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An agent-based approach for structured modeling, analysis and improvement of safety culture

Author

Listed:
  • Alexei Sharpanskykh

    (Vrije Universiteit Amsterdam)

  • Sybert H. Stroeve

    (Air Transport Safety Institute)

Abstract

Safety culture is broadly recognized as important for operational safety in various fields, including air traffic management, power plant control and health care. Previous studies addressed characterization and assessment of safety culture extensively. Nevertheless, relations between safety culture and formal and informal organizational structures and processes are yet not well understood. To address this gap, a new, formal, agent-based approach is proposed. This paper shows the application of the approach to an air navigation service provider, including structured modeling, analysis and identification of improvement strategies for the organizational safety culture. The model results have been validated using safety culture data that had been achieved by an independent safety culture survey study.

Suggested Citation

  • Alexei Sharpanskykh & Sybert H. Stroeve, 2011. "An agent-based approach for structured modeling, analysis and improvement of safety culture," Computational and Mathematical Organization Theory, Springer, vol. 17(1), pages 77-117, March.
    • Handle: RePEc:spr:comaot:v:17:y:2011:i:1:d:10.1007_s10588-011-9083-9
    DOI: 10.1007/s10588-011-9083-9
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    References listed on IDEAS

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    1. Stroeve, Sybert H. & Sharpanskykh, Alexei & Kirwan, Barry, 2011. "Agent-based organizational modelling for analysis of safety culture at an air navigation service provider," Reliability Engineering and System Safety, Elsevier, vol. 96(5), pages 515-533.
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    Cited by:

    1. Davide Secchi & Raffaello Seri, 2017. "Controlling for false negatives in agent-based models: a review of power analysis in organizational research," Computational and Mathematical Organization Theory, Springer, vol. 23(1), pages 94-121, March.
    2. Gui Ye & Hongzhe Yue & Jingjing Yang & Hongyang Li & Qingting Xiang & Yuan Fu & Can Cui, 2020. "Understanding the Sociocognitive Process of Construction Workers’ Unsafe Behaviors: An Agent-Based Modeling Approach," IJERPH, MDPI, vol. 17(5), pages 1-33, March.
    3. Fan, Changjun & Liu, Zhong & Lu, Xin & Xiu, Baoxin & Chen, Qing, 2017. "An efficient link prediction index for complex military organization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 572-587.
    4. Cook, Andrew & Blom, Henk A.P. & Lillo, Fabrizio & Mantegna, Rosario Nunzio & Miccichè, Salvatore & Rivas, Damián & Vázquez, Rafael & Zanin, Massimiliano, 2015. "Applying complexity science to air traffic management," Journal of Air Transport Management, Elsevier, vol. 42(C), pages 149-158.
    5. Justin Pence & Zahra Mohaghegh, 2020. "A Discourse on the Incorporation of Organizational Factors into Probabilistic Risk Assessment: Key Questions and Categorical Review," Risk Analysis, John Wiley & Sons, vol. 40(6), pages 1183-1211, June.
    6. Fredy Tantri & Sulfikar Amir, 2019. "Modeling a Simulation for Sociotechnical Resilience," Complexity, Hindawi, vol. 2019, pages 1-11, December.
    7. Christine Chou & Steven O. Kimbrough, 2016. "An agent-based model of organizational ambidexterity decisions and strategies in new product development," Computational and Mathematical Organization Theory, Springer, vol. 22(1), pages 4-46, March.

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