Evolutionary game theory analysis for understanding the decision-making mechanisms of governments and developers on green building incentives

激励 政府(语言学) 公共经济学 相互依存 有限理性 过程(计算) 情感(语言学) 跨国公司 微观经济学 业务 博弈论 产业组织 经济 营销 计算机科学 政治学 财务 哲学 法学 操作系统 语言学
作者
Ke Fan,Eddie C.M. Hui
出处
期刊:Building and Environment [Elsevier]
卷期号:179: 106972-106972 被引量:109
标识
DOI:10.1016/j.buildenv.2020.106972
摘要

Green building incentives are widely implemented. Under each incentive, governments and developers have different payoffs and dominant strategies that affect incentive effectiveness. Existing studies have examined incentive effectiveness through different methods but have failed to reveal the decision-making mechanisms of governments and developers in a dynamic process of a game. As governments and developers have bounded rationality, and their strategies may change from time to time, this study employed evolutionary game theory to model the evolutionary behaviours of two players, thus providing a quantitative method to illustrate the effectiveness of incentives and the strategy changes of the players. This study concluded that four types of interactions between governments and developers affect incentive effectiveness, namely, 1) governments' dominant strategies depend on developers' choices; 2) developers' dominant strategies rely on governments' choices; 3) two parties' dominant strategies are independent; 4) their dominant strategies are interdependent. Under these interactions, the price premium of green building and the level and affordability of incentives were found to be the critical factors for the decision makings of the leading players. Policy recommendations were proposed accordingly. This study adopted a mathematical approach to investigate the conflicts of interests between governments and developers. It also provided a general model which can fit various contexts. In addition, the research introduced a valuable angle of government payoffs. Results can advance policymakers' understanding of green building incentives, help policymakers predict developers' behaviours and the incentive effectiveness in the long run and justify the design or improvement of multinational incentives.

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