EconPapers    
Economics at your fingertips  
 

Characterization of unknown unknowns using separation principles in case study on Deepwater Horizon oil spill

Seong Dae Kim

Journal of Risk Research, 2017, vol. 20, issue 1, 151-168

Abstract: Unidentified risks, also known as unknown unknowns, have traditionally been underemphasized by risk management. Most unknown unknowns are believed to be impossible to find or imagine in advance. But this study reveals that many are not truly unidentifiable. This study develops a model using separation principles of the Theory of Inventive Problem Solving (whose Russian acronym is TRIZ) to explain the mechanism that makes some risks hard to find in advance and show potential areas for identifying hidden risks. The separation principles used in the model are separation by time, separation by space, separation upon condition, separation between parts and whole, and separation by perspective. It shows that some risks are hard to identify because of hidden assumptions and illustrates how separation principles can be used to formulate assumptions behind what is already known, show how the assumptions can be broken, and thus identify hidden risks. A case study illustrates how the model can be applied to the Deepwater Horizon oil spill and explains why some risks in the oil rig, which were identified after the incident, were not identified in advance.

Date: 2017
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/13669877.2014.983949 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jriskr:v:20:y:2017:i:1:p:151-168

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RJRR20

DOI: 10.1080/13669877.2014.983949

Access Statistics for this article

Journal of Risk Research is currently edited by Bryan MacGregor

More articles in Journal of Risk Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:jriskr:v:20:y:2017:i:1:p:151-168