| Project/Area Number |
09630111
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Business administration
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| Research Institution | University of Tokyo |
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Principal Investigator |
TAKAHASHI Nobuo Professor, Graduate School of Economics, University of Tokyo, 大学院・経済学研究科, 教授 (30171507)
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| Project Period (FY) |
1997 – 2000
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| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥3,400,000 (Direct Cost: ¥3,400,000)
Fiscal Year 2000: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 1999: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 1998: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 1997: ¥1,400,000 (Direct Cost: ¥1,400,000)
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| Keywords | organizational ecology / intraorganizational ecology / agent-based model / organizational learning / organizational routine / complexity / computer simulation / communication competition model (ComCom Model) / エコロジカル・モデル / マルチ・エージェント / 学習曲線 / ゲートキーパー / 製品開発論 / 生態学的モデル / シミュレーション / 組織間関係 / 生存時間解析 / マルチエージェント / 意思決定原理 / 未来傾斜原理 / 終身コミットメント / 生態学モデル / 組織学習モデル / 組織慣性 |
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| Research Abstract |
This study considers ecological aspects of managerial evolution. The ecological structure of organizational learning complicates the systematic modeling of learning process. First, this study describes and criticizes the computer simulation model of mutual learning developed by J.G.March. His simulation model has pitfalls in analyzing non-equilibrium lock-in, and he draws a wrong and opposite conclusion. We formulate an Excel version of March's simulation model in order to trace the causes of lock-in phenomena and equilibrium in the intraorganizational ecology of learning. On the basis of proper evidence, we reach a sound and logical conclusion that the persistence of organizational routine is a necessary condition to obtain a good organizational performance.
Second, this study is to analyze the emerging process of organizations by using agent-based simulation. The agent-based simulation is one of the representative methods of complexity research and recently used to learn from local problems and to devise a global solution. We develop an agent-based communication competition model which is familiarly called "ComCom Model." The implications of the simulations are as follows : (1) The big agents cannot win small agents over their side. (2) The big agents increase the emerging speed of the large clusters in the start up phase. However, they cannot improve clusters' communication performance in the steady phase. (3) The big agents are not at the centers of the clusters. They move around at outskirts of the clusters. It looks like tentacles. (4) The wandering model of agents having high propensity to change has never reached any equilibrium points. But the wandering model improves clusters' communication performance in comparison with the bounded rational and equilibrium model.
(270 words)
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