Data Envelopment Analysis as a Decision-Making Tool for Transportation Professionals

Ozbek, Mehmet E.; Garza, Jesús M. de la; Triantis, Konstantinos

doi:10.1061/(asce)te.1943-5436.0000069

Cited by 44 publications

(32 citation statements)

References 18 publications

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“…(2) they perform such tasks under the same market conditions; and (3) they use the same technologies (Ozbek et al, 2009). Individual bridges are proposed to be used as DMUs in the study.…”

Section: Methodsmentioning

confidence: 99%

“…Subsequently, an alternative method, viz., data envelopment analysis (DEA) is proposed for fund allocation. The DEA is a mathematical method based on production theory and the principles of linear programming (Ozbek et al, 2009). The DEA is a nonparametric method of measuring the efficiency of decision making units (DMUs) (Ray, 2004;Li and Liu, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Prioritization of bridges for maintenance planning using data envelopment analysis

Wakchaure¹,

Jha

2011

Construction Management and Economics

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Resources-especially funds allotted-for the maintenance of bridges, are generally scanty. Thus, it becomes difficult to select bridges for maintenance from among several competing bridges to ensure their safety and serviceability to the desired level. A bridge health index is considered a reasonably accurate depiction of the condition of a bridge and hence is the basis for most of the decisions on fund allocation. However, it still remains to be seen whether such a decision-making tool results in an efficient fund allocation. From data collected on Indian bridges, it is observed that fund allocation based on bridge condition is not always judicious. Rather, a number of factors affect the final decision on fund allocation. Hence, an alternative approach of data envelopment analysis (DEA) has been used for scoring the efficiency of 14 bridges selected for the study. Depending on the availability of data, this method can take into account other factors besides the bridge health index that influence decisions on maintenance planning. The variables selected for the DEA are: bridge health index, deck area of the bridge, maintenance cost of the bridge, and the age of the bridge. The allocation of funds for the maintenance of bridges based on DEA has proved to be comparatively more efficient. This has been illustrated with the help of a numerical example. The proposed method would enable bridge authorities to formulate better strategies for planning and executing bridge maintenance activities in a cost-effective manner.

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“…(2) they perform such tasks under the same market conditions; and (3) they use the same technologies (Ozbek et al, 2009). Individual bridges are proposed to be used as DMUs in the study.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prioritization of bridges for maintenance planning using data envelopment analysis

Wakchaure¹,

Jha

2011

Construction Management and Economics

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“…Dyson et al (2001) and Ozbek (2009) extended the previous work to include six phases. This work is based on the Ozbek methodology.…”

Section: Methodsmentioning

confidence: 99%

“…DEA is the most used tool for comparing the performance of organizations with multiple variables and has been utilized to evaluate various contexts. Some applications of DEA in the area of logistics include Karlaftis (2004); Karlaftis and Tsamboulas (2012); Ozbek et al (2009);Novaes (2001);and Tamagawa, et. al (2010), among others.…”

Section: Introductionmentioning

confidence: 99%

Efficiency and Effectiveness Analysis of Public Transport of Brazilian Cities

Carvalho

Syguiy

Silva³

2015

J. Transp. Lit.

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Keywords: Urban Public Transportation Data Envelopment Analysis, Government and Public PoliciesThe public sector is responsible for the implementation of transport public policies that maximize the competitiveness of urban space and minimize the negative effects of its growth. For that, the proposal of actions must be guided by good performance indices. Taking the Competitiveness Indicators of Campinas (ICC) as a reference, this paper introduces three main contributions: improve the ICC public transport performance indicator; evaluate the performance of Brazilian municipalities over six years and analyses the efficiency vs. effectiveness strategy for each city. The Data Envelopment Analysis (DEA) results show the conflict among different municipalities strategies, while Curitiba and Betim emphasize the effectiveness of the service delivered São Bernardo e Salvador strategy is centered on efficiency.

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“…This Table 1 Different issues concerning the application of DEA (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) Author(s) Application No. Ramanathan, 2005;Wang & Cullinane, 2006;Ozbek et al, 2009;Wu et al, 2010;Ju et al, 2012;Haralambides & Gujar, 2012. Transportation 6 Liu et al, 2000Førsund & Hjalmarsson, 2004;Mostafa, 2010;Lozano & Villa, 2010;Lin et al, 2011;Xuanli & Yuan, 2011;Wei & Chang, 2011;Ruiz & Sirvent, 2011;Cook & Zhu, 2011;Zhang et al, 2012;Falagario et al, 2012;Luo et al, 2012.…”

Section: Introductionmentioning

confidence: 99%

A state-of-art review on supplier selection problem

Khodadadzadeh¹,

Sadjadi²

2013

10.5267/j.dsl

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Many supplier selection problems are involved with various criteria such as quality of supplier, price, delivery time, etc. This paper presents a survey on the implementation of using different multi criteria decision making (MCDM) methods for supplier selection problems. The reviews covers recent advances of MCDM techniques such as data envelopment analysis (DEA), analytical hierarchy process, etc. over the period 2000-2012. The review also reveals that nearly 60% of the applications are associated with business unit, 15% is related to economy, 9% is devoted to service and development and 8% is dedicated to research and development. In our survey, DEA has become the most popular technique for supplier selection problem followed by Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Analytical Hierarchy Process (AHP).

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Data Envelopment Analysis as a Decision-Making Tool for Transportation Professionals

Cited by 44 publications

References 18 publications

Prioritization of bridges for maintenance planning using data envelopment analysis

Prioritization of bridges for maintenance planning using data envelopment analysis

Efficiency and Effectiveness Analysis of Public Transport of Brazilian Cities

A state-of-art review on supplier selection problem

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