Evolutionary Game Theory and Typology: A Case Study

Language ◽  
2007 ◽  
Vol 83 (1) ◽  
pp. 74-109 ◽  
Author(s):  
Gerhard Jäger
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Tianjian Yang ◽  
Ye Li ◽  
Yu Zhang

In the practice of various Internet-based sharing economies, environmental issues of shared products become more prominent and urgent. By analysing the relationship among government, enterprises, and consumers, this paper develops a system dynamics model based on the evolutionary game theory to explore the quantity change pattern of environment-friendly products in a sharing industry. A discrete dynamic system simulation of the quantity change process takes shared bikes in Beijing as a case study. The simulation results are consistent with the analysis of evolutionary game theory. The results show that government subsidies to both enterprises and consumers can lead to higher quantities of environment-friendly shared products, while consumer subsidy is better than enterprise subsidy. In addition, governments and enterprises need to ensure moderate investments to improve consumer experience and environmental awareness.


2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Zhu Bai ◽  
Mingxia Huang ◽  
Shuai Bian ◽  
Huandong Wu

The emergence of online car-hailing service provides an innovative approach to vehicle booking but has negatively influenced the taxi industry in China. This paper modeled taxi service mode choice based on evolutionary game theory (EGT). The modes included the dispatching and online car-hailing modes. We constructed an EGT framework, including determining the strategies and the payoff matrix. We introduced different behaviors, including taxi company management, driver operation, and passenger choice. This allowed us to model the impact of these behaviors on the evolving process of service mode choice. The results show that adjustments in taxi company, driver, and passenger behaviors impact the evolutionary path and convergence speed of our evolutionary game model. However, it also reveals that, regardless of adjustments, the stable states in the game model remain unchanged. The conclusion provides a basis for studying taxi system operation and management.


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