BUILDING KNOWLEDGE ABOUT STRATEGY FOR GROWTH: SYSTEM DYNAMICS APPROACH 1

Abstract

Various social (and ecological subsystems), shaping our world, are inter-related in a very complex manner. Globalization brings with it a large increase of interactions, the complexity of the decision-making problem grows, the number of unstable and disturbing effects in the competitive environment rises. We can not keep up with this level of mutual interdependence when developing our mental capabilities. We are only able to understand a small number of variables in mutual interaction and cannot imagine dynamic consequences. Many models allow the determining of the optimal solution for the given moment. We make a decision and we cannot verify how this decision will influence the system in the future. Every system shows dynamic properties. Our mind is not able to link together all the relationships between individual items (moreover, we often do not know which items), nor to imagine their development in time. If we want to understand the complexity of the EU economy and the behavior of the system within the process of time, we have to understand its structure. This includes defining the elements of the system and marking their mutual relationships. Understanding based on learning the structure of the system and its implicit formulation is the beginning of innovative thinking, and detecting the proper reasons of the problems. The main aim of the paper is to contribute to the topic of building knowledge about strategy of growth with a discussion of a strand of systems theory: System Dynamics. The authors will try to develop a theoretical knowledge and made practical recommendations for the use of system dynamics methods in EU conditions, especially for decision making support in problems which are related to complex social systems with a high level of complexity. Feed-back loops are recognized as the main methods for describing the problems of growth of the EU. It points out the possibilities of using the principles and tools of system dynamics methodology, as well as the limits of system dynamics. The turbulent global economic environment of the EU economy requires changes in thinking and behavior. The further purpose of the following paper is to discuss the possibility for improving systems thinking and for the support of “complexity thinking”. It is useful to provide some kind of system detachment and information on how system dynamics helps in solving complex problems within complexity in the economic environment, mainly with respect to the integration. According to their usual long-run orientation, the simulation system dynamics models are often used for various purposes – testing of the decision-making strategies and policies. The paper will emphasize the importance of system dynamics applications for the simulation of decision-making processes, strategy learning, better possibility of predicting the behaviour of complex systems (information “ex ante” and not only “ex post”) and the possibility of the system’s long-term optimization. It is obvious that we can not consider any solution to be the correct one and it is necessary to preserve the holistic view while respecting the fact that every approach has its contributions and limits.