Performance based clustering for benchmarking of US airports

被引:149
|
作者
Sarkis, J
Talluri, S [2 ]
机构
[1] Clark Univ, Grad Sch Management, Worcester, MA 01610 USA
[2] Michigan State Univ, Broad Coll Business, Dept Mkt & Supply Chain Management, E Lansing, MI 48824 USA
关键词
data envelopment analysis; clustering; benchmarking; performance analysis;
D O I
10.1016/j.tra.2003.11.001
中图分类号
F [经济];
学科分类号
02 ;
摘要
Managing service operations is gaining significant attention in both academic and practitioner circles. In this broad area, performance evaluation and process improvement of airlines and air carriers has been the focus of several studies. Although efficient airport operations are critical for improved performance of airlines and air carriers, few studies have focused on airport performance measurement. This study evaluates the operational efficiencies of 44 major US airports across 5 years using multi-criteria non-parametric models. These efficiency scores are treated by a clustering method in identifying benchmarks for improving poorly performing airports. Efficiency measures are based on four resource input measures including airport operational costs, number of airport employees, gates and runways, and five output measures including operational revenue, passenger flow, commercial and general aviation movement, and total cargo transportation. The methodology presented here can be generalized to other industries and institutions. (C) 2003 Elsevier Ltd. All rights reserved.
引用
收藏
页码:329 / 346
页数:18
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