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dc.contributor.authorTarasyeva, T. V.en
dc.contributor.authorAgarkov, G. A.en
dc.contributor.authorTarasyev, A. A.en
dc.contributor.authorKoksharov, V. A.en
dc.date.accessioned2024-04-22T15:52:53Z-
dc.date.available2024-04-22T15:52:53Z-
dc.date.issued2022-
dc.identifier.citationTarasyeva, TV, Agarkov, GA, Tarasyev, AA & Koksharov, VA 2022, 'Modeling the Choice of an Optimal Educational Trajectory in the Conditions of Digital Transformation of the Economy', IFAC-PapersOnLine, Том. 55, № 16, стр. 382-387. https://doi.org/10.1016/j.ifacol.2022.09.054harvard_pure
dc.identifier.citationTarasyeva, T. V., Agarkov, G. A., Tarasyev, A. A., & Koksharov, V. A. (2022). Modeling the Choice of an Optimal Educational Trajectory in the Conditions of Digital Transformation of the Economy. IFAC-PapersOnLine, 55(16), 382-387. https://doi.org/10.1016/j.ifacol.2022.09.054apa_pure
dc.identifier.issn2405-8963
dc.identifier.otherFinal2
dc.identifier.otherAll Open Access; Bronze Open Access3
dc.identifier.otherhttps://doi.org/10.1016/j.ifacol.2022.09.0541
dc.identifier.otherhttps://doi.org/10.1016/j.ifacol.2022.09.054pdf
dc.identifier.urihttp://elar.urfu.ru/handle/10995/132365-
dc.description.abstractThe processes of transformation of the modern economy taking place in recent decades encourage researchers to determine the place of higher education in general and of sets of educational programs in particular, in the new conditions of the educational services market. In the context of significant changes in the processes of market structures interaction, employers are forced to impose new requirements on university graduates, whose qualifications should be relevant to the current market. Since the university in this case is an intermediary between enterprises and skilled labor, its goal is to solve the shortage of personnel with a level of training that meets the new objectives of employers in the regional labor market. In these conditions, optimizing recruitment of students for the areas necessary for the market becomes relevant. To solve these problems, the following tools can be used: identifying value orientations and incentives for applicants in the process of choosing bachelor's degree programs, and admission of master's degree applicants who have shown an inclination for professional activity related to their undergraduate degree field. Thus, there is a need to study the applicants' educational trajectories in relation to their economic incentives, such as the amount of expected income after graduation. The method of this study combines an agent-based model with econometric modeling to determine the maximum expected salary after graduation. The first stage of modeling involves the use of an econometric model to adapt students' educational trajectories to their preferences. At the second stage of modeling, an agent-based model is used, which allows determining the behavior of students within the overall sample. To determine the probability of a student changing their educational trajectory, a fuzzy logical model was developed. Copyright © 2022 The Authors.en
dc.description.sponsorshipRussian Science Foundation, RSF, (22-28-01010)en
dc.description.sponsorshipThe research work of Tarasyev A.A. is supported by a grant from the Russian Science Foundation, scientific research project No. 22-28-01010 “People’s Savings as a Basis for Safe Socio-Economic Development of Russian Regions: Analysis, Forecast and System of Measures for Localization and Neutralization of Threats”.en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherElsevier B.V.en
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.sourceIFAC-PapersOnLine2
dc.sourceIFAC-PapersOnLineen
dc.subjectAGENT-BASED MODELINGen
dc.subjectBEHAVIORAL ECONOMICSen
dc.subjectDYNAMIC GAMESen
dc.subjectDYNAMIC MODELen
dc.subjectEDUCATIONAL TRAJECTORIESen
dc.subjectHIGHER EDUCATIONen
dc.subjectREGIONAL LABOR MARKETen
dc.subjectAUTONOMOUS AGENTSen
dc.subjectCOMMERCEen
dc.subjectCOMPENSATION (PERSONNEL)en
dc.subjectCOMPUTATIONAL METHODSen
dc.subjectECONOMIC ANALYSISen
dc.subjectEMPLOYMENTen
dc.subjectPERSONNEL TRAININGen
dc.subjectSIMULATION PLATFORMen
dc.subjectTRAJECTORIESen
dc.subjectAGENT-BASED MODELen
dc.subjectBEHAVIORAL ECONOMICSen
dc.subjectCONDITIONen
dc.subjectDYNAMIC GAMEen
dc.subjectDYNAMICS MODELSen
dc.subjectECONOMETRIC MODELLINGen
dc.subjectEDUCATIONAL TRAJECTORYen
dc.subjectHIGH EDUCATIONSen
dc.subjectLABOUR MARKETen
dc.subjectREGIONAL LABOR MARKETen
dc.subjectSTUDENTSen
dc.titleModeling the Choice of an Optimal Educational Trajectory in the Conditions of Digital Transformation of the Economyen
dc.typeConference paperen
dc.typeinfo:eu-repo/semantics/conferenceObjecten
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.conference.name18 July 2022 through 22 July 2022en
dc.conference.date18th IFAC Workshop on Control Applications of Optimization, CAO 2022
dc.identifier.doi10.1016/j.ifacol.2022.09.054-
dc.identifier.scopus85142292217-
local.contributor.employeeTarasyeva T.V., Ural Federal University Named after the First President of Russia B.N. Yeltsin, Mira 19, Yekaterinburg, 620002, Russian Federationen
local.contributor.employeeAgarkov G.A., Ural Federal University Named after the First President of Russia B.N. Yeltsin, Mira 19, Yekaterinburg, 620002, Russian Federationen
local.contributor.employeeTarasyev A.A., Ural Federal University Named after the First President of Russia B.N. Yeltsin, Mira 19, Yekaterinburg, 620002, Russian Federationen
local.contributor.employeeKoksharov V.A., Ural Federal University Named after the First President of Russia B.N. Yeltsin, Mira 19, Yekaterinburg, 620002, Russian Federationen
local.description.firstpage382
local.description.lastpage387
local.issue16
local.volume55
dc.identifier.wos000855235100063-
local.contributor.departmentUral Federal University Named after the First President of Russia B.N. Yeltsin, Mira 19, Yekaterinburg, 620002, Russian Federationen
local.identifier.pured54ae134-9789-4486-995d-79b25cbfeba6uuid
local.identifier.pure30960284-
local.identifier.eid2-s2.0-85142292217-
local.identifier.wosWOS:000855235100063-
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