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Estimating Engineering and Manufacturing Development Cost Risk Using Logistic and Multiple Regression

Bibliographic Details
Title: Estimating Engineering and Manufacturing Development Cost Risk Using Logistic and Multiple Regression
Authors: Bielecki, John V.
Source: Theses and Dissertations
Publisher Information: AFIT Scholar
Publication Year: 2003
Collection: AFTI Scholar (Air Force Institute of Technology)
Subject Terms: United States. Air Force--Cost control, United States. Air Force--Weapons systems--Finance, Logistic regression analysis, Mathematical statistics--Computer programs, Risk Analysis
Description: 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 the research and development 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 cost growth will occur in a program. If applicable, the multiple regression step is implemented to predict how much cost growth will occur. Our study focuses on four of the seven SAR cost growth categories within the research and development accounts - schedule, estimating, support, and other. We study each of these four categories individually for significant cost growth characteristics and develop predictive models for each.
Document Type: text
File Description: application/pdf
Language: unknown
Relation: https://scholar.afit.edu/etd/4182; https://scholar.afit.edu/context/etd/article/5184/viewcontent/AFIT_GCA_ENC_03_01_Bielecki_J_ADA413231.pdf
Availability: https://scholar.afit.edu/etd/4182
https://scholar.afit.edu/context/etd/article/5184/viewcontent/AFIT_GCA_ENC_03_01_Bielecki_J_ADA413231.pdf
Accession Number: edsbas.390571C3
Database: BASE
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  Data: Estimating Engineering and Manufacturing Development Cost Risk Using Logistic and Multiple Regression
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  Data: <searchLink fieldCode="AR" term="%22Bielecki%2C+John+V%2E%22">Bielecki, John V.</searchLink>
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  Data: Theses and Dissertations
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  Data: 2003
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  Data: AFTI Scholar (Air Force Institute of Technology)
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  Data: <searchLink fieldCode="DE" term="%22United+States%2E+Air+Force--Cost+control%22">United States. Air Force--Cost control</searchLink><br /><searchLink fieldCode="DE" term="%22United+States%2E+Air+Force--Weapons+systems--Finance%22">United States. Air Force--Weapons systems--Finance</searchLink><br /><searchLink fieldCode="DE" term="%22Logistic+regression+analysis%22">Logistic regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+statistics--Computer+programs%22">Mathematical statistics--Computer programs</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+Analysis%22">Risk Analysis</searchLink>
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  Data: 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 the research and development 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 cost growth will occur in a program. If applicable, the multiple regression step is implemented to predict how much cost growth will occur. Our study focuses on four of the seven SAR cost growth categories within the research and development accounts - schedule, estimating, support, and other. We study each of these four categories individually for significant cost growth characteristics and develop predictive models for each.
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        Type: general
      – SubjectFull: United States. Air Force--Weapons systems--Finance
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      – SubjectFull: Logistic regression analysis
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      – SubjectFull: Mathematical statistics--Computer programs
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      – SubjectFull: Risk Analysis
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