Applying data mining techniques to explore factors contributing to occupational injuries in Taiwan's construction industry |
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| Authors: | Ching-Wu Cheng Sou-Sen Leu Ying-Mei Cheng Tsung-Chih Wu Chen-Chung Lin |
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| Affiliation: | 1. Department of Safety, Health and Environmental Engineering, Ming Chi University of Technology, 84 Gungjuan Rd., Taishan District, New Taipei City 243, Taiwan;2. Department of Construction Engineering, National Taiwan University of Science and Technology, 43 Keelung Rd., Section 4, Taipei City 106, Taiwan;3. Department of Civil Engineering, China University of Technology, 56 Hsing-Lung Rd., Section 3, Taipei City 116, Taiwan;4. Department of Safety, Health and Environmental Engineering, HungKuang University, 34 Chung-Chie Rd., Shalu District, Taichung City 433, Taiwan;5. Institute of Occupational Safety and Health, 99, Lane 407, Hengke Rd., Sijhih District, New Taipei City 221, Taiwan |
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| Abstract: | Construction accident research involves the systematic sorting, classification, and encoding of comprehensive databases of injuries and fatalities. The present study explores the causes and distribution of occupational accidents in the Taiwan construction industry by analyzing such a database using the data mining method known as classification and regression tree (CART). Utilizing a database of 1542 accident cases during the period 2000–2009, the study seeks to establish potential cause-and-effect relationships regarding serious occupational accidents in the industry. The results of this study show that the occurrence rules for falls and collapses in both public and private project construction industries serve as key factors to predict the occurrence of occupational injuries. The results of the study provide a framework for improving the safety practices and training programs that are essential to protecting construction workers from occasional or unexpected accidents. |
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| Keywords: | Construction industry Occupational accidents Data mining Safety management Data analysis |
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