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Near‐Miss Incident Management in the Chemical Process Industry

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  • James R. Phimister
  • Ulku Oktem
  • Paul R. Kleindorfer
  • Howard Kunreuther

Abstract

This article provides a systematic framework for the analysis and improvement of near‐miss programs in the chemical process industries. Near‐miss programs improve corporate environmental, health, and safety (EHS) performance through the identification and management of near misses. Based on more than 100 interviews at 20 chemical and pharmaceutical facilities, a seven‐stage framework has been developed and is presented herein. The framework enables sites to analyze their own near‐miss programs, identify weak management links, and implement systemwide improvements.

Suggested Citation

  • James R. Phimister & Ulku Oktem & Paul R. Kleindorfer & Howard Kunreuther, 2003. "Near‐Miss Incident Management in the Chemical Process Industry," Risk Analysis, John Wiley & Sons, vol. 23(3), pages 445-459, June.
    • Handle: RePEc:wly:riskan:v:23:y:2003:i:3:p:445-459
    DOI: 10.1111/1539-6924.00326
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    References listed on IDEAS

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    1. James G. March & Lee S. Sproull & Michal Tamuz, 1991. "Learning from Samples of One or Fewer," Organization Science, INFORMS, vol. 2(1), pages 1-13, February.
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    1. Sarah Maslen & Jan Hayes & Janice Wong & Christina Scott-Young, 2020. "Witch hunts and scapegoats: an investigation into the impact of personal liability concerns on engineers’ reporting of risks," Environment Systems and Decisions, Springer, vol. 40(3), pages 413-426, September.
    2. Azadegan, Arash & Srinivasan, Ravi & Blome, Constantin & Tajeddini, Kayhan, 2019. "Learning from near-miss events: An organizational learning perspective on supply chain disruption response," International Journal of Production Economics, Elsevier, vol. 216(C), pages 215-226.
    3. Xie, Shuyi & Huang, Zimeng & Wu, Gang & Luo, Jinheng & Li, Lifeng & Ma, Weifeng & Wang, Bohong, 2024. "Combining precursor and Cloud Leaky noisy-OR logic gate Bayesian network for dynamic probability analysis of major accidents in the oil depots," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    4. Junko Shimazoe & Richard M. Burton, 2013. "Justification shift and uncertainty: why are low-probability near misses underrated against organizational routines?," Computational and Mathematical Organization Theory, Springer, vol. 19(1), pages 78-100, March.
    5. Patrick L. Yorio & Dana R. Willmer & Joel M. Haight, 2014. "Interpreting MSHA Citations Through the Lens of Occupational Health and Safety Management Systems: Investigating Their Impact on Mine Injuries and Illnesses 2003–2010," Risk Analysis, John Wiley & Sons, vol. 34(8), pages 1538-1553, August.
    6. Nima Khakzad & Faisal Khan & Paul Amyotte, 2015. "Major Accidents (Gray Swans) Likelihood Modeling Using Accident Precursors and Approximate Reasoning," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1336-1347, July.
    7. Federica De Leo & Valerio Elia & Maria Grazia Gnoni & Fabiana Tornese, 2023. "Integrating Safety-I and Safety-II Approaches in Near Miss Management: A Critical Analysis," Sustainability, MDPI, vol. 15(3), pages 1-14, January.
    8. Patrick L. Yorio & Susan M. Moore, 2018. "Examining Factors that Influence the Existence of Heinrich's Safety Triangle Using Site‐Specific H&S Data from More than 25,000 Establishments," Risk Analysis, John Wiley & Sons, vol. 38(4), pages 839-852, April.

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