User Continuance Intention of Chatbot in Telemedicine Applications: An Integration of IS Success Model and Perceived Justice

Telemedicine service providers utilize chatbots to help people understand their health or to handle user complaints. While chatbots can provide many benefits such as high availability and quick response, the success of this technology depends on its continued usage. This study discusses the factors that influence users to continue using chatbot services in telemedicine applications by integrating the IS success model and the perceived justice concept. Factors that will be analyzed include information quality, service quality, system quality, distributive justice, procedural justice, interactional justice, perceived usefulness, satisfaction, trust, and continuance intention. We collect data using a questionnaire involving 223 respondents who have used telemedicine applications in Indonesia. To analyze data, we used Structural Equation Modeling-Partial Least Square. Based on the results, service quality and interactional justice in chatbots have the greatest impacts on continuance intention because both affect perceived usefulness and satisfaction, while the distributive justice factor did not affect continuance intention. The results of this study are expected to provide recommendations to improve the quality of chatbots in telemedicine applications in Indonesia.