dc.creator | Perišić, Natalija | |
dc.creator | Spasojević Brkić, Vesna | |
dc.creator | Jovanović, Radiša | |
dc.creator | Mihajlović, Ivan | |
dc.creator | Perišić, Martina | |
dc.date.accessioned | 2023-05-29T08:47:33Z | |
dc.date.available | 2023-05-29T08:47:33Z | |
dc.date.issued | 2023 | |
dc.identifier.isbn | 978-86-6305-136-2 | |
dc.identifier.issn | 2620-0597 | |
dc.identifier.uri | https://machinery.mas.bg.ac.rs/handle/123456789/6863 | |
dc.description.abstract | A company’s development performance and growth may be impacted by a wide range
of different factors, which unquestionably affect number of the employees in the loop. Taking into
account all influencing factors, companies would benefit if have possibility to predict the degree of
change in the number of employees in future period in order to adjust their internal strategy or to
make appropriate decisions that enable the survival and progress of the company in the market. The
aim of this research is to predict the change in number of employees based on current state of
contingency and quality management factors, using information obtained from a survey of 67
different companies from Serbia. In the first part of the research, a correlation analysis is used with
the aim to identify the specific contingency and quality management factors that are most closely
associated to the subject of interest, which is, in this case, degree of change in the number of
employes. The second part of the research involves feedforward neural network training for
prediction of the degree of change in number of employees based on feature extraction of main
factors. The training accuracy that proposed network achieved is 77.36%, while testing accuracy
amounts 71.43%. | sr |
dc.language.iso | en | sr |
dc.publisher | Bor : University of Belgrade, Technical Faculty, Department of Engineering Management | sr |
dc.relation | info:eu-repo/grantAgreement/MESTD/inst-2020/200105/RS//" | sr |
dc.relation | RESMOD SAF€RA project | sr |
dc.rights | openAccess | sr |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.source | International May Conference on Strategic Management – IMCSM23 May, 2023, Bor, Serbia | sr |
dc.subject | Correlation analysis | sr |
dc.subject | number of employees | sr |
dc.subject | feedforward neural networks | sr |
dc.title | PREDICTION OF THE CHANGE IN NUMBER OF EMPLOYEES IN SERBIAN COMPANIES BASED ON CONTINGENCY AND QUALITY MANAGEMENT FACTORS | sr |
dc.type | conferenceObject | sr |
dc.rights.license | BY | sr |
dc.rights.holder | Bor : University of Belgrade, Technical Faculty, Department of Engineering Management | sr |
dc.citation.epage | 48 | |
dc.citation.issue | 1 | |
dc.citation.rank | M33 | |
dc.citation.spage | 39 | |
dc.citation.volume | 19 | |
dc.identifier.fulltext | http://machinery.mas.bg.ac.rs/bitstream/id/17244/bitstream_17244.pdf | |
dc.identifier.rcub | https://hdl.handle.net/21.15107/rcub_machinery_6863 | |
dc.type.version | publishedVersion | sr |