A new approach to analysing human-related accidents by combined use of HFACS and activity theory-based method

Article


Yoon, Y., Ham, D. and Yoon, W. 2017. A new approach to analysing human-related accidents by combined use of HFACS and activity theory-based method. Cognition, Technology and Work. 19 (4), pp. 759-783. https://doi.org/10.1007/s10111-017-0433-3
TypeArticle
TitleA new approach to analysing human-related accidents by combined use of HFACS and activity theory-based method
AuthorsYoon, Y., Ham, D. and Yoon, W.
Abstract

This study proposes a new method for modelling and analysing human-related accidents. It integrates HFACS (Human Factors Analysis and Classification System), which addresses most of the socio-technical system levels and offers a comprehensive failure taxonomy for analysing human errors, and AT (Activity Theory)-based approach, which provides an effective way for considering various contextual factors systematically in accident investigation. By combining them, the proposed method makes it more efficient to use the concepts and principles of AT. Additionally, it can help analysts use HFACS taxonomy more coherently to identify meaningful causal factors with a sound theoretical basis of human activities. Therefore, the proposed method can be effectively used to mitigate the limitations of traditional approaches to accident analysis, such as over-relying on a causality model and sticking to a root-cause, by making analysts look at an accident from a range of perspectives. To demonstrate the usefulness of the proposed method, we conducted a case study in nuclear power plants. Through the case study, we could confirm that it would be a useful method for modelling and analysing human-related accidents, enabling analysts to identify a plausible set of causal factors efficiently in a methodical consideration of contextual backgrounds surrounding human activities.

KeywordsHuman error; Activity theory; HFACS ; Accident analysis; Accident model
PublisherSpringer
JournalCognition, Technology and Work
ISSN1435-5558
Electronic1435-5566
Publication dates
Online06 Sep 2017
Print01 Nov 2017
Publication process dates
Deposited23 Feb 2018
Accepted31 Aug 2017
Output statusPublished
Accepted author manuscript
Copyright Statement

This is a post-peer-review, pre-copyedit version of an article published in Cognition, Technology and Work. The final authenticated version is available online at: https://doi.org/10.1007/s10111-017-0433-3

Digital Object Identifier (DOI)https://doi.org/10.1007/s10111-017-0433-3
Web of Science identifierWOS:000417269600015
LanguageEnglish
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