IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/75214.html
   My bibliography  Save this paper

Trust and Performance: Exploring Socio-Economic Mechanisms in the “Deep” Network Structure with Agent-Based Modeling

Author

Listed:
  • Gao, Lin

Abstract

This paper extends the concept of interaction platforms and explores the evolution of interaction and cooperation supported by individuals’ changing trust and trustworthiness on directed weighted regular ring network from the angle of micro scope by using agent-based modeling. This agent-based model integrates several considerations below via a relatively delicate experimental design: 1) a characteristic of trust is that trust is destroyed easily and built harder (Slovic, 1993); 2) trustworthiness may be reflected on both strategy decision and payoff structure decision; 3) individuals can decide whether or not to be involved in an interaction; 4) interaction density exists, not only between neighbors and strangers (Macy and Skvoretz, 1998), but also within neighbors; 5) information diffusion. In this agent-based model, marginal rate of exploitation of original payoff matrix and relative exploitation degree between two payoff matrices are stressed in their influence of trust-destroying; influence of observing is introduced via imagined strategy; relationship is maintained through relationship maintenance strength, and so on. This paper treats number of immediate neighbors, degree of embeddedness in social network, mutation probability of payoff matrix, mutated payoff matrix, proportion of high trust agents and probabilities of information diffusion within neighborhood and among non-neighbors as important aspects happening on interaction platforms, and the influences of these factors are probed respectively on the base of a base-line simulation.

