Workplace organizational correlates of lost‐time accident rates in manufacturing (original) (raw)
Related papers
Data Exploration and Statistical Analysis of Lost Time Injury in Manufacturing Industries
Journal of Advances in Mathematics and Computer Science
Accident (whether major or minor) is unexpected and inevitable due to dynamic nature of works, lack of workmanship, and lots of activities in industries. Some occur due to negligence, lack of knowledge or skill, improper handling of tools or equipment, lackadaisical attitudes towards the safety precautions. These attitudes result to highly prevalent exposure to dangers by employees in some industries. The study identified the industries with peculiar risk cases and safety conditions, design questionnaires applicable to accident reporting cases for the industries, model the percentage effect of injuries, illnesses, and fatalities (variables) on yearly basis, and model lost time injuries, illnesses, and fatalities with statistical analysis against the cost of implications. The software used in this study was SPSS version 25 while model built was Multi-linear regression and a correlation matrix was used to check the relationship between the dependent variable (i.e. cost of implication)...
Empirical analysis of the incidence of accidents in the workplace on firms’ financial performance
Safety Science, 2014
(J.M. Argilés) of productivity. Similarly, Saurin et al. (2004) find contradictory evidence when examining the integration of production and safety plans in two industrial building projects in Brazil. Taking a qualitative approach, Smallman and John (2001) conducted in-depth interviews with eight business leaders of FTSE 500 organizations. On the basis of these responses, they report that poor occupational health safety performance would appear to lead to competitive disadvantage, but they offer no quantitative evidence to support this. According to the business leaders, this competitive disadvantage is the result of the impairment of a firm's status in the eyes of one or more of its stakeholders. The authors report that the companies have little idea of their ongoing outlay on safety-related items or of the financial return on their investment in safety. Elsewhere, Kjellén et al. (1997) analyzed a Norwegian aluminum plant that implemented a quality control system and a safety, health and environment management system over a ten-year period. They report a reduction in the plant's operation expenditures, in parallel with an improvement in quality control, safety, health and environment indicators, but the authors do not perform any statistical tests. Moreover, the study only includes one manufacturing plant, which impedes the drawing of any statistical inferences. Fernández-Muñiz et al. (2009, 2012) report a significant positive relation between safety management and firm performance, but their studies have several limitations. As their findings are based on the responses to a questionnaire conducted with the firms' safety officers, the ultimate sample reflects the willingness of these officers to take part, a fact that could originate biases, with the firms with the best safety culture (and presumably the lowest accident rates) being more predisposed to participate. Similarly, the authors measured the firms' safety management systems in the light of participant responses, but presented no data for the firms' actual accident rates. Moreover, while the authors test the incidence of safety climate and safety management on company performance and competitiveness, they do not examine the incidence of accidents in the workplace on financial performance. In addition, as the authors themselves stress, they do not conduct a time-series data analysis in these studies. Multiple circumstances influence the incidence of occupational accidents, and many factors have been proposed as contributing to such hazards (e.g. Cheng et al., 2010). While the most important factors influencing accident rates would appear to be economic
Industry differences in accident causation
Safety Science, 1996
Occupational fatalities are thought to have similar origins across different types of work. In this study all occupational fatalities occurring in Australia over a three year period were coded and classified using a method designed to describe the comprehensive causes of accidents. The aim of the study was to determine whether there are general causation patterns for fatalities at work across all industry. One thousand and twenty occupational fatalities were coded for the analysis. Correspondence analysis and cluster analysis were used to describe the patterns and relationships between occupational groups and nature of the accident precursor sequence. The results of the final cluster analysis showed that fatalities occurred in a similar manner for most occupational groups. The major exceptions were timbergetters and electrical trades workers. Two main factors seemed to be important, however, in distinguishing the nature of accident precursors of the occupational groups -the gross nature of the accident sequence with respect to the involvement of behavioural or environmental factors and the presence or absence of unsafe work practices as contributors to the sequences. There was some interaction between these two factors.
Estimating Worker Risk Levels Using Accident/Incident Data
2000
The purpose of the work described in this report was to identify methods that are currently being used in the Department of Energy (DOE) complex to identify and control hazards/risks in the workplace, evaluate them in terms of their effectiveness in reducing risk to the workers, and develop a preliminary method that could be used to predict the relative risks to workers performing proposed tasks using some of the current methodology. It is recognized that some of the methods discussed in this report on the evaluation of workplace safety levels or the reduction of risks in the workplace do not apply to lower-risk work environments. They are more applicable to high-risk tasks, projects, or programs.
