Performance based clustering for benchmarking of US airports |
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| Institution: | 1. Graduate School of Management, Clark University, 950 Main Street, Worcester, MA 01610, USA;2. Department of Marketing and Supply Chain Management, Broad College of Business, Michigan State University, East Lansing, MI 48824, USA;1. Associate Professor of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba''i University, Dehkadeh-ye-Olympic, 1997967556, Tehran, Iran;2. Professor of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Dehkadeh-ye-Olympic, 1997967556, Tehran, Iran;3. Assistant Professor of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Dehkadeh-ye-Olympic, 1997967556, Tehran, Iran;4. Ph.D. Student of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Dehkadeh-ye-Olympic, 1997967556, Tehran, Iran |
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| Abstract: | 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. |
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