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Methodological provisions of building models of industrial enterprise development

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  • Yu. Yu. Kostyukhin

Abstract

In the age of information technology, characterized by a large amount of current data, the process of processing and structuring information has become particularly relevant. The basic approach for selecting information in the context of an information explosion should be the principle of sufficiency, i.e. information should be no more and no less, it should be enough to make a decision. After all, excessive information leads to informational noise and the risk of making the wrong decision. The correct and accurate formulation of the problem is the first and necessary stage of any system research. An important methodological issue is the need to identify the following relationships: a tool for realizing the goal, when it is most effective, what is the cost of its implementation and profitability, and the last question is the reverse return from this tool.The emerging problems are usually distinguished by the degree of their structuring: by clarity, by the awareness of their formulation, by the degree of their specification and specification, by the ratio of quantitative and qualitative factors. Considering this, there are three classes of problems: well-structured and quantitatively structured, poorly structured or mixed problems, unstructured or qualitative problems.And the last methodological problem is how to determine the criteria and indicators for achieving the goal, whether it is necessary to have a standard approach to determining the fulfillment of the goal or to take into account possible changes during the period of the fulfillment of the goal and correlate them to real changes that have occurred. The article proposes a 9-stage management decision making algorithm. It is shown that for poorly formalized tasks an effective tool is the method of qualitative modeling of complex organizational structures.

Suggested Citation

  • Yu. Yu. Kostyukhin, 2019. "Methodological provisions of building models of industrial enterprise development," Russian Journal of Industrial Economics, MISIS, vol. 12(1).
  • Handle: RePEc:ach:journl:y:2019:id:723
    DOI: 10.17073/2072-1633-2019-1-69-78
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    References listed on IDEAS

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    1. Natali Hritonenko & Yuri Yatsenko, 2013. "Mathematical Modeling in Economics, Ecology and the Environment," Springer Optimization and Its Applications, Springer, edition 2, number 978-1-4614-9311-2, June.
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