Building an economically sustainable online learning ecosystem with freemium model : A sequential mixed-method approach

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Journal / PublicationEducation and Information Technologies
Online published7 Dec 2023
Publication statusOnline published - 7 Dec 2023

Abstract

Online learning communities play a crucial role in delivering high-quality courses to a large number of learners. However, to maintain an economically sustainable and constantly evolving online learning ecosystem, it is essential to create a virtuous cycle from knowledge production to knowledge consumption by charging learners to incentivize course providers and to build and maintain online learning systems. This study examines online learners' willingness to pay for high-quality online courses and develops the FSEP model (Flow-Satisfaction-Expectancy-Purchasing). The model is based on the assumption that learners who have a good experience with a free course are more likely to purchase the paid version. The study employs an explanatory sequential mixed-method design. The quantitative results demonstrate that online learners' flow experience and satisfaction with the free course directly affect their expectations for paid courses, which in turn increase their intention to purchase. In particular, three full mediation effects clearly reveal the importance of the psychological paths identified in this study. The subsequent qualitative results further validate each hypothesis proposed in the FSEP model. This research advances our understanding of economically sustainable online learning ecosystems and also adds to existing knowledge of digital economies and the freemium model. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Research Area(s)

  • Flow experience, Freemium model, Learning satisfaction, Online learning ecosystem, Purchase intention, Sequential mixed-method approach, Value expectancy