A methodology to engineer government incentive design for subsidized air transportation
This work attempts to quantify the benefits and guide future policy decisions for subsidized air transportation programs. This is accomplished through applying new analytical methodologies to the Essential Air Service (EAS) subsidy in the United States. This work begins by enumerating the benefits of EAS stated in previous research and government publications. Transportation data from the FAA and US DOT, as well as economic data from the US Census is then collected for a selection of the benefits. First, geospatial analysis techniques are applied to select and compare counties with and without EAS service to determine if differences in benefits can be found in the data. Economic factors (per capita income) as well as social factors (racial diversity and crime rate) are compared between the communities with and without EAS. It is found that the proposed methodology does not provide supporting evidence that counties with EAS have a measurable benefit for the tested factors than counties without EAS. Second, a multi-criteria decision model is developed to first gauge an airport’s reliance on EAS and then make system-wide decisions on which airports to continue funding if the program is faced with budgetary cutbacks. This multi-criteria decision model is tested against a single criterion decision model from previous research using a cost-benefit analysis to quantify the effects of a 20% reduction in EAS budget. It is found that the use of the multi-criteria decision model can result in continued service to an additional 47,000 current EAS passengers while spending $2.5 million less than the previously introduced decision model. Third, an electronic questionnaire was sent out to EAS airport managers and directors in an attempt to validate the decision criteria in the multi-criteria decision model as well as gauge if any metrics for economic and social benefits of EAS currently exist. It is found that the decision criteria cannot be easily validated through stakeholder feedback due to discrepancies between the collected data and stakeholder accounting. Additionally, no system-wide metrics exists for economic and social benefits.
Landry, Purdue University.
Industrial engineering|Political science|Transportation planning
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