Mathematical Model of Economic Information
( Pp. 48-56)
More about authors
Shamin Roman V.
Dr. Sci. (Phys.-Math.); Professor, Department of Enterprise Programming, Institute of Advanced Technologies and Industrial Programming
MIREA – Russian Technological University
Moscow, Russian Federation Grosheva Polina Yu. Cand. Sci. (Econ.); associate professor, Department of Enterprise Programming, Institute of Advanced Technologies and Industrial Programming; MIREA – Russian Technological University; Moscow, Russian Federation Golovanov Stanislav O. postgraduate student, Department of Enterprise Programming, Institute of Advanced Technologies and Industrial Programming; MIREA – Russian Technological University; Moscow, Russian Federation.
MIREA – Russian Technological University
Moscow, Russian Federation Grosheva Polina Yu. Cand. Sci. (Econ.); associate professor, Department of Enterprise Programming, Institute of Advanced Technologies and Industrial Programming; MIREA – Russian Technological University; Moscow, Russian Federation Golovanov Stanislav O. postgraduate student, Department of Enterprise Programming, Institute of Advanced Technologies and Industrial Programming; MIREA – Russian Technological University; Moscow, Russian Federation.
Abstract:
This article shows that economic information can be formally described using an information field, which is a topological space with an introduced system of subsets that is closed with respect to the union operation. This system of subsets consists of information quanta – sets of information that can be used by a subject when making economic decisions. On this information field, a set function is introduced, defined on information quanta, which has the meaning of the economic value of the information quanta when the subject solves an economic problem. Many economic problems can be described by optimization problems, when a subject need to make a certain choice from a set of feasible solutions, and by game-theoretic models, when it is necessary to choose the best strategy in the face of opposition from other subjects. For these models, it is shown how a function can be constructed to evaluate the economic usefulness of information quanta.
How to Cite:
Shamin R.V., Grosheva P.Yu., Golovanov S.O. Mathematical Model of Economic Information. Computational Nanotechnology. 2024. Vol. 11. No. 1. Pp. 48–56. (In Rus.) DOI: 10.33693/2313-223X-2024-11-1-48-56. EDN: DRPVXI
Reference list:
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Shamin R.V., Uryngaliyeva A.A., Shermadini M.V., Filippov P.G. The model of evolutionary optimization of production processes at advanced technological enterprises. Espacios. 2019. Vol. 40. No. 20. P. 26.
Danko E.V., Obrabin N.M. Investigation of the expected usefulness of additional information when using the subjective utility function. In: Proceedings of the seminar on geometry and mathematical modeling. 2020. No. 6. Pp. 48–51.
Kugotova M.N. Discrete mathematical model of information dissemination. In: Actual problems of applied mathematics and physics. Materials of the international scientific conference. 2017. P. 114.
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Hartley R.V.L. Transmission of information. In: Information theory and its applications. Moscow: Fizmatgiz, 1959.
Shamin R.V., Shmeleva A.G., Shermadini M.V. et al. Quantitative assessment of the effectiveness of innovations. Proceedings of the NSTU named after R.E. Alekseev. 2019. No. 1 (124). Pp. 61–66. (In Rus.)
Shannon K. Works on information theory and cybernetics. Moscow: Publishing House of Foreign Literature, 1963.
Friedland G. Information theory. 2023. DOI: 10.1007/978-3-031-39477-5_4.
Harris Z. Theory of language and information: A mathematical approach. 2023. DOI: 10.1093/oso/9780198242246.001.0001.
Krugly A. The relational approach to the mathematical model of meaning of information. Metaphysics. 2021. Pp. 70–91. DOI: 10.22363/2224-7580-2021-3-70-91.
Lindgren K. Information theory for complex systems: An information perspective on complexity in dynamical systems and statistical mechanics. 2024. DOI: 10.1007/978-3-662-68214-2.
Manca V., Bonnici V. Information theory. 2023. DOI: 10.1007/978-3-031-44501-9_3.
Shamin R.V., Uryngaliyeva A.A., Shermadini M.V., Filippov P.G. The model of evolutionary optimization of production processes at advanced technological enterprises. Espacios. 2019. Vol. 40. No. 20. P. 26.
Danko E.V., Obrabin N.M. Investigation of the expected usefulness of additional information when using the subjective utility function. In: Proceedings of the seminar on geometry and mathematical modeling. 2020. No. 6. Pp. 48–51.
Kugotova M.N. Discrete mathematical model of information dissemination. In: Actual problems of applied mathematics and physics. Materials of the international scientific conference. 2017. P. 114.
Neumann J. von, Morgenstern O. Game theory and economic behavior. Moscow: Nauka, 1970.
Timofeev S.V. Mathematical model of dissemination of new information in society. Questions of the Theory and Practice of Journalism. 2020. Vol. 9. No. 1. Pp. 5–17. (In Rus.)
Khalikov M.A., Lyakh D.A., Deryabina A.I. A model for estimating the value of information on tax audit. Bulletin of the Altai Academy of Economics and Law. 2020. No. 4-1. Pp. 141–148. (In Rus.)
Hartley R.V.L. Transmission of information. In: Information theory and its applications. Moscow: Fizmatgiz, 1959.
Shamin R.V., Shmeleva A.G., Shermadini M.V. et al. Quantitative assessment of the effectiveness of innovations. Proceedings of the NSTU named after R.E. Alekseev. 2019. No. 1 (124). Pp. 61–66. (In Rus.)
Shannon K. Works on information theory and cybernetics. Moscow: Publishing House of Foreign Literature, 1963.
Keywords:
mathematical model, economic information, information field topology, economic utility.
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