The big picture on accident causation: A review, synthesis and meta-analysis of AcciMap studies
The big picture on accident causation: A review, synthesis and meta-analysis of AcciMap studies
As AcciMap is now arguably the most popular accident analysis method in the peer-reviewed literature, there are key learnings to be taken from reviewing and synthesising published AcciMap analyses. In particular, the extent to which the network of contributory factors underpinning accidents is consistent across safety critical domains. This study reviewed and synthesised 23 AcciMap analyses published in the peer-reviewed literature. Contributory factors and relationships were extracted and thematically coded to form a single multi-domain, multi-incident AcciMap. The resulting AcciMap contains 5587 contributory factors spanning seventy-nine distinct contributory factor types. The findings reveal a set of generic contributory factors that consistently play a role in major accidents regardless of domain. Additionally, contributory factors previously only associated with sharp-end human operators are, in fact, prevalent across multiple levels of accident systems. The implications of these findings for accident theory and accident analysis and prevention activities are discussed. For future AcciMap analyses it is recommended that the contributory factor classification scheme developed in the present study is used to support the identification and classification of contributory factors. In addition, further education for analysts on the systems thinking perspective on accident causation is recommended.
AcciMap, Accident analysis, Accident causation, Systems thinking
Salmon, Paul M.
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Hulme, Adam
110afcb6-92b2-40ff-a6be-25f66ea133ca
Walker, Guy H.
50ec35f0-b93b-431e-b4e4-2f1a5fae7904
Waterson, Patrick
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Berber, Elise
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Stanton, Neville A.
351a44ab-09a0-422a-a738-01df1fe0fadd
1 June 2020
Salmon, Paul M.
8fcdacc0-31f9-4276-bd9e-8127db6c806e
Hulme, Adam
110afcb6-92b2-40ff-a6be-25f66ea133ca
Walker, Guy H.
50ec35f0-b93b-431e-b4e4-2f1a5fae7904
Waterson, Patrick
708fcc53-ddcc-45d1-9360-7a92b815cb3b
Berber, Elise
4c791803-f1c2-430e-b1e2-905e96c67628
Stanton, Neville A.
351a44ab-09a0-422a-a738-01df1fe0fadd
Salmon, Paul M., Hulme, Adam, Walker, Guy H., Waterson, Patrick, Berber, Elise and Stanton, Neville A.
(2020)
The big picture on accident causation: A review, synthesis and meta-analysis of AcciMap studies.
Safety Science, 126, [104650].
(doi:10.1016/j.ssci.2020.104650).
Abstract
As AcciMap is now arguably the most popular accident analysis method in the peer-reviewed literature, there are key learnings to be taken from reviewing and synthesising published AcciMap analyses. In particular, the extent to which the network of contributory factors underpinning accidents is consistent across safety critical domains. This study reviewed and synthesised 23 AcciMap analyses published in the peer-reviewed literature. Contributory factors and relationships were extracted and thematically coded to form a single multi-domain, multi-incident AcciMap. The resulting AcciMap contains 5587 contributory factors spanning seventy-nine distinct contributory factor types. The findings reveal a set of generic contributory factors that consistently play a role in major accidents regardless of domain. Additionally, contributory factors previously only associated with sharp-end human operators are, in fact, prevalent across multiple levels of accident systems. The implications of these findings for accident theory and accident analysis and prevention activities are discussed. For future AcciMap analyses it is recommended that the contributory factor classification scheme developed in the present study is used to support the identification and classification of contributory factors. In addition, further education for analysts on the systems thinking perspective on accident causation is recommended.
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Accepted/In Press date: 28 January 2020
e-pub ahead of print date: 13 February 2020
Published date: 1 June 2020
Keywords:
AcciMap, Accident analysis, Accident causation, Systems thinking
Identifiers
Local EPrints ID: 438739
URI: http://eprints.soton.ac.uk/id/eprint/438739
ISSN: 0925-7535
PURE UUID: c956e46a-e652-46fb-8f76-2066251beaae
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Date deposited: 23 Mar 2020 17:38
Last modified: 17 Mar 2024 05:23
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Contributors
Author:
Paul M. Salmon
Author:
Adam Hulme
Author:
Guy H. Walker
Author:
Patrick Waterson
Author:
Elise Berber
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