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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Taschenbuch. Etat : Neu. Neuware - 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.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. N° de réf. du vendeur 9781288293988
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