心态
背景(考古学)
损失厌恶
政府(语言学)
经济
情感(语言学)
利益相关者
晋升(国际象棋)
结果(博弈论)
公共经济学
微观经济学
心理学
计算机科学
政治学
人工智能
管理
法学
古生物学
哲学
政治
生物
沟通
语言学
作者
Ruyin Long,Tian Qian,Xufeng Zhang,Ruyin Long,Hong Chen,Han Huang,Lei Liu,Lingkai Zhu,Han-Min Jiang,Haiwei Zhu
标识
DOI:10.1016/j.eap.2023.09.015
摘要
Incorporating the principles of loss aversion psychology within the context of green housing stakeholders – the government, realtors, and residents – this study extends its purview into an evolutionary game model. This model takes into account the consequences of inaction in the absence of government oversight, the additional loss incurred by realtors due to the unmarketable development of green housing, and the psychological loss experienced by residents when their green housing acquisitions fall short of their expectations. To further enrich our analysis, three distinct scenarios are considered for the government: exclusive rewards without penalties, exclusive penalties without rewards, and a combination of both rewards and penalties. The simulation results show that: (1) The initial probability values assigned to the three parties do not significantly impact the long-term stable equilibrium. Interestingly, a higher initial probability value tends to steer all three parties towards selecting the stable equilibrium solution. (2) Within the context of the three reward–penalty scenarios, it becomes evident that an increase in the magnitude of government rewards and penalties inclines realtors towards a greater inclination to engage in green housing development. Nonetheless, a balanced approach appears to yield the most favorable results. (3) A sensitivity analysis reveals that a heightened aversion to loss within the government’s decision-making process leads to a higher likelihood of regulatory intervention. Conversely, a diminished loss aversion mindset among realtors and residents correlates with an increased propensity for realtors to invest in green housing development, while residents are more inclined to purchase green housing. Finally, corresponding policy implications are given according to the conclusions.
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