7. Conclusion and Further Work
7.3. Further work
The procedure of composite indicators building, introduced in this dissertation, has the potential to be improved by several ways as well as flexibility and transparency in the procedures of composite indicator building, utilization, and adjustment. First of all, there is a need to clearly understand what the composite indicator is aimed to conceptualize and monitor. In this dissertation, the process of composite indicators design was utilized to conceptualize the concept of disaster resilience in the context of earthquake hazard in Tehran. However, in order to optimize the presented procedures and to generalize it to other natural or man-made disasters, improving the process of composite indicators building and an expansion to further additional case studies are aspired.
The composite indicator should be designed in a flexible manner. This means that each of its stage as well as structure scheme, variable selection, weighting and aggregation techniques, visualization, and validation methods can be easily modified over the process. A sound composite indicator should also have high standard in both methodology and result.
Furthermore, composite indicators should be based on trustable, valid, and available data sources.
There is however, a common challenge in composite indicators construction related to data limitations in particular when the study area is smaller. Although this research was based on combination of primary and secondary data, more refined field survey data on adaptive capacity indicators as well as disaster emergency response plan, recovery plan, and other social capital parameters, may improve the results of further research.
As stated, disaster resilience is a multidimensional phenomenon, which includes many factors.
Validation of such a measure is often problematic. Thus, further research needs to focus on developing more external criteria. This is a serious problem in communities such as Tehran because there is no similar study to be addressed. Furthermore, it is expected that a disaster resilient city will need a shorter time to recover while it will be a long-lasting process for the ones with less disaster resilience level. However, this kind of data cannot be extracted from secondary data and it needs more empirically results (data observed over time as well as space).
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