A Complex Adaptive Model of Economic Production Networks

2004 ◽  
pp. 338-343
Author(s):  
A. Ponzi ◽  
A. Yasutomi ◽  
K. Kaneko
2011 ◽  
Vol 5 (1) ◽  
pp. 58-68 ◽  
Author(s):  
James Moffat ◽  
Michael Bathe ◽  
Lorna Frewer

2011 ◽  
Vol 460-461 ◽  
pp. 261-267
Author(s):  
Ying Peng ◽  
Jin Ling Hou ◽  
Jing Wang

Since the 90s of last century, learning organization as a new organizational mode is highly prized by the management scholars all over the world. It is considered as a new trend and an ideal mode of the global organizational management in the knowledge economy era. In consideration of learning organizations with attributes of complex system, the theory of complex adaptive system provides a possible route on methodology for the study of its organizational change. This paper starts from the view of complex adaptive system theory, analyzes the initiative, adaptability of the learning organization and its interaction with the environment. It assumes that with the constant change of the performance parameters, functions and attributes of the organization, the entire organization mode and the structure will also change. Furthermore by constructing a complex adaptive model of learning organization, this paper elaborates the organizational change process, and extracts the information communication, organizational mood, leadership style and organizational knowledge as the impact indicators. The conclusion of this research has some significance as reference for those who try to improve the level of the adaptability of organizations in the various changing environment.


Author(s):  
Béla Pátkai ◽  

The investigation (i.e. modelling, simulation, understanding and control) of complex adaptive systems is a problematic issue mainly due to the immaturity of systems scientific modelling paradigms. The apparent analogies between complex adaptive systems and production networks provide the opportunity to formulate the latter one in terms of the first, and to integrate the knowledge and the way of thinking of both fields. Through the application of the method of analogy and agent-based modelling and the development of a methodology a disciplined way of thinking is presented that involves the formulation of natural scientific concepts in terms of simulation models.


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