Data Envelopment Analysis as a Decision-Making Tool for Transportation Professionals
Publication: Journal of Transportation Engineering
Volume 135, Issue 11
Abstract
Data envelopment analysis (DEA) is a mathematical method based on production theory and the principles of linear programming. It enables one to assess how efficiently a firm, organization, agency, or such other unit uses the resources available (inputs) to generate a set of outputs relative to other units in the data set. Recent papers by different writers present different applications of DEA in the transportation engineering domain. All of these papers are published in transportation journals. These papers are mainly aimed at addressing the transportation-related issues and thus do not focus too much on the DEA concept itself. It can be asserted that DEA is very likely to be used more and more in the transportation engineering domain. Given this, there is a need for the transportation professionals to fully understand the DEA concept. It is essential for such a community to identify cases where the application of this innovative and powerful method can be useful to help the decision-making process, to accurately apply DEA in a particular setting, to derive meaningful conclusions from the obtained results, and to acknowledge the limitations of DEA in certain cases so as to approach the results with caution. The purpose of this paper is to illustrate to the civil engineering, more specifically to the transportation engineering community the use of this powerful approach in performing comparative performance measurement. Within this context, this paper will address a transportation-related problem by using the DEA approach. Different from the other papers containing transportation-related DEA applications (as mentioned above), this paper will discuss, in detail, the steps that need to be taken to generate the DEA model and solve it.
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Acknowledgments
The research work described in this paper has been funded by the Virginia Department of Transportation (VDOT) and the National Science Foundation (NSF Grant No. NSF0726789). The opinions and findings are those of the writers and do not necessarily represent the views of VDOT or NSF.UNSPECIFIED
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 135 • Issue 11 • November 2009
Pages: 822 - 831
Copyright
© 2009 ASCE.
History
Received: Apr 23, 2008
Accepted: May 12, 2009
Published online: May 22, 2009
Published in print: Nov 2009
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