| Remuneration management under conditions of uncertainty |
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Аuthors: Anna A. Fedchenko, Dr. Sc. (Econ.), Professor of Psychology and Human Capital Development Dept. Financial University under the Government of the Russian Federation Inna V. Filimonova, Cand. Sc. (Econ.), Associate Professor of Psychology and Human Capital Development Dept. Financial University under the Government of the Russian Federation Valeriya N. Yaryshina, Cand. Sc. (Econ.), Associate Professor of Labour Economics and Fundamentals of Management Dept. Voronezh State University Abstract: The lack of tools for assessing employee performance when remunerating in the conditions of uncertainty and nonlinearity of the processes in the digital economy seems to be a serious multifaceted problem that needs to be solved. The article aims to develop and test a system for assessing employees to remunerate them in an uncertain socio-economic environment. Methodologically, the research relies on the synthesis of theories of management and decision-making under conditions of socio-economic uncertainty. The methods of linguistic and expert evaluation with fuzzy sets were used. The empirical evidence was in-house documentation obtained at the industrial enterprises of AO RIF Corporation (Voronezh) and in the ORS Service Desk division of the Voronezh representative office of OOO Siemens Business Services. The testing of the proposed system for evaluating employee performance justified its practical use in organizations. The research results showed that the integrated approach allows increasing the validity of managerial decision-making under socio-economic uncertainty. The developed toolkit can be used to form not only the bonus part of remuneration, but also other elements of compensation and benefits. Among its major advantages is the possibility to apply it at enterprises of all forms of ownership, which is extremely important in a competitive environment. Keywords: uncertainty; socio-economic processes; employee performance evaluation; remuneration; fuzzy sets; linguistic evaluation; expert evaluation. |
