Commitment, Learning, and Alliance Performance: A Formal Analysis Using an Agent-Based Network Formation Model
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commitment_final.pdf
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356.67 KB
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Author(s)
Anjos, Fernando
Reagans, Ray Eugene
Date Issued
December 2012
Journal
Journal of Mathematical Sociology
Citation
Anjos, Fernando, and Ray Reagans. “Commitment, Learning, and Alliance Performance: A Formal Analysis Using an Agent-Based Network Formation Model.” The Journal of Mathematical Sociology 37.1 (2013): 1–23.
Version
Author's final manuscript
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 strategy|i.e. immediately abandon current
partners when a more pro table alternative is presented|are 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 tradeo : moderately-committed actors sacri ce
short-term performance for the superior knowledge and information that allows them
to eventually do better.
MIT Department
Sloan School of Management
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.1080/0022250X.2012.724600
https://doi.org/10.1080/0022250X.2012.724600
