Estimation of the Risk of Work-Related Accidents for Underground Hard Coal Mine Workers by Logistic Regression

dc.contributor.author Bilim, Niyazi
dc.contributor.author Bilim, Atiye
dc.date.accessioned 2021-12-13T10:23:56Z
dc.date.available 2021-12-13T10:23:56Z
dc.date.issued 2022
dc.description.abstract Coal mining has the most risk in all of the mining sectors. Hence, in this sector, most work accidents encountered are intensive. The demographic characteristics of workers affect the occurrence of occupational accidents. This study aims to develop an equation that predicts workday loss by analyzing the relationship between workers' demographic characteristics and having an accident with workday loss. In this study, work-related accidents between 2014 and 2019 in underground hard coal mines in Turkey were analyzed using logistic regression analysis. An equation is derived that estimates the workday loss with the characteristics of workers in hard coal mines. With the equation derived in this study, employers can determine the potential for work accidents according to the demographic characteristics of the workers and serious work accidents will be prevented. Therefore, proactive solutions can be produced by applying the methods used in this study to different industries. en_US
dc.identifier.doi 10.1080/10803548.2021.1990571
dc.identifier.issn 1080-3548
dc.identifier.issn 2376-9130
dc.identifier.scopus 2-s2.0-85119359327
dc.identifier.uri https://doi.org/10.1080/10803548.2021.1990571
dc.identifier.uri https://hdl.handle.net/20.500.13091/270
dc.language.iso en en_US
dc.publisher TAYLOR & FRANCIS LTD en_US
dc.relation.ispartof INTERNATIONAL JOURNAL OF OCCUPATIONAL SAFETY AND ERGONOMICS en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Logistic Regression en_US
dc.subject Work Safety en_US
dc.subject Work Accident en_US
dc.subject Coal Mine Accident en_US
dc.subject Accident Analyses en_US
dc.subject Occupational-Health Hazards en_US
dc.subject Statistical-Analysis en_US
dc.subject Safety Evaluation en_US
dc.subject Mining Safety en_US
dc.subject Injuries en_US
dc.subject China en_US
dc.subject Explosions en_US
dc.subject Management en_US
dc.subject Lost en_US
dc.subject Experience en_US
dc.title Estimation of the Risk of Work-Related Accidents for Underground Hard Coal Mine Workers by Logistic Regression en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Bilim, Niyazi/0000-0002-6711-0453
gdc.author.scopusid 24167680000
gdc.author.scopusid 57132984700
gdc.bip.impulseclass C4
gdc.bip.influenceclass C5
gdc.bip.popularityclass C4
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.description.department Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Maden Mühendisliği Bölümü en_US
gdc.description.endpage 2369
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q2
gdc.description.startpage 2362
gdc.description.volume 28
gdc.description.wosquality Q3
gdc.identifier.openalex W3204227455
gdc.identifier.pmid 34622745
gdc.identifier.wos WOS:000718223400001
gdc.index.type WoS
gdc.index.type Scopus
gdc.index.type PubMed
gdc.oaire.diamondjournal false
gdc.oaire.impulse 5.0
gdc.oaire.influence 2.8109575E-9
gdc.oaire.isgreen false
gdc.oaire.keywords Logistic Models
gdc.oaire.keywords Coal
gdc.oaire.keywords Humans
gdc.oaire.keywords Accidents, Occupational
gdc.oaire.keywords Miners
gdc.oaire.keywords Coal Mining
gdc.oaire.popularity 6.195802E-9
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0502 economics and business
gdc.oaire.sciencefields 05 social sciences
gdc.openalex.collaboration National
gdc.openalex.fwci 1.38705137
gdc.openalex.normalizedpercentile 0.79
gdc.opencitations.count 6
gdc.plumx.crossrefcites 2
gdc.plumx.mendeley 25
gdc.plumx.scopuscites 7
gdc.scopus.citedcount 7
gdc.virtual.author Bilim, Niyazi
gdc.virtual.author Bilim, Atiye
gdc.wos.citedcount 5
relation.isAuthorOfPublication 579fd597-79f1-44fa-bf7a-0a42518f9ee1
relation.isAuthorOfPublication 87dac23d-6774-4d75-8b91-aea688e69b56
relation.isAuthorOfPublication.latestForDiscovery 579fd597-79f1-44fa-bf7a-0a42518f9ee1

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