IDEAS home Printed from https://ideas.repec.org/a/spr/comaot/v22y2016i4d10.1007_s10588-016-9212-6.html
   My bibliography  Save this article

Modeling safety culture as a socially emergent phenomenon: a case study in aircraft maintenance

Author

Listed:
  • David Passenier

    (VU University Amsterdam)

  • Colin Mols

    (VU University Amsterdam)

  • Jan Bím

    (VU University Amsterdam)

  • Alexei Sharpanskykh

    (Delft University of Technology)

Abstract

Safety culture is often understood as encompassing organizational members’ shared attitudes, beliefs, perceptions and values associated with safety. Safety culture theory development is fraught with inconsistencies and superficiality of measurement methods, because the dynamic and political nature of culture is often ignored. Traditionally, safety culture is analyzed by survey-based approaches. In this paper we propose a novel, systemic, interdisciplinary approach for investigating safety culture that combines multi-agent system modeling with organizational ethnography. By using this approach, mechanisms of emergence of safety culture from daily practices, operations and interactions of organizational actors can be modeled and analyzed. The approach is illustrated by a case study from the aircraft maintenance domain, based on existing ethnographic data. Using the proposed approach we were able to reproduce and explain emergent characteristic patterns of commitment to safety in the maintenance organization from this study. The model can be used for theory development and as a management tool to evaluate non-linear impacts of organizational arrangements on workers’ commitment to safety.

