Dynamic DEA models with network structure: An application for Iranian airlines |
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| Affiliation: | 1. School of Aerospace Engineering, Aerospace Systems Design Laboratory, Georgia Institute of Technology, 275 Ferst Dr., Atlanta, GA 30332-0150, USA;2. Civil Aviation Research Division, School of Aerospace Engineering, Aerospace Systems Design Laboratory, Georgia Institute of Technology, 275 Ferst Dr., Atlanta, GA 30332-0150, USA;3. Boeing Regents Professor of Advanced Aerospace Systems Analysis, School of Aerospace Engineering, Aerospace Systems Design Laboratory, Georgia Institute of Technology, 275 Ferst Dr., Atlanta, GA 30332-0150, USA;1. FU Berlin, Department of Information Systems, Germany;2. RWTH Aachen University, Department of Business and Economics, Germany;1. Faculty of Management and Economics, Dalian University of Technology, No. 2 Linggong Road, Dalian City, 116024, China;2. Transportation Management College, Dalian Maritime University, No. 1 Linghai Road, Dalian City, 116026, China;1. Transportation Management College, Dalian Maritime University, Dalian 116026, China;2. School of Economics and Management, Southeast University, Nanjing 211189, China;1. Aristotle University of Thessaloniki, School of Economic Sciences, MSc Programme in Logistics and Supply Chain Management, University Campus, 54124, Thessaloniki, Greece;2. University of Macedonia, Department of Applied Informatics, Information Systems and e-Business Laboratory (ISeB), 156, Egnatia Str., 54636, Thessaloniki, Greece |
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| Abstract: | Efficiency estimation of interdependent divisions within a company or assessing the interrelated processes in a production system provides insights for improving the operational performance. Recent developments in network data envelopment analysis (NDEA) models enable decision making units (DMUs) to be informed of inefficient processes within the system. The NDEA model assesses the processes of the system in a specific moment and ignores the dynamic effects within the production processes. Thus, without considering the temporal dimension of production processes, biased efficiency measurement will be obtained that provides misleading information to DMUs. For evaluating the performance of a DMU with interrelated processes during specified multiple periods, this paper proposes a relational dynamic NDEA (DNDEA) model which measures the efficiencies of the system and its internal processes over the time, simultaneously. To illustrate the capability of the proposed model, this study for the first time measures the efficiency of eight Iranian airlines in several periods connected to each other by carry over flows. The actual data is gathered in three periods from 2010 to 2012 and the results are compared with the dynamic DEA and network DEA models in the same time span. |
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| Keywords: | Efficiency Dynamic network DEA Airlines Relational analysis |
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