Figure 4. Probability of acceptance as a function of proposed workload and power treatment. Error bars are 95% Agresti-Coull approximate confidence intervals. We find monotonic acceptance rate, except for few hyperfair offers in the “balanced” treatment. Different treatment elicit different bargaining behaviors.

Power and Fairness in a Generalized Ultimatum Game

Figure 4. Probability of acceptance as a function of proposed workload and power treatment. Error bars are 95% Agresti-Coull approximate confidence intervals. We find monotonic acceptance rate, except for few hyperfair offers in the “balanced” treatment. Different treatment elicit different bargaining behaviors.

Power and Fairness in a Generalized Ultimatum Game

Abstract

Power is the ability to influence others towards the attainment of specific goals, and it is a fundamental force that shapes behavior at all levels of human existence. Several theories on the nature of power in social life exist, especially in the context of social influence. Yet, in bargaining situations, surprisingly little is known about its role in shaping social preferences. Such preferences are considered to be the main explanation for observed behavior in a wide range of experimental settings. In this work, we set out to understand the role of bargaining power in the stylized environment of a Generalized Ultimatum Game (GUG). We modify the payoff structure of the standard Ultimatum Game (UG) to investigate three situations: two in which the power balance is either against the proposer or against the responder, and a balanced situation. We find that other-regarding preferences, as measured by the amount of money donated by participants, do not change with the amount of power, but power changes the offers and acceptance rates systematically. Notably, unusually high acceptance rates for lower offers were observed. This finding suggests that social preferences may be invariant to the balance of power and confirms that the role of power on human behavior deserves more attention.

Publication
PLOS ONE 9 (6) p. 1–9
Date

For a more advanced platform to conduct online real-time synchronous experiments, please see also nodeGame by Stefano Balietti.