Understanding the sharing economy and its implication on sustainability in smart cities

被引:39
|
作者
Akande, Adeoluwa [1 ]
Cabral, Pedro [1 ]
Casteleyn, Sven [2 ]
机构
[1] Univ Nova Lisboa, NOVA Informat Management Sch NOVA IMS, Campus Campolide, P-1070312 Lisbon, Portugal
[2] Univ Jaime I, Inst New Imaging Technol, GEOTEC, Ave Sos Baynat, E-12071 Castellon De La Plana, Spain
基金
欧盟地平线“2020”;
关键词
Smart cities; Sustainable cities; Sharing economy; Collaborative consumption; Meta-analysis; Weight analysis; COLLABORATIVE CONSUMPTION; CUSTOMER SATISFACTION; PEOPLE PARTICIPATE; ADOPTION; INTENTION; ACCESS; VALUES; PERSPECTIVE; ACCEPTANCE; PLATFORMS;
D O I
10.1016/j.jclepro.2020.124077
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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. (C) 2020 The Authors. Published by Elsevier Ltd.
引用
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页数:11
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