Cost Growth in Department of Defense (DoD) major weapon systems has been an on-going problem for more than 30 years. Previous research has demonstrated the use of a two-step logistic and multiple regression methodology to predicting cost growth produces desirable results versus traditional single-step regression. This research effort validates, and further explores the use of a two-step procedure for assessing DoD major weapon system cost growth using historical data. We compile programmatic data from the Selected Acquisition Reports (SARs) between 1990 and 2001 for programs covering all defense departments. Our analysis concentrates on cost growth in procurement dollar accounts for the Engineering and Manufacturing Development phase of acquisition. We investigate the use of logistic regression in cost growth analysis to predict whether or not procurement cost growth will occur in a program. If applicable, the multiple regression step is implemented to predict how much procurement cost growth will occur. Our study considers all seven SAR categories within the procurement accounts engineering, schedule, estimating, support, quantity, economic, and other, but we refrain from analyzing these categories individually. Consequently, we focus on the total procurement cost growth incurred from these five categories during the Engineering and Manufacturing Development phase of acquisition.
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Taschenbuch. Etat : Neu. Neuware - Cost Growth in Department of Defense (DoD) major weapon systems has been an on-going problem for more than 30 years. Previous research has demonstrated the use of a two-step logistic and multiple regression methodology to predicting cost growth produces desirable results versus traditional single-step regression. This research effort validates, and further explores the use of a two-step procedure for assessing DoD major weapon system cost growth using historical data. We compile programmatic data from the Selected Acquisition Reports (SARs) between 1990 and 2001 for programs covering all defense departments. Our analysis concentrates on cost growth in procurement dollar accounts for the Engineering and Manufacturing Development phase of acquisition. We investigate the use of logistic regression in cost growth analysis to predict whether or not procurement cost growth will occur in a program. If applicable, the multiple regression step is implemented to predict how much procurement cost growth will occur. Our study considers all seven SAR categories within the procurement accounts engineering, schedule, estimating, support, quantity, economic, and other, but we refrain from analyzing these categories individually. Consequently, we focus on the total procurement cost growth incurred from these five categories during the Engineering and Manufacturing Development phase of acquisition.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 9781288289103
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Etat : New. KlappentextrnrnCost Growth in Department of Defense (DoD) major weapon systems has been an on-going problem for more than 30 years. Previous research has demonstrated the use of a two-step logistic and multiple regression methodology to predicti. N° de réf. du vendeur 6553358
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