| Issue |
E3S Web Conf.
Volume 409, 2023
International Conference on Management Science and Engineering Management (ICMSEM 2023)
|
|
|---|---|---|
| Article Number | 01007 | |
| Number of page(s) | 10 | |
| Section | Sustainable Development | |
| DOI | https://doi.org/10.1051/e3sconf/202340901007 | |
| Published online | 01 August 2023 | |
Impact of Community Trust on Residents Perceptions of Green Governance Performance: Evidence from Chengdu
Business School of Sichuan University, Chengdu, 610065, People’s Republic of China
* e-mail: miaosaliu@163.com
Green is the underlying requirement for China’s high-quality development. The extent to which residents perceive the performance of green governance is related to the formation of a green governance community and the achievement of green value objectives. Based on 295 valid questionnaires and qualitative interview data in Chengdu, this paper employs a mixed-methods research to investigate the role of community trust on the resident perceptions of green governance performance from the perspective of individual differences. The findings demonstrate that community trust promotes social interaction and information flow and significantly positively affects the resident’s perception of green governance performance. Public perceptions of green governance performance can be effectively enhanced by actively cultivating general trust and special trust.
Key words: Social networking / Trust / Green governance / Perceived performance / Mixed-methods research
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.