Extended Abstract
Introduction: In industrial society, the work process was transferred to factories in order to improve productivity. Employees, interacting with each other and with technology, began to work. However, work-related accidents soon became one of the major concerns in factories. Work-related accidents cause death or injury to millions of workers all over the world annually and destroy 4% of Gross National Production (GDP). Work-related accidents pose a serious social problem due to physical and mental harm to workers, reduction in productivity, and negative impact on the stability and well-being of society. In Iran, work-related accidents are increasing rapidly, but they have not been given much attention especially from a sociological point of view. The aim of the present study is to examine work-related accidents in Iran in terms of macro socioeconomic indicators.
Method: This study employs a quantitative longitudinal approach, utilizing time-series methodology to examine the relationship between variables from 1997 to 2022. The number of recorded accidents was used as the measure of work-related accidents. In addition, female labor force participation, urban population, literacy rate, inflation, labor force participation, and GDP per capita were used to measure the socio-economic indicators. The required data were collected from the Social Security Organization (SSO), the Statistical Center of Iran (SCI), the Ministry of Cooperatives, Labor and Social Welfare (MCLSW), the Central Bank of Islamic Republic of Iran (CBI), and the World Bank (WB). To investigate both short-term and long-term relationships, the Autoregressive Distributed Lag (ARDL) model was implemented utilizing Microfit software version 5.
Findings: According to the results of the research, in the long-term period, there is a negative and significant relationship between urban population (T-Ratio = - 4.85, Prob.= .005) and inflation rate (T-Ratio = - 5.53, Prob.= .003), and work-related accidents. On the other hand, the findings indicate that GDP per capita (T-Ratio = 15.2, Prob.= .000), literacy rate (T-Ratio = 6.57, Prob.= .001), and labor force participation (T-Ratio = 3.23, Prob.= .023) have a positive and significant relationship with work-related accidents. Additionally, based on the research findings, female labor force participation rate does not have a significant relationship with work-related accidents (T-Ratio= -1.81, Prob.= .130).
Conclusion: Based on the research findings, the conclusion of the present study is that work-related accidents at the macro level are affected by some socio-economic indicators. This means that understanding the mechanism of the relationships between variables can help reduce the work-related accidents and their harmful consequences in Iran.