Hooper and Hensher (1997HOOPER P & HENSHER D. 1997. Measuring total factor productivity of airports - an index number approach. Transportation Research Part E , 33: 249-259. Available at: https://doi.org/10.1016/S1366-5545(97)00033-1. https://doi.org/10.1016/S1366-5545(97)00...
) |
6 Australian airports, 1988-1993 |
TFP index and OLS regression |
• Labor costs |
• Non-aeronautical revenues |
• Size of operation (output index) |
|
|
|
• Capital costs |
• Aeronautical revenues |
• Airport-specific dummy variables |
|
|
|
• Other operating costs |
|
|
Gillen and Lall (1997GILLEN D & LALL A. 1997. Developing measures of airport productivity and performance: an application of data envelopment analysis. Transportation Research Part E , 33: 261-273. Available at: https://doi.org/10.1016/S1366-5545(97)00028-8. https://doi.org/10.1016/S1366-5545(97)00...
) |
21 US airports, 1989-1993 |
Two-stage DEA model: |
(i) Terminal services
|
(i) Terminal services
|
i) Structural variables
|
|
|
1) DEA |
• Number of runways |
• Number of passengers |
• Number of runways |
|
|
2) Tobit regression |
• Number of gates |
• Cargo |
• Terminal area |
|
|
|
• Terminal area |
(ii) Movements
|
• Number of gates |
|
|
|
• Number of employees |
• Aircraft movements |
• Number of baggage claim belts per gate |
|
|
|
• Number of baggage claim belts |
• Number of passengers |
ii) Environmental variables
|
|
|
|
• Number of vehicle parking lots |
|
• Annual service volume |
|
|
|
(ii) Movements
|
|
iii) Dummy variables for the time period
|
|
|
|
• Airport area |
|
• Year 1989 |
|
|
|
• Number of runways |
|
• Year 1990 |
|
|
|
• Runway area |
|
• Year 1991 |
|
|
|
• Number of employees |
|
• year 1992 |
|
|
|
|
|
iv) Dummy variables for hub airports
|
|
|
|
|
|
• Atlanta |
|
|
|
|
|
• San Francisco |
|
|
|
|
|
• Minnesota and St Paul |
|
|
|
|
|
• Seattle - Tacoma |
|
|
|
|
|
• Phoenix |
|
|
|
|
|
v) Noise strategy variables
|
|
|
|
|
|
• Preferential flight path |
|
|
|
|
|
• Preferential runway use |
|
|
|
|
|
• Limit on operations |
|
|
|
|
|
• Limit on stage II aircraft |
|
|
|
|
|
• Limit on operating hours |
|
|
|
|
|
• Noise budget |
|
|
|
|
|
vi) Management operational and investment variables
|
|
|
|
|
|
• Number of airlines hubs |
|
|
|
|
|
• % of gates common use |
|
|
|
|
|
• % of gates exclusive use |
|
|
|
|
|
• % of international airports |
|
|
|
|
|
• Financing regime |
|
|
|
|
|
• % of general aviation traffic |
Sarkis (2000) |
44 major US airports, 1990-1994 |
DEA, Multi-factor efficiency models and CA |
• Operating costs |
• Operating revenues |
|
|
|
|
• Number of employees |
• Aircraft movements |
|
|
|
|
• Number of gates |
• General aviation movements |
|
|
|
|
• Number of runways |
• Number of passengers |
|
|
|
|
|
• Cargo |
|
Martín and Román (2001MARTÍN J & ROMÁN C. 2001. An application of DEA to measure the efficiency of Spanish airports prior to privatization. Journal of Air Transport Management , 7: 149-157. Available at: https://doi.org/10.1016/S0969-6997(00)00044-2. https://doi.org/10.1016/S0969-6997(00)00...
