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An Analysis on the Accident Influence Factor and Severity of Construction General Workers

건설 보통인부의 안전재해 영향요인 및 재해강도 분석

  • Received : 2017.12.07
  • Accepted : 2018.01.08
  • Published : 2018.03.30

Abstract

General workers who assist various technicians in different fields with their work across the whole construction sites without having a particular skill are at risk of the highest accident rate and their accident form becomes varied. Accordingly, this study was conducted to identify the relationship between form of safety accident and influence factor in general workers and analyze accident severity by influence factor. The followings are the results from this study. First, as a result of analyzing major form of accident and influence factors in general workers with network analysis methodology, nine forms of accident and seventeen influence factors were drawn. Second, it was found that in accident severity among general workers, collapsing, among various forms of accident, appeared the highest, followed by fall, electric shock, fire, hit by an object, bumped against, trip, scission getting cut chopped in order. Third, main points of special, concentrated, and permanent management were presented in order to reduce the safety accident in general workers effectively.

Keywords

Acknowledgement

Supported by : 한국연구재단

References

  1. Ahn, S. J., Park, Y. J., Park, T. H., & Kim, T. H. (2015). Development of Safety Training Delivery Method Using 3D Simulation Technology for Construction Worker. Journal of Korea Institute of Building Construction, 15(6), 621-629 https://doi.org/10.5345/JKIBC.2015.15.6.621
  2. Ahn, S. M., Kim, I. H., Choi, B. G., Cho, Y. H., Kim, E. H., & Kim, M. K. (2012). Understanding the Performance of Collaborative Filtering Recommendation through Social Network Analysis. Journal of Society for e-Business Studies, 17(2), 129-47 https://doi.org/10.7838/JSEBS.2012.17.2.129
  3. Cho, Y. R., Kim, Y. C., & Shin, Y. S. (2017). Prediction Model of Construction Safety Accidents using Decision Tree Technique. Journal of Korea Institute of Building Construction, 17(3), 295-303 https://doi.org/10.5345/JKIBC.2017.17.3.295
  4. Choi, H. O. (2015). Analysis of Cadastral Survey Issues by Text Mining on Social Media Trends. Journal of the Korean Urban Management Association, 28(3), 147-61
  5. Chun, J. H., Lee, C. S., & Lee, S. J. (2016). Central Technology Deriving for the Patents of Medical Device using Social Network Analysis. Journal of Management and Information System, 35(2), 221-54
  6. Chun, H. J., & Leem, B. H. (2013). Analysis to Customer Churn Provoker's Roles Using Call Network of a Telecom Company. The Korean Journal of Applied Statistics, 26(1), 23-36 https://doi.org/10.5351/KJAS.2013.26.1.023
  7. Chung, T. J. (2016). Countermeasure strategy for the international crime and terrorism by use of SNA and Big data analysis. Journal of Information Security, 16(2), 25-34
  8. Hong, J. R., Shon, S. D., & Lee, S. J. (2015). A Study on the Improvement of the Construction Safety Hands-on Education Course to Prevent the Construction Death Accidents. Journal of the Architectural Institute of Korea, 31(12), 3-10
  9. Hong, J. R., Shon, S. D., & Lee, S. J. (2016). A Study on Construction Safety Curriculum Development Based on National Competency Standard. Journal of the Architectural Institute of Korea, 32(3), 47-56
  10. Ko, G. S., Kim, B. H., Kim, D. Y., Choi, M. W., Lim, J. T., Bok, K. S., & Yoo, J. S. (2017). Contents Recommendation Scheme Considering User Activity in Social Network Environments. Journal of The Korea Contents Association, 17(2), 404-14 https://doi.org/10.5392/JKCA.2017.17.02.404
  11. Kim, J. W., Lee, H. S., Park, M. S., & Kwon, N. H. (2017). A System Dynamics Approach for Modeling Cognitive Process of Construction Workers' Unsafe Behaviors. Korea Journal of Construction Engineering and Management, 18(2), 38-48 https://doi.org/10.6106/KJCEM.2017.18.2.038
  12. Kim, P. K., Bang, S. D., Kim, K. S., & Kim, H. K. (2017). Research of actual condition and mitigation plan for aging workers' health and safety at construction sites. Korea Journal of Construction Engineering and Management, 18(1), 37-47 https://doi.org/10.6106/KJCEM.2017.18.1.037
  13. Lee, K. J. (2014). A Comparison of Income Level and Work-Related Fatalities for Finding Causes and Measures for Construction Sector. Korea Journal of Construction Engineering and Management, 15(4), 3-10 https://doi.org/10.6106/KJCEM.2014.15.4.003
  14. Lee, K. J. (2017). Preventive Occupational Health and Safety Expense Estimation Method based on Fatality Statistics and Progress Model. Journal of Korea Institute of Building Construction, 17(2), 191-197 https://doi.org/10.5345/JKIBC.2017.17.2.191
  15. Lee, M. Y., Oh, S. W., & Lim, S. J. (2016). A Study of Improvement on Accident Rate Index of Construction Industry. Korea Journal of Construction Engineering and Management, 17(5), 108-119 https://doi.org/10.6106/KJCEM.2016.17.5.108
  16. Lim, T. K., Lee, S. S., & Lee, D. E. (2014). A Methodology for Measuring and Assessing Construction Worker's Near-misses. Journal of The Korea Contents Association, 30(1), 71-79
  17. Oh, M. H., Park, T. H., Park, Y. J., Son, K. Y., Ahn, S. J., & Kim, T. H. (2014). An Assessment of Safety Education Contents Propriety Analyzing Accident Types by Work Classification in Construction Site. Journal of the Architectural Institute of Korea, 30(3), 131-139
  18. Park, D. H., Kim, T. G., & Lee, G. H. (2016). An Analysis of Tourism Information Network using Social Big Data. International Journal of Tourism and Hospitality Research, 30(8), 195-208
  19. Shin, W. S., & Son, C. B. (2017). An Analysis on the Relationship between Occurrence Type and Influence Factor of Construction Safety Accident using SNA Method. Journal of the Architectural Institute of Korea, 33(4), 47-54
  20. Yang, K. W. (2017). Research Trend Analysis of 'International Commerce and Information Review' using SNA-based Keyword Network Analysis. International Commerce and Information Review, 19(1), 23-42