Promoting the Sustainable Building Market: an Evolution Analysis and System Dynamics Simulation on Behaviors of Real Estate Developers and Government

Xiuli Xie, Yisheng Liu, Jing Hou

Abstract


Purpose: The Chinese government takes measures to promote the development of green building (GB). But until 2013, there are only few green buildings in China. The real estate developers are skeptical in entering GB market, which requires theories to explain developers and government’s behaviors.

Design/methodology/approach: In this study, we attempt Evolutionary game theory and System dynamics (SD) into the analysis. A system dynamics model is built for studying evolutionary games between the government and developers in greening building decision making.

Findings and Originality/value: The results of mixed-strategy stability analysis and SD simulation show that evolutionary equilibrium does not exist with a static government incentive. Therefore, a dynamical incentive is suggested in the SD model for promoting the green building market. The symmetric game and asymmetric game between two developers show, if the primary proportion who choose GB strategy is lower, all the group in game may finally evolve to GB strategy. In this case and in this time, the government should take measures to encourage developers to enter into the GB market. If the proportion who choose GB strategy is high enough, the government should gradually cancel or reduce those incentive measure.

Research limitations/implications: an Evolution Analysis and System Dynamics Simulation on Behaviors of Real Estate Developers and Government could give some advice for the government to promote the green building market.


Keywords


Green Building;Evolutionary Game; System dynamics;Real estate market

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DOI: http://dx.doi.org/10.3926/jiem.1042


Licencia de Creative Commons 

This work is licensed under a Creative Commons Attribution 4.0 International License

Journal of Industrial Engineering and Management, 2008-2019

Online ISSN: 2013-0953; Print ISSN: 2013-8423; Online DL: B-28744-2008

Publisher: OmniaScience