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

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.

Allelopathy as an evolutionarily stable strategy

In plants, most competition is resource competition, where one plant simply pre-empts the resources away from its neighbours. Interference competition, as the name implies, is a form of direct interference to prevent resource access. Interference competition is common among animals who can physically fight, but in plants, one of the main mechanisms of interference competition is Allelopathy. allelopathic plants release of cytotoxic chemicals into the environment which can increase their ability to compete with surrounding organisms for limited resources. The circumstances and conditions favoring the development and maintenance of allelochemicals, however, is not well understood. Particularly, it seems strange that, despite the obvious benefits of allelopathy, it seems to have only rarely evolved. To gain insight into the cost and benefit of allelopathy, we have developed a 2x2 matrix game to model the interaction between plants that produce allelochemicals and plants that do not. Production of an allelochemical introduces novel cost associated with synthesis and detoxifying a toxic chemical but may also convey a competitive advantage. A plant that does not produce an allelochemical will suffer the cost of encountering one. Our model predicts three cases in which the evolutionarily stable strategies are different. In the first, the non-allelopathic plant is a stronger competitor, and not producing allelochemicals is the evolutionarily stable strategy. In the second, the allelopathic plant is the better competitor and production of allelochemicals is the more beneficial strategy. In the last case, neither is the evolutionarily stable strategy. Instead, there are alternating stable states, depending on whether the allelopathic or non-allelopathic plant arrived first. The generated model reveals circumstances leading to the evolution of allelochemicals and sheds light on utilizing allelochemicals as part of weed management strategies. In particular, the wide region of alternative stable states in most parameterizations, combined with the fact that the absence of allelopathy is likely the ancestral state, provides an elegant answer to the question of why allelopathy rarely evolves despite its obvious benefits. Allelopathic plants can indeed outcompete non-allelopathic plants, but this benefit is simply not great enough to allow them to go to fixation and spread through the population. Thus, most populations would remain purely non-allelopathic.

The study of evolutionary parasitology

An overview of the evolutionary process and the four basic questions that can be asked for biological phenomena. Furthermore, what biological units evolve, and the particular role of genes, is explained. Life history is introduced as a basic scheme that applies to individuals as well as to infections within a host. In particular, life history theory highlights the relevance of transmission as an equivalent to reproduction in the life history of individuals. The last section mentions several major methods for studying evolutionary parasitology; in particular, optimality approaches, the study of evolutionarily stable strategies, and comparative studies. Introducing the disease space as an illustrative tool for major topics in the book chapters.

Host phenology can select for multiple stable parasite virulence strategies

Host phenology is an important driver of parasite transmission and evolution. In a seasonal environment, monocyclic, obligate-killer parasites evolve optimal virulence strategies such that all parasite progeny are released near the end of the host season to limit parasite progeny death in the environment. It is unclear whether host seasonality imposes different constraints on polycyclic parasites such that both polycyclic and monocyclic parasites are maintained. We develop a mathematical model of a disease system with seasonal host activity to study the evolutionary consequences of host phenology on polycyclic, obligate-killer parasite virulence strategies. Seasonal host activity patterns create both monocyclic and polycyclic parasite evolutionarily stable strategies (ESS) separated by less-fit strategies (evolutionary repellors). The ESS that evolves in each system is a function of the virulence strategy of the parasite introduced into the system. The trait value for both monocyclic and polycyclic strategies is determined by two aspects of host phenology: the duration of the host activity period and the distribution in the time at which hosts first become active within each season. Longer host activity periods and more synchronous host emergence drive both the monocyclic and polycyclic strategies towards lower virulence. The results demonstrate that host phenology can, in theory, maintain diverse parasite strategies among isolated geographic locations.

Evolution of an asymptomatic first stage of infection in a heterogeneous population

Pathogens evolve different life-history strategies, which depend in part on differences in their host populations. A central feature of hosts is their population structure (e.g. spatial). Additionally, hosts themselves can exhibit different degrees of symptoms when newly infected; this latency is a key life-history property of pathogens. With an evolutionary-epidemiological model, we examine the role of population structure on the evolutionary dynamics of latency. We focus on specific power-law-like formulations for transmission and progression from the first infectious stage as a function of latency, assuming that the across-group to within-group transmission ratio increases if hosts are less symptomatic. We find that simple population heterogeneity can lead to local evolutionarily stable strategies (ESSs) at zero and infinite latency in situations where a unique ESS exists in the corresponding homogeneous case. Furthermore, there can exist more than one interior evolutionarily singular strategy. We find that this diversity of outcomes is due to the (possibly slight) advantage of across-group transmission for pathogens that produce fewer symptoms in a first infectious stage. Thus, our work reveals that allowing individuals without symptoms to travel can have important unintended evolutionary effects and is thus fundamentally problematic in view of the evolutionary dynamics of latency.

EVOLUTIONARILY STABLE STRATEGIES OF ECONOMIC BEHAVIOR

Modern science proceeds from the fact that the basis of economic behavior is volitional «controllability», i.e. awareness of the possible consequences of one's action/inaction by a person, on the basis of which the most effective behavioral models, common in a particular socio-cultural community, are formed from the position of satisfying one's needs. This article analyzes the theoretical and practical properties of understanding evolutionarily stable strategies of economic behavior, which at a subconscious level determine the further development of economic relations.

Asymmetric Partisan Voter Turnout Games

Since Downs proposed that the act of voting is irrational in 1957, myriad models have been proposed to explain voting and account for observed turnout patterns. We propose a model in which partisans consider both the instrumental and expressive benefits of their vote when deciding whether or not to abstain in an election, introducing an asymmetry that most other models do not consider. Allowing learning processes within our electorate, we analyze what evolutionarily stable strategies are rationalizable under various conditions. Upon varying electorate size, the partisan split of the electorate, and the degree to which an electorate takes underdog considerations into account in its payoff structure, we find that different equilibria arise. Our model predicts comparative statics that are consistent with voter behavior, specifically affirming a “size effect,” in which turnout decreases as electorate size increases. Furthermore, relaxing some of our preliminary assumptions eliminates some of the discrepancies between the predictions of our model and empirical voter behavior. In particular, our work demonstrates that misperceptions about the partisan split of an electorate may account for high turnout behavior .