Status maximization as a source of fairness in a networked dictator game

TL;DR

This paper proposes that humans aim to maximize their social status, which explains both selfish and altruistic behaviors, demonstrated through an agent-based model of repeated dictator games on social networks.

Contribution

It introduces a status maximization framework to unify selfish and altruistic behaviors and analyzes how social network dynamics emerge from this perspective.

Findings

Strategies range from selfish to selfless

Living costs influence network cohesion

Memory of infractions affects social structure formation

Abstract

Human behavioural patterns exhibit selfish or competitive, as well as selfless or altruistic tendencies, both of which have demonstrable effects on human social and economic activity. In behavioural economics, such effects have traditionally been illustrated experimentally via simple games like the dictator and ultimatum games. Experiments with these games suggest that, beyond rational economic thinking, human decision-making processes are influenced by social preferences, such as an inclination to fairness. In this study we suggest that the apparent gap between competitive and altruistic human tendencies can be bridged by assuming that people are primarily maximising their status, i.e., a utility function different from simple profit maximisation. To this end we analyse a simple agent-based model, where individuals play the repeated dictator game in a social network they can modify. As model parameters we consider the living costs and the rate at which agents forget infractions by others. We find that individual strategies used in the game vary greatly, from selfish to selfless, and that both of the above parameters determine when individuals form complex and cohesive social networks.