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Understanding the sharing economy and its implication on sustainability in smart cities
dc.contributor.author | Akande, Adeoluwa | |
dc.contributor.author | Cabral, Pedro | |
dc.contributor.author | Casteleyn, Sven | |
dc.date.accessioned | 2020-11-26T11:55:11Z | |
dc.date.available | 2020-11-26T11:55:11Z | |
dc.date.issued | 2020-09-06 | |
dc.identifier.citation | AKANDE, Adeoluwa; CABRAL, Pedro; CASTELEYN, Sven. Understanding the sharing economy and its implication on sustainability in smart cities. Journal of Cleaner Production, 2020, p. 124077. | ca_CA |
dc.identifier.issn | 0959-6526 | |
dc.identifier.uri | http://hdl.handle.net/10234/190509 | |
dc.description.abstract | The purpose of this article is to evaluate the main drivers of the sharing economy through an exhaustive weighting and meta-analysis of previous relevant quantitative research articles, obtained using a systematic literature review methodology. The authors analysed 22 quantitative studies from 2008 through. Out of the 249 extracted relationships (independent e dependent variable), the paper identifies the “best” predictors used in theoretical models to study the sharing economy. These include: attitude on intention to share, perceived behavioural control on intention to share, subjective norm on intention to share, economic benefit on attitude, and perceived risk on attitude. Geographically, Germany and the United States of America were found to be the nations with the highest number of respondents. Temporally, an increasing trend in the number of articles on the sharing economy and respondents was observed. The consolidation of the drivers of the sharing economy provides a solid theoretical foundation for the research community to explore existing hypotheses further and test new hypotheses in emerging contexts of the sharing economy. Given the different conceptual theories that have been used to study the sharing economy and their application to different contexts, this study presents the first attempt at advancing knowledge by quantitatively synthesizing findings presented in previous literature. | ca_CA |
dc.format.extent | 11 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Elsevier | ca_CA |
dc.relation.isPartOf | Journal of Cleaner Production 277 (2020) 124077 | ca_CA |
dc.rights | © 2020 The Authors. Published by Elsevier Ltd | ca_CA |
dc.rights | Atribución 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-sa/4.0/ | * |
dc.subject | smart cities | ca_CA |
dc.subject | sustainable cities | ca_CA |
dc.subject | sharing economy | ca_CA |
dc.subject | collaborative consumption | ca_CA |
dc.subject | meta-analysis | ca_CA |
dc.subject | weight analysis | ca_CA |
dc.title | Understanding the sharing economy and its implication on sustainability in smart cities | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.1016/j.jclepro.2020.124077 | |
dc.relation.projectID | 642332-GEO-C-H2020-MSCA-ITN-2014 ; RYC-2014-16606 | ca_CA |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.relation.publisherVersion | https://www.sciencedirect.com/journal/journal-of-cleaner-production | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
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