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Investigating Users’ Continued Usage Intentions of Online Learning Applications

1,†, 2,3,*, 4,† and 2,†
1
Department of Safety and Security, Huzhou University, Huzhou 313000, China
2
School of Information Management Engineering, Shanghai University of Finance and Economics, Shanghai 200086, China
3
Business School, Huzhou University, 313000 Huzhou, China
4
Data Science and Cloud Service Research Centre, Shanghai University of Finance and Economics, Shanghai 200086, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Information 2019, 10(6), 198; https://doi.org/10.3390/info10060198
Received: 4 May 2019 / Revised: 31 May 2019 / Accepted: 31 May 2019 / Published: 4 June 2019
(This article belongs to the Section Information Applications)
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Abstract

Understanding users’ continued usage intentions for online learning applications is significant for online education. In this paper, we explore a scale to measure users’ usage intentions of online learning applications and empirically investigate the factors that influence users’ continued usage intentions of online learning applications based on 275 participant data. Using the extended Technology Acceptance Model (TAM) and the Structural Equation Modelling (SEM), the results show that males or users off campus are more likely to use online learning applications; that system characteristics (SC), social influence (SI), and perceived ease of use (PEOU) positively affect the perceived usefulness (PU), with coefficients of 0.74, 0.23, and 0.04, which imply that SC is the most significant to the PU of online learning applications; that facilitating conditions (FC) and individual differences (ID) positively affect the PEOU, with coefficients of 0.72 and 0.37, which suggest that FC is more important to the PEOU of online learning applications; and that both PEOU and PU positively affect the behavioral intention (BI), with coefficients of 0.83 and 0.51, which indicate that PEOU is more influential than PU to users’ continued usage intentions of online learning applications. In particular, the output quality, perceived enjoyment, and objective usability are critical to the users’ continued usage intentions of online learning applications. This study contributes to the technology acceptance research field with a fast growing market named online learning applications. Our methods and results would benefit both academics and managers with useful suggestions for research directions and user-centered strategies for the design of online learning applications.
Keywords: online learning applications; users’ continuance usage intention; technology acceptance; structural equation modelling online learning applications; users’ continuance usage intention; technology acceptance; structural equation modelling
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 (CC BY 4.0).
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Ji, Z.; Yang, Z.; Liu, J.; Yu, C. Investigating Users’ Continued Usage Intentions of Online Learning Applications. Information 2019, 10, 198.

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