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In this article the authors have developed a computational algorithm for assessing the value of business depending on the influencing factors using the income approach and economic-mathematical model, which allows to optimize the process of making managerial decisions when buying or selling a ready-made business or its individual assets. The research materials are databases: Habr (Russian Internet platform dedicated to technology, science, IT and business) and SPARK (System of Primary Analytics and Client Registration, Russian information system providing access to data on legal entities and individual entrepreneurs). Research methods: algorithmic design, income approach to business value assessment, discounted cash flow method and Gordon’s model, economic and mathematical modeling, data analysis, comparative analysis, use of digital and information technologies, programming in the high-level language Python, methods of expert evaluations, data algorithmizing. As a result, computational intelligence and intellectual analysis of data on financial results on forms OKUD1 and OKUD2 on the example of reporting 40 dental clinics in the Russian Federation is demonstrated and it is shown that the programming language Python, due to its simplicity, readability and powerful libraries for data analysis, such as Pandas, NumPy and SciPy, is an effective tool for solving problems associated with the development of data analysis algorithm for assessing the value of business using the income approach. The practical significance of the study is the possibility of using the developed toolkit to determine the optimal number of universal dental seats in order to maximize the value of the dental business.

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Intelligent Analysis of Financial Results Data as a Management Decision Support System

  • 会议论文

  • 发表日期：

    2025年

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  • Evgeny Kostyrin,
  • Daniil Rozanov,
  • Stephan Kerasov,
  • Sergey Arutyunov

摘要

In this article the authors have developed a computational algorithm for assessing the value of business depending on the influencing factors using the income approach and economic-mathematical model, which allows to optimize the process of making managerial decisions when buying or selling a ready-made business or its individual assets. The research materials are databases: Habr (Russian Internet platform dedicated to technology, science, IT and business) and SPARK (System of Primary Analytics and Client Registration, Russian information system providing access to data on legal entities and individual entrepreneurs). Research methods: algorithmic design, income approach to business value assessment, discounted cash flow method and Gordon’s model, economic and mathematical modeling, data analysis, comparative analysis, use of digital and information technologies, programming in the high-level language Python, methods of expert evaluations, data algorithmizing. As a result, computational intelligence and intellectual analysis of data on financial results on forms OKUD1 and OKUD2 on the example of reporting 40 dental clinics in the Russian Federation is demonstrated and it is shown that the programming language Python, due to its simplicity, readability and powerful libraries for data analysis, such as Pandas, NumPy and SciPy, is an effective tool for solving problems associated with the development of data analysis algorithm for assessing the value of business using the income approach. The practical significance of the study is the possibility of using the developed toolkit to determine the optimal number of universal dental seats in order to maximize the value of the dental business.