System dynamics modeling of collaborative governance in smart cities: a case study of Dongguan, China
The smart city, characterized by its complexity and expansiveness, entails intricate collaborative governance processes involving a multitude of elements. We have established a smart city collaborative governance system and formulated a system dynamics model based on the interaction dynamics among t...
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| Published in | Scientific reports Vol. 14; no. 1; pp. 31758 - 19 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
30.12.2024
Nature Publishing Group Nature Portfolio |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2045-2322 2045-2322 |
| DOI | 10.1038/s41598-024-82363-1 |
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| Abstract | The smart city, characterized by its complexity and expansiveness, entails intricate collaborative governance processes involving a multitude of elements. We have established a smart city collaborative governance system and formulated a system dynamics model based on the interaction dynamics among the internal elements of the collaborative governance subsystems: the subject, object, and environment. Policy adjustment variables were carefully selected to simulate six policy combination scenarios, illustrating the developmental trajectory of Dongguan City’s smart city collaborative governance system from 2015 to 2030, within the context of various policy paradigms. Our findings emphasize that enhanced policy input from collaborative governance subjects and the governance environment can foster improvement in collaborative governance efficiency. The intensity of policy input in smart city collaborative governance significantly influences the system’s operational effectiveness, with scenarios of rapid development, marked by higher policy investment, outperforming those of steady development. The input of policy adjustment variables induces synergy within the smart city collaborative governance system, and distinct governance models, such as technology-led, society-led, and government-led, exhibit unique focus in their influence on the smart city collaborative governance system. Together, these models play a crucial role in advancing the smart city collaborative governance system towards an effective and beneficial operation. |
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| AbstractList | The smart city, characterized by its complexity and expansiveness, entails intricate collaborative governance processes involving a multitude of elements. We have established a smart city collaborative governance system and formulated a system dynamics model based on the interaction dynamics among the internal elements of the collaborative governance subsystems: the subject, object, and environment. Policy adjustment variables were carefully selected to simulate six policy combination scenarios, illustrating the developmental trajectory of Dongguan City’s smart city collaborative governance system from 2015 to 2030, within the context of various policy paradigms. Our findings emphasize that enhanced policy input from collaborative governance subjects and the governance environment can foster improvement in collaborative governance efficiency. The intensity of policy input in smart city collaborative governance significantly influences the system’s operational effectiveness, with scenarios of rapid development, marked by higher policy investment, outperforming those of steady development. The input of policy adjustment variables induces synergy within the smart city collaborative governance system, and distinct governance models, such as technology-led, society-led, and government-led, exhibit unique focus in their influence on the smart city collaborative governance system. Together, these models play a crucial role in advancing the smart city collaborative governance system towards an effective and beneficial operation. The smart city, characterized by its complexity and expansiveness, entails intricate collaborative governance processes involving a multitude of elements. We have established a smart city collaborative governance system and formulated a system dynamics model based on the interaction dynamics among the internal elements of the collaborative governance subsystems: the subject, object, and environment. Policy adjustment variables were carefully selected to simulate six policy combination scenarios, illustrating the developmental trajectory of Dongguan City's smart city collaborative governance system from 2015 to 2030, within the context of various policy paradigms. Our findings emphasize that enhanced policy input from collaborative governance subjects and the governance environment can foster improvement in collaborative governance efficiency. The intensity of policy input in smart city collaborative governance significantly influences the system's operational effectiveness, with scenarios of rapid development, marked by higher policy investment, outperforming those of steady development. The input of policy adjustment variables induces synergy within the smart city collaborative governance system, and distinct governance models, such as technology-led, society-led, and government-led, exhibit unique focus in their influence on the smart city collaborative governance system. Together, these models play a crucial role in advancing the smart city collaborative governance system towards an effective and beneficial operation.The smart city, characterized by its complexity and expansiveness, entails intricate collaborative governance processes involving a multitude of elements. We have established a smart city collaborative governance system and formulated a system dynamics model based on the interaction dynamics among the internal elements of the collaborative governance subsystems: the subject, object, and environment. Policy adjustment variables were carefully selected to simulate six policy combination scenarios, illustrating the developmental trajectory of Dongguan City's smart city collaborative governance system from 2015 to 2030, within the context of various policy paradigms. Our findings emphasize that enhanced policy input from collaborative governance subjects and the governance environment can foster improvement in collaborative governance efficiency. The intensity of policy input in smart city collaborative governance significantly influences the system's operational effectiveness, with scenarios of rapid development, marked by higher policy investment, outperforming those of steady development. The input of policy adjustment variables induces synergy within the smart city collaborative governance system, and distinct governance models, such as technology-led, society-led, and government-led, exhibit unique focus in their influence on the smart city collaborative governance system. Together, these models play a crucial role in advancing the smart city collaborative governance system towards an effective and beneficial operation. Abstract The smart city, characterized by its complexity and expansiveness, entails intricate collaborative governance processes involving a multitude of elements. We have established a smart city collaborative governance system and formulated a system dynamics model based on the interaction dynamics among the internal elements of the collaborative governance subsystems: the subject, object, and environment. Policy adjustment variables were carefully selected to simulate six policy combination scenarios, illustrating the developmental trajectory of Dongguan City’s smart city collaborative governance system from 2015 to 2030, within the context of various policy paradigms. Our findings emphasize that enhanced policy input from collaborative governance subjects and the governance environment can foster improvement in collaborative governance efficiency. The intensity of policy input in smart city collaborative governance significantly influences the system’s operational effectiveness, with scenarios of rapid development, marked by higher policy investment, outperforming those of steady development. The input of policy adjustment variables induces synergy within the smart city collaborative governance system, and distinct governance models, such as technology-led, society-led, and government-led, exhibit unique focus in their influence on the smart city collaborative governance system. Together, these models play a crucial role in advancing the smart city collaborative governance system towards an effective and beneficial operation. |
| ArticleNumber | 31758 |
| Author | Jiang, Guoxin Dong, Jiawen Liu, Shuai Wu, Yuchao |
| Author_xml | – sequence: 1 givenname: Shuai surname: Liu fullname: Liu, Shuai organization: Ordos Institute of Liaoning Technical University, Collaborative Innovation Center of Mine Major Disaster Prevention and Environment Resoration, School of Business Administration, Liaoning Technical University – sequence: 2 givenname: Yuchao surname: Wu fullname: Wu, Yuchao organization: School of Business Administration, Liaoning Technical University – sequence: 3 givenname: Guoxin surname: Jiang fullname: Jiang, Guoxin email: jiangguoxin2008@126.com organization: School of Economics and Management, China University of Mining and Technology, School of Software, Liaoning Technical University – sequence: 4 givenname: Jiawen surname: Dong fullname: Dong, Jiawen organization: School of Business Administration, Liaoning Technical University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39738382$$D View this record in MEDLINE/PubMed |
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| Keywords | Collaborative governance Policy simulation System dynamics Smart city |
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| Title | System dynamics modeling of collaborative governance in smart cities: a case study of Dongguan, China |
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