Development of a Navy Recruiting Vehicle Budget Model.

Abstract

This thesis attempts to develop a predicting model for Commander, Navy Recruiting Command (CNRC) and Recruiting District Commanding Officers to use in distributing vehicles to each Navy Recruiting District. The thesis attempts to identify the relevant data on vehicle activity and vehicle costs across four Navy Recruiting Areas and 31 Navy Recruiting Districts that will be usefulness in developing a model to predict the demand for vehicles. The data file consists of pooled, cross-sectional time-series data covering three fiscal years, 1995, 1996, and 1997, and 31 Recruiting Districts. This data file is used to estimate regression models of vehicle demand using ordinary least squares techniques. The candidate independent variables whose values are statistically significant are used as the explanatory (predictor) variables to explain the variation in the number of vehicles across Districts. The thesis concludes that there is a strong relationship between the number of enlisted production recruiters and total vehicle mileage in explaining the number of recruiting vehicles. Using these relationships a simple model is developed that can be used to predict future vehicle demand by District and assist decision makers in making vehicle distribution decisions.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1997
Accession Number
ADA342560

Entities

People

  • Jennifer D. Gundayao

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Administrative Personnel
  • Analysis Of Variance
  • Business Administration
  • Data Science
  • Department Of Defense
  • Enlisted Personnel
  • Information Science
  • Least Squares Method
  • Management Personnel
  • New York
  • Organizational Structure
  • Personnel Management
  • Production
  • Recruiting
  • Regression Analysis
  • Statistical Analysis
  • Statistical Tests

Readers

  • Computational Modeling and Simulation
  • Logistics and Supply Chain Management.
  • Naval Personnel Management