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The humanitarian emergencies of past years have evidenced significant lack of cooperation and coordination among aid organizations. One way to improve the situation is that the big aid organizations leading the cooperation and coordination efforts in a given country make use of open aid data available online to rapidly evaluate the performance of all aid organizations, and then use the insights obtained as a complement to create better coordination strategies and policies. The big aid organizations can evaluate the performance using indicators. This research is about proposing two indicators based on a model (built from open aid data) of humanitarian aid viewed as an economic supply-demand system. The first indicator measures how is the supply of humanitarian aid proportional to the demands, and the second measures how well are aid organizations reaching the provinces with the most deficit of humanitarian aid. Both indicators were tested in the Afghanistan 2015 humanitarian scenario. They brought to light information about which aid organizations and humanitarian areas (clusters) need greater improvement in coordination.
supply-demand theory, humanitarian aid, data science, indicators, online data
supply-demand theory, humanitarian aid, data science, indicators, online data
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