| Budget Amount *help |
¥2,700,000 (Direct Cost: ¥2,700,000)
Fiscal Year 2004: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2003: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2002: ¥1,100,000 (Direct Cost: ¥1,100,000)
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| Research Abstract |
Economic systems are made of a large number of interacting agents and display also surprising self organizing features and macroscopic order in spite of the underlying disorder among its constituents. It is easy to understand why there is a great temptation to extrapolate that line of thought to account for some basic, stylized facts of economic systems. This approach however amounts to take especially into account the interactions among the agents, and the way in which they coadapt to each other and to regard equilibrium in a more dynamical way.
In this research we construct a virtual market (VM) in computer, and the macro dynamisms of the market are analyzed from the micro point of view. The VM is constructed based on the model of 'Economics of Complex Systems'. Economics of Complex Systems has several features : increasing returns to scale, bounded rationality, self-organization, one-to-one trading, and so on.
In this model, the market consists of three types of heterogeneous agents, named Supply agent, Demand agent, and Intermediate agent. Partnering between supply and demand agent is decided by '4-Heap algorithm'. In this market, supply agents produce one kind of goods, and demand agents consume all kinds of goods. Multiple intermediate agents are existing in this market, and then multiple local 'markets' are formed.
At First, we introduced the idea of economics of complex systems, and the basic market model, which abstracts and simplifies an actual market, was defined and constructed. Then several simulation experiments have been executed to analyse basic characteristics of the VM. Some distinctive characteristics of the price dynamisms have been described in that simulation, and the decision mechanism on the market price has been analysed by the behaviour of each agent. Finally the applicability of the proposed framework into resource allocation problem for supply chain management has been also discussed.
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