Exploring the Switching Intention of Learners on Social Network-based Learning Platforms: A Perspective of the Push–Pull–Mooring Model
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Yi-Wen Liao 1, Yueh-Min Huang 2, Shu-Hsien Huang 2, Hsin-Chin Chen 2, Chun-Wang Wei 3 4 *
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1 Department of Information Management, Cheng Shiu University, TAIWAN2 Department of Engineering Science, National Cheng Kung University, TAIWAN3 Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, TAIWAN4 Department of Medical Research, Kaohsiung Medical University Hospital, TAIWAN* Corresponding Author

Abstract

Social media or social networking sites have been used to support online learning with good interactive features. If an existing system can retain current users and attract new users, it can provide greater benefits and influence in the field of online learning. However, most previous studies focus on learner participation intention, and rarely note their switching intention. Therefore, this study attempts to analyze and discuss the learner switching intention from the perspective of Push-Pull-Mooring Model. A research framework was proposed for examining the switching intention of learners in social network-based learning platforms. A total of 371 valid samples were used to examine the research framework using the partial least squares approach. The results show that switching intention is significantly affected by the push effects (social interaction and service quality), mooring effects (switching costs and prior switching experience) and pull effects (attractiveness of new services and social effect). To retain and attract users, platform providers can raise switching costs through improving service quality and system capabilities and educators can develop appropriate approaches to enhance social interaction and social effects.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, 2019, Volume 15, Issue 9, Article No: em1747

https://doi.org/10.29333/ejmste/108483

Publication date: 12 Apr 2019

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Article Downloads: 3006

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