已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Exploring effective incentive policies for sustainable development of green buildings in China: based on evolutionary game theory and numerical simulation analysis

激励 中国 可持续发展 博弈论 进化博弈论 环境经济学 进化稳定策略 计算机科学 经济 自然资源经济学 经济体制 微观经济学 政治学 生态学 生物 法学
作者
Chunmei Fan,Xiaoyue Li
出处
期刊:Engineering, Construction and Architectural Management [Emerald (MCB UP)]
卷期号:32 (5): 3326-3348 被引量:9
标识
DOI:10.1108/ecam-06-2023-0622
摘要

Purpose This study reveals the green building development path and analyzes the optimal government subsidy equilibrium through evolutionary game theory and numerical simulation. This was done to explore the feasible measures and optimal incentives to achieve higher levels of green building in China. Design/methodology/approach First, the practice of green building in China was analyzed, and the specific influencing factors and incentive measures for green building development were extracted. Second, China-specific evolutionary game models were constructed between developers and homebuyers under the market regulation and government incentive mechanism scenarios, and the evolutionary paths were analyzed. Finally, real-case numerical simulations were conducted, subsidy impacts were mainly analyzed and optimal subsidy equilibriums were solved. Findings (1) Simultaneously subsidizing developers and homebuyers proved to be the most effective measure to promote the sustainability of green buildings. (2) The sensitivity of developers and homebuyers to subsidies varied across scenarios, and the optimal subsidy level diminished marginally as building greenness and public awareness increased. (3) The optimal subsidy level for developers was intricately tied to the building greenness benchmark. A higher benchmark intensified the developer’s responsiveness to losses, at which point increasing subsidies were justified. Conversely, a reduction in subsidy might have been appropriate when the benchmark was set at a lower level. Practical implications The expeditious advancement of green buildings holds paramount importance for the high-quality development of the construction industry. Nevertheless, the pace of green building expansion in China has experienced a recent deceleration. Drawing insights from the practices of green building in China, the exploration of viable strategies and the determination of optimal government subsidies stand as imperative initiatives. These endeavors aim to propel the acceleration of green building proliferation and materialize high-quality development at the earliest juncture possible. Originality/value The model is grounded in China’s green building practices, which makes the conclusions drawn more specific. Furthermore, research results provide practical references for governments to formulate green building incentive policies.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
寒冷芝完成签到 ,获得积分10
刚刚
刚刚
科研fw完成签到 ,获得积分10
1秒前
陈七完成签到,获得积分10
2秒前
2秒前
Lucas应助ceeray23采纳,获得200
3秒前
4秒前
思源应助ttang11采纳,获得10
5秒前
zgjc发布了新的文献求助10
5秒前
Owen应助linjt采纳,获得10
6秒前
无花果应助禹冷玉采纳,获得10
7秒前
bmhs2017应助阿歪歪采纳,获得10
8秒前
8秒前
南曦完成签到 ,获得积分10
8秒前
kls完成签到 ,获得积分10
8秒前
10秒前
liu完成签到,获得积分10
12秒前
ii发布了新的文献求助10
14秒前
qin给朱志伟的求助进行了留言
15秒前
yxc完成签到 ,获得积分10
15秒前
务实觅松完成签到 ,获得积分10
16秒前
翊嘉完成签到 ,获得积分10
16秒前
16秒前
pure完成签到 ,获得积分10
17秒前
风中幻天完成签到,获得积分10
18秒前
zzww发布了新的文献求助10
19秒前
zgjc完成签到,获得积分10
20秒前
属实有点拉胯完成签到 ,获得积分10
23秒前
HHYYAA发布了新的文献求助10
23秒前
科研小菜完成签到 ,获得积分10
25秒前
26秒前
香蕉觅云应助HHYYAA采纳,获得10
27秒前
咩咩完成签到 ,获得积分10
28秒前
翊嘉完成签到 ,获得积分10
29秒前
DryDry完成签到 ,获得积分10
30秒前
怜熙完成签到 ,获得积分10
32秒前
38秒前
tutu完成签到,获得积分0
39秒前
科研同路人完成签到,获得积分0
40秒前
内向的哈密瓜完成签到,获得积分10
40秒前
高分求助中
晶体学对称群—如何读懂和应用国际晶体学表 1500
Constitutional and Administrative Law 1000
Microbially Influenced Corrosion of Materials 500
Die Fliegen der Palaearktischen Region. Familie 64 g: Larvaevorinae (Tachininae). 1975 500
Numerical controlled progressive forming as dieless forming 400
Rural Geographies People, Place and the Countryside 400
Machine Learning for Polymer Informatics 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5385140
求助须知:如何正确求助?哪些是违规求助? 4507821
关于积分的说明 14029039
捐赠科研通 4417666
什么是DOI,文献DOI怎么找? 2426643
邀请新用户注册赠送积分活动 1419324
关于科研通互助平台的介绍 1397721