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Predicting PM2.5 reduction behavior among college students: The role of beliefs and descriptive norms

DC Field Value Language
dc.contributor.authorPark, Seona-
dc.contributor.authorKim, Hyun Suk-
dc.contributor.authorYun, Sun-Jin-
dc.date.accessioned2022-10-05T04:13:20Z-
dc.date.available2022-10-05T04:13:20Z-
dc.date.created2022-06-08-
dc.date.issued2022-12-
dc.identifier.citationSustainable Environment, Vol.8 No.1, pp.1-13-
dc.identifier.issn2765-8511-
dc.identifier.urihttps://hdl.handle.net/10371/185374-
dc.description.abstractUnderstanding how psychological factors affect individual intentions is essential to designing a better communication campaign that promotes sustainable transport. This empirical study investigates the roles of beliefs and descriptive norms on behavior that would reduce particulate matter (PM2.5). We proposed public bikeshare usage as a way college students could help reduce PM 2.5 and analyzed cognitive factors affecting public bikeshare usage intentions through partial least squares structural equation modeling (PLS-SEM). The analysis results show that attitude, self-efficacy, and descriptive norms had a significant effect on behavioral intention; among these, descriptive norms had the greatest effect. Beliefs about personal benefits also had a positive effect on attitudes and descriptive norms; in contrast, beliefs about social benefits did not have a significant effect. Based on the findings, we suggest foregrounding the personal benefits and making effective normative appeals to overcome the difficulty of following the practice.-
dc.language영어-
dc.publisherTAYLOR & FRANCIS LTD-
dc.titlePredicting PM2.5 reduction behavior among college students: The role of beliefs and descriptive norms-
dc.typeArticle-
dc.identifier.doi10.1080/27658511.2022.2079190-
dc.citation.journaltitleSustainable Environment-
dc.identifier.wosid000799745700001-
dc.citation.endpage13-
dc.citation.number1-
dc.citation.startpage1-
dc.citation.volume8-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorYun, Sun-Jin-
dc.type.docTypeArticle-
dc.description.journalClass1-
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