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Adjusting for the environment in DEA: A comparison of alternative models based on empirical data
Affiliation:1. Department of Economics, National Chung Cheng University, Taiwan;2. Department of Economics, State University of New York at Binghamton, Binghamton, 13902 NY, United States;3. University of Stavanger Business School, Stavanger N-4036, Norway
Abstract:Due to the existence of free software and pedagogical guides, the use of Data Envelopment Analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run their own efficiency analysis. Within DEA, several alternative models allow for an environmental adjustment. Four alternative models, each user-friendly and easily accessible to practitioners and decision makers, are performed using empirical data of 90 primary schools in the State of Geneva, Switzerland. Results show that the majority of alternative models deliver divergent results. From a political and a managerial standpoint, these diverging results could lead to potentially ineffective decisions. As no consensus emerges on the best model to use, practitioners and decision makers may be tempted to select the model that is right for them, in other words, the model that best reflects their own preferences. Further studies should investigate how an appropriate multi-criteria decision analysis method could help decision makers to select the right model.
Keywords:Data envelopment analysis  Environmental variables  Comparison  Empirical data
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