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Modeling No-Show Passengers on PACOM Exercise Airlift
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The issue of no-shows plagues many different industries that rely on reservationor appointment-type processes. Everything from the restaurant to healthcare tocommercial airline industry has had to come up with solutions to this problem in order toremain both profitable and customer-service oriented. Many of these industries haveused statistical models to predict no-shows such that seats or appointments that wouldotherwise go unused are filled with customers that were overbooked for those vacancies.This is a balancing act between trying to predict the number of no-shows and planningthe number t...
The issue of no-shows plagues many different industries that rely on reservationor appointment-type processes. Everything from the restaurant to healthcare tocommercial airline industry has had to come up with solutions to this problem in order toremain both profitable and customer-service oriented. Many of these industries haveused statistical models to predict no-shows such that seats or appointments that wouldotherwise go unused are filled with customers that were overbooked for those vacancies.This is a balancing act between trying to predict the number of no-shows and planningthe number to overbook, without having more customers show up than able toaccommodate, a dangling proposition. The military has been dealing with this sameproblem on its commercially chartered flights that move troops overseas for exercises, contingencies, and other requirements. This research is aimed at using a statistical model to predict the number of noshowson chartered passenger airlift for Pacific Command joint exercises to try tomaximize the utilization of seats left unused by no-shows through overbookingtechniques. If the number of no-shows can be predicted accurately, airlift planners willbe able to overbook missions to fill those seats and minimize wasted resources. This willbe done using a purely quantitative approach with correlation analysis and building amultiple regression model. The model will be built using both personnel and missioncharacteristic factors from historical airlift data from major joint exercises in the Pacific Command's area of responsibility.
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