| Title |
The consequences of environmental big data information disclosure on hard-to-abate Chinese enterprises' green innovation |
| ID_Doc |
31160 |
| Authors |
Zhang, C; Zhou, B; Wang, QW; Jian, YD |
| Title |
The consequences of environmental big data information disclosure on hard-to-abate Chinese enterprises' green innovation |
| Year |
2024 |
| Published |
Journal Of Innovation & Knowledge, 9, 2 |
| DOI |
10.1016/j.jik.2024.100474 |
| Abstract |
Big data technology may improve the quality of environmental information disclosure and address the challenge of information asymmetry. This study adopts a difference -in -differences strategy to investigate the effectiveness of the big data -based environmental information disclosure system launched by the Chinese Ministry of Environmental Protection in 2013. The results reveal that, the system signi ficantly stimulates green innovation in hard -to -abate enterprises with an entrepreneurial orientation. A mechanism exploration suggests that environmental big data information disclosure drives of ficials to implement environmental policies aimed at hard -to -abate enterprises and raises public concern regarding environmental quality; however, the mechanism of public attention is found to be ineffective in stimulating corporate green innovation in the sample period. This study identi fies a useful channel for policymakers to develop green innovation by enhancing the current system of environmental big data information disclosure. (c) 2024 The Authors. Published by Elsevier Espa & ntilde;a, S.L.U. on behalf of Journal of Innovation & Knowledge. This is an open access article under the CC BY -NC -ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
| Author Keywords |
Big data; Environmental information disclosure; Environmental policies; Public attention; Green innovation |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Social Science Citation Index (SSCI) |
| EID |
WOS:001221897600001 |
| WoS Category |
Business; Management |
| Research Area |
Business & Economics |
| PDF |
https://doi.org/10.1016/j.jik.2024.100474
|