Development of a method for assessing the functioning of a grain product sub-complex using mathematical modeling

Perizat Beisekova (), Assel Ilyas, Yelena Kaliyeva, Zhanar Kirbetova and Meruert Baimoldayeva
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Perizat Beisekova: Esil University
Assel Ilyas: Almaty Technological University
Yelena Kaliyeva: Almaty Technological University
Zhanar Kirbetova: Almaty Technological University
Meruert Baimoldayeva: International Technical and Humanitarian University

Eastern-European Journal of Enterprise Technologies, 2023, vol. 2, issue 13(122), 92-101

Abstract: The object of the study is the process of functioning of enterprises of the grain product subcomplex. In the course of the study, the problem of the growth rate and the peculiarities of the functioning of enterprises of the grain product subcomplex were solved. An assessment of the functioning of the grain product subcomplex was carried out Republic of Kazakhstan using mathematical modeling, for which a methodology has been developed that allows considering factors with a heterogeneous metric, which includes the following steps: 1) index analysis twenty-one indicators, divided into groups; 2) development of formulas for calculation and integral indicators characterizing their dynamics; 3) determining the pace of functioning of the grain product subcomplex for 2011–2021. Graphs were made and a forecast of the performance indicators of the subcomplex until 2024 is presented for one of each group with the maximum coefficient of determination R2. According to three scenarios: optimistic, probabilistic and pessimistic. R2 is an indicator of the quality of forecasts: than the closer its value is to one, the higher the probability of execution. For eleven charts, the coefficient of determination is in the range from 0.9003 (pessimistic forecast for other industrial use of grain) to 0.9838 (optimistic forecast for the number of granaries). For ten, from 0.8025 to 0.8702, and for nine, from 0.705 to 0.7932. This means that the reliability of the calculations for twenty-nine forecast options is in the range from 70 to 98 %. This indicates fairly objective predictive values of the subcomplex performance indicators until 2024. Based on the results of the studies, optimistic and pessimistic scenarios are more likely to be implemented.

Keywords: assessment methodology; growth rate; integral indicator; mathematical modeling; agro-industrial complex (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:baq:jetart:v:2:y:2023:i:13:p:92-101

DOI: 10.15587/1729-4061.2023.276433

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