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

被引:10
作者
Anjos, Fernando [1 ]
Reagans, Ray [2 ]
机构
[1] Univ Texas Austin, Dept Finance, McCombs Sch Business, Austin, TX 78751 USA
[2] MIT, Alfred P Sloan Sch Management, Behav & Policy Sci Dept, Cambridge, MA 02139 USA
关键词
agent-based modeling; commitment; social networks; STRUCTURAL HOLES; EMBEDDEDNESS; TIES; KNOWLEDGE; MARKET;
D O I
10.1080/0022250X.2012.724600
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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.]
引用
收藏
页码:1 / 23
页数:23
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