Abstract
BACKGROUND: Online healthcare platforms (OHPs) promote the accessibility of health services while integrating online and offline service delivery. Continuous adoption of these platforms can reduce the information asymmetry between patients and healthcare providers. However, existing study has rarely focused on how the network externalities of these platforms influence patients' continuous adoption. Expectation Confirmation Model (ECM) explains the continuous behavior after initial adoption and reveal the factors influencing satisfaction and continuous adoption intention. Few studies have integrated network externalities with the ECM to understand patients' continuous adoption of OHPs. OBJECTIVE: This study aims to explore what factors affect the continuous adoption of OHPs based on an extension to the ECM and network externalities. We propose a comprehensive model for the continuous adoption of OHPs by patients with chronic diseases. We extend the conceptual framework by incorporating constructs related to perceived value, habits, and switching costs. METHODS: This study utilized a web-based survey to collect data from participants in China. We selected a sample of individuals who had experience with OHPs using a random sampling method. This method ensured that participants was randomly chosen from a pool of patients without any regional bias. A total of 568 questionnaires were collected and 518 valid questionnaires were obtained. Structural equation modeling was applied to assess the relationships among the constructs. Hierarchical regression analysis was utilized to examine the moderating effects, while the mediating effects were investigated using the bootstrapping approach. RESULTS: Direct network externality had significant positive impacts on the confirmation (β = 0.232, p < 0.001) and perceived value (β = 0.167, p < 0.010). Cross network externality had significant positive impacts on confirmation (β = 0.307, p < 0.001) and perceived value (β = 0.120, p < 0.05). Indirect network externality had significant positive impacts on confirmation (β = 0.169, p < 0.010) and perceived value (β = 0.270, p < 0.001). Confirmation had a significant positive impact on perceived value (β = 0.205, p < 0.001) and satisfaction (β = 0.508, p < 0.001). In addition, satisfaction had a significant positive impact on continuous adoption intention (β = 0.579, p < 0.001). Continuous adoption intention had a significant positive impact on continuous adoption behavior (β = 0.547, p < 0.001). Confirmation and perceived value significantly mediate the relationship between network externalities and satisfaction. Moreover, both confirmation and perceived value enhance continuous adoption intention by positively influencing satisfaction, which serves as a mediator. Additionally, confirmation directly influences satisfaction through the mediating role of perceived value. Habits and switching costs positively moderate the relationship between continuous adoption intention and behavior. CONCLUSIONS: This study contributes by expanding the incorporation of network externalities into the ECM. Results enrich the existing literature on the continuous adoption of professional online platforms.