The Ecological Simulation Approach to The Evolution of Interorganizational Relations

组织间关系演化的生态模拟方法

基本信息

批准号：
09630111
负责人：
TAKAHASHI Nobuo
金额：
$ 2.18万
依托单位：
University of Tokyo
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1997
资助国家：
日本
起止时间：
1997 至 2000
项目状态：
已结题

项目摘要

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)

这项研究考虑了管理进化的生态方面。组织学习的生态结构使学习过程的系统建模变得复杂。首先，本研究描述并批评J.G. March开发的相互学习的计算机模拟模型。他的仿真模型在分析非平衡锁定时具有陷阱，他得出了一个错误和相反的结论。我们制定了March的模拟模型的Excel版本，以追踪学习的锁定现象的原因和均衡性的学习生态学。根据适当的证据，我们得出一个合理的结论，即组织常规的持久性是获得良好组织绩效的必要条件。第二，本研究是通过使用基于代理的模拟来分析组织的新兴过程。基于代理的仿真是复杂性研究的代表性方法之一，最近用于从当地问题中学习并设计全球解决方案。我们开发了一个基于代理的通信竞争模型，该模型被称为“ COMCOM模型”。模拟的含义如下：（1）大型代理商不能赢得小型代理商的身边。（2）大型代理在启动阶段提高了大簇的新兴速度。但是，他们无法在稳定阶段提高集群的沟通性能。（3）大型代理不在集群中心。他们在集群的郊区四处走动。看起来像触手。（4）具有高变化倾向的代理的流浪模型从未达到任何平衡点。但是，与有限的有理和均衡模型相比，流浪模型可以改善集群的沟通性能。（270个单词）