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Application of the Loughborough Construction Accident Causation model: a framework for organizational learning

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  • Michael Behm
  • Arthur Schneller

Abstract

In order for the construction industry to improve its poor safety performance it needs to learn from its safety mistakes and put the lessons learned to good use. Incident investigation theories and techniques vary widely in the peer-reviewed literature. The Loughborough Construction Accident Causation (ConAC) model was applied to State Department of Transportation construction accidents, and is proposed as a tool to facilitate organizational learning in the construction industry. Details of the methodology utilized are described so that it can be duplicated in research and in practice. By investigating 27 DOT construction incidents, the research demonstrates how the model can be used both in research and in practice. The model yielded 6.63 causes/factors/influences identified per incident, and correlated the causes to determine relationships. Incident causality is complex and multi-faceted. The Loughborough model facilitates a holistic view of incident causality and thus organizational learning.

Suggested Citation

  • Michael Behm & Arthur Schneller, 2013. "Application of the Loughborough Construction Accident Causation model: a framework for organizational learning," Construction Management and Economics, Taylor & Francis Journals, vol. 31(6), pages 580-595, June.
    • Handle: RePEc:taf:conmgt:v:31:y:2013:i:6:p:580-595
    DOI: 10.1080/01446193.2012.690884
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    Cited by:

    1. Peipei Wang & Yunhan Huang & Jianguo Zhu & Ming Shan, 2022. "Construction Dispute Potentials: Mechanism versus Empiricism in Artificial Neural Networks," Sustainability, MDPI, vol. 14(22), pages 1-23, November.
    2. Albert P. C. Chan & Yang Yang & Tracy N. Y. Choi & Janet Mayowa Nwaogu, 2022. "Characteristics and Causes of Construction Accidents in a Large-Scale Development Project," Sustainability, MDPI, vol. 14(8), pages 1-25, April.
    3. Pouya Gholizadeh & Behzad Esmaeili, 2020. "Developing a Multi-variate Logistic Regression Model to Analyze Accident Scenarios: Case of Electrical Contractors," IJERPH, MDPI, vol. 17(13), pages 1-24, July.
    4. Yikun Su & Shijing Yang & Kangning Liu & Kaicheng Hua & Qi Yao, 2019. "Developing A Case-Based Reasoning Model for Safety Accident Pre-Control and Decision Making in the Construction Industry," IJERPH, MDPI, vol. 16(9), pages 1-20, April.
    5. Dimitrios Dimitriou & Konstantinos Papakostas, 2022. "Review of Management Comprehensiveness on Occupational Health and Safety for PPP Transportation Projects," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    6. Nuria Gamero & Inmaculada Silla & Rubén Sainz-González & Beatriz Sora, 2018. "The Influence of Organizational Factors on Road Transport Safety," IJERPH, MDPI, vol. 15(9), pages 1-8, September.

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