An empirical study of Iranian regional airports using robust data envelopment analysis

Emad Roghanian

doi:10.5267/j.ijiec.2010.01.006

Abstract

Article history: Received 1 Feb 2010 Received in revised form 20 March 2010 Accepted 1 April 2010 Available online 7 April 2010 Data Envelopment Analysis (DEA) has been one of the most important tools on measuring the relative efficiency of different similar units such as transportation systems using terminals, airports, etc. In this study, we perform an empirical analysis on Iranian airports based on DEA methods to measure the efficiencies of various airports. One of the primary issues on many traditional DEA methods is that the data are almost always contaminated with noise. We use a DEA method which could handle the uncertainty associated with input and output data. The results of this comprehensive study show that most of the active airlines are practically inefficient and the government could significantly increase the efficiencies of the airports by setting new regulations and rules. © 2010 Growing Science Ltd. All rights reserved.

Highlights

Data Envelopment Analysis (DEA) has become one of the most important techniques on measuring the relative efficiency of different units especially when the units do not generate any profit (Wu et al 2010; Pulina et al 2010)
A traditional method to measure the relative efficiency is the direct implementation of DEA methods
We present the implementation of the proposed RDEA

Summary

Introduction

DEA has become one of the most important techniques on measuring the relative efficiency of different units especially when the units do not generate any profit (Wu et al 2010; Pulina et al 2010). Martin and Roman (2001) use DEA to measure the performance of 37 major Spanish airports using three inputs of the number of employees, the capital and the fixed assets. They consider the number of flights, the number of passengers and the net income as the outputs of their model. Lin and Hong (2006) use DEA for measuring the relative efficiency of major international airports In their DEA implementation, they use five inputs of the number of employees, the landing band length, the parking size, the airlines stations and the terminal spaces. Using the three outputs of the number of passengers, the cargo and number of trips, they implement DEA and extract the ranking of various airlines in four groups. Tseng, et al (2008) perform a comprehensive study on the performance evaluation of major international airports in the world. Wang et al (2004) perform similar study on Taiwan airports. Barros (2008) uses DEA for different airports in Argentina and analyzes the results in economic crisis. Pels et al (2003) examine the performance of the European airlines using DEA and report that the airlines are mostly efficient. Lam et al (2009) analyze different dimensions of operational efficiencies in major Asia Pacific airports through DEA models which are

Problem statement

Robust optimization

Experimental Results

Conclusions