) |
37 Spanish airports, 1997 |
DEA models |
• Labor costs |
• Number of passengers |
|
|
|
|
• Capital costs |
• Cargo |
|
|
|
|
• Material costs |
• Aircraft movements |
|
Pels et al. (2001PELS E, NIJKAMP P & RIETVELD P. 2001. Relative efficiency of European airports. Transport Policy, 8: 183-192. Available at: https://doi.org/10.1016/S0967-070X(01)00012-9. https://doi.org/10.1016/S0967-070X(01)00...
) |
34 European airports, 1995-1997 |
DEA and SFA |
i - DEA (PAX model)
|
i - DEA (PAX model)
|
|
|
|
|
• Terminal size |
• Number of passengers |
|
|
|
|
• Number of aircraft parking positions (terminal) |
ii - DEA (ATM model)
|
|
|
|
|
• Number of remote aircraft parking positions |
• Aircraft movements |
|
|
|
|
• Number of check-in counters |
iii - SFA (PAX model)
|
|
|
|
|
• Number of baggage claim belts |
• Number of passengers |
|
|
|
|
ii - DEA (ATM model)
|
iv - SFA (ATM model)
|
|
|
|
|
• Airport area |
• Aircraft movements |
|
|
|
|
• Number of runways |
|
|
|
|
|
• Runway length |
|
|
|
|
|
• Number of aircraft parking positions (terminal) |
|
|
|
|
|
• Number of remote aircraft parking positions |
|
|
|
|
|
iii - SFA (PAX model) |
|
|
|
|
|
• Number of baggage claim belts |
|
|
|
|
|
• Number of aircraft parking positions (terminal) |
|
|
|
|
|
• Number of remote aircraft parking positions |
|
|
|
|
|
iv - SFA (ATM model)
|
|
|
|
|
|
• Number of runways |
|
|
|
|
|
• Number of aircraft parking positions (terminal) |
|
|
|
|
|
• Number of remote aircraft parking positions |
|
|
Fernandes and Pacheco (2002FERNANDES E & PACHECO R. 2002. Efficient use of airport capacity. Transportation Research Part A , 36: 225-238. Available at: https://doi.org/10.1016/S0965-8564(00)00046-X. https://doi.org/10.1016/S0965-8564(00)00...
) |
35 Brazilian airports, 1998 |
DEA |
• Apron area |
• Number of passengers |
|
|
|
|
• Departure lounge |
|
|
|
|
|
• Number of check-in counters |
|
|
|
|
|
• Curb frontage |
|
|
|
|
|
• Number of vehicle parking lots |
|
|
|
|
|
• Baggage claim area |
|
|
Bazargan and Vasigh (2003BAZARGAN M & VASIGH B. 2003. Size versus efficiency: a case study of US commercial airports. Journal of Air Transport Management , 9: 187-193. Available at: https://doi.org/10.1016/S0969-6997(02)00084-4. https://doi.org/10.1016/S0969-6997(02)00...
) |
45 US airports, 1996-2000 |
DEA |
• Number of runways |
• Number of passengers |
|
|
|
|
• Number of gates |
• Aircrafts movements |
|
|
|
|
• Operating costs |
• Other movements |
|
|
|
|
• Non-operating costs |
• Aeronautical revenues |
|
|
|
|
|
• Non-aeronautical revenues |
|
|
|
|
|
• % of on-time operations |
|
Oum et al. (2003OUM T, YU C & FU X. 2003. A comparative analysis of productivity performance of the world’s major airports: summary report of the ATRS global airport benchmarking research report-2002. Journal of Air Transport Management , 9: 285-297. Available at: https://doi.org/10.1016/S0969-6997(03)00037-1. https://doi.org/10.1016/S0969-6997(03)00...
