DEVELOPMENT OF MENTAL MODEL FOR REGIONAL SYSTEM-DYNAMIC MODEL

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R. S. RAMAZANOV
M. V. IVANOVSKA

Abstract

Nowadays the most widespread tool of government is strategic planning, which is used by most developed countries. Most of Ukrainian regions use the social-economic strategies of the development. Previous researches showed that using of Balanced Scorecard helps to implement regional’s strategies. The region is considered as a dynamic system, all the main components of which are constantly changing. So the system dynamic models should help to track the impact of management on the state of the region. Analysis of recent research showed that using existing models with the Balanced Scorecard is impossible because of model’s redundancy. That is why there is a need to construct the regional system-dynamic model that can be used with Balanced Scorecard of region. The purpose of article is the development of mental model needed to build regional system-dynamic model. The methodology of system dynamics includes qualitative and quantitative phases. The qualitative stage defines and describes the relationships between regional subsystems. The quantitative stage conducts the simulation and verification of model. So the development of system-dynamic model is impossible without creating a mental model that represents the existing knowledge on the structure and communications of subsystems. The fig.1 of the article describes the established mental model. A complex systems are built by elements, that interact each other through a feedback loops. The fig.2 of the article describes the feedback loops. The combination of positive and negative feedbacks determines the behavior of the system as a whole. As it seen on fig.2 the most of feedbacks are balancing loops, this indicates the non-linearity of complex system. The non-linearity of complex systems is not only because of mathematical models containing nonlinear equation or inequality, but the changes in the system, that is not sequential from one state to another. The obtained knowledge is needed for computer simulation.

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References

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