens’ user experience and user satisfaction. Also, they should more positively promote the use of mental health chatbots during the public health emergency.

Urban–rural divide becomes an obstacle to the development of e-government in China. This research devotes to promoting the adoption of e-government in China. It investigates the attitudes of urban residents versus rural residents toward e-government use in Chongqing, one of most important municipalities of China which is fraught with a serious urban–rural divide. A research model is created to assess the differences between urban and rural residents according to previous literatures and theories. A Structural Equation Model approach is employed to examine the research model. The survey data were collected from 596 urban residents and 477 rural residents in Chongqing. The results reveal that there are differences between urban and rural groups. Many enabling factors and inhibiting factors in previous studies, such as perceived behavioural control and resistance to change, can positively influence rural residents’ intentions to use but fail to exert great effects on urban residents’ motivations. Thus, it is necessary for government agencies in China to take actions based on those significant enabling factors and inhibiting factors to promote e-government acceptance. In addition, it is also necessary to conduct deeper research on e-government acceptance of urban residents in China.

The growing use of social media leads to a growing public engagement with professional questions and issues. During the period of Covid-19 pandemic, a large number of non-expert people participate in the discussion on the virus and official intervention process. These people are more likely to be influenced by Covid-19 disinformation and lose their trust in government. As one of the first countries suffered from Covid-19, China has been faced with this serious "infodemic". In this context, government agencies in China adopted the four-stages strategies (immediate response, diagnosis, reforming interventions and evaluation) on social media to weaken the impact of disinformation and repair public trust. Based on the structural equation model (SEM), this study constructs a research model to statistically test the roles of the four-stages strategies on public trust repair in China. The findings reveal that each media strategy shows positive impact on citizens' perception of their government. From the lesson in China, it is suggested that government agencies need constantly cooperate with a wide range of social organizations to ensure the greater voice on social media. Also, it is necessary to regularize the four-stage strategies on social media as a whole system to mitigate the spread of disinformation and improve public attitudes toward government.