) |
50 worldwide airports, 1999 |
TFP and log-linear regression |
• Number of employees |
• Aircraft movements |
Factors beyond managerial control
|
|
|
|
• Number of runways |
• Number of passengers |
• Ownership structure |
|
|
|
• Terminal area |
• Cargo |
• Airport size |
|
|
|
• Number of gates |
• Non-aeronautical revenue |
• Average aircraft size |
|
|
|
• Soft cost input |
|
• % of international passengers |
|
|
|
|
|
Factors under managerial control
|
|
|
|
|
|
• Business diversification strategy |
|
|
|
|
|
• Outsourcing |
|
|
|
|
|
• Service quality |
Pacheco and Fernandes (2003PACHECO R & FERNANDES E. 2003. Managerial efficiency of Brazilian airports. Transportation Research Part A , 37: 667-680. Available at: https://doi.org/10.1016/S0965-8564(03)00013-2. https://doi.org/10.1016/S0965-8564(03)00...
) |
35 Brazilian domestic airports, 1998 |
DEA |
• Number of employees |
• Domestic passengers |
|
|
|
|
• Payroll |
• Cargo plus mail |
|
|
|
|
• Operating costs |
• Operating revenue |
|
|
|
|
|
• Non-aeronautical revenues |
|
|
|
|
|
• Other revenues |
|
Pels et al. (2003PELS E, NIJKAMP P & RIETVELD P. 2003. Inefficiencies and scale economies of European airport operations. Transportation Research Part E , 39: 341-361. Available at: https://doi.org/10.1016/S1366-5545(03)00016-4. https://doi.org/10.1016/S1366-5545(03)00...
) |
33 European airports, 1995-1997 |
DEA and SFA |
i - ATM model
|
i - ATM model
|
|
|
|
|
• Airport area |
• Aircraft movements |
|
|
|
|
• Number of runways |
ii - APM model
|
|
|
|
|
• Number of terminal aircraft parking positions |
• Number of passengers |
|
|
|
|
• Number of remote aircraft parking positions |
|
|
|
|
|
ii - APM model
|
|
|
|
|
|
• Number of check-in counters |
|
|
|
|
|
• Number of baggage claim belts |
|
|
|
|
|
• Aircraft movements |
|
|
Oum and Yu (2004OUM T & YU C. 2004. Measuring airport’s operating efficiency: a summary of the 2003 ATRS global airport benchmarking report. Transportation Research Part E , 40: 515-532. Available at: https://doi.org/10.1016/j.tre.2004.08.002. https://doi.org/10.1016/j.tre.2004.08.00...
) |
76 worldwide airports, 2000-2001 |
VFP and log-linear regression |
• Number of employees |
• Number of passengers |
Factors beyond airport control
|
|
|
|
• Soft cost input |
• Cargo |
• Airport size |
|
|
|
|
• Aircraft movements |
• Average aircraft size |
|
|
|
|
• Non-aeronautical revenues |
• % of international passengers |
|
|
|
|
|
• % of cargo in total traffic |
|
|
|
|
|
• Capacity constraints |
|
|
|
|
|
Factors within airport control
|
|
|
|
|
|
• Passenger satisfaction |
|
|
|
|
|
• % of non-aeronautical revenue |
|
|
|
|
|
• Terminal operator |
Sarkis and Talluri (2004SARKIS J & TALLURI S. 2004. Performance based clustering for benchmarking of US airports. Transportation Research Part A , 38: 329-346. Available at: https://doi.org/10.1016/j.tra.2003.11.001. https://doi.org/10.1016/j.tra.2003.11.00...
) |
44 US airports, 1990-1994 |
DEA, Multi-factor efficiency models and CA |
• Operating costs |
• Operating revenues |
|
|
|
|
• Number of employees |
• Aircraft movements |
|
|
|
|
• Number of gates |
• General aviation movements |
|
|
|
|
• Number of runways |
• Number of passengers |
|
|
|
|
|
• Cargo |
|
Yoshida and Fujimoto (2004YOSHIDA Y & FUJIMOTO H. 2004. Japanese-airport benchmarking with the DEA and endogenous-weight TFP methods: testing the criticism of overinvestment in Japanese regional airports. Transportation Research Part E , 40: 533-546. Available at: https://doi.org/10.1016/j.tre.2004.08.003. https://doi.org/10.1016/j.tre.2004.08.00...
