TY - JOUR
T1 - Understanding the sharing economy and its implication on sustainability in smart cities
AU - Akande, Adeoluwa
AU - Cabral, Pedro
AU - Casteleyn, Sven
N1 - info:eu-repo/grantAgreement/EC/H2020/642332/EU#
Akande, A., Cabral, P., & Casteleyn, S. (2020). Understanding the sharing economy and its implication on sustainability in smart cities. Journal of Cleaner Production, 277, 1-11. [124077]. https://doi.org/10.1016/j.jclepro.2020.124077
PY - 2020/12/20
Y1 - 2020/12/20
N2 - 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 – 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.
AB - 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 – 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.
KW - Collaborative consumption
KW - Meta-analysis
KW - Sharing economy
KW - Smart cities
KW - Sustainable cities
KW - Weight analysis
UR - http://www.scopus.com/inward/record.url?scp=85090731359&partnerID=8YFLogxK
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000586917600194
U2 - 10.1016/j.jclepro.2020.124077
DO - 10.1016/j.jclepro.2020.124077
M3 - Review article
AN - SCOPUS:85090731359
SN - 0959-6526
VL - 277
SP - 1
EP - 11
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 124077
ER -