Commitment, Learning, and Alliance Performance: A Formal Analysis Using an Agent-Based Network Formation Model

Authored by Fernando Anjos, Ray Reagans

Date Published: 2013-01-01

DOI: 10.1080/0022250x.2012.724600

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

Current theoretical arguments highlight a dilemma faced by actors who either adopt a weak or strong commitment strategy for managing their alliances and partnerships. Actors who pursue a weak commitment strategythat is, immediately abandon current partners when a more profitable alternative is presentedare more likely to identify the most rewarding alliances. On the other hand, actors who enact a strong commitment approach are more likely to take advantage of whatever opportunities can be found in existing partnerships. Using agent-based modeling, we show that actors who adopt a moderate commitment strategy overcome this dilemma and outperform actors who adopt either weak or strong commitment approaches. We also show that avoiding this dilemma rests on experiencing a related tradeoff: moderately-committed actors sacrifice short-term performance for the superior knowledge and information that allows them to eventually do better. [Supplementary material is available for this article. Go to the publisher's online edition of The Journal of Mathematical Sociology for the following free supplemental resource: Technical Appendix.]

Tags

Social networks Agent-based modeling commitment