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Analysis of Transportation Infrastru...

Juni, Emil R.

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Analysis of Transportation Infrastructure Maintenance Efficiency Using Two- Stage Data Envelopment Analysis Method.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analysis of Transportation Infrastructure Maintenance Efficiency Using Two- Stage Data Envelopment Analysis Method./
Author:	Juni, Emil R.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	164 p.
Notes:	Source: Dissertations Abstracts International, Volume: 79-02, Section: B.
Contained By:	Dissertations Abstracts International79-02B.
Subject:	Engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10288909
ISBN:	9780355069389

Analysis of Transportation Infrastructure Maintenance Efficiency Using Two- Stage Data Envelopment Analysis Method.
Juni, Emil R.

Analysis of Transportation Infrastructure Maintenance Efficiency Using Two- Stage Data Envelopment Analysis Method. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 164 p.

Source: Dissertations Abstracts International, Volume: 79-02, Section: B.

Thesis (Ph.D.)--The University of Wisconsin - Madison, 2017.

This item must not be sold to any third party vendors.

As transportation state agencies transitioned to performance-based maintenance method, the expectation for establishing a well-informed maintenance investment strategy is increasing, with a heavy focus on performance-based maintenance management. Despite the fact that the efficiency of maintenance units is an important aspect in evaluating performance, most research efforts in performance-based resource management have not been taking into account efficiency concept and relating it to the performance of a maintenance unit. The framework for efficiency measurement of road maintenance strategies using Data Envelopment Analysis (DEA) recognizes the importance of the efficiency of maintenance units. The framework focuses on the performance of maintenance units, and compares their technical efficiencies. Following the concept of production function, technical efficiency of a maintenance unit is defined as the process of converting all maintenance effort (input) into condition rating (output). In support of this framework, this research implements the Two-stage Data Envelopment Analysis (2DEA) technique to advance and improve the framework's usability and reliability. The 2DEA method enhances the DEA framework by adding statistical basis, bringing legitimacy to the method, validating the usage of efficiency factors to be used as parameters in the models, and allowing the DEA models to be statistically tested. With the existence of statistical basis in the 2DEA method, two different statistical tests were performed on the data. The first test evaluates the impact of efficiency factors in the models, allowing maintenance administrators to validate the significance of the efficiency factors used in the models. The second test is an efficiency comparison test, allowing maintenance administrators to check whether units from different groups can be compared based on their efficiency scores. The result of this research contributes to the state of knowledge in transportation infrastructure maintenance, improving the DEA framework for infrastructure maintenance by adding a statistical basis, which helps develop a sound selection and evaluation process for efficiency factors used in the DEA models, increasing the legitimacy and usability of implementation of DEA method in performance-based resource allocation and maintenance management.

ISBN: 9780355069389Subjects--Topical Terms:

586835
Engineering.

Analysis of Transportation Infrastructure Maintenance Efficiency Using Two- Stage Data Envelopment Analysis Method.
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506 $a This item must not be sold to any third party vendors.
520 $a As transportation state agencies transitioned to performance-based maintenance method, the expectation for establishing a well-informed maintenance investment strategy is increasing, with a heavy focus on performance-based maintenance management. Despite the fact that the efficiency of maintenance units is an important aspect in evaluating performance, most research efforts in performance-based resource management have not been taking into account efficiency concept and relating it to the performance of a maintenance unit. The framework for efficiency measurement of road maintenance strategies using Data Envelopment Analysis (DEA) recognizes the importance of the efficiency of maintenance units. The framework focuses on the performance of maintenance units, and compares their technical efficiencies. Following the concept of production function, technical efficiency of a maintenance unit is defined as the process of converting all maintenance effort (input) into condition rating (output). In support of this framework, this research implements the Two-stage Data Envelopment Analysis (2DEA) technique to advance and improve the framework's usability and reliability. The 2DEA method enhances the DEA framework by adding statistical basis, bringing legitimacy to the method, validating the usage of efficiency factors to be used as parameters in the models, and allowing the DEA models to be statistically tested. With the existence of statistical basis in the 2DEA method, two different statistical tests were performed on the data. The first test evaluates the impact of efficiency factors in the models, allowing maintenance administrators to validate the significance of the efficiency factors used in the models. The second test is an efficiency comparison test, allowing maintenance administrators to check whether units from different groups can be compared based on their efficiency scores. The result of this research contributes to the state of knowledge in transportation infrastructure maintenance, improving the DEA framework for infrastructure maintenance by adding a statistical basis, which helps develop a sound selection and evaluation process for efficiency factors used in the DEA models, increasing the legitimacy and usability of implementation of DEA method in performance-based resource allocation and maintenance management.
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