Doctoral Dissertations

Date of Award

3-1982

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Civil Engineering

Major Professor

Michael S. Bronzini

Committee Members

Frederick J. Wegmann, William S. Grecco, Thomas L. Bell, Ray A. Mundy

Abstract

In times past, fleet management consisted mainly of traditional motor pool activities such as vehicle acquisition and maintenance. Changes in employee travel demands, reduced fuel supplies, spiraling operating expenses, and double digit inflation are factors which have created additional fleet management responsibilities. The concept of merely maintaining fleet vehicles is being replaced by management's desire to improve vehicle productivity.

The initial phase of this research studied the state of the art of fleet management from various perspectives. Results from a literature review and additional information from interviews with private consultants, representatives of various organizations, and practicing fleet managers are presented. These investigations revealed that fleet managers need additional analytical tools in making vehicle utilization decisions. Thus, evaluating vehicle utilization and improving the efficiency of vehicle trips became the major purposes of this research.

After reviewing several mathematical procedures, four were used in developing vehicle utilization evaluation models. The four evaluation models use set theory, discriminant analysis, linear regression, and logarithmic transformations.

Two vehicle utilization evaluation models require that each utilization variable satisfies individual criterion, while the remaining two models use a combined utilization index score. The models using individual utilization criterion appear to be more reliable than models using a combined index score in consistently identifying the same group of insufficiently utilized vehicles. Comparable results were obtained from a "1/n by m Ranking" model, using ranking techniques and set theory, and a more statistically elaborate discriminant analysis model. The similar results add credibility to both models, but the potential for using the simpler "1/n by m Ranking" model with increased confidence is especially important.

A case study documents the travel patterns and vehicle use for a large industrial complex with approximately 1,400 vehicles. Origin-destination vehicle trip data were collected and analyzed, and subsequent changes in management policies resulted in substantial cost savings. This vehicle trip information was also used to illustrate the potential for improving vehicle trip efficiencies by combining or linking certain trips, systematically removing fleet vehicles which fail to meet established utilization criteria, and rescheduling trip starting times.

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