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
相关论文
共 50 条
  • [21] Analysis of a Teleworking Technology Adoption Case: An Agent-Based Model
    Arbelaez-Velasquez, Carlos A.
    Giraldo, Diana
    Quintero, Santiago
    SUSTAINABILITY, 2022, 14 (16)
  • [22] A Social Approach to Rule Dynamics Using an Agent-Based Model
    Cuskley, Christine
    Loreto, Vittorio
    Kirby, Simon
    TOPICS IN COGNITIVE SCIENCE, 2018, 10 (04) : 745 - 758
  • [23] Using Ego Network Data to Inform Agent-based Models of Diffusion
    Smith, Jeffrey A.
    Burow, Jessica
    SOCIOLOGICAL METHODS & RESEARCH, 2020, 49 (04) : 1018 - 1063
  • [24] Increasing homeowners' insulation activity in Germany: An empirically grounded agent-based model analysis
    Friege, Jonas
    ENERGY AND BUILDINGS, 2016, 128 : 756 - 771
  • [25] The Effects of Mental Model Formation on Group Decision Making: An Agent-Based Simulation
    Sayama, Hiroki
    Farrell, Dene L.
    Dionne, Shelley D.
    COMPLEXITY, 2011, 16 (03) : 49 - 57
  • [26] SYSTEMIC RISK OF THE GLOBAL BANKING SYSTEM - AN AGENT-BASED NETWORK MODEL APPROACH
    Klinger, Tomas
    Teply, Petr
    PRAGUE ECONOMIC PAPERS, 2014, 23 (01): : 24 - 41
  • [27] A framework for the comparison of errors in agent-based models using machine learning
    Beerman, Jack T.
    Beaumont, Gwendal G.
    Giabbanelli, Philippe J.
    JOURNAL OF COMPUTATIONAL SCIENCE, 2023, 72
  • [28] A multicriteria integral framework for agent-based model calibration using evolutionary multiobjective optimization and network-based visualization
    Moya, Ignacio
    Chica, Manuel
    Cordon, Oscar
    DECISION SUPPORT SYSTEMS, 2019, 124
  • [29] COMPARATIVE ANALYSIS OF METAMODELING TECHNIQUES BASED ON AN AGENT-BASED SUPPLY CHAIN MODEL
    Edali, Mert
    Yucel, Gonenc
    32ND EUROPEAN CONFERENCE ON MODELLING AND SIMULATION (ECMS 2018), 2018, : 114 - 120
  • [30] Transition pathways of household heating in Serbia: Analysis based on an agent-based model
    Pavlovic, Boban
    Ivezic, Dejan
    Zivkovic, Marija
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2022, 163