An evolutionary game model with reputation threshold and reputation score to promote trust in the sharing economy

This paper presents an evolutionary trust game model that sets a reputation threshold and implements a reward mechanism for participants whose individual reputation scores are above this threshold; conversely, a punishment mechanism is applied to those whose scores are below it, to investigate the formation of trust in the sharing economy. By conducting simulation experiments, we present the dynamic evolution of the proportion of four types of participants as the reputation threshold increases under five different initial scenarios. Additionally, we provide heatmaps to detailedly show the strategy and reputation score evolution of 10,000 participants over time steps when the reputation threshold is low, moderate, and high. Our results indicate that when the initial proportion of trustworthy participants is equal to that of untrustworthy participants, a higher reputation threshold facilitates the establishment of trust. Even if the initial proportion of trustworthy participants is lower than that of untrustworthy participants, there still exist some appropriate reputation thresholds that can promote the total proportion of trustworthy participants to reach 100% eventually. Furthermore, the heatmaps of strategy evolution indicate that a higher reputation threshold also results in untrustworthy participants, whether providers or consumers, eventually forming clusters of the same strategy, making it impossible for them to engage in transactions with their neighbors, thereby reducing the occurrence of untrustworthy transactions. In contrast, the two trustworthy strategies are found to be evenly interdependent.Additionally, it is observed that a higher reputation threshold gradually narrows the gap between the proportions of trustworthy providers and consumers during the evolution process, potentially reducing it to zero, which is conducive to achieving supply-demand balance.