Study on green building promotion incentive strategy based on evolutionary game between government and construction unit

Green buildings are considered to be an effective way to save energy, reduce emissions, and protect the environment. As one of the main bodies of green building construction, the construction unit’s willingness to build seriously affects the promotion of green building. Therefore, based on the viewp...

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Main Authors: Li, Xiaojuan, Wang, Chen, A. Kassem, Mukhtar, Liu, Yishu, Ali, Kherun Nita
Format: Article
Language:English
Published: MDPI 2022
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Online Access:http://eprints.utm.my/104398/1/KherunNitaAli2022_StudyonGreenBuildingPromotionIncentive.pdf
http://eprints.utm.my/104398/
http://dx.doi.org/10.3390/su141610155
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Institution: Universiti Teknologi Malaysia
Language: English
id my.utm.104398
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spelling my.utm.1043982024-02-04T09:49:57Z http://eprints.utm.my/104398/ Study on green building promotion incentive strategy based on evolutionary game between government and construction unit Li, Xiaojuan Wang, Chen A. Kassem, Mukhtar Liu, Yishu Ali, Kherun Nita TA Engineering (General). Civil engineering (General) TH Building construction Green buildings are considered to be an effective way to save energy, reduce emissions, and protect the environment. As one of the main bodies of green building construction, the construction unit’s willingness to build seriously affects the promotion of green building. Therefore, based on the viewpoints of natural persons and bounded rationality, this study constructs an evolutionary game analysis model, analyzes the impact of local government subsidy policies on the application strategies of construction units, and analyzes the steady-state and selection strategies. The system dynamics model is established using a flow chart, and the simulation results show that, in the long run, increasing the government subsidy and inspection cost cannot improve the application probability of the construction unit. Furthermore, the inspection intensity of the government and the indirect income of the construction unit has a direct influence on the application probability of the construction unit. The results show that the government should adjust the amount of the subsidy reasonably, improve the penalty mechanism, reduce development costs, strengthen publicity, and encourage construction units to actively apply for green buildings, so as to realize the transformation and upgrade of China’s construction industry. MDPI 2022-08 Article PeerReviewed application/pdf en http://eprints.utm.my/104398/1/KherunNitaAli2022_StudyonGreenBuildingPromotionIncentive.pdf Li, Xiaojuan and Wang, Chen and A. Kassem, Mukhtar and Liu, Yishu and Ali, Kherun Nita (2022) Study on green building promotion incentive strategy based on evolutionary game between government and construction unit. Sustainability, 14 (16). pp. 1-15. ISSN 2071-1050 http://dx.doi.org/10.3390/su141610155 DOI:10.3390/su141610155
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TA Engineering (General). Civil engineering (General)
TH Building construction
spellingShingle TA Engineering (General). Civil engineering (General)
TH Building construction
Li, Xiaojuan
Wang, Chen
A. Kassem, Mukhtar
Liu, Yishu
Ali, Kherun Nita
Study on green building promotion incentive strategy based on evolutionary game between government and construction unit
description Green buildings are considered to be an effective way to save energy, reduce emissions, and protect the environment. As one of the main bodies of green building construction, the construction unit’s willingness to build seriously affects the promotion of green building. Therefore, based on the viewpoints of natural persons and bounded rationality, this study constructs an evolutionary game analysis model, analyzes the impact of local government subsidy policies on the application strategies of construction units, and analyzes the steady-state and selection strategies. The system dynamics model is established using a flow chart, and the simulation results show that, in the long run, increasing the government subsidy and inspection cost cannot improve the application probability of the construction unit. Furthermore, the inspection intensity of the government and the indirect income of the construction unit has a direct influence on the application probability of the construction unit. The results show that the government should adjust the amount of the subsidy reasonably, improve the penalty mechanism, reduce development costs, strengthen publicity, and encourage construction units to actively apply for green buildings, so as to realize the transformation and upgrade of China’s construction industry.
format Article
author Li, Xiaojuan
Wang, Chen
A. Kassem, Mukhtar
Liu, Yishu
Ali, Kherun Nita
author_facet Li, Xiaojuan
Wang, Chen
A. Kassem, Mukhtar
Liu, Yishu
Ali, Kherun Nita
author_sort Li, Xiaojuan
title Study on green building promotion incentive strategy based on evolutionary game between government and construction unit
title_short Study on green building promotion incentive strategy based on evolutionary game between government and construction unit
title_full Study on green building promotion incentive strategy based on evolutionary game between government and construction unit
title_fullStr Study on green building promotion incentive strategy based on evolutionary game between government and construction unit
title_full_unstemmed Study on green building promotion incentive strategy based on evolutionary game between government and construction unit
title_sort study on green building promotion incentive strategy based on evolutionary game between government and construction unit
publisher MDPI
publishDate 2022
url http://eprints.utm.my/104398/1/KherunNitaAli2022_StudyonGreenBuildingPromotionIncentive.pdf
http://eprints.utm.my/104398/
http://dx.doi.org/10.3390/su141610155
_version_ 1792147729604935680