Quantifying the Selective, Stochastic, and Complementary Drivers of Institutional Evolution in Online Communities.

Area of Science:

• Evolutionary Social Science
• Organizational Behavior
• Computational Social Science

Background:

• Institutions and cultures adapt to environmental pressures.
• However, non-adaptive factors like drift and imitation also drive institutional change.
• Understanding both selective and stochastic influences is key to organizational development.

Purpose of the Study:

• To empirically disentangle selective and stochastic drivers of institutional change.
• To identify key features of long-term organizational development.
• To analyze evolutionary dynamics in large-scale digital communities.

Main Methods:

• Utilized the Price equation and bet-hedging models for empirical measurement.
• Analyzed a dataset of 20,000 Minecraft communities.
• Quantified the influence of selection and stochasticity on rule frequency.

Main Results:

• Identified strong selection pressure on administrative and information rules, correlating with community fitness.
• Observed that stochastic drivers reduce the frequency of administrative rules.
• Demonstrated that institutional diversity, via bet-hedging, enhances rule stability in information, communication, and economic behaviors.

Conclusions:

• Selection is a primary driver for adaptive rules in organizations.
• Stochastic processes can decrease the prevalence of certain institutional rules.
• Promoting institutional diversity supports robust and growing organizational systems.