) |
67 Japanese airports, 2000 |
Two-stage DEA model: |
• Runway length |
• Number of passengers |
• Third-category regional airports |
|
|
1) DEA and TFP index; |
• Terminal area |
• Cargo |
• Airports that started their operations in the 1990s |
|
|
2) OLS regression |
• Access cost |
• Aircraft movements |
|
|
|
|
• Number of employees |
|
|
Lin and Hong (2006LIN L & HONG C. 2006. Operational performance evaluation of international major airports: an application of data envelopment analysis. Journal of Air Transport Management , 12: 342-351. Available at: https://doi.org/10.1016/j.jairtraman.2006.08.002. https://doi.org/10.1016/j.jairtraman.200...
) |
20 major worldwide airports, 2003 |
DEA models |
• Number of employees |
• Number of passengers |
|
|
|
|
• Number of check-in counters |
• Cargo |
|
|
|
|
• Number of runways |
• Aircraft movements |
|
|
|
|
• Number of parking positions |
|
|
|
|
|
• Number of baggage claim belts |
|
|
|
|
|
• Number of aprons |
|
|
|
|
|
• Number of boarding gates |
|
|
|
|
|
• Terminal area |
|
|
Oum et al. (2006OUM T, ADLER N & YU C. 2006. Privatization, corporatization, ownership forms and their effects on the performance of the world’s major airports. Journal of Air Transport Management , 12: 109-121. Available at: https://doi.org/10.1016/j.jairtraman.2005.11.003. https://doi.org/10.1016/j.jairtraman.200...
) |
116 worldwide airports, 2001-2003 |
VFP and log-linear regression |
• Number of employees |
• Number of passengers |
Airport characteristics
|
|
|
|
• Soft cost input |
• Aircraft movements |
• Airport size |
|
|
|
|
• Non-aeronautical revenues |
• Runway utilization |
|
|
|
|
|
• Average aircraft size |
|
|
|
|
|
• % of international passengers |
|
|
|
|
|
• % of cargo in total traffic |
|
|
|
|
|
Other factors
|
|
|
|
|
|
• Ownership structure |
|
|
|
|
|
• Regional business environments |
|
|
|
|
|
• Business diversification (% of non-aeronautical revenue) |
Barros and Dieke (2007BARROS C & DIEKE P. 2007. Performance evaluation of Italian airports: a data envelopment analysis. Journal of Air Transport Management , 13: 184-191. Available at: https://doi.org/10.1016/j.jairtraman.2007.03.001. https://doi.org/10.1016/j.jairtraman.200...
) |
31 Italian airports, 2001-2003 |
DEA models |
• Labor |
• Aircraft movements |
|
|
|
|
• Capital costs |
• Number of passengers |
|
|
|
|
• Other operating costs |
• Cargo |
|
|
|
|
|
• Handling receipts |
|
|
|
|
|
• Aeronautical sales |
|
|
|
|
|
• Non-aeronautical sales |
|
Barros (2008aBARROS C & DIEKE P. 2008. Measuring the economic efficiency of airports: a Simar-Wilson methodology analysis. Transportation Research Part E, 44: 1039-1051. Available at: https://doi.org/10.1016/j.tre.2008.01.001. https://doi.org/10.1016/j.tre.2008.01.00...
) |
32 Argentine airports, 2003-2007 |
Two-stage DEA model: |
• Number of employees |
• Aircraft movements |
• Time trend |
|
|
1) DEA |
• Runway area |
• Number of passengers |
• Airport hub status |
|
|
2) SWBT regression |
• Apron area |
• Cargo |
• Work load units (WLU) |
|
|
|
• Passenger terminal area |
|
|
Barros (2008bBARROS C. 2008b. Technical efficiency of UK airports. Journal of Air Transport Management , 14: 175-178. Available at: https://doi.org/10.1016/j.jairtraman.2008.04.002. https://doi.org/10.1016/j.jairtraman.200...
