COGNITIVE MODELING OF LABOR ACTIVITY PROCESSES IN R&D
( Pp. 88-94)

More about authors
Viktor D. Orekhov
International Institute of Management LINK
Zhukovsky, Russian Federation Lyutova Tatiana V. kand. polit. nauk, direktor kursa
International Institute of Management LINK, Russia, Zhukovsky Panfilova Elena A. Cand. Sci (Econ), Associate Professor
Rostov State University of Economics (RINH)
Rostov-on-Don, Russian Federation
Abstract:
In this paper, a comprehensive study of the processes of intellectual activity in the field of R & D and the development of proposals to improve the effectiveness of scientific activity. The study was performed using the system analysis methodology and cognitive modeling using the electronic decision support system (DSS) of the NEEDLE. The main subsystems of the labor system of R&D - specialists, affecting the efficiency of its activities, are identified. An iterative method using surveys of an expert group formed a system of the most important and quantitatively evaluated concepts. Identified the problematic factors in this area that are most important to increase for Russia: wages, the demand for scientific research, financing and provision of resources, the R&D support system. The cognitive matrix of this weakly structured system is constructed. With the help of DSS, it is shown that the matrix has a high total level of consonance (confidence) of 72%. The system has little effect on the group of mental factors. For coordinated work of the system, such key concepts as the demand for scientific research, the R & D support system in the company, innovative business culture, teamwork training, and self-control are of high importance. Dynamic modeling of the system behavior under the influence of the controlling factor “Retraining of Scientific Personnel” showed that with its increase by 14%, the increase in the effectiveness of scientific work is 14%, and the salary by 11%, the growth of education level by 21%. At a low rate (~ 6%), organizational concepts and the slowest concepts of group work are growing. The developed model can be used in the management of research activities to improve labor efficiency. The work can be used for conceptual modeling in the field of economics of scientific labor
How to Cite:
Viktor D.O., Lyutova T.V., Panfilova E.A., (2019), COGNITIVE MODELING OF LABOR ACTIVITY PROCESSES IN R&D. Economic Problems and Legal Practice, 1 => 88-94.
Reference list:
Barabanov D.D. Razvitie volevoy regulyatsii studentov. M., MGU. Dissertatsiya na soiskanie uchenoy stepeni kandidata psikhologicheskikh nauk, 2015.
Burova I.L., Lenkovskaya R.R. Pravovaya priroda prav na rezul taty intellektual noy deyatel nosti i sredstva individualizatsii. V sbornike: Nauchnye issledovaniya v chastnom prave Rossii/ Sbornik nauchnykh trudov yuridicheskogo fakul teta Rossiyskogo gosudarstvennogo sotsial nogo universiteta. Pod redaktsiey R.R. Lenkovskoy. Moskva, 2018. S. 20-28.
Kapitsa S.P. Paradoksy rosta: zakony global nogo razvitiya chelovechestva. - M.: Al pina non-fikshin, 2012.
Lenkovskaya R.R. Osobennosti individualizatsii prav intellektual noy sobstvennosti. V sbornike: Realizatsiya chastnopravovykh otnosheniy s uchastiem publichnogo elementa/Sbornik nauchnykh trudov po itogam provedeniya nauchno-metodicheskogo seminara. 2017. S. 17-24.
Makkonnell K.R., Bryu S.L. Ekonomiks. M., Infra-M, izd. 16, 2006 g.
Orekhov V.D. Prognozirovanie razvitiya chelovechestva s uchetom faktora znaniya. Monogr. - ZHukovskiy: MIM LINK, 2015. - 210 s. URL: www.world-evolution.ru
Shinkareva Olga V., Orekhov Viktor D., Soloduha Peter V., Prichina Olga S., Gizyatova Aliya Sh. Multifactor Assessment of Indicators on Dynamic Modeling of Programs for Managin the Perfomance of Scientific Labor. International Journal of Civil Engineering and Technology (IJCIET). Volume 9, Issue 13, December 2018, rr. 303-317.
Puankare A. O nauke: Per. s fr. / Pod red. L. S. Pontryagina. - 2-e izd. - M.: Nauka, 1983.
Spitsnadel V.N. Osnovy sistemnogo analiza. - SPb. Biznes-pressa, 2000.
Axelrod R. The Structure of Decision: Cognitive Maps of Political Elites. Princeton // NJ: Princeton University Press, 1976. - 404 p.
Barro, R.J., Lee, J.W. International Data on Education Attainment: Updates and Implications, Oxford Economic Papers, 2001, Vol. 53, No. 3.
Belbin R.M. Management Teams. Why They Succeed or Fail. 2004. Second edition. London, Elsevier. - 238 p.
Isaev R.A., Podvesovskii A.G. Generalized Model of Pulse Process for Dynamic Analysis of Sylov s Fuzzy Cognitive Maps // CEUR Workshop Proceedings of the Mathematical Modeling Session at the International Conference Information Technology and Nanotechnology (MM-ITNT 2017), Vol. 1904. - P. 57-63.
Kosko B. Fuzzy CognitiveMaps // International Journal of Man-Machine Studies, 1986. - Vol. 1. - P. 65-75.
Podvesovskii, A.G., Lagerev, D.G., Korostelev, D.A. Primenenie nechetkikh kognitivnykh modeley dlya formirovaniya mnozhestva al ternativ v zadachakh prinyatiya resheniy // Vestnik Bryanskogo gosudarstvennogo tekhnicheskogo universiteta, 2009, № 4 (24). - S. 77-84.
Schofer E., Meyer J. W. The Worldwide Expansion of Higher Education in the Twentieth Century, American Sociological Review. Vol. 70, № 6, pp. 898-920, 2006. URL: http://www.jstor.org/stable/4145399
Temple C. Critical thinking and critical literacy. Change (Peremena), № 2, 2005. - P. 15-20.