2011International Journal for Traffic and Transport EngineeringRequires access

Ranking Efficient and Inefficient Decision Making Units in Data Envelopment Analysis

Rita Markovits-Somogyi

Open publisher page 29 citations

Abstract

Data envelopment analysis is a non-parametric linear programming method capable of the efficiency evaluation of decision making units (e.g. public transport companies). It is very often used in the transport sector for the efficiency assessment of airports, ports, railways and public transport companies. However, the original DEA method does not differentiate the efficient firms and thus, does not create full ranking. To overcome this problem, several methods have been developed with the aim of enlarging the distinguishing power of DEA. The present article aims to review these methods with a special emphasis on the ones elaborated in the last decade.

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What this paper is about

Data envelopment analysis is a non-parametric linear programming method capable of the efficiency evaluation of decision making units (e.g. public transport companies). It is very often used in the transport sector for the efficiency assessment of airports, ports, railways and public transport companies. However, the original DEA method does not differentiate the efficient firms and thus, does not create full ranking. To overcome this problem, several methods have been developed with the aim of enlarging the distinguishing power of DEA. The present article aims to review these methods with a special emphasis on the ones elaborated in the last decade.

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Available abstract

Data envelopment analysis is a non-parametric linear programming method capable of the efficiency evaluation of decision making units (e.g. public transport companies). It is very often used in the transport sector for the efficiency assessment of airports, ports, railways and public transport companies. However, the original DEA method does not differentiate the efficient firms and thus, does not create full ranking. To overcome this problem, several methods have been developed with the aim of enlarging the distinguishing power of DEA. The present article aims to review these methods with a special emphasis on the ones elaborated in the last decade.

Key concepts: Data envelopment analysis, Ranking (information retrieval), Operations research, Computer science, Linear programming, Performance measurement, Parametric statistics, Efficiency

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