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Modeling of motivation of key executives of government agencies of regions using a multi-objective genetic algorithm

Vol. 28, Iss. 5, MAY 2022

Received: 14 March 2022

Received in revised form: 28 March 2022

Accepted: 11 April 2022

Available online: 30 May 2022

Subject Heading: INVESTING

JEL Classification: C63, E17, O21, O36

Pages: 972–999

https://doi.org/10.24891/fc.28.5.972

Sergei N. YASHIN National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation
jashinsn@yandex.ru

https://orcid.org/0000-0002-7182-2808

Egor V. KOSHELEV National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation
ekoshelev@yandex.ru

https://orcid.org/0000-0001-5290-7913

Dmitrii A. SUKHANOV Non-State Educational Private Institution for Advanced Vocational Education Biota – Plus, Nizhny Novgorod, Russian Federation
svx85@yandex.ru

https://orcid.org/0000-0002-4600-0108

Subject. This article explores the motivation of top managers of government entities to bring into line the interests of the population, the State and its key executives.
Objectives. The article aims to create a model of motivation of key executives of government institutions of the regions, which will make it possible to make the intangible motivation of top managers contingent on the achieved strategic potential of the region and their financial incentives.
Methods. For the study, we used a multi-objective genetic algorithm and the Pareto Frontier solutions set.
Results. The article proposes a procedure for reaching a conclusion about the actual bonus award (incentivization) of key executives of government agencies of the regions.
Conclusions and Relevance. The results obtained can be useful to government agencies to develop a rational system of financial and non- financial incentives of their senior leadership.

Keywords: motivation, senior leadership, multi-purpose genetic algorithm

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