| Summary: | Online courses have become the main source of income for online education platforms. It is of great value to explore the factors affecting users’ intention to buy online courses. Based on the technology acceptance model, perceived value theory and perceived risk theory, this study constructs the structural equation model of the purchase intention of online courses by taking users on online education platforms as the research object, and resorts PLS-SEM for analysis. This research explores factors that impact the intention to buy online courses and levels of these impact. The research questionnaire of this study was developed through literature review, and 669 valid questionnaires were collected. Data analysis was performed using IBM SPSS V24.0 and SmartPLS 3.2.8. Before the multi-group analysis, it is found that perceived value, time and space autonomy, course free trail exert positive impact on purchase intention, while perceived risk has negative impact on it. Perceived cost does not significantly affect purchase intention. Time and space autonomy, perceived usefulness, and perceived ease of use are positively affecting perceived value, while perceived cost and perceived risk negatively affect perceived value. Course free trail does not significantly affect perceived value. Perceived value completely mediates perceived cost, and partially mediates the impact of time and space autonomy and perceived risk on purchase intention. Word-of-mouth positively moderates the impact of perceived value on purchase intention. Age has negative impact on purchase intention, while education positively affects purchase intention. Perceived profit (perceived ease of use, perceived usefulness, time and space autonomy) significantly and positively affects perceived value, and perceived loss (perceived cost, perceived risk) significantly and negatively affects perceived value. Perceived value mediates the impact of perceived gain and perceived loss on the users’ purchase intention. PLS multi-group analysis is conducted according to the users’ experience in buying a course. Users with different purchasing experience have different significance in terms of Online courses have become the main source of income for online education platforms. It is of great value to explore the factors affecting users’ intention to buy online courses. Based on the technology acceptance model, perceived value theory and perceived risk theory, this study constructs the structural equation model of the purchase intention of online courses by taking users on online education platforms as the research object, and resorts PLS-SEM for analysis. This research explores factors that impact the intention to buy online courses and levels of these impact. The research questionnaire of this study was developed through literature review, and 669 valid questionnaires were collected. Data analysis was performed using IBM SPSS V24.0 and SmartPLS 3.2.8. Before the multi-group analysis, it is found that perceived value, time and space autonomy, course free trail exert positive impact on purchase intention, while perceived risk has negative impact on it. Perceived cost does not significantly affect purchase intention. Time and space autonomy, perceived usefulness, and perceived ease of use are positively affecting perceived value, while perceived cost and perceived risk negatively affect perceived value. Course free trail does not significantly affect perceived value. Perceived value completely mediates perceived cost, and partially mediates the impact of time and space autonomy and perceived risk on purchase intention. Word-of-mouth positively moderates the impact of perceived value on purchase intention. Age has negative impact on purchase intention, while education positively affects purchase intention. Perceived profit (perceived ease of use, perceived usefulness, time and space autonomy) significantly and positively affects perceived value, and perceived loss (perceived cost, perceived risk) significantly and negatively affects perceived value. Perceived value mediates the impact of perceived gain and perceived loss on the users’ purchase intention. PLS multi-group analysis is conducted according to the users’ experience in buying a course. Users with different purchasing experience have different significance in terms of course free trail, perceived risk, perceived ease of use, time and space autonomy, and education. Based on the data analysis, this study also discussed the corresponding recommendations, such as guaranteeing course quality, providing word-of-mouth, grouping users according to their purchasing experience, using artificial intelligence to recommend online courses for users; optimizing functions of time and space autonomy, improving user experience with 5G, virtual reality, and augmented reality; reducing course price with cloud services and big data technologies, and providing more course free trial in an attempt to reduce users’ perceived risk.
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