This article explores the use of 'agent-based computational economics' (ACE) for modelling the development of transactions between firms. Transaction cost economics neglects learning and the development of trust, ignores the complexity of multiple agents, and assumes rather than investigates the efficiency of outcomes. Efficiency here refers to minimum cost or maximum profit. We model how co-operation and trust emerge and shift adaptively as relations evolve in a context of multiple, interacting agents. This may open up a new area of application for the ACE methodology. A simulation model is developed in which agents make and break transaction relations on the basis of preferences, based on trust and potential profit. Profit is a function of product differentiation, specificity of assets, economy of scale and learning by doing in ongoing relations. Agents adapt their trust in a partner as a function of his loyalty, exhibited by his continuation of a relation. They also adapt the weight they attach to trust on the basis of realized profit. The model enables an assessment of the efficiency of outcomes relative to the optimum, as a function of trust and market conditions. We conduct a few experiments to illustrate this application of ACE.

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doi.org/10.1016/S0165-1889(00)00034-8, hdl.handle.net/1765/71036
Journal of Economic Dynamics and Control
Erasmus Research Institute of Management

Klos, T., & Nooteboom, B. (2001). Agent-based computational transaction cost economics. Journal of Economic Dynamics and Control, 25(3-4), 503–526. doi:10.1016/S0165-1889(00)00034-8