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Massive open online course (MOOC) is an innovative educational model that has attracted widespread attention in recent years. Despite a growing number of registered users, many have given up continuously using MOOC platforms after the first-time user experience; thus, a high dropout rate has severely hindered the sustainable development of MOOC platforms. To address the problem, this study started with the quality factors of MOOC platforms and the confirmation of user expectations by integrating the D&amp;M ISS model and the expectation confirmation model into one, with the goal of identifying the factors that affect users’ continuance intention to use MOOC platforms. In this study, online questionnaires were distributed to Chinese users with experience in using MOOC platforms, and a total of 550 valid samples were recovered. In addition, the theoretical model was tested using structural equation modeling (SEM). The research results showed that there are three critical antecedents affecting the confirmation of user expectations for a MOOC platform, including information quality, system quality, and service quality, of which service quality has the greatest impact on users’ expectation confirmation. If user expectations for an MOOC platform are positively confirmed, the perceived usefulness of the platform as well as the satisfaction with it will effectively be improved. Moreover, perceived usefulness has been proven to be a critical factor affecting users’ continuance intention to use MOOC platforms, which is followed by user satisfaction. Compared to the original ECM, the integrated research model has delivered significantly improved explanatory power for users’ continuance intention. Hence, this study makes up for the insufficiency of ECM in explaining the factors affecting users’ expectation confirmation and provides theoretical support for MOOC platform developers.

Does MOOC Quality Affect Users’ Continuance Intention? Based on an Integrated Model