Journal article
Identifying risks and emergent risks across sociotechnical systems: the NETworked hazard analysis and risk management system (NET-HARMS)
Theoretical Issues in Ergonomics Science, Vol.19(4), pp.456-482
2018
Abstract
Accidents are a systems phenomenon and multiple methods are available to enable retrospective analysis of accidents through this lens. However, the same cannot be said for the methods available for forecasting risk and accidents. This paper describes a new systems-based risk assessment method, the NETworked hazard analysis and risk management system (NET-HARMS), that was designed to support practitioners in identifying (1) risks across overall work systems, and (2) emergent risks that are created when risks across the system interact with one another. An overview of NET-HARMS is provided and demonstrated through a case study application. An initial test of the method is provided by comparing case study outcomes (i.e. predicted risks) with accident data (i.e. actual risks) from the domain in question. Findings show that NET-HARMS is capable of forecasting systemic and emergent risks and that it could identify almost all risks that featured in the accidents in the comparison data-set.
Details
- Title
- Identifying risks and emergent risks across sociotechnical systems: the NETworked hazard analysis and risk management system (NET-HARMS)
- Authors
- Clare Dallat (Author) - University of the Sunshine Coast - Faculty of Arts, Business and LawPaul M Salmon (Author) - University of the Sunshine Coast - Faculty of Arts, Business and LawNatassia Goode (Author) - University of the Sunshine Coast - Faculty of Arts, Business and Law
- Publication details
- Theoretical Issues in Ergonomics Science, Vol.19(4), pp.456-482
- Publisher
- Taylor & Francis Ltd.
- Date published
- 2018
- DOI
- 10.1080/1463922X.2017.1381197
- ISSN
- 1463-922X
- Organisation Unit
- Centre for Human Factors and Systems Science; School of Social Sciences - Legacy; School of Law and Society
- Language
- English
- Record Identifier
- 99450596402621
- Output Type
- Journal article
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