Iranian Rehabilitation Journal, 2022
Work-related accidents as one of the most prominent indicators of safety and health in the industry play an undeniable role in developing and improving the quality of industrial health management. Therefore, their accurate analysis on a large scale is essential. To provide controlling solutions, we aimed to investigate the causes of occupational accidents in Iran for 10 years (2007-2017). Methods: At first, the reports of 10-year work-related accidents were taken from the Social Security Organization, then classified, and entered into SPSS software, version 18.0. Analyses were performed in two stages. Descriptive analyses were initially performed and then multivariate Cox regression was implemented to determine the significance of the effects of the identified factors. Accordingly, six parameters including the cause of the occurrence, gender, type of insurance, time of the accident, marital status, and type of accident were extracted as the effective factors. Next, the effect of each parameter was examined using multivariate Cox regression with a 95% confidence interval. Results: The findings showed that falls and slips (18.3%) and physical strikes (14.6%) were the most common causes of accidents, and carelessness (61.9%) and equipment density (21.1%) had the strongest impact on accidents. Accidents had the highest incidence rate from 9 AM to noon (34.77%). The findings also showed that accident location (P<0.001), cause of the accident (P<0.001), type of insurance (P<0.001), and age (P<0.001) had significant effects on the duration of absence from work. Moreover, the findings demonstrated that the mental condition of workers and workplace design/layout had the strongest impacts on the rate of accidents. Discussion: to control and reduce the risk of occupational accidents, appropriate working situations should be provided.
Individual and job characteristics as predictors of industrial accidents
Accident Analysis & Prevention, 1986
This study asks whether individual or job characteristics are better predictors of industrial accidents. Data include a subset of employees drawn from the nationally-based Panel Study of Income Dynamics for 1978 and 1979. Individuals are classified as suffering a new accident if they began receiving workers' compensation during the study year. Evidence is produced that job characteristics such as frequent overtime, operative or laborer occupational categories, length of time with the job and hazardous working conditions are better predictors of industrial accidents than are personal characteristics such as age, marital status and schooling.
Investigating Some Individual Factors Effect on the Consequence Severity of Occupational Accidents
2020
Most industrial accidents are due to unsafe behaviors in the workplace. Therefore, the present study was aimed to investigate the role of individual factors on the consequence of accidents. This descriptive-analytical study was carried out based on data obtained from 1048 accidents registered in the Labor Inspection Office of one of the industrial provinces of Iran. In this study, individual factors were extracted from accident reporting forms and analyzed by SPSS software version 18. In the current study, the results showed that the least number of accidents was related to employee who had a bachelor degree or above. Of 95% reported fatalities were male and 73% of them were married. The results of statistical test showed that there is a significant relationship between outcome type and marital status (p <0.001). It was also found that the employees under 30 years old had the highest number of minor injuries and death. Fisher test showed a significant relationship between age and...
INTERNATIONAL JOURNAL OF PREVENTIVE, CURATIVE & COMMUNITY MEDICINE, 2017
Introduction: Human and organisational factors (HOF) are essential components of all types of industry. On one hand, HOF is found to be the influencing factor that contributes to the workplace injuries while on the other hand, HOF has long been accepted as having a significant role in accident prevention in any industries. Nevertheless, no study was found to be conducted on contribution and prevention of workplace accident due to HOF in Ferroalloy industry in Bhutan. Objectives: to describe how the HOF contribute to accident and their association with workplace accident in the ferroalloy industries. Methods: This is a cross-sectional study with a sample size of 300 workers selected proportionately among the six ferroalloy industries in Bhutan. Results: Among the human factors, this study found a significant association between regular employment, workers with dependents, and four occupations of 12 listed. Among the occupations, Tapper, Electrician, Mechanic, and Lab technician were found significantly associated with workplace accident. The nature of these jobs was found physically demanding and more hazardous than other occupations. The significant result between workers with dependent and workplace accident was supported by higher incidence of workplace accident among the married and divorced workers (21.2%) compared to single (17.4%). The equipment and training of organisational factors were found to be significantly associated with workplace accident. Conclusion: The social factors were also found to be the triggering factors of a workplace accident. Similarly, poor level of equipment and training of an organisation such as lack of regular safety training, and inadequate and sub-standards equipment were the contributing factors of the workplace accident. HOF was also influenced by lack of strong OHSMS at the workplace and National OHSA in the country.