Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на этот ресурс: http://earchive.tpu.ru/handle/11683/74935
Полная запись метаданных
Поле DCЗначениеЯзык
dc.contributor.authorMitsel, Artur Aleksandrovichen
dc.contributor.authorShilnikov, Aleksandr Sergeevichen
dc.contributor.authorSenchenko, Pavel Vasiljevichen
dc.contributor.authorSidorov, Arkady Iljichen
dc.date.accessioned2023-03-31T07:12:59Z-
dc.date.available2023-03-31T07:12:59Z-
dc.date.issued2021-
dc.identifier.citationEnterprise 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.].en
dc.identifier.urihttp://earchive.tpu.ru/handle/11683/74935-
dc.description.abstractThis 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.en
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.publisherMDPI AGen
dc.relation.ispartofMathematics. 2021. Vol. 9, iss. 23en
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.rightsAttribution-NonCommercial 4.0 Internationalen
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/-
dc.sourceMathematicsen
dc.subjectстатическое моделированиеru
dc.subjectплотность вероятностиru
dc.subjectимитационное моделированиеru
dc.subjectподдержка решенийru
dc.subjectcompensation systemen
dc.subjectstatistical modelingen
dc.subjectprobability densityen
dc.subjectimitation modelingen
dc.subjectdecision support systemen
dc.titleEnterprise Compensation System Statistical Modeling for Decision Support System Developmenten
dc.typeArticleen
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dcterms.audienceResearchesen
local.description.firstpage3126-
local.filepathreprint-nw-39229.pdf-
local.filepathhttps://doi.org/10.3390/math9233126-
local.identifier.bibrecRU\TPU\network\39229-
local.identifier.perskeyRU\TPU\pers\35618-
local.issue23-
local.localtypeСтатьяru
local.volume9-
dc.identifier.doi10.3390/math9233126-
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.