The impact of reputation-based dynamic reward mechanism on the evolution of fairness

In real life, a positive reputation usually provides individuals with additional benefits. Reward mechanisms within organizations are generally adjusted dynamically in accordance with the actual circumstances of the groups being rewarded. The main purpose of these adjustments is to optimize motivational outcomes while ensuring the most effective use of limited reward resources. Considering this within a small-world networked ultimatum game model, we introduce a reputation-based dynamic reward mechanism, aiming to encourage fairness behaviors within populations. Specifically, each individual has a unique reputation threshold, which is determined by a combination of the average reputation of their neighbors and the overall global reputation. Individuals are rewarded only when their reputations exceed these personalized thresholds. The extent to which an individual’s past reputation is retained over time is governed by a decay factor. Moreover, the reward strength is inversely related to the proportion of individuals who qualify for rewards at any given time. We investigate the dynamic interplay of three key parameters—the weight factor, the decay factor, and the rate of change in reward strength—on the evolution of fairness behaviors. Simulation outcomes show that the reputation-based dynamic reward mechanism significantly promotes the emergence of fairness within population. Specifically, higher values of the weight factor and lower values of the decay factor are found to strongly encourage fair behavior. Additionally, a slower rate of change in reward strength further enhances fairness. These findings contribute to the theoretical understanding of fairness dynamics in social systems and offer practical guidance for designing effective personalized incentive mechanisms.