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

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.