A risk-mitigation model driven from the level of forecastability of Black Swans: prepare and respond to major Earthquakes through a dynamic Temporal and Spatial Aggregation forecasting framework
Konstantinos Nikolopoulos (),
Fotios Petropoulos,
Vasco Sanchez Rodrigues,
Stephen Pettit and
Anthony Beresford
Additional contact information
Fotios Petropoulos: University of Bath
Vasco Sanchez Rodrigues: Cardiff University
Stephen Pettit: Cardiff University
Anthony Beresford: Cardiff University
No 19017, Working Papers from Bangor Business School, Prifysgol Bangor University (Cymru / Wales)
Abstract:
Major earthquakes are black swan, or quasi-random, events capable of disrupting supply chains to an entire country, region or even the whole world as the case of the Fukushima disaster profoundly demonstrated. They are amongst the most unpredictable types of natural disasters, and can have a severe impact on supply chains and distribution networks. This research develops a supply chain risk management model in the anticipation of such a black swan event. The research considers major earthquake data for the period 1985 – 2014, and temporal as well as spatial aggregation is undertaken. The aim is to identify the optimum grid size where forecasting variance is minimized and forecastability is maximized. Building on that a risk-mitigation model is developed. The dynamic model – updated every time a new event is added in the database - includes preparedness, responsiveness and centralization strategies for the different levels of time and geographical aggregation.
Keywords: Risk, Black Swans, Forecastability, Statistical Aggregation, Disaster Relief (search for similar items in EconPapers)
Date: 2019-08
New Economics Papers: this item is included in nep-for, nep-rmg and nep-ure
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.bangor.ac.uk/business/research/documents/BBSWP-19-17.pdf (application/pdf)
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:bng:wpaper:19017
Access Statistics for this paper
More papers in Working Papers from Bangor Business School, Prifysgol Bangor University (Cymru / Wales) Contact information at EDIRC.
Bibliographic data for series maintained by Alan Thomas ( this e-mail address is bad, please contact ).