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An Empirical Study on Users' Intention to Pay in B2C Online Education Platform

机译:B2C在线教育平台中用户支付意愿的实证研究

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Online education has been developing since the 1990s, and many traditional education institutions have begun to explore online education development models. Therefore, this paper aims to study the new profit model of B2C online education and improve user stickiness and intention to pay, promoting the healthy development of B2C online education platforms. This paper uses a combination of structural equation model and artificial neural network prediction to conduct empirical research. 557 valid questionnaires were collected, and data analysis was performed using SPSS24.0 and Amos22.0. The research results show that perceived utilitarian value, Word-of-Mouth, and personalization have a positive effect on MOOC continuance intention, which then have a positive effect on willingness to pay with perceived price fairness. The innovation of this research is to build a structural equation model by reading the literature, and then combine it with artificial neural network methods. Few scholars in the field of B2C online education used two empirical methods. The research of this paper is specifically targeted at B2C online education companies, and the results have important guiding effects in this field.
机译:自20世纪90年代以来,在线教育一直在发展,许多传统教育机构已经开始探索在线教育发展模式。因此,本文旨在研究B2C在线教育的新利润模型,提高用户粘性和意图,促进B2C在线教育平台的健康发展。本文采用结构方程模型和人工神经网络预测的组合来进行实证研究。收集了557个有效问卷,使用SPSS24.0和AMOS22.0进行数据分析。研究结果表明,感知的功利价值,口碑和个性化对MooC持续意图具有积极影响,然后对愿望的价格公平性愿意达成积极影响。本研究的创新是通过阅读文献来构建结构方程模型,然后将其与人工神经网络方法相结合。 B2C在线教育领域的少数学者使用了两种实证方法。本文的研究专门针对B2C在线教育公司,结果在这一领域具有重要的指导作用。

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