Suggested Citation

  • David Passenier & Colin Mols & Jan Bím & Alexei Sharpanskykh, 2016. "Modeling safety culture as a socially emergent phenomenon: a case study in aircraft maintenance," Computational and Mathematical Organization Theory, Springer, vol. 22(4), pages 487-520, December.
    • Handle: RePEc:spr:comaot:v:22:y:2016:i:4:d:10.1007_s10588-016-9212-6
    DOI: 10.1007/s10588-016-9212-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10588-016-9212-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10588-016-9212-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sascha Holzhauer & Friedrich Krebs & Andreas Ernst, 2013. "Considering baseline homophily when generating spatial social networks for agent-based modelling," Computational and Mathematical Organization Theory, Springer, vol. 19(2), pages 128-150, June.
    2. Richard M. Burton, 2003. "Computational Laboratories for Organization Science: Questions, Validity and Docking," Computational and Mathematical Organization Theory, Springer, vol. 9(2), pages 91-108, July.
    3. Rubén Fuentes-Fernández & Samer Hassan & Juan Pavón & José M. Galán & Adolfo López-Paredes, 2012. "Metamodels for role-driven agent-based modelling," Computational and Mathematical Organization Theory, Springer, vol. 18(1), pages 91-112, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stefano Guarino & Enrico Mastrostefano & Massimo Bernaschi & Alessandro Celestini & Marco Cianfriglia & Davide Torre & Lena Rebecca Zastrow, 2021. "Inferring Urban Social Networks from Publicly Available Data," Future Internet, MDPI, vol. 13(5), pages 1-45, April.
    2. Jonas Friege & Georg Holtz & Emile Chappin, 2016. "Exploring Homeowners’ Insulation Activity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(1), pages 1-4.
    3. Robert Marks, 2007. "Validating Simulation Models: A General Framework and Four Applied Examples," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 265-290, October.
    4. Kent D. Miller & Shu-Jou Lin, 2010. "Different Truths in Different Worlds," Organization Science, INFORMS, vol. 21(1), pages 97-114, February.
    5. Enrico Cozzoni & Carmine Passavanti & Cristina Ponsiglione & Simonetta Primario & Pierluigi Rippa, 2021. "Interorganizational Collaboration in Innovation Networks: An Agent Based Model for Responsible Research and Innovation in Additive Manufacturing," Sustainability, MDPI, vol. 13(13), pages 1-17, July.
    6. Bing Bai & Byungjoon Yoo & Xiuquan Deng & Iljoo Kim & Dehua Gao, 2016. "Linking routines to the evolution of IT capability on agent-based modeling and simulation: a dynamic perspective," Computational and Mathematical Organization Theory, Springer, vol. 22(2), pages 184-211, June.
    7. Concetta Sorropago, 2012. "Incentive Design and Manager Performances: an ABM Approach," Working papers 008, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    8. Meysam Alizadeh & Claudio Cioffi-Revilla & Andrew Crooks, 2017. "Generating and analyzing spatial social networks," Computational and Mathematical Organization Theory, Springer, vol. 23(3), pages 362-390, September.
    9. Wersching, Klaus, 2010. "Schumpeterian competition, technological regimes and learning through knowledge spillover," Journal of Economic Behavior & Organization, Elsevier, vol. 75(3), pages 482-493, September.
    10. Geoffrey Fairchild & Kyle S. Hickmann & Susan M. Mniszewski & Sara Y. Del Valle & James M. Hyman, 2014. "Optimizing human activity patterns using global sensitivity analysis," Computational and Mathematical Organization Theory, Springer, vol. 20(4), pages 394-416, December.
    11. Lucio Biggiero & Enrico Sevi, 2009. "Opportunism by cheating and its effects on industry profitability. The CIOPS model," Computational and Mathematical Organization Theory, Springer, vol. 15(3), pages 191-236, September.
    12. Tamaki Horii & Yan Jin & Raymond E. Levitt, 2005. "Modeling and Analyzing Cultural Influences on Project Team Performance," Computational and Mathematical Organization Theory, Springer, vol. 10(4), pages 305-321, January.
    13. Myong-Hun Chang & Joseph E. Harrington, 2007. "Innovators, Imitators, and the Evolving Architecture of Problem-Solving Networks," Organization Science, INFORMS, vol. 18(4), pages 648-666, August.
    14. Klaus Wersching, 2010. "Schumpeterian Competition, Technological Regimes and Learning through Knowledge Spillover," Post-Print hal-00849408, HAL.
    15. repec:tur:wpapnw:8 is not listed on IDEAS
    16. Kent D. Miller & Shu-Jou Lin, 2015. "Analogical reasoning for diagnosing strategic issues in dynamic and complex environments," Strategic Management Journal, Wiley Blackwell, vol. 36(13), pages 2000-2020, December.
    17. Chris Graziul & Alexander Belikov & Ishanu Chattopadyay & Ziwen Chen & Hongbo Fang & Anuraag Girdhar & Xiaoshuang Jia & P. M. Krafft & Max Kleiman-Weiner & Candice Lewis & Chen Liang & John Muchovej &, 2023. "Does big data serve policy? Not without context. An experiment with in silico social science," Computational and Mathematical Organization Theory, Springer, vol. 29(1), pages 188-219, March.
    18. Sasanka Sekhar Chanda, 2017. "Inferring final organizational outcomes from intermediate outcomes of exploration and exploitation: the complexity link," Computational and Mathematical Organization Theory, Springer, vol. 23(1), pages 61-93, March.
    19. Richard M. Burton & Børge Obel, 2011. "Computational Modeling for What-Is, What-Might-Be, and What-Should-Be Studies---And Triangulation," Organization Science, INFORMS, vol. 22(5), pages 1195-1202, October.
    20. Chris P. Long & Sim B. Sitkin & Laura B. Cardinal & Richard M. Burton, 2015. "How controls influence organizational information processing: insights from a computational modeling investigation," Computational and Mathematical Organization Theory, Springer, vol. 21(4), pages 406-436, December.
    21. Dmitry Sharapov & Jan‐Michael Ross, 2023. "Whom should a leader imitate? Using rivalry‐based imitation to manage strategic risk in changing environments," Strategic Management Journal, Wiley Blackwell, vol. 44(1), pages 311-342, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:comaot:v:22:y:2016:i:4:d:10.1007_s10588-016-9212-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.