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Chance, or serendipity, plays a crucial role in socio-economic success. Over-reliance on imitation can lead to unfair outcomes, while embracing chance promotes more equitable results.

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Area of Science:

  • Socio-economics
  • Agent-based modeling
  • Complexity science

Background:

  • Socio-economic systems often rank participants by performance.
  • Rankings simplify complex systems but may not reflect true merit.
  • Chance (serendipity) influences success, yet its role is often underestimated.

Purpose of the Study:

  • Investigate the tradeoff between imitation and serendipity in determining success.
  • Analyze how different strategies affect outcomes in ranked systems.
  • Understand the dynamics of meritocracy versus egalitarianism.

Main Methods:

  • Developed an agent-based model to simulate socio-economic interactions.
  • Agents switch actions via imitation or random selection (serendipity).
  • Analyzed outcomes based on the prevalence of imitation versus chance.

Main Results:

  • High imitation leads to coordination on a single action, resulting in non-meritocratic outcomes.
  • A minority accumulates most payoffs, not necessarily due to superior skill.
  • Dominance of serendipity leads to more egalitarian outcomes.
  • A sharp transition separates imitation-driven and serendipity-driven regimes.

Conclusions:

  • The balance between imitation and serendipity significantly impacts fairness in socio-economic systems.
  • Over-imitation can obscure true merit and create inequalities.
  • Promoting serendipity can foster more equitable distribution of success.