An Airport can be considered as a mean to promote the economic welfare and the competitiveness of one region. Because of the need to contrast market imperfections, airports are subjected to several different regulations which regard operational, economic and environmental issues. In this framework, some techniques for evaluating global airport performances are necessary in order to help public authorities to investigate whether some airports are more efficiently run than others. For this purpose, the so-called Data Envelopment Analysis (DEA) can be used. DEA is a linear programming based methodology which provides a scalar measure of relative efficiency for a certain set of decision making units (DMUs) that carry out similar functions, transforming multiple inputs in multiple outputs. DEA is a synthetic, flexible and easy to use technique which generalises the notion of the so-called productivity ratio. In the paper, after having pointed out the importance of global measures of performance in the air transport market, a synthetic revision of DEA technique is carried out; then DEA is applied to evaluate the performances of Italian airports. DEA create a piecewise linear efficient production frontier, which represents the relation between inputs and maximal outputs. Any deviation from the efficient frontier is labelled as inefficient. In the paper the basic DEA model CCR and BCC are used. The so-called CCR model (Charnes, Cooper and Rhodes) is based on the hypothesis of constant returns to scale. The so-called BCC model (Banker, Charnes and Cooper), instead, is based on the assumption of variable returns to scale. Both DEA basic models, CCR and BCC, can be “input oriented models” and “output oriented models”. In the paper, DEA is used in order to evaluate both technical and scale efficiency of Italian airports. The DMUs that form the study sample are the 38 Italian international airports. The data set refers to year 2006. Three input and four output variables are considered. The input variables are: runway length; apron area; number of gates in the passenger terminal; total length of runways. For the output side, four variables are chosen: number of aircraft movements; number of “full-service” airlines passenger movements; number of “low-cost” airlines passenger movements; tonns of cargo loaded and unloaded. Both CCR input oriented model (CCR-I) and BCC input oriented model (BCC-I) are applied in the analysis. A partition of Italian airports in three classes, according to the yearly number of total passengers processed, is proposed. The 38 Italian commercial airports have been ranked according to their efficiency scores. Each airport has been labelled as efficient or inefficient and distinction has been made between purely technical and scale inefficiencies. The results of the application, which refers to year 2006, indicate that: almost all airports which belong to class 1 are CCR-efficient, conversely, no airport with less than 3 million passengers per year is CCR-efficient (with one exception), however, five small regional airports prove to be BCC-efficient; in terms of global technical efficiency, 24/100 of Italian airports are efficient, with an average GTE score of 0.687; in terms of purely technical efficiency, 37/100 of Italian airports are efficient, with an average PTE score of 0.814; the average scale efficiency of Italian airports is equal to 0.826 and 10 airports operate at constant returns to scale, one airport operates at a decreasing return to scale, while the remaining 27 airports operate at increasing returns to scale; as airport passenger traffic decreases, the global technical efficiency decreases, due to a decrease in both purely technical and scale efficiency. Therefore, several Italian airports are inefficient also, or mainly, because their scale of operation is not enough large

### An application of Data Envelopment Analysis(DEA) to evaluate technical and scale efficiency of Italian airports

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*LUPI, MARINO*

##### 2008-01-01

#### Abstract

An Airport can be considered as a mean to promote the economic welfare and the competitiveness of one region. Because of the need to contrast market imperfections, airports are subjected to several different regulations which regard operational, economic and environmental issues. In this framework, some techniques for evaluating global airport performances are necessary in order to help public authorities to investigate whether some airports are more efficiently run than others. For this purpose, the so-called Data Envelopment Analysis (DEA) can be used. DEA is a linear programming based methodology which provides a scalar measure of relative efficiency for a certain set of decision making units (DMUs) that carry out similar functions, transforming multiple inputs in multiple outputs. DEA is a synthetic, flexible and easy to use technique which generalises the notion of the so-called productivity ratio. In the paper, after having pointed out the importance of global measures of performance in the air transport market, a synthetic revision of DEA technique is carried out; then DEA is applied to evaluate the performances of Italian airports. DEA create a piecewise linear efficient production frontier, which represents the relation between inputs and maximal outputs. Any deviation from the efficient frontier is labelled as inefficient. In the paper the basic DEA model CCR and BCC are used. The so-called CCR model (Charnes, Cooper and Rhodes) is based on the hypothesis of constant returns to scale. The so-called BCC model (Banker, Charnes and Cooper), instead, is based on the assumption of variable returns to scale. Both DEA basic models, CCR and BCC, can be “input oriented models” and “output oriented models”. In the paper, DEA is used in order to evaluate both technical and scale efficiency of Italian airports. The DMUs that form the study sample are the 38 Italian international airports. The data set refers to year 2006. Three input and four output variables are considered. The input variables are: runway length; apron area; number of gates in the passenger terminal; total length of runways. For the output side, four variables are chosen: number of aircraft movements; number of “full-service” airlines passenger movements; number of “low-cost” airlines passenger movements; tonns of cargo loaded and unloaded. Both CCR input oriented model (CCR-I) and BCC input oriented model (BCC-I) are applied in the analysis. A partition of Italian airports in three classes, according to the yearly number of total passengers processed, is proposed. The 38 Italian commercial airports have been ranked according to their efficiency scores. Each airport has been labelled as efficient or inefficient and distinction has been made between purely technical and scale inefficiencies. The results of the application, which refers to year 2006, indicate that: almost all airports which belong to class 1 are CCR-efficient, conversely, no airport with less than 3 million passengers per year is CCR-efficient (with one exception), however, five small regional airports prove to be BCC-efficient; in terms of global technical efficiency, 24/100 of Italian airports are efficient, with an average GTE score of 0.687; in terms of purely technical efficiency, 37/100 of Italian airports are efficient, with an average PTE score of 0.814; the average scale efficiency of Italian airports is equal to 0.826 and 10 airports operate at constant returns to scale, one airport operates at a decreasing return to scale, while the remaining 27 airports operate at increasing returns to scale; as airport passenger traffic decreases, the global technical efficiency decreases, due to a decrease in both purely technical and scale efficiency. Therefore, several Italian airports are inefficient also, or mainly, because their scale of operation is not enough largeI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.