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

Author(s)
Anjos, Fernando; Reagans, Ray Eugene
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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.
Date issued
2012-12
URI
http://hdl.handle.net/1721.1/73907
Department
Sloan School of Management
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
ISSN
0022-250X
1545-5874

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