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

Gao, Lin (2016): Trust and Performance: Exploring Socio-Economic Mechanisms in the “Deep” Network Structure with Agent-Based Modeling.

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.

• Item Type: MPRA Paper
• Language: English
• 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
• Subjects: B - History of Economic Thought, Methodology, and Heterodox Approaches > B5 - Current Heterodox Approaches > B52 - Institutional ; Evolutionary; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling; D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D82 - Asymmetric and Private Information ; Mechanism Design; D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D85 - Network Formation and Analysis: Theory

References

Axelrod, R.M., 1997. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press.

Axelrod, R.M., 1984/2006. The Evolution of Cooperation. rev. ed 2006. Basic Books, New York. Banisch, S., Lima, R., Araújo, T., 2012. Agent based models and opinion dynamics as Markov chains. Social Networks, Vol.34, pp.549-561.

Chen, S.-H., Chie, B.-T., Zhang, T., 2015. Network-Based Trust Games: An Agent-Based Model. The Journal of Artificial Societies and Social Simulation, 18(3)5, <http://jasss.soc.surrey.ac.uk/18/3/5.html>.

Dai, S., 2015. Networks of Institutions: Institutional emergence, social structure and national systems of policies. Routledge, London, UK/New York, NY.

Elsner, W., 2007. Why Meso? On “aggregation” and “Emergence”, and why and How the Meso Level is Essential in Social Economics. Forum for Social Economics, Vol.36, No.1, pp.1-16.

Elsner, W., 2010. The Process and a Simple Logic of ‘Meso’. Emergence and the Co-evolution of Institutions and Group Size. Journal of Evolutionary Economics, Vol.20, No.3, pp.445-477.

Elsner, W., Heinrich, T., 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. The Journal of Socio-Economics, Vol.38, No.5, pp. 843-858.

Elsner, W., and Heinrich, T., 2011. Coordination on ‘Meso’-Levels: On the Co-evolution of Institutions, Networks and Platform Size. In S Mann (Ed.), Sectors matter! Exploring mesoeconomics (pp. 115-163). Berlin: Springer.

Elsner, W., Schwardt, H., 2014. Trust and Arena Size: Expectations, Institutions, and General Trust, and Critical Population and Group Sizes. Journal of Institutional Economics, Vol.10, No.1, pp.107-134.

Elsner, W., Schwardt, H., 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, Vol.44, No.1, pp.69-86.

Geanakoplos J., Axtell, R., Farmer, J.D., Howitt, P., Conlee, B., Goldstein, J., Hendrey, M., Palmer, N.M., Yang, C.-Y., 2012. Getting at Systemic Risk via an Agent-Based Model of the Housing Market. American Economic Review, Vol.102, No.3, pp. 53-58.

Gilbert, N., 2008. Agent-Based Models. Series: Quantitative Applications in the Social Sciences. SAGE Publications, No.153.

Gowdy, J., Mazzucato, M., van den Bergh, J.C.J.M., van der Leeuw, S.E., Wilson, D.S., 2016. Shaping the Evolution of Complex Societies. In: Wilson, D.S., Kirman, A. (Eds.), Complexity and Evolution: Toward a New Synthesis for Economics. The MIT Press, Cambridge, Massachusetts/ London, England, pp.327-350.

Kim, W.-S., 2009. Effects of a Trust Mechanism on Complex Adaptive Supply Networks: An Agent-Based Social Simulation Study, The Journal of Artificial Societies and Social Simulation, 12 (3) 4, <http://jasss.soc.surrey.ac.uk/12/3/4.html>.

Macy, M.W., Skvoretz, J., 1998. The Evolution of Trust and Cooperation between Strangers: A Computational Model. American Sociological Review, Vol.63, No.5, pp. 638-660.

Macy, M.W., Willer, R., 2002. From Factors to Actors: Computational Sociology and Agent-Based Modeling. Annual Review of Sociology, Vol. 28, pp. 143-166.

Pyka, A., Fagiolo, G., 2005. Agent-based Modelling: A Methodology for Neo-Schumpeterian Economics. In: Hanusch, H., Pyka, A. (Eds.), The Elgar Companion to Neo-Schumpeterian Economics. Edward Elgar, Cheltenham.

Seltzer, N., Smirnov, O., 2015. Degrees of Separation, Social Learning, and the Evolution of Cooperation in a Small-World Network. The Journal of Artificial Societies and Social Simulation, 18(4)12, <http://jasss.soc.surrey.ac.uk/18/4/12.html>.

Slovic, P., 1993. Perceived Risk, Trust, and Democracy. Risk Analysis, Vol.13, No.6, pp.675-682.

Spaiser, V., Sumpter, D.J.T., 2016. Revising the Human Development Sequence Theory Using an Agent-Based Approach and Data. The Journal of Artificial Societies and Social Simulation, 19(3)1, <http://jasss.soc.surrey.ac.uk/19/3/1.html>.

Tesfatsion, L., Judd, K.L. (Eds.), 2006. Handbook of Computational Economics Volume 2: Agent-Based Computational Economics. Elsevier, Amsterdam.

Tran, T., Cohen, R., 2004. Improving User Satisfaction in Agent-Based Electronic Marketplaces by Reputation Modelling and Adjustable Product Quality. AAMAS’04: Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems (Washington, DC, USA), IEEE Computer Society, pp. 828-835.