scholarly journals The Impact of Penalty and Subsidy Mechanisms On The Decisions of Governments, Businesses, and Consumers During COVID-19 ——Tripartite Evolutionary Game Theory Analysis

2021 ◽  
Author(s):  
Yuxun Zhou ◽  
Rahman Mohammad Mafizur ◽  
Khanam Rasheda ◽  
Brad R. Taylor
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Virus Disease ◽  
Evolutionary Game ◽  
Initial Point ◽  
Evolutionarily Stable Strategies ◽  
Corona Virus ◽  
Evolutionary Stable Strategies ◽  
The Impact

Abstract Purpose – Based on the fact that punishment and subsidy mechanisms affect the anti-epidemic incentives of major participants in a society, the issue of this paper is how the penalty and subsidy mechanisms affect the decisions of governments, businesses, and consumers during Corona Virus Disease 2019. The goal of this paper is to understand strategic selections from governments, enterprises, and consumers to maximize their respective utility during Corona Virus Disease 2019, and the impact of penalty and subsidy mechanism on the decisions of governments, businesses, and consumers.Design/Methodology/approach - This paper proposes a tripartite evolutionary game theory, involving governments, businesses, and consumers, to firstly analyze the evolutionary stable strategies and to secondly analyze the impact of penalty and subsidy mechanism on their strategy selection during Corona Virus Disease 2019. Thirdly, this paper uses numerical analysis to simulate the strategy formation process of governments, enterprises, and consumers in Japan and India based on their different penalty and subsidy mechanism.Findings – This paper suggests that there are four evolutionarily stable strategies corresponding to the actual anti-epidemic situations of different countries in reality. We find that different subsidy and penalty mechanisms lead to different evolutionary stable strategies. If governments, enterprises, and consumers fighting the pandemic together, the government need to set a low subsidy mechanism and a high penalty mechanism.Originality/value - There are some limitations in the literature, such as long term strategies, rational hypothesis, and convergence path analysis in higher dimensional evolutionary game theory. This paper fills the gap and extends the theory of COVID-19 management theory. Firstly, this paper has important practical significance. This paper finds out the long-term equilibrium strategies of governments, businesses, and consumers under Corona Virus Disease 2019, which can provide an important theoretical and decision-making basis for pandemic prevention and control. Secondly, our paper extends the analytical paradigm of the tripartite evolutionary game theory. We extend the analysis of the dynamic process from the initial point to the convergence point and make a theoretical contribution to the development of high-dimensional evolutionary game theory.

scholarly journals A Study of Taxi Service Mode Choice Based on Evolutionary Game Theory

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Zhu Bai ◽  
Mingxia Huang ◽  
Shuai Bian ◽  
Huandong Wu
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Mode Choice ◽  
Evolutionary Game ◽  
Payoff Matrix ◽  
Game Model ◽  
Stable States ◽  
Taxi Service ◽  
Service Mode ◽  
The Impact

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.

An Analysis of Quality Liability Insurance for Prefabricated Components Using Evolutionary Game Theory

2021 ◽  
Author(s):  
Yan Liu ◽  
Chenyao Lv ◽  
Hong Xian Li ◽  
Yan Li ◽  
Zhen Lei ◽  
...  
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Payoff Matrix ◽  
Liability Insurance ◽  
Insurance Companies ◽  
Social Benefits ◽  
Simulation Calculation ◽  
The Government

Managing quality risks of prefabricated components is one of the challenges for prefabricated construction. The Quality Liability Insurance for Prefabricated Components (QLIPC) is an effective approach to transfer such risks; however, limited research has been conducted regarding the development of QLIPC. This study introduces an Evolutionary Game Theory (EGT)-based approach incorporating decisions from both the government and insurance companies. In the EGT model, a payoff matrix under disparate strategies is constructed, and the evolutionary stable strategies (ESS) are deduced. The simulation calculation is then carried out by MATLAB using sample virtual data to demonstrate the analysis. The results show that the government should act as the game promoter because the QLIPC can reduce governance cost and has significant social benefits. This research contributes a theoretical framework to analyze the QLIPC development using the EGT theory, and it could help the government to make long-term strategies for developing the QLIPC market.

