Enterprise Compensation System Statistical Modeling for Decision Support System Development

Λεπτομέρειες βιβλιογραφικής εγγραφής
Parent link:Mathematics
Vol. 9, iss. 23.— 2021.— [3126, 19 p.]
Συγγραφή απο Οργανισμό/Αρχή: Национальный исследовательский Томский политехнический университет Инженерная школа ядерных технологий Отделение экспериментальной физики
Άλλοι συγγραφείς: Mitsel A. A. Artur Aleksandrovich, Shilnikov A. S. Aleksandr Sergeevich, Senchenko P. V. Pavel Vasiljevich, Sidorov A. I. Arkady Iljich
Περίληψη:Title screen
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.
Γλώσσα:Αγγλικά
Έκδοση: 2021
Θέματα:
Διαθέσιμο Online:http://earchive.tpu.ru/handle/11683/74935
https://doi.org/10.3390/math9233126
Μορφή: Ηλεκτρονική πηγή Κεφάλαιο βιβλίου
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=668018

MARC

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330 |a 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. 
461 |t Mathematics 
463 |t Vol. 9, iss. 23  |v [3126, 19 p.]  |d 2021 
610 1 |a электронный ресурс 
610 1 |a труды учёных ТПУ 
610 1 |a compensation system 
610 1 |a statistical modeling 
610 1 |a probability density 
610 1 |a imitation modeling 
610 1 |a decision support system 
610 1 |a статическое моделирование 
610 1 |a плотность вероятности 
610 1 |a имитационное моделирование 
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