Assessment of accident severity in the construction industry using the Bayesian theorem

Alizadeh, Seyed Shamseddin; Mortazavi, Seyed Bagher; Sepehri, Mohammad Mehdi

doi:10.1080/10803548.2015.1095546

Cited by 34 publications

(10 citation statements)

References 30 publications

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“…Building construction workers are also generally exposed to an excessive risk of being injured at work (Almen Larsson and Thunqvist, 2012). Alizadeh, Mortazavi and Sepehri (2015) acknowledged that in construction, workers perform a great diversity of activities, each one with a specific associated risk. Zavadskas, Turskis and Tamošaitiene (2010), Kozlovská and Struková (2012) and Muiruri and Mulinge (2014) also agreed that many construction activities inherently possess high health and safety risk factors.…”

Section: Introductionmentioning

confidence: 99%

Occupational Health and Safety Risk Levels of Building Construction Trades in Nigeria

Okoye¹

2018

CEB

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This study assessed the occupational health and safety risk-level of common building construction trades in Nigeria. It also identified the sources, frequency and magnitude of risks inherent in the activities of various building construction trades. Being site-based survey research, it made use of a structured questionnaire administered to the selected building construction workers of different trades in Anambra State, Nigeria. The collected data were subjected to quantitative risk analysis using mean value method and risk prioritisation number. The study found that masonry, carpentry (including formwork and roofing), and iron bending and steel fixing are common building trades associated with high risks; whereas electrical fitting and installation, painting, tiling, and plumbing are medium risk building trades. It also found that the rate of occurrence and magnitude of impact of different safety risk factors differ across the building trades, which could be attributed to the differences in activities and modes of operation in different building trades. On this premise, the study suggested a multi-risk management and control approach for construction managers on building construction sites since the frequency of risk occurrence and the magnitude of risk severity differ across trades. It further called for institutional and legislative re-strengthening of extant labour laws in Nigeria.

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Section: Introductionmentioning

confidence: 99%

Occupational Health and Safety Risk Levels of Building Construction Trades in Nigeria

Okoye¹

2018

CEB

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“…SSCPs are associated with S&H risks [13,28], and the results of ANN modeling in the present study indicated that some RMFs could also predict AFR, including HAZID, periodic risk assessment, development and implementation of risk control measures, and housekeeping. Moreover, some researchers have reported that the most important influential factors in SSCP accidents are the weaknesses of the S&H risk management systems, such as the deficiencies in HAZID, risk assessment, and risk control [22,29,30].…”

Section: Feature Selectionmentioning

confidence: 51%

Accident Modeling in Small-scale Construction Projects Based on Artificial Neural Networks

Savareh

Mahdinia

Ghiyasi

et al. 2019

J. Hum. Environ. Health Promot

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Journal of Human, Environment, and Health PromotionJournal homepage: www.zums.ac.ir/jhehp Background: Several factors contribute to accidents in small-scale construction projects (SSCPs). The present study aimed to assess the influential factors in SSCP accidents and introduce a model to predict their frequency. Methods: In total, 38 SSCPs were within the scope of this investigation. The safety index of accident frequency rate (AFR) causing 452 injury construction accidents during 12 years (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018) was analyzed and modeled. Data analysis was performed based on feature selection using Pearson's χ 2 coefficient and SPSS modeler, as well as the artificial neural networks (ANNs) in MATLAB software. Results: Mean AFR was estimated at 26.32 ± 14.83, and the results of both approaches revealed that individual factors, organizational factors, training factors, and risk management-related factors could predict the AFR involved in SSCPs. Conclusion:The findings of this research could be reliably applied in the decisionmaking regarding safety and health construction issues. Furthermore, Pearson's correlation-coefficient and ANN modeling are considered to be reliable tools for accident modeling in SSCPs.

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“…1) Impact scale (I) with categories 1 -3. The scales used for measuring impact (I) with categories 1 -3 were found in up to 4 reference sources [4,[9][10][11]. The impact scale with categories 1 -3 has been described in Table 1.…”

Section: Risk Impact Categorization Scalementioning

confidence: 99%

A Concept Model to Scale the Impact of Safety Risk in a Construction Project Using a Semi Quantitative Method

Sudarsana¹

2021

cea

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Assessment of accident severity in the construction industry using the Bayesian theorem

Abstract: The findings provide a direction for more effective safety strategies and occupational accident prevention and emergency programmes.

Cited by 34 publications

References 30 publications

Occupational Health and Safety Risk Levels of Building Construction Trades in Nigeria

Occupational Health and Safety Risk Levels of Building Construction Trades in Nigeria

Accident Modeling in Small-scale Construction Projects Based on Artificial Neural Networks

A Concept Model to Scale the Impact of Safety Risk in a Construction Project Using a Semi Quantitative Method

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