Organizational Learning Oriented Model of Organizational Adaptation

This paper proposes an agent-based simulation model for analyzing adaptive processes of organizations with organizational learning. The model is based on a framework of organizational cybernetics and represents organizational activities both decision-makings and task resolutions. Organizational cybernetics helps us to grasp an organization concretely as an aggregation of functions. The model provides four functional layers (self-organization, adaptation, coordination, and process) and interactions among them. The activities of decision-makings correspond to processes of organizational learning, and the activities of task resolutions are performed as in Computational Organization Theory (COT). In the COT it should be pointed out that there are few researches to introduce both functional hierarchies and the concept of the organizational learning in each functional layer. In each functional layer, the organizational learning realizes the progress of the ability of making decisions to fulfill good performances of the organization as a whole. In this paper we confirm several desired factors on effective criteria in an adaptive learning mechanism: how to learn for the adaptation to the environment in each functional layer? In each functional layer, we propose better criteria for the organizational performance. In the self-organization and the adaptation layer, it works to use the inter-organizational learning for the evaluation of individuals’ internal models. And in the coordination and the process layer, it is important to learn from using the differences between the each layer’s decision variables and individuals’ ones.The original publication is available at JAIST Press http://www.jaist.ac.jp/library/jaist-press/index.htmlIFSR 2005 : Proceedings of the First World Congress of the International Federation for Systems Research : The New Roles of Systems Sciences For a Knowledge-based Society : Nov. 14-17, 2025, Kobe, JapanSymposium 2, Session 2 : Creation of Agent-Based Social Systems Sciences Management System