The relationship of the source of punishment and personality traits with investment and punishment in a public goods game

In this study, we investigated the motivations behind punishing individuals who exploit common resources, a phenomenon crucial for resource preservation. While some researchers suggest punishment stems from concern for the common good, others propose it is driven by anger toward free riders. To probe these motivations, we developed a modified public goods game in which participants had the option to use their own money or the money from the common pool to punish free riders. The analysis included choice behavior, mouse trajectories, and personality traits like anger, empathy, and altruism. According to our results, investments were highest, and punishment was strongest if participants could punish using credits from the common pool, indicating that this is the preferred option to diminish free riding and maintain cooperation in public goods and common good contexts. Also, punishment was highest if the punisher's own investment was high, and the investment of others was low. Concerning traits, highly altruistic individuals tended to invest more and punish less in general but gave harsher punishments when they did choose to use the common pool punitively. Conversely, trait anger and trait empathy were linked to low investment while trait empathy also tended to be related to lower punishment. Taken together, these findings underscore the role of situational factors and personality traits in fostering cooperative behavior and shaping societal norms around costly punishment.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-09-09
DOI
https://doi.org/10.1038/s41598-024-71106-x
Primary Topic
Evolutionary Game Theory and Cooperation
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The relationship of the source of punishment and personality traits with investment and punishment in a public goods game

Johannes Rodrigues, Grit Hein, Johannes Hewig, Natasha Leipold
Scientific Reports
Evolutionary Game Theory and Cooperation
article

The relationship of the source of punishment and personality traits with investment and punishment in a public goods game

Johannes Rodrigues, Grit Hein, Johannes Hewig, Natasha Leipold
article en

Abstract

In this study, we investigated the motivations behind punishing individuals who exploit common resources, a phenomenon crucial for resource preservation. While some researchers suggest punishment stems from concern for the common good, others propose it is driven by anger toward free riders. To probe these motivations, we developed a modified public goods game in which participants had the option to use their own money or the money from the common pool to punish free riders. The analysis included choice behavior, mouse trajectories, and personality traits like anger, empathy, and altruism. According to our results, investments were highest, and punishment was strongest if participants could punish using credits from the common pool, indicating that this is the preferred option to diminish free riding and maintain cooperation in public goods and common good contexts. Also, punishment was highest if the punisher's own investment was high, and the investment of others was low. Concerning traits, highly altruistic individuals tended to invest more and punish less in general but gave harsher punishments when they did choose to use the common pool punitively. Conversely, trait anger and trait empathy were linked to low investment while trait empathy also tended to be related to lower punishment. Taken together, these findings underscore the role of situational factors and personality traits in fostering cooperative behavior and shaping societal norms around costly punishment.

Scientific ReportsVol. 14(1)
University of Würzburg (DE), Universitätsklinikum Würzburg (DE)
Julius-Maximilians-Universität Würzburg, European Regional Development Fund
Openalex Percentile: Top 76%
Evolutionary Game Theory and Cooperation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.