Monday, March 11, 2013

Use of Rehabilitation Decision-Making For Buildings In the Wenchuan Area

Rehabilitation Decision-Making For Buildings In the Wenchuan Area

            In 2008 an 8.0 magnitude earthquake occurred in the Wenchuan area of China.  The Earthquake left over 88,000 people dead or missing, and resulted in economic losses up to $125.6 billion.  After the earthquake, talks occurred within building owners in the Wenchuan area if seismic rehabilitation measures should be pursued.  Most individuals worried that spending the money to make their properties upgraded in terms of seismic design would prove futile if another earthquake didn’t occur.  To present possible decision options to building owners in the Wenchuan area of China, the authors present a Decision-Making Tree Model (DMT) to develop both risks and rewards for each option of action for the building owners. 
            The DMT model used by the authors consists of five components: decision nodes, decision options, uncertainty nodes, possible outcomes, and end nodes.  With the use of the DMT model, the authors broke down possible outcomes into three distinctions that building owners would want answers on: possible damage states and possibilities, possible earthquake intensities and probabilities, and rehabilitation options and costs.  The overall goal of the use of the DMT model is to inform building owners which of the three options is the most viable: restoring the buildings to original seismic consistency, repair and strengthen building seismic resistance, and upgrade seismic resistance to the highest level. 
            Overall, the use of the DMT model was able to demonstrate that upgrading building levels to the highest seismic resistance was economically justified.  When the authors examined whether seismic rehabilitation would occur, the DMT models displayed cost as the key factor influencing decision-makers.  The other factors of building vulnerability and the probability of seismic activity the authors concluded as remaining constant among regions.  Thus, the DMT model demonstrated that reducing rehabilitative costs made it more likely for building owners to choose to rehabilitate their building to higher standards of seismic resistance.  

            The use of DMT modeling as a tool for risk assessment of earthquake probabilities and different options for economic improvement initiatives was a manner in which to reduce uncertainty and unwillingness to improve building quality.  For the purposes of this study, decision-makers needed to have a willingness to be open to the outcomes of the DMT model results despite their perceptions beforehand.  To make the DMT model as an analytical technique more reliable, the authors could have considered incorporating the building owners overall attitude to improving seismic stability of their buildings.  Incorporating the building owners’ attitudes might offer intriguing insights of the situation in the Wenchuan area of China as it relates to earthquake probability and citizen perceptions.      

            However, DMT modeling could be applied to any situation in which a decision-maker considers both the risks and benefits of a proposed action.  DMT models would be especially relevant in analysis endeavors in the intelligence community.  DMT modeling not only is a way to display visually different outcomes of action for a decision-maker, but also effective at analyzing information in probabilistic thinking terms.   DMT modeling allows for probabilistic thinking that creates more reliable measures that uses words of estimative probability within their estimates.  Overall, DMT modeling is an effective manner in which to display the possible options available to the decision-maker and has the capability to display both the risks and benefits in terms of probability measures.  In the intelligence field probability measures are the most crucial aspect of intelligence estimates and what decision-makers look for to reduce their uncertainty in actions proposed to them.    

Zhang, Hong, Xing, Feng, and Liu, Juan. (2011). Rehabilitation Decision-Making For Buildings In the Wenchuan Area. Construction Management and Economics, 29, 569-578. Retrieved from


  1. This is an interesting topic to use decision tree analysis on. It is also interesting how the DMT used economic justification rather than safety as the end point of the model. Rather than have the three decisions end with how much they increased safety, they based it on an economic incentive. I also imagine one of the deciding factors in using economic benefits rather than the safety benefits is the frequency of earthquakes in the region. If the frequency was high than I would guess that costs would not have been as important of an issue.

  2. Money is usually a large factor in a decision, although it is odd that the people of Wenchuan favored it so highly as opposed to their own safety. As Ethan mentioned, it would be useful background information to note whether this area saw frequent earthquakes or if they were a rare occurrence. Either way it is odd after the deaths of over 88,000 people the individuals would not be more interested in safety. Furthermore, it seems likely the study was conducted fairly quickly after the earthquake took place. Directly after an event people are oftentimes more sensitive and willing to take drastic measures with an increased interest in safety. It would be useful to know the amount of time between the earthquake and the study.

    Due to the heavy weight finances played, the use of the DMT to economically justify the conversion to the highest seismic resistance may, in the future, save many lives. It would be interesting to find out how many individuals chose to upgrade to the highest seismic resistance as a result of the findings the DMT provided.

  3. To clarify some points the region in China that was studied did have a frequency of having decent measured earthquakes according to the Richter Scale, meaning that earthquakes in the area were not uncommon occurrences. In terms of the earthquake event, the earthquake that totaled 88,000 deaths occurred in 2008. The study was completed by the authors in 2010. In the article it did not clarify how many building owners chose to upgrade their homes, but rather the researchers gave the most viable response based on the information presented in the decision tree.

  4. I think it is interesting the cost was found to be more important to people than safety. My instinct is that the people surveyed may have been landlords of large apartment complexes or business owners where people do not live who would be more concerned about saving a dollar than safety. I feel that it would be interesting to know both the time span between the earthquake and the survey, the average amount of damage done to the area (a few buildings vs. a whole section of the town), and the general wealth of the area. Additionally, if the buildings were 1 story houses or 20 story apartment complexes would have a great impact on how to rehabilitate the buildings. The conclusion seems obvious- lower prices increase the likelihood that someone will wish to upgrade their seismic resistance.

    In the realm of decision trees I think this is an interesting way to go about finding solutions to a natural disaster. It takes a potentially panicked population and logically explains various decisions complete with costs and frequency of potential future earthquakes.