Modeling the continuance usage intention of online learning environments
作者：
Highlights：
• This study explores students’ intentions to continue using online learning environments.
• We developed a continuance usage intention model for online learning environments.
• Quality variables have significant effects on confirmation and satisfaction.
• Confirmation has the strongest predictive effect on satisfaction.
• Satisfaction has the strongest predictive effect on continuance intention.
摘要
•This study explores students’ intentions to continue using online learning environments.•We developed a continuance usage intention model for online learning environments.•Quality variables have significant effects on confirmation and satisfaction.•Confirmation has the strongest predictive effect on satisfaction.•Satisfaction has the strongest predictive effect on continuance intention.
论文关键词：Continuance usage,Information systems,Information quality,Online learning environments,Service quality,System quality
论文评审过程：Received 3 October 2015, Revised 14 February 2016, Accepted 16 February 2016, Available online 27 February 2016, Version of Record 27 February 2016.
论文官网地址：https://doi.org/10.1016/j.chb.2016.02.066
