Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на этот ресурс: http://earchive.tpu.ru/handle/11683/74935
Название: Enterprise Compensation System Statistical Modeling for Decision Support System Development
Авторы: Mitsel, Artur Aleksandrovich
Shilnikov, Aleksandr Sergeevich
Senchenko, Pavel Vasiljevich
Sidorov, Arkady Iljich
Ключевые слова: статическое моделирование; плотность вероятности; имитационное моделирование; поддержка решений; compensation system; statistical modeling; probability density; imitation modeling; decision support system
Дата публикации: 2021
Издатель: MDPI AG
Библиографическое описание: Enterprise Compensation System Statistical Modeling for Decision Support System Development / A. A. Mitsel, A. S. Shilnikov, P. V. Senchenko, A. I. Sidorov // Mathematics. — 2021. — Vol. 9, iss. 23. — [3126, 19 p.].
Аннотация: This article raises the issue of decision support system (DSS) development in enterprises concerning the compensation system (CS). The topic is relevant as the CS is one of the main components in human resource management in business. A key element of such DSSs is CS models that provide predictive analytics. Such models are able to give information about how a particular CS affects output, product quality, employee satisfaction, and wage fund. Thus, the main goal of this article is to obtain a CS statistical model and its formulas for determining the probability densities of resultant indicators. To achieve this goal, the authors conducted several blocks of research. Firstly, mathematical formalization of CS functionality was described. Secondly, a statistical model of CS was built. Thirdly, calculations of CS result indicators were made. Reliable scientific methods were used: black box modeling and statistical modeling. This article proposes a statistical and analytical model. As an example, a piecework-bonus system statistical model is demonstrated. The discussion derives formulas of integral estimations showing the probability density of the resulting CS indicators and the related statistical characteristics. These results can be used to predict the behavior of the workforce. This constitutes the scientific novelty of the study, which will establish significant advances in the development of DSSs in the field of labor economics and HR management.
URI: http://earchive.tpu.ru/handle/11683/74935
Располагается в коллекциях:Репринты научных публикаций

Файлы этого ресурса:
Файл Описание РазмерФормат 
reprint-nw-39229.pdf2,03 MBAdobe PDFПросмотреть/Открыть


Все ресурсы в архиве электронных ресурсов защищены авторским правом, все права сохранены.