Agent-based computational transaction cost economics☆

Inter-firm relations in general, and buyer–supplier relations in particular, have increasingly been analyzed by means of transaction cost economics (TCE). However, as has been widely acknowledged, TCE does not include any dynamics of learning, adaptation or innovation. Williamson himself (1985, p. 144) admitted that ‘the study of economic organization in a regime of rapid innovation poses much more difficult issues than those addressed here’. A more fundamental problem is that as in economics more in general it is assumed rather than investigated that efficient outcomes will arise. Here, in inter-firm relations, it is assumed that optimal forms of organization or governance will arise, suited to characteristics of transactions such as the need for transaction-specific investments, frequency of transactions, and uncertainty concerning conditions that may affect future transactions (Williamson 1975, Williamson 1985). Two arguments are used for this: an argument of rationality and an argument of selection.

Williamson granted that rationality is bounded and transactions are subject to radical uncertainty, which precludes complete contingent contracting. But he proceeded to assume a higher level of rationality: people can rationally, calculatively deal with conditions of bounded rationality. Aware of their bounded rationality and radical uncertainty, people rationally design governance structures to deal with those conditions. However, if rationality is bounded, then rationality of dealing with bounded rationality is bounded as well. To rationally calculate economizing on bounded rationality, one would need to know the marginal (opportunity) costs and benefits of seeking further information and of further calculation, but for that one would need to decide upon the marginal costs and benefits of the efforts to find that out. This yields an infinite regress (Hodgson, 1998; Pagano, 1999). Here we accept bounded rationality more fully and deal with it on the basis of the methodology of adaptive agents.

When confronted with arguments against rationality, economists usually concede that assumptions of full rationality are counterfactual, and then resort to the argument of economic selection. We can proceed as if agents make rational, optimal choices, because selection by forces of competition will ensure that only the optimal survives (Alchian, 1950; Friedman, 1953). Williamson was no exception in this respect. He held that in due course, inefficient forms of organization will be selected out by market forces. However, that argument of selection has been shown to be dubious. For example, Winter (1964) showed that in evolution it is not the best conceivable but the best that happens to be available that survives. Due to effects of scale a large firm that is inefficient for its size may win out over efficient small firms. Furthermore, the selection efficiency of markets may be hampered by entry barriers. Koopmans (1957) concluded long ago that if the assumption of efficient outcomes is based on an argument of evolutionary process, its validity should be tested by explicit modelling of that process. Then, particularly in the study of inter-firm relations, we have to take into account the complexities and path-dependencies that may arise in the making and breaking of relations between multiple agents. That is what we aim to do in this article. As Coase (1998) recently admitted:

[t]he analysis cannot be confined to what happens within a single firm. The costs of co-ordination within a firm and the level of transaction costs that it faces are affected by its ability to purchase inputs from other firms, and their ability to supply these inputs depends in part on their costs of co-ordination and the level of transaction costs that they face which are similarly affected by what these are in still other firms. What we are dealing with is a complex interrelated structure.

Following up on Epstein and Axtell's (1996) suggestion, we let the distribution of economic activity across different organizational forms emerge from processes of interaction between these agents, as they adapt future decisions to past experiences. The system may or may not settle down and if it does, the resulting equilibrium may or may not be transaction cost economic. In any case, ‘[i]t is the process of becoming rather than the never-reached end points that we must study if we are to gain insight’ (Holland, 1992, p. 19).

The methodology of artificial adaptive agents, in ACE, seems just the right methodology to deal with this ‘complex interrelated structure’ of ‘processes of interaction in which future decisions are adapted to past experiences’. We use that methodology to model interactions between firms, in the making and breaking of relations on the basis of a boundedly rational, adaptive, mutual evaluation of transaction partners that takes into account trust, costs and profits. We model a system of buyer–supplier relations, because that best illustrates transaction cost issues.

We focus on the role of trust, for two reasons. The first reason is that TCE does not incorporate trust, and this is an area where development of insight has priority. The second reason is that the central feature, in ACE, of adaptation in the light of experience seems particularly relevant to trust (Gulati, 1995; Zucker, 1986; Zand, 1972).

Section 2 briefly characterizes the methodology of agent-based computational economics (ACE) that will be used. Section 3 discusses the issue of trust and opportunism. Section 4 discusses costs and profits of transactions. Then we proceed to explain the design of our model. Section 5 indicates how buyers and suppliers are matched on the basis of their preferences, which include trust next to expected profit. Section 6 shows how we model costs and profits. Section 7 shows how we model trust. Section 8 shows how we model adaptation. Section 9 summarizes the simulation model. Section 10 discusses a few illustrative experiments. Finally, Section 11 discusses limitations and further research.