Suggested Citation

  • Gao, Lin, 2016. "Trust and Performance: Exploring Socio-Economic Mechanisms in the “Deep” Network Structure with Agent-Based Modeling," MPRA Paper 75214, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:75214
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/75214/1/MPRA_paper_75214.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wolfram Elsner, 2007. "Why Meso? On “Aggregation” and “Emergence”, and Why and How the Meso Level is Essential in Social Economics," Forum for Social Economics, Taylor & Francis Journals, vol. 36(1), pages 1-16, January.
    2. John Geanakoplos & Robert Axtell & J. Doyne Farmer & Peter Howitt & Benjamin Conlee & Jonathan Goldstein & Matthew Hendrey & Nathan M. Palmer & Chun-Yi Yang, 2012. "Getting at Systemic Risk via an Agent-Based Model of the Housing Market," American Economic Review, American Economic Association, vol. 102(3), pages 53-58, May.
    3. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    4. Viktoria Spaiser & David J. T. Sumpter, 2016. "Revising the Human Development Sequence Theory Using an Agent-Based Approach and Data," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(3), pages 1-1.
    5. Wolfram Elsner & Henning Schwardt, 2015. "From Emergent Cooperation to Contextual Trust, and to General Trust: Overlapping Meso-Sized Interaction Arenas and Cooperation Platforms as a Foundation of Pro-Social Behavior," Forum for Social Economics, Taylor & Francis Journals, vol. 44(1), pages 69-86, April.
    6. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2, 00.
    7. Shu-Heng Chen & Bin-Tzong Chie & Tong Zhang, 2015. "Network-Based Trust Games: An Agent-Based Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-5.
    8. Whan-Seon Kim, 2009. "Effects of a Trust Mechanism on Complex Adaptive Supply Networks: An Agent-Based Social Simulation Study," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(3), pages 1-4.
    9. Wolfram Elsner, 2010. "The process and a simple logic of ‘meso’. Emergence and the co-evolution of institutions and group size," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 445-477, June.
    10. Nicholas Seltzer & Oleg Smirnov, 2015. "Degrees of Separation, Social Learning, and the Evolution of Cooperation in a Small-World Network," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(4), pages 1-12.
    11. Elsner, Wolfram & Heinrich, Torsten, 2009. "A simple theory of 'meso'. On the co-evolution of institutions and platform size--With an application to varieties of capitalism and 'medium-sized' countries," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 38(5), pages 843-858, October.
    12. A. Pyka & G. Fagiolo, 2007. "Agent-based Modelling: A Methodology for Neo-Schumpetarian Economics," Chapters, in: Horst Hanusch & Andreas Pyka (ed.), Elgar Companion to Neo-Schumpeterian Economics, chapter 29, Edward Elgar Publishing.
    13. Elsner, Wolfram & Schwardt, Henning, 2014. "Trust and arena size: expectations, institutions, and general trust, and critical population and group sizes," Journal of Institutional Economics, Cambridge University Press, vol. 10(1), pages 107-134, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Andrea Venturelli & Fabio Caputo & Simone Pizzi, 2018. "L’impatto del contratto di rete nei processi di internazionalizzazione: alcune evidenze empiriche sulle PMI italiane," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(2), pages 61-83.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gao, Lin, 2017. "Between Trust and Performance: Exploring Socio-Economic Mechanisms on Directed Weighted Regular Ring with Agent-Based Modeling," MPRA Paper 78428, University Library of Munich, Germany.
    2. G. Fagiolo & A. Roventini., 2009. "On the Scientific Status of Economic Policy: A Tale of Alternative Paradigms," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 6.
    3. Bolt, Wilko & Demertzis, Maria & Diks, Cees & Hommes, Cars & Leij, Marco van der, 2019. "Identifying booms and busts in house prices under heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 103(C), pages 234-259.
    4. Elsner, Wolfram, 2015. "Policy Implications of Economic Complexity and Complexity Economics," MPRA Paper 63252, University Library of Munich, Germany.
    5. Rengs, Bernhard & Scholz-Waeckerle, Manuel, 2017. "Consumption & Class in Evolutionary Macroeconomics," MPRA Paper 80021, University Library of Munich, Germany.
    6. Paola Tubaro, 2011. "Computational Economics," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 10, Edward Elgar Publishing.
    7. Elsner, Wolfram & Schwardt, Henning, 2015. "The (dis-)embedded firm: Complex structure and dynamics in inter-firm relations. Adding institutionalization as a Veblenian dimension to the Coase-Williamson approach – An emerging triangular organiza," MPRA Paper 67193, University Library of Munich, Germany.
    8. Kirill S. Glavatskiy & Mikhail Prokopenko & Adrian Carro & Paul Ormerod & Michael Harre, 2020. "Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large scale agent-based model," Papers 2004.07571, arXiv.org.
    9. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2017. "Taming macroeconomic instability: Monetary and macro-prudential policy interactions in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 117-140.
    10. Richard Bookstaber & Mark Paddrik & Brian Tivnan, 2018. "An agent-based model for financial vulnerability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(2), pages 433-466, July.
    11. Giorgio Fagiolo & Alessio Moneta & Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 195-226, October.
    12. Trond G. Husby & Elco E. Koks, 2017. "Household migration in disaster impact analysis: incorporating behavioural responses to risk," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(1), pages 287-305, May.
    13. Thomas Ankenbrand & Fabian Kostadinov & Faten Ben Bouheni & Mondher Bellalah, 2020. "Cyclical behaviour of the Swiss real estate market," International Journal of Entrepreneurship and Small Business, Inderscience Enterprises Ltd, vol. 39(1/2), pages 71-99.
    14. Bernardo Alves Furtado, 2022. "PolicySpace2: Modeling Markets and Endogenous Public Policies," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 25(1), pages 1-8.
    15. Gualdi, Stanislao & Tarzia, Marco & Zamponi, Francesco & Bouchaud, Jean-Philippe, 2015. "Tipping points in macroeconomic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 29-61.
    16. Stuart Holland & Andrew Black, 2018. "Cherchez la Firme: Redressing the Missing – Meso – Middle in Mainstream Economics," Economic Thought, World Economics Association, vol. 7(2), pages 15-53, November.
    17. Marcelo De Carvalho Pereira, 2014. "When Competition May Hinder Technologydiffusion: The Case Of Internet Access Services In Brazil," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 152, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    18. Steven Kimbrough & Frederic Murphy, 2009. "Learning to Collude Tacitly on Production Levels by Oligopolistic Agents," Computational Economics, Springer;Society for Computational Economics, vol. 33(1), pages 47-78, February.
    19. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    20. Bernhard Rengs & Manuel Scholz-Wäckerle, 2019. "Consumption & class in evolutionary macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 229-263, March.

    More about this item

    Keywords

    Trust; trustworthiness; directed weighted regular ring network; agent-based modeling; marginal rate of exploitation; relative exploitation degree; imagined strategy; relationship maintenance strength; number of neighbors; degree of embeddedness in social network; mutation of payoff matrix; information diffusion; social mobility; institutional quality; evolution of interaction; evolution of cooperation;
    All these keywords.

    JEL classification:

    • B52 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Historical; Institutional; Evolutionary; Modern Monetary Theory;
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:75214. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.