Risk perception and data mining in the iron and steel industry
| dc.contributor.author | Ersöz, Taner | |
| dc.contributor.author | Bulut, Bennur | |
| dc.date.accessioned | 2024-09-29T16:31:10Z | |
| dc.date.available | 2024-09-29T16:31:10Z | |
| dc.date.issued | 2021 | |
| dc.department | Karabük Üniversitesi | en_US |
| dc.description.abstract | Risk is the possibility of threat, that is, potential harm. There may be risks like price fluctuations, exchange rate changes, demand and request changes, and inaccessibility of the material for an enterprise. The biggest mistake is to consider the risk as a possibly harmful circumstance that should only be avoided. When the risk is successfully managed, it empowers the formation of exceptionally imperative vital steps for businesses. Businesses have to show serious patterns to understand, anticipate, prevent, reduce and manage risk correctly and avoid the conceivable loss of life and property. A culture of trust is created in companies that understand the risk correctly and manages it with the right steps. The culture of trust prevents workers from getting distracted, as well as enabling workers to embrace the job and do their job lovingly. Thus, productivity increases in the long run. The purpose of this study is to determine the risk perception of the employees of a firm operating in the iron and steel industry. Possible risks are always high as the enterprise operates as a heavy industry. The questionnaire applied to the employees consists of two parts. The first part consists of demographic features, and the second part consists of questions regarding employees' perceptions of risk. According to the findings which will be obtained with the help of the research, the effect levels of the demographic characteristics of the employees on the employees will be determined and improved findings will be presented to the business management. According to the socio - demographic status of the employees in the enterprise, it is pointed to uncover the risk discernment levels by cluster analysis. | en_US |
| dc.identifier.doi | 10.46519/ij3dptdi.958712 | |
| dc.identifier.endpage | 325 | en_US |
| dc.identifier.issn | 2602-3350 | |
| dc.identifier.issue | 2 | en_US |
| dc.identifier.startpage | 313 | en_US |
| dc.identifier.trdizinid | 441279 | en_US |
| dc.identifier.uri | https://doi.org/10.46519/ij3dptdi.958712 | |
| dc.identifier.uri | https://search.trdizin.gov.tr/tr/yayin/detay/441279 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14619/11205 | |
| dc.identifier.volume | 5 | en_US |
| dc.indekslendigikaynak | TR-Dizin | en_US |
| dc.language.iso | tr | en_US |
| dc.relation.ispartof | International Journal of 3D Printing Technologies and Digital Industry | en_US |
| dc.relation.publicationcategory | Makale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.title | Risk perception and data mining in the iron and steel industry | en_US |
| dc.type | Article | en_US |
