Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/10438
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Du, Helen S. | en_US |
dc.contributor.author | Dr. KE Xiaobo, Bob | en_US |
dc.contributor.author | Wagner, Christian | en_US |
dc.date.accessioned | 2024-09-05T02:28:57Z | - |
dc.date.available | 2024-09-05T02:28:57Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Industrial Management & Data Systems, 2020, vol. 120(4), pp. 692-713. | en_US |
dc.identifier.issn | 0263-5577 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11861/10438 | - |
dc.description.abstract | Purpose This research draws on goal framing theory and gamification affordance to understand how gamification design encourages users' continuous usage of information systems (IS) to perform proenvironmental behaviors. Design/methodology/approach Survey data (N = 307) were collected from users of a gamified IS designed for environmental protection. The research model was examined with structural equation modeling. Findings Satisfying users' demand on green effectiveness, enjoyment, and social gain directly/indirectly predicts users' intention to continue to utilize the gamified IS for proenvironmental behaviors. Moreover, gamification affordance of autonomy support, visibility of achievement, competition, and interactivity influences the satisfaction of the users' relevant demands. Originality/value This research contributes to the IS research for environmental sustainability at the individual level. Specifically, this research extends the understanding of users' decision-making on continuance and the role of gamification design in the context of gamified IS developed for environmental conservation. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Industrial Management & Data Systems | en_US |
dc.title | Inducing individuals to engage in a gamified platform for environmental conservation | en_US |
dc.type | Peer Reviewed Journal Article | en_US |
dc.identifier.doi | https://doi.org/10.1108/IMDS-09-2019-0517 | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Department of Applied Data Science | - |
Appears in Collections: | Applied Data Science - Publication |
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