• Journal of the Korean Society of Safety
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• v.20 no.4 s.72
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• pp.122-129
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• 2005

With Zohar(1980)'s research on safety climate and industrial safety, occupational safety and health literatures begin to emphasize the influence of organizational context. Based on this research trend, this paper tried to review the relationship between individual/ organizational factors and occupational accidents. Based on the responses from 294 manufacturing workers, this paper reviewed the relationships among safety climates, safety performance, and age. The results of statistical analysis showed that all safety climate factors have affirmative effects on safety participation and safety attitudes negative effect on accident number, and job load affirmative effect on accident number. Job load and management commitment showed interactive effects on accident number with age.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.2116-2120
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• 2008

Recently, in the national railway industry there has been interested in the methodology of hazard analysis and risk assessment. The need of safety management system based on the technology of hazard analysis and risk assessment is being extended to identify in advance the weakness and threat factors causing the accident and cope with the accident actively. It is important to manage the risk of railway casualty accidents having a majority of railway accident. Especially, a hazard event of people struck takes the highest proportion of the railway casualty accidents. This paper describes the result of analysis for environment properties such as an age of casualty, time happened, day, month and weather conditions being concerned in the hazard event of people struck.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.169-170
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• 2022

As the size of construction projects has become larger in recent years, the nature of the disaster safety factors along with the progress of construction is also becoming more complex and diversified. Accordingly, the introduction of computerized construction, new technologies, and new construction methods has resulted in a variety of risk factors in the process and operations, and many new safety construction methods are being tried. Since the construction industry has variable working environments and constantly changes working methods and components depending on the rate of progress, workers at construction sites are always exposed to risk depending on the specific circumstances of the construction industry. This study attempts to collect and analyze major accident cases generated by major accident construction projects as a result of progress in construction work, and to derive the major causes and causes for each safety management activity that affect safety accidents.

• Safety and Health at Work
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• v.8 no.3
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• pp.267-275
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• 2017

Background: The mining industry is known worldwide for its highly risky and hazardous working environment. Technological advancement in ore extraction techniques for proliferation of production levels has caused further concern for safety in this industry. Research so far in the area of safety has revealed that the majority of incidents in hazardous industry take place because of human error, the control of which would enhance safety levels in working sites to a considerable extent. Methods: The present work focuses upon the analysis of human factors such as unsafe acts, preconditions for unsafe acts, unsafe leadership, and organizational influences. A modified human factor analysis and classification system (HFACS) was adopted and an accident predictive fuzzy reasoning approach (FRA)-based system was developed to predict the likelihood of accidents for manganese mines in India, using analysis of factors such as age, experience of worker, shift of work, etc. Results: The outcome of the analysis indicated that skill-based errors are most critical and require immediate attention for mitigation. The FRA-based accident prediction system developed gives an outcome as an indicative risk score associated with the identified accident-prone situation, based upon which a suitable plan for mitigation can be developed. Conclusion: Unsafe acts of the worker are the most critical human factors identified to be controlled on priority basis. A significant association of factors (namely age, experience of the worker, and shift of work) with unsafe acts performed by the operator is identified based upon which the FRA-based accident prediction model is proposed.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.121-129
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• 2012

PURPOSES : Traffic accidents at intersections have been increased annually so that it is required to examine the causations to reduce the accidents. However, the current existing accident models were developed mainly with non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal complicated causations for traffic accidents, though they are right choices to study randomness and non-linearity of accidents. Therefore, to reveal the complicated causations of traffic accidents, this study used structural equation methods(SEM). METHODS : SEM used in this study is a statistical technique for estimating causal relations using a combination of statistical data and qualitative causal assumptions. SEM allow exploratory modeling, meaning they are suited to theory development. The method is tested against the obtained measurement data to determine how well the model fits the data. Among the strengths of SEM is the ability to construct latent variables: variables which are not measured directly, but are estimated in the model from several measured variables. This allows the modeler to explicitly capture the unreliability of measurement in the model, which allows the structural relations between latent variables to be accurately estimated. RESULTS : The study results showed that causal factors could be grouped into 3. Factor 1 includes traffic variables, and Factor 2 contains turning traffic variables. Factor 3 consists of other road element variables such as speed limits or signal cycles. CONCLUSIONS : Non-linear regression models can be used to develop accident predictions models. However, they lack to estimate causal factors, because they select only few significant variables to raise the accuracy of the model performance. Compared to the regressions, SEM has merits to estimate causal factors affecting accidents, because it allows the structural relations between latent variables. Therefore, this study used SEM to estimate causal factors affecting accident at urban signalized intersections.

• Journal of Biosystems Engineering
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• v.39 no.3
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• pp.151-157
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• 2014

Purpose: In order to develop strategies to prevent farm-work accidents relating to agricultural machinery, influential factors were examined in this paper. The effects of these factors were quantified using logistic regression. Methods: Based on the results of a survey on farm-work accidents conducted by the National Academy of Agricultural Science, 21 tentative independent variables were selected. To apply these variables to regression, the presence of multicollinearity was examined by comparing correlation coefficients, checking the statistical significance of the coefficients in a simple linear regression model, and calculating the variance inflation factor. A logistic regression model and determination method of its goodness of fit was defined. Results: Among 21 independent variables, 13 variables were not collinear each other. The results of a logistic regression analysis using these variables showed that the model was significant and acceptable, with deviance of 714.053. Parameter estimation results showed that four variables (age, power tiller ownership, cognizance of the government's safety policy, and consciousness of safety) were significant. The logistic regression model predicted that the former two increased accident odds by 1.027 and 8.506 times, respectively, while the latter two decreased the odds by 0.243 and 0.545 times, respectively. Conclusions: Prevention strategies against factors causing an accident, such as the age of farmers and the use of a power tiller, are necessary. In addition, more efficient trainings to elevate the farmer's consciousness about safety must be provided.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.447-457
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• 2017

