With the deepening of population aging in China, chronic diseases are a major public health concern that threatens the life and health of nationals. Mobile health or mHealth can effectively monitor chronic diseases, which holds vital significance to the alleviation of social pressure caused by aging. To patients with chronic diseases, mHealth cannot give full play to its value, only when it is used in the long term. However, there is not yet research exploring mHealth continuance intention from the perspective of elders with chronic diseases. So, this research represents the first attempt to empirically analyze mHealth continuance intention from the perspective of elders with chronic diseases. The purpose of this research is to make up the research gap of the mHealth field and to put forward theoretical and practical implications based on research results. To obtain research data, a questionnaire was conducted. A total of 926 copies were collected online and 527 copies were collected offline. The structural equation model (SEM) was used for data analysis. Research results suggest that confirmation can significantly influence satisfaction, performance expectancy and effort expectancy. Meanwhile, confirmation and performance expectancy can significantly influence satisfaction. Additionally, effort expectancy, performance expectancy, social influence and facilitating conditions can directly and significantly influence continuance intention. Among them, performance expectancy can directly influence continuance intention in the most significant way. This research provides solid evidence for the validity of the integrated model of ECM-ISC and UTAUT in the mHealth field, which can be a theoretical basis for mHealth operators’ product R&D.

Due to the outbreak of COVID-19, many people have to accept remote working. However, as COVID-19 has been effectively controlled in China, remote office services provided by enterprise social networks (ESNs) is no longer a necessary choice of users. There has not yet been any referential research for ESN enterprises concerning how to encourage users willing to use ESNs continuously. Therefore, the purpose of this research is to identify the critical factors of ESN continuous usage intention to make up the research gap of ESN continuous usage intention and to help enterprises address the issue of sustained growth. This research combines elements of the task technology fit (TTF) model and D&M information systems success (ISS) model, explaining the continuous usage intention of ESN users. The empirical analysis results are based on the sample data of 668 Chinese respondents with experience in ESNs use and analyzed using structural equation modeling (SEM). Results show that task technology fit, performance expectancy and the satisfaction degree have a significant influence on continuous usage intention of ESNs. The research findings can provide the theoretical basis for sustained development and follow-up research of the ESN industry.

As the national awareness of health keeps deepening, online health communities (OHCs) have achieved rapid development. Users’ participation is critically important to the sustainable development of OHCs. Nevertheless, users usually lack the motive for participation. Based on the social capital theory, this research examines factors influencing users’ participation in OHCs. The purpose of this research is to find out decisive factors that influence users’ participation in OHCs, enrich the understanding of users’ participation in OHCs, and help OHCs address the issue of sustainable development. The research model was empirically tested using 1277 responses from an online survey conducted in China. Data was analyzed using the structural equation modeling (SEM). We found informational support and emotional support to have significant direct effects over the structural capital, relational capital and cognitive capital of OHCs. Meanwhile, it is observed that relational capital and cognitive capital degree have a significant influence on knowledge acquisition and knowledge contribution of OHCs. For researchers this study provides a basis for further refinement of individual models of users’ participation. For practitioners, understanding the social capital is crucial to users’ knowledge acquisition and knowledge contribution that achieve high participation in OHCs.