| With the continuous deepening of "Healthy China" strategy and the impact of COVID-19,leading to a tremendous growth of China’s online healthcare platforms.As a new type of medical service supply platform,the online healthcare platform provides a good "bridge" for its key bilateral users,doctors and patients to obtain online medical information and services,and enables them to communicate and interact with each other more easily.However,the current online healthcare platforms are facing a dilemma of adoption by doctors and patients.On the one hand,the online activity of doctors is not high;on the other hand,both the adoption rate of patients and their willingness to continue to adopt are low.The influencing mechanism of doctors and patients on the adoption of online healthcare platforms remains to be explored.Although the research on online healthcare platforms has attracted the attention of scholars at home and abroad in recent years,the discussion of the factors that influence users to adopt online healthcare platforms is neither systematic nor comprehensive.The research,based on the doctor-patient bilateral perspective,that takes into account the influence of online platforms’ own network externalities is limited.Based on the analysis of online healthcare platforms,network externalities,user-generated content and user technology adoption and other related theories,this paper adopts empirical research methods such as econometric analysis,questionnaire surveys,and structural equation modeling to try to explore the relationship of externalities between doctors and patients,construct the regression and adoption models of doctors and patients,systematically discusses the influencing mechanism of platforms’ adoption by doctors and patients,which supplements the research gaps in the fields of medical and health,information system technology,and user adoption behavior.At the practical level,it will also provide specific suggestions for platform managers,doctors and patients,which will help promote the adoption of doctor-patient users and achieve the long-term and stable development of online healthcare platforms.Through related theoretical research,as well as the collection,analysis and inspection of data,the main innovative conclusions obtained in this paper are as follows:(1)This paper explores the internal operating mechanism of platforms’ direct network externality,cross network externality,and indirect network externality in different contexts,and analyzes the network externality relationship between doctors and patients in the specific field-online healthcare platforms.It is believed that network externalities will accompany the whole process of doctor and patient users’ adoption of platforms,its role or impact cannot be ignored.(2)Based on network externalities and user-generated content,this paper uses "Good Doctor Online" platform as an example to empirically explore the effects of user-generated content on doctors’ activity and the heterogeneous impact among the groups of doctors who diagnose and treat different serious diseases under network externalities.The results show that the non-price factors and price factors from online healthcare platform generated by doctor and patient user-generated content will affect the activity of doctors,and there are certain differences in the impact of the activity of doctors who diagnose and treat diseases of different severity.In addition to the negative impact of price factors,the positive feedback effect of non-price factors will promote the increase in the supply of online doctor services and have a significant positive impact on the adoption of online doctors.Incentives and medical titles have a greater impact on the activity of doctors who diagnose and treat serious diseases;online word-of-mouth,responsiveness,involvement,and service pricing have a greater impact on doctors who diagnose and treat mild or moderate diseases.(3)Based on different types of network externalities and modified Technology Acceptance Models(TAM),combined with personal perception factors(perceived risks and perceived disease threats)of patient users,the initial adoption behavior model for patients on online healthcare platforms is constructed.The results show that the three different dimensions of network externality(direct network externality,cross network externality,and indirect network externality)can positively and significantly affect the perceived usefulness,perceived ease of use,initial adoption intention and negatively predict perceived risks.Secondly,perceived usefulness,perceived disease threats,and perceived ease of use can all positively affect the initial adoption intention of the patient user,while perceived risk negatively affects the initial adoption intention,but its impact is greater than the first three.In addition,it verifies the partial mediation effect of perceived usefulness,perceived ease of use,and perceived risk and the complete mediation effect of the initial adoption intention,and discovers that patients with different education levels will have significant differences in their initial adoption of online healthcare platforms,while other demographics have no significant impact on their initial adoption behavior.(4)Based on different types of network externalities and modified Expectation Confirmation Model-Continuous use of information technology(ECM-ITC),combined with patients’ perceived value,and by using the habit and switching costs as the moderating variables in the process of patients’ transition from continuous adoption intention to continuous adoption behavior,the continuous adoption behavior model for patients on online healthcare platforms is constructed.The results show that the three different dimensions of network externality(direct network externality,cross network externality,and indirect network externality)can significantly and positively affect the degree of expectation confirmation and perceived value.It can be seen that cross-network externalities have a greater impact on expected confirmation,while indirect network externalities have a greater impact on perceived value.Secondly,the degree of confirmation of patient users’ expectations will also significantly and positively affect their perceived value and satisfaction with online medical platforms,which will further positively affect their intention to continue to adopt,thereby promoting continuous adoption behavior.However,the impact of perceived value on satisfaction is not significant.In addition,it verifies the positive moderating effect of habits and switching costs between continuous adoption intention and continuous adoption behavior,and discovers that in the continuous adoption stage,patients’ adoption behavior will not be significantly different due to their demographics and other characteristics.Finally,there are 30 figures and 40 tables in this dissertation,and 187 reference documents are referred. |
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