An Evolutionary Game Model with Punishment and Protection to Promote Trust in the Sharing Economy

Success-driven opinion formation determines social tensions

Polarization is common in politics and public opinion. It is believed to be shaped by media as well as ideologies, and often incited by misinformation. However, little is known about the microscopic dynamics behind polarization and the resulting social tensions. By coupling opinion formation with the strategy selection in different social dilemmas, we reveal how success at an individual level transforms to global consensus or lack thereof. When defection carries with it the fear of punishment in the absence of greed, as in the stag-hunt game, opinion fragmentation is the smallest. Conversely, if defection promises a higher payoff and also evokes greed, like in the prisoner's dilemma and snowdrift game, consensus is more difficult to attain. Our research thus challenges the top-down narrative of social tensions, showing they might originate from fundamental principles at individual level, like the desire to prevail in pairwise evolutionary comparisons.

An evolutionary game-theoretic analysis of construction workers' unsafe behavior: Considering incentive and risk loss

The behavior of construction workers has a significant impact on the overall safety climate of a project. The purpose of this paper is to figure out the evolutionary pattern of workers' unsafe behavior and to minimize its occurrence. We constructed a two-sided evolutionary game model consisting of workers and managers to explore the focal point of interest, strategy equilibrium conditions, and behavior evolution process. The experimental results of stability analysis and system dynamics show that there are two stable states in all four cases, (Safe behavior, Negative management) as well as (Unsafe behavior, Negative management). The lower the initial willingness of workers to behave unsafely, the faster they reach a safe steady state. By contrast, managers' strategy choices have a certain lag. Workers are discouraged from choosing unsafe behavior under both the positive incentive of raising bonuses and the negative incentive of raising fines. And the sensitivity of the two incentives is similar. For indirect effect risk loss, when it is effectively controlled during safe construction, workers quickly gravitate toward safe behavior. These findings provide a reference for construction safety management. Several practical suggestions were proposed from three perspectives: the worker, the manager, and the site safety climate, focus on the theme of reducing unsafe behavior and achieving a virtuous cycle of safety climate.

Evolution of cooperation and trust in an N-player social dilemma game with tags for migration decisions

We present an evolutionary game model that integrates the concept of tags, trust and migration to study how trust in social and physical groups influence cooperation and migration decisions. All agents have a tag, and they gain or lose trust in other tags as they interact with other agents. This trust in different tags determines their trust in other players and groups. In contrast to other models in the literature, our model does not use tags to determine the cooperation/defection decisions of the agents, but rather their migration decisions. Agents decide whether to cooperate or defect based purely on social learning (i.e. imitation from others). Agents use information about tags and their trust in tags to determine how much they trust a particular group of agents and whether they want to migrate to that group. Comprehensive experiments show that the model can promote high levels of cooperation and trust under different game scenarios, and that curbing the migration decisions of agents can negatively impact both cooperation and trust in the system. We also observed that trust becomes scarce in the system as the diversity of tags increases. This work is one of the first to study the impact of tags on trust in the system and migration behaviour of the agents using evolutionary game theory.

An Evolutionary Numerical Method of Supply Chain Trust Networks with the Degree of Distribution

We study the structure of supply chain trust networks (SCTNs) by analyzing the evolution of the networks. An SCTN here comprises enterprises in a fully competitive market connected through the preferential attachment mechanism. A Markov chain analysis is used to understand how various factors affect the structure of the SCTNs. The evolution of the SCTNs is also analyzed to identify the asymmetric conditions required for the degree distribution of the SCTNs to obey the power law distribution. The simulation results show that, when the degree of willingness to initiate a trust relationship and the attractiveness index of the supply chain networks meet certain criteria, the underlying network is of a scale-free nature.