Japanese Earthquake
Impact and Lessons Learned from the 2011 Japanese Earthquake
On March 11, a Richter scale 9.0 earthquake devastated the chief island of Honshu Japan. The earthquake, tsunami and its consequences made devastating personal, social and economic harm. People worldwide were astonished by videos of blowing up nuclear power plant buildings, knocked down cities and personal stories of the disaster. The earthquake also seriously interrupted global manufacturing supply chains. In this paper, we shall expound, through modelling, comparison and analysis - issues that caused business interruptions, impacted businesses, operations management issues, and effectiveness of business decision-making relating to the 2011 Japanese Earthquake.
Earthquake Risk Modelling
To manage earthquake risk, it is essential to know the size of the risk and the amount by which the risk is reduced by taking some particular action or set of actions. We thus need to be able to quantify one or more of the nine socio-economic consequences of earthquakes. Earthquake risk is generally quantified by computer modelling, which takes account of the hazard and the quantity and nature of the people and/or property at risk. To fully account for the seismic hazard, not only the ground shaking has to be considered, but also associated earthquake-induced hazards which include the nine mainly geological consequences such as liquefaction and landslides, and earthquake-induced fires.
Earthquake risk modelling is carried out for a wide range of elements of the built environment, i.e.
. buildings; - contents of buildings;
. fixed and mobile plant and equipment;
. lifelines.
Such modelling may be carried out in its own right, and of course is also a necessary first step in modelling risk of death or injury to people. Another step in risk modelling and management is to identify all the contributing factors which could be improved in order to reduce risk, as discussed for the recent earthquake in Japan, in 2011.
Material Damage Costs
The most common type of earthquake risk modelling is the estimation of the direct financial cost due to material damage to a subset of the built environment. This is done (for widely disparate sets of property ranging from a single item or parcel of items such as the contents of a particular building to all, or selections of all, the property in a city, or for the total losses for a given earthquake. Damage costs directly due to ground shaking using empirical damage ratios. Consider the case of a large earthquake, occurring on a surface rupturing fault.
Business Interruption
By the term business, we here refer to any organization, such as, shops, factories, schools, clubs, hospitals, governmental bodies, etc. Business interruption is the name often given to the costs of loss of business arising from any cause, in our case from an earthquake. Business interruption is one of a list of nine socio-economic consequences of earthquakes and is one of the hardest to model. It is seen that there are three general areas which may cause business loss, i.e.
* upstream effects;
* direct material damage; and * downstream effects.
Figure. 1
Upstream effects are those to do with supplies of anything that a business uses or consumes, such as power, raw materials or components. Downstream effects comprise damage to dispatch routes or loss of a market, for example, a customer's business. The consequences of an earthquake can be both negative and/or positive for any given business. An example of related negative and positive effects comes from the 1987 Edgecumbe, New Zealand, earthquake, in which the public hospital in the largest affected town was put out of commission for some time (Fluchter, 2003). This caused a serious decrease in business to the local undertaker (who was not insured against such a loss), because fatally ill patients were being sent to hospitals elsewhere. This of course led to a corresponding increase in business for undertakers in other places. Business interruption can be caused by local or distant earthquakes, even those in other countries. The effects on businesses are clearly very variable and often unpredictable.
There are a range of very different possible outcomes which can be considered as those for either different businesses, or alternative negative and positive outcomes for the same business in different scenarios. Because of this inherent variability, estimation of effects of earthquakes on businesses is best studied by considering various likely scenarios, modelling a range of possible upstream and downstream effects to supplier and customer bases for each scenario. Such modelling involves estimating the length of time after the earthquake that each consequence lasts. An interesting example of such a study is that of modelling time delays caused by damage to the transportation system in the San Francisco areas in a magnitude 7.5 earthquake on the San Andreas fault (Milliken, 2011), using GIS-based methodology to tackle a complex problem.
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