Insights into the Impact of Social Networks on Evolutionary Games

2008 ◽  
pp. 306-323
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Weibull, 1995; Taylor & Jonker, 1978; Nowak & May, 1993) to model the dynamics of adaptive opponent strategies for large population of players. In particular, we explore effects of information propagation through social networks in Evolutionary Games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

scholarly journals Evolutionary Game Theory: A Generalization of the ESS Definition

2019 ◽  
Vol 21 (04) ◽  
pp. 1950005
Author(s):  
Elvio Accinelli ◽  
Filipe Martins ◽  
Jorge Oviedo
Keyword(s):  
Game Theory ◽  
Strategic Planning ◽  
Evolutionary Game Theory ◽  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Previous Literature ◽  
Evolutionarily Stable Strategies ◽  
Symmetric Games ◽  
Two Populations ◽  
Evolutionarily Stable

In this paper, we study the concept of Evolutionarily Stable Strategies (ESSs) for symmetric games with [Formula: see text] players. The main properties of these games and strategies are analyzed and several examples are provided. We relate the concept of ESS with previous literature and provide a proof of finiteness of ESS in the context of symmetric games with [Formula: see text] players. We show that unlike the case of [Formula: see text], when there are more than two populations an ESS does not have a uniform invasion barrier, or equivalently, it is not equivalent to the strategy performing better against all strategies in a neighborhood. We also construct the extended replicator dynamics for these games and we study an application to a model of strategic planning of investment.

scholarly journals Social evolution and genetic interactions in the short and long term

2014 ◽  
Author(s):  
Jeremy Van Cleve
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Social Evolution ◽  
Evolutionary Game ◽  
Genetic Interactions ◽  
Short Term ◽  
Hamilton’S Rule ◽  
Analytical Approaches ◽  
Hamilton's Rule

The evolution of social traits remains one of the most fascinating and feisty topics in evolutionary biology even after half a century of theoretical research. W. D. Hamilton shaped much of the field initially with his 1964 papers that laid out the foundation for understanding the effect of genetic relatedness on the evolution of social behavior. Early theoretical investigations revealed two critical assumptions required for Hamilton's rule to hold in dynamical models: weak selection and additive genetic interactions. However, only recently have analytical approaches from population genetics and evolutionary game theory developed sufficiently so that social evolution can be studied under the joint action of selection, mutation, and genetic drift. We review how these approaches suggest two timescales for evolution under weak mutation: (i) a short-term timescale where evolution occurs between a finite set of alleles, and (ii) a long-term timescale where a continuum of alleles are possible and populations evolve continuously from one monomorphic trait to another. We show how Hamilton's rule emerges from the short-term analysis under additivity and how non-additive genetic interactions can be accounted for more generally. This short-term approach reproduces, synthesizes, and generalizes many previous results including the one-third law from evolutionary game theory and risk dominance from economic game theory. Using the long-term approach, we illustrate how trait evolution can be described with a diffusion equation that is a stochastic analogue of the canonical equation of adaptive dynamics. Peaks in the stationary distribution of the diffusion capture classic notions of convergence stability from evolutionary game theory and generally depend on the additive genetic interactions inherent in Hamilton's rule. Surprisingly, the peaks of the long-term stationary distribution can predict the effects of simple kinds of non-additive interactions. Additionally, the peaks capture both weak and strong effects of social payoffs in a manner difficult to replicate with the short-term approach. Together, the results from the short and long-term approaches suggest both how Hamilton's insight may be robust in unexpected ways and how current analytical approaches can expand our understanding of social evolution far beyond Hamilton's original work.

Insights into the Impact of Social Networks on Evolutionary Games

2010 ◽  
pp. 150-159
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

The chapter explores the use of evolutionary game theory (EGT) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, it explores effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. The chapter presents experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Insights into the Impact of Social Networks on Evolutionary Games

2009 ◽  
pp. 1477-1488
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Nowak & May, 1993; Taylor & Jonker, 1978; Weibull, 1995) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, we explore effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Long-term Hydropower Pricing in the Spot Market with Evolutionary Game Theory

2020 ◽  
Vol 103 (sp1) ◽  
pp. 117
Author(s):  
Liling Lin ◽  
Chaorong Huang ◽  
Linfeng Zhao
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Spot Market
Sign in / Sign up

Export Citation Format

Share Document