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Articles

How to lessen the effects of user resistance on the adoption of an e-learning environment: screenshot annotation on Flickr

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Pages 506-524 | Received 07 May 2016, Accepted 19 Jul 2017, Published online: 28 Jul 2017
 

ABSTRACT

The study makes use of the photo-hosting site, namely Flickr, for students to upload screenshots to demonstrate computer software problems and troubleshooting software. By creating non-text stickers and text-based annotations above the screenshots, students are able to help one another to diagnose and solve problems with greater certainty. In addition to applying the technology acceptance model, three factors from the user resistance perspective, namely, user resistance, peer opinion, and self-efficacy for change, were chosen as the basis for the research model. Based on data collected from 399 students, the results indicated that students’ resistance had a negative and direct effect on their behavioral intention. Both peer opinions and students’ self-efficacy for change had negative and direct effects on their resistance, which positively and indirectly influenced behavioral intention. User resistance could be significantly improved by promoting positive peer opinions or enhancing students’ self-efficacy for change.

Acknowledgments

The author wishes to thank anonymous reviewers for their helpful feedback and suggestions.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes on contributor

Travis K. Huang works as Assistant Professor of Department of Information Management at Ling Tung University in Taiwan. His research interests include knowledge management, e-learning, information systems implementation, and human–computer interaction. His research appears or is forthcoming in such journals as Computers & Education, Decision Support Systems, Behaviour & Information Technology, Journal of Computer Information Systems, and Journal of Theoretical and Applied Information Technology.

Additional information

Funding

This research is partially supported by Ministry of Science and Technology in Taiwan under project number [MOST-103-2410-H-275-006-MY2].

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