Impact of policy adjustments on low carbon transition strategies in construction using evolutionary game theory
Abstract The construction industry is generally characterized by high emissions, making its transition to low-carbon practices essential for achieving a low-carbon economy. However, due to information asymmetry, there remains a gap in research regarding the strategic interactions and reward/punishme...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-87770-6 |
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| author | Song Wang Dongliang Zhu Jiachen Wang |
| author_facet | Song Wang Dongliang Zhu Jiachen Wang |
| author_sort | Song Wang |
| collection | DOAJ |
| description | Abstract The construction industry is generally characterized by high emissions, making its transition to low-carbon practices essential for achieving a low-carbon economy. However, due to information asymmetry, there remains a gap in research regarding the strategic interactions and reward/punishment mechanisms between governments and firms throughout this transition. This paper addresses this gap by investigating probabilistic and static reward and punishment evolutionary games. The findings indicate that (1) Probabilistic rewards and penalties policies are more effective during the initial stages of the transition, whereas static mechanisms are more conducive to ensuring long-term stability. (2) The maximum values of rewards and penalties significantly influence the evolution of the low-carbon transition, with higher incentives enhancing motivation and more significant penalties imposing stricter constraints. (3) An increase in the cost of government involvement facilitates the low-carbon transition. (4) The benefits to both government and enterprises are critical in determining the application of static versus probabilistic rewards and penalties. The government may decide to cap probabilistic rewards and penalties by the magnitude of the benefits or adopt static rewards and penalties. This study offers theoretical support and a decision-making framework for developing effective low-carbon policies. |
| format | Article |
| id | doaj-art-856afbfeba20487cb4d5d11ef72c727f |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-856afbfeba20487cb4d5d11ef72c727f2025-02-02T12:16:30ZengNature PortfolioScientific Reports2045-23222025-01-0115112110.1038/s41598-025-87770-6Impact of policy adjustments on low carbon transition strategies in construction using evolutionary game theorySong Wang0Dongliang Zhu1Jiachen Wang2College of Architecture and Civil Engineering, Xinyang Normal UniversityCollege of Architecture and Civil Engineering, Xinyang Normal UniversityCollege of Architecture and Civil Engineering, Xinyang Normal UniversityAbstract The construction industry is generally characterized by high emissions, making its transition to low-carbon practices essential for achieving a low-carbon economy. However, due to information asymmetry, there remains a gap in research regarding the strategic interactions and reward/punishment mechanisms between governments and firms throughout this transition. This paper addresses this gap by investigating probabilistic and static reward and punishment evolutionary games. The findings indicate that (1) Probabilistic rewards and penalties policies are more effective during the initial stages of the transition, whereas static mechanisms are more conducive to ensuring long-term stability. (2) The maximum values of rewards and penalties significantly influence the evolution of the low-carbon transition, with higher incentives enhancing motivation and more significant penalties imposing stricter constraints. (3) An increase in the cost of government involvement facilitates the low-carbon transition. (4) The benefits to both government and enterprises are critical in determining the application of static versus probabilistic rewards and penalties. The government may decide to cap probabilistic rewards and penalties by the magnitude of the benefits or adopt static rewards and penalties. This study offers theoretical support and a decision-making framework for developing effective low-carbon policies.https://doi.org/10.1038/s41598-025-87770-6Low-carbon economyLow-carbon transitionEvolutionary gameProbabilistic rewards and punishmentsStatic rewards and punishments |
| spellingShingle | Song Wang Dongliang Zhu Jiachen Wang Impact of policy adjustments on low carbon transition strategies in construction using evolutionary game theory Scientific Reports Low-carbon economy Low-carbon transition Evolutionary game Probabilistic rewards and punishments Static rewards and punishments |
| title | Impact of policy adjustments on low carbon transition strategies in construction using evolutionary game theory |
| title_full | Impact of policy adjustments on low carbon transition strategies in construction using evolutionary game theory |
| title_fullStr | Impact of policy adjustments on low carbon transition strategies in construction using evolutionary game theory |
| title_full_unstemmed | Impact of policy adjustments on low carbon transition strategies in construction using evolutionary game theory |
| title_short | Impact of policy adjustments on low carbon transition strategies in construction using evolutionary game theory |
| title_sort | impact of policy adjustments on low carbon transition strategies in construction using evolutionary game theory |
| topic | Low-carbon economy Low-carbon transition Evolutionary game Probabilistic rewards and punishments Static rewards and punishments |
| url | https://doi.org/10.1038/s41598-025-87770-6 |
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