/Air-Demand-Elasticity

A project for CSE6242/CX4242 which investigates the impact of fuel prices on the cross-price elasticity of demand on domestic airline routes.

Primary LanguageHTML

Our software is an economic visualization tool that dynamically displays cross price elasticity of air travel demand and fuel prices in the domestic US airline market. Cross price elasticity is defined as the percent change in demand divided by the percent change in price. The values describe how two goods interact based on changes in price. For instance, a negative value means that as the prices of the good increases, the demand of the other good decreases. A value of 0 tells you that the two goods are independent. The map takes three user inputs:the origin airport, and the year and month for an indexed demand and fuel price (because elasticity is a function of time). The map then displays every connection from that airport as well as a bubble that displays the demand as radius and the cross price elasticity with a color scale. In our case, we defined demand as a load factor: the percent of filled seats in a plane--often used as a benchmark or route demand in the industry. 
         
To run, download the entire project from GitHub. You will need to install the PyBrain library and all of its dependencies. Details on doing so can be found http://pybrain.org/docs/quickstart/installation.html. Additionally, you will need to be running python 3.

You will need to start the server before you will be able to see the visualization. To start the server type
    python server.py
into your terminal when in the top-level of the Air-Elasticity-Demand directory.

Navigate in your browser of choice to http://localhost:8001/visualization/index.html
It will take a few seconds for the visualization to load initially and then you will be greeted with a drop down menu and three sliders above a graph of the continental United States. To use the tool, select an airport. The tool will update dynamically as you change sliders or the airport. In the case of larger airports, it may take a few seconds for the bubbles to appear on the map.