This study aims to analyze the accidents of green mode bicycle. In pursuing the above, this study gave special emphasis on modeling the bicycle accidents reflecting the regional characteristics. The main results are as follows. First, the null hypotheses that the number of accident and ratio of serious injury and fatality (FSI) were the same over regions were rejected. Second, as the common variables, the number of bicycle was judged to have positive (+) impact to the accidents and the bicycle using ratio was inferred to increase the ratio of FSI. Third, the elderly population ratio among 3 factors which gave impact to the accidents of Si_A (city-county consolidation) was concluded to have the greatest elasticity. The developed area ratio between 2 factors in Si_B (city which is not consolidated) was, however, estimated to have the higher elasticity. Fourth, the number of car registration among 5 accident factors of Gun (county) was analyzed to have the greatest elasticity. Finally, the commuting trip ratio among 7 accident factors of Gu (district) was judged to have the greatest elasticity. This study can be expected to give some implications to regional policy-making related to bicycle.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.2
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• pp.138-146
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• 2020

Stow net fishery is one of the fishery with high fishing work accidents in southwestern sea of Korea. We conducted to serve as basic data for improving the healthy and safe working environment of fisher using risk assessment process (ISO45001) with fishermen's occupational accidents of the National Federation of Fisheries Cooperative (NFFC) from 2016 to 2018. The average occurrence rate of victim in this fishery was 9.04%, 16.7 times more than such rate in all industries. In addition, the average fatality rate was found to have a very serious level management to 31.06‱, 27.7 times more than such rate in all industries. The safety hazards of stow net fishery was more likely to occur by other general industrial groups, with more severe consequences after the accident. According to 4M analysis, 58.6% of all accidents were caused by human factors, 24.0% by environmental factors, 16.0% by mechanical factors, and 1.5% by managerial factors, respectively. The occurrence frequency by accident type was the highest in 187 cases (32.2%) for struck by object, 158 cases (27.2%) for slipping, and 94 cases (16.2%) for being in contact with machinery. Severity is the highest for others such as diseases etc., in the order of being struck by object, being in contact with machinery, falling from above slipping, collapsing, bumping, and burning. Being struck by object, being in contact with machinery, and slipping are high-risk groups, falling from above others, bumping, and burning are medium-risk groups based on the risk assessment using the occurrence frequency and severity of accident. The obtained results are expected to contribute to the safe operation environment subsidy for fishing crews on the stow net fishing vessel.

• Journal of the Korea Institute of Building Construction
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• v.23 no.6
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• pp.821-830
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• 2023

This research aims to identify risk factors for fall accidents at small and medium-sized construction sites through a comprehensive regression analysis. Initially, the study involved collecting a decade's worth of fall accident data from these sites. A t-test confirmed a significant variation in the treatment duration following fall accidents between two distinct groups: small and medium-sized versus large construction sites. Subsequently, a regression analysis was conducted to establish a model highlighting the risk factors associated with safety accidents. The factors influencing fall accidents were determined to be, in descending order of impact, the time of the accident, the day of the accident, and the occupational classification. The findings from this study are expected to serve as foundational data for enhancing policies and conducting statistical analyses tailored to construction site sizes. They also provide crucial information for future research on risk quantification at small and medium-sized construction sites.

• Journal of the Korean Society of Safety
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• v.31 no.3
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• pp.143-155
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• 2016

Recently, a massive loss of life and property is occurring in Korea due to traffic accidents, with the rapid increase in cars. For improvement of traffic safety, the Korea Transportation Safety Authority intensively analyzes accident data in local governments with low traffic safety index, performs a field investigation to extract problems and offers local governments improvements for problems, by conducting the 'Special Survey of Actual Conditions of Traffic Safety' each year, starting 2008. But local governments cannot strongly push forward the improvement projects due to the limited budget and the uncertainty of the improvement plan effects. Therefore, this study suggested a model which applied the Utility concept to the AHP theory, in order to efficiently decide a priority of the improvement plans in accident black spots in consideration of the limited budget of local governments. The number of accidents in each spot for improvement and accident severity, traffic volume, pedestrian volume, the improvement project cost and the accident reduction effect were chosen as evaluation factors for deciding a priority, and data about the improvement plan costs and the accident reduction effects, traffic accidents and traffic volume in the spots to undergo the special research on the real condition of traffic accident in the past were collected from the existing studies. Then, regression analysis was carried out and the Utility Curve of each evaluation factor was computed. Based on the AHP analysis findings, this study devised a priority decision method which calculated the weight and the utility function of each evaluation factor and compared the total utility values. The AHP analysis findings showed that among the evaluation factors, accident severity had the biggest importance and it was followed by the improvement plan cost, the number of accidents, the improvement effect, traffic volume and pedestrian volume. The calculated utility function shows a rise in utility, as the variables of the 5 evaluation factors; the number of accidents, accident severity, the improvement plan effect, traffic volume and pedestrian volume increase and a fall in utility, as the variables of the improvement plan cost increase, since the improvement plan cost is included in the budget spent by a local government.