Forecasting US Army enlistment contract production in complex geographical marketing areas
Purpose – The purpose of this paper is to demonstrate an improved method for forecasting the US Army recruiting. Design/methodology/approach – Time series methods, regression modeling, principle components and marketing research are included in this paper. Findings – This paper found the unique abil...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Emerald Publishing
2018-02-01
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| Series: | Journal of Defense Analytics and Logistics |
| Subjects: | |
| Online Access: | https://www.emerald.com/insight/content/doi/10.1108/JDAL-03-2017-0001/full/pdf?title=forecasting-us-army-enlistment-contract-production-in-complex-geographical-marketing-areas |
| _version_ | 1811268324244324352 |
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| author | Joshua L. McDonald Edward D. White Raymond R. Hill Christian Pardo |
| author_facet | Joshua L. McDonald Edward D. White Raymond R. Hill Christian Pardo |
| author_sort | Joshua L. McDonald |
| collection | DOAJ |
| description | Purpose – The purpose of this paper is to demonstrate an improved method for forecasting the US Army recruiting. Design/methodology/approach – Time series methods, regression modeling, principle components and marketing research are included in this paper. Findings – This paper found the unique ability of multiple statistical methods applied to a forecasting context to consider the effects of inputs that are controlled to some degree by a decision maker. Research limitations/implications – This work will successfully inform the US Army recruiting leadership on how this improved methodology will improve their recruitment process. Practical implications – Improved US Army analytical technique for forecasting recruiting goals.. Originality/value – This work culls data from open sources, using a zip-code-based classification method to develop more comprehensive forecasting methods with which US Army recruiting leaders can better establish recruiting goals. |
| first_indexed | 2024-04-12T21:19:46Z |
| format | Article |
| id | doaj.art-da3de5ca43b7491893dbd2f0fe88a13d |
| institution | Directory Open Access Journal |
| issn | 2399-6439 2399-6447 |
| language | English |
| last_indexed | 2024-04-12T21:19:46Z |
| publishDate | 2018-02-01 |
| publisher | Emerald Publishing |
| record_format | Article |
| series | Journal of Defense Analytics and Logistics |
| spelling | doaj.art-da3de5ca43b7491893dbd2f0fe88a13d2022-12-22T03:16:20ZengEmerald PublishingJournal of Defense Analytics and Logistics2399-64392399-64472018-02-0111698710.1108/JDAL-03-2017-0001600305Forecasting US Army enlistment contract production in complex geographical marketing areasJoshua L. McDonald0Edward D. White1Raymond R. Hill2Christian Pardo3Army Materiel Systems Analysis Activity, Aberdeen Proving Ground, Maryland, USADepartment of Mathematics and Statistics, Air Force Institute of Technology, Wright Patterson AFB, Ohio, USADepartment of Operational Sciences, Air Force Institute of Technology, Wright Patterson AFB, Ohio, USADefense Threat Reduction Agency, Kirtland Air Force Base, New Mexico, USAPurpose – The purpose of this paper is to demonstrate an improved method for forecasting the US Army recruiting. Design/methodology/approach – Time series methods, regression modeling, principle components and marketing research are included in this paper. Findings – This paper found the unique ability of multiple statistical methods applied to a forecasting context to consider the effects of inputs that are controlled to some degree by a decision maker. Research limitations/implications – This work will successfully inform the US Army recruiting leadership on how this improved methodology will improve their recruitment process. Practical implications – Improved US Army analytical technique for forecasting recruiting goals.. Originality/value – This work culls data from open sources, using a zip-code-based classification method to develop more comprehensive forecasting methods with which US Army recruiting leaders can better establish recruiting goals.https://www.emerald.com/insight/content/doi/10.1108/JDAL-03-2017-0001/full/pdf?title=forecasting-us-army-enlistment-contract-production-in-complex-geographical-marketing-areasregressioncomparative studiessales forecasting |
| spellingShingle | Joshua L. McDonald Edward D. White Raymond R. Hill Christian Pardo Forecasting US Army enlistment contract production in complex geographical marketing areas Journal of Defense Analytics and Logistics regression comparative studies sales forecasting |
| title | Forecasting US Army enlistment contract production in complex geographical marketing areas |
| title_full | Forecasting US Army enlistment contract production in complex geographical marketing areas |
| title_fullStr | Forecasting US Army enlistment contract production in complex geographical marketing areas |
| title_full_unstemmed | Forecasting US Army enlistment contract production in complex geographical marketing areas |
| title_short | Forecasting US Army enlistment contract production in complex geographical marketing areas |
| title_sort | forecasting us army enlistment contract production in complex geographical marketing areas |
| topic | regression comparative studies sales forecasting |
| url | https://www.emerald.com/insight/content/doi/10.1108/JDAL-03-2017-0001/full/pdf?title=forecasting-us-army-enlistment-contract-production-in-complex-geographical-marketing-areas |
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