| Title |
Government Low-Carbon Policies Optimization for Smart Transportation Enterprises |
| ID_Doc |
35153 |
| Authors |
Gao, K; Guo, X; Liu, TT; Han, R |
| Title |
Government Low-Carbon Policies Optimization for Smart Transportation Enterprises |
| Year |
2022 |
| Published |
|
| DOI |
10.1155/2022/1099147 |
| Abstract |
As an important part of energy saving and carbon reduction, the low-carbon development of the transportation industry is imperative. It is the responsibility of smart transportation enterprises to closely combine their own digital technology with the governments' policies to achieve green innovation. In this study, we conducted an evolutionary game model of the interaction between the governments and smart transportation enterprises, which depended on innovation subsidies and punitive taxes. Besides, we derived the evolutionarily stable strategy of the governments and enterprises and used a simulation to analyze the impact of various policy tools on green innovation strategy. The results showed that the behavior of the governments relies on the benefits of supervision and the costs of supporting green technology innovation. The enterprises' behavior depends on the benefits of green innovation and the loss of no green innovation. Moreover, different policy tools provided by the governments can accelerate the implementation of enterprises' green innovation. |
| Author Keywords |
|
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000769750600001 |
| WoS Category |
Mathematics, Interdisciplinary Applications; Multidisciplinary Sciences |
| Research Area |
Mathematics; Science & Technology - Other Topics |
| PDF |
https://downloads.hindawi.com/journals/ddns/2022/1099147.pdf
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