This study extends the Technology Acceptance Model (TAM) by incorporating relationship quality as a mediator to construct a comprehensive framework for understanding the influence on continuance intention in the hospital e-appointment system. A survey of 334 Taiwanese citizens who were contacted via phone or the Internet and Structural Equation Modeling (SEM) is used for path analysis and hypothesis tests. The study shows that perceived ease of use (PEOU) and perceived usefulness (PU) have significant influence on continuance intention through the mediation of relationship quality, consisting of satisfaction and trust. The direct impact of relationship quality on continuance intention is also significant. The analytical results reveal that the relationship between the hospital, patients and e-appointment users can be improved via enhancing the continued usage of e-appointment. This paper also proposes a general model to synthesize the essence of PEOU, PU, and relationship quality for explaining users' continuous intention of e-appointment.

In addition to the rapid development of global information and communications technology (ICT) and the Internet, recent rapid growth in cloud computing technology represents another important trend. Individual continuance intention towards information technology is a critical area in which information systems research can be performed. This study aims to develop an integrated model designed to explain and predict an individual’s continuance intention towards personal cloud services based on the concepts of technology readiness (TR) and the unified theory of acceptance and use of technology 2 (UTAUT2), moderated by gender, age, and experience of personal cloud services. The key results of the partial least square test largely support the proposed model’s validity and the significant impact of effort expectancy, social influence, hedonic motivation, price value, habit, and technology readiness on continuance intention towards personal cloud services. In addition to providing symmetric theoretical support with the proposed model and transforming the individual characteristics of TR into UTAUT2, this study could be used to enhance and analyze users’ adoption of personal cloud services and also increase the symmetry of the model’s explanation and prediction. The findings from this research contribute to providing practical implications and academic resources as well as improving our understanding of personal cloud service applications.