) |
27 UK airports, 2000-2005 |
SCF (LR) estimated using ML |
• Operating costs |
• Number of passengers |
• Time trend |
|
|
|
• Labor costs |
• Aircraft movements |
• Labor costs |
|
|
|
• Capital premises |
|
• Capital premises |
|
|
|
• Capital investments |
|
• Capital investments |
|
|
|
|
|
• Number of passengers |
|
|
|
|
|
• Aircraft movements |
|
|
|
|
|
• Owned by BAA |
|
|
|
|
|
• Owned by Manchester airports |
|
|
|
|
|
• Owned by TBI |
Barros and Dieke (2008BARROS C & DIEKE P. 2008. Measuring the economic efficiency of airports: a Simar-Wilson methodology analysis. Transportation Research Part E, 44: 1039-1051. Available at: https://doi.org/10.1016/j.tre.2008.01.001. https://doi.org/10.1016/j.tre.2008.01.00...
) |
31 Italian airports, 2001-2003 |
Two-stage DEA model: |
• Labor costs |
• Aircraft movements |
• Time trend |
|
|
1) DEA models |
• Capital invested |
• Number of passengers |
• Airport hub status |
|
|
2) SWBT regression |
• Operating costs excluding labor costs |
• Cargo |
• Work load units (WLU) |
|
|
|
|
• Handling receipts |
• Ownership structure |
|
|
|
|
• Aeronautical revenues |
• Location |
|
|
|
|
• Non-aeronautical revenues |
|
Oum et al. (2008OUM T, YAN J & YU C. 2008. Ownership forms matter for airport efficiency: A stochastic frontier investigation of worldwide airports. Journal of Urban Economics, 64: 422-435. Available at: https://doi.org/10.1016/j.jue.2008.03.001. https://doi.org/10.1016/j.jue.2008.03.00...
) |
109 Worldwide airports, 2001-2004 |
SCF (SR) estimated via Bayesian approach |
Variable inputs
|
• Number of passengers |
(i) Geographic distribution of airports (%)
|
|
|
|
• Number of employees |
• Aircraft movements |
(ii) Ownership structure (%)
|
|
|
|
• Non-labor variable cost |
• Non-aeronautical revenue |
(iii) Airport characteristics
|
|
|
|
Fixed inputs
|
|
• % of international passengers |
|
|
|
• Number of runways |
|
• % of cargo |
|
|
|
• Passenger terminal area |
|
|
|
|
|
Variable inputs’ prices
|
|
|
|
|
|
• Wage rate |
|
|
|
|
|
• Non-labor input price |
|
|
|
|
|
Variable inputs’ share
|
|
|
|
|
|
• Labor cost share |
|
|
Pathomsiri et al. (2008PATHOMSIRI S, HAGHANI A, DRESNER M & WINDLE R. 2008. Impact of undesirable outputs on the productivity of US airports. Transportation Research Part E , 44: 235-259. Available at: https://doi.org/10.1016/j.tre.2007.07.002. https://doi.org/10.1016/j.tre.2007.07.00...
) |
56 US airports, 2000-2003 |
DDF and Luenberger productivity index |
• Land area |
Desirable outputs
|
|
|
|
|
• Number of runways |
• Non-delayed flights |
|
|
|
|
• Runway area |
• Number of passengers |
|
|
|
|
|
• Cargo |
|
|
|
|
|
Undesirable outputs
|
|
|
|
|
|
• Delayed flights |
|
|
|
|
|
• Time delays |
|
Yu et al. (2008YU MM, HSU SH, CHANG CC & LEE DH. 2008. Productivity growth of Taiwan’s major domestic airports in the presence of aircraft noise. Transportation Research Part E , 44: 543-544. Available at: https://doi.org/10.1016/j.tre.2007.01.005. https://doi.org/10.1016/j.tre.2007.01.00...
) |
4 Taiwan’s airports, 1995-1999 |
• Traditional MPI |
Inputs
|
Desirable output
|
|
|
|
• Extended MPI |
• Operating costs |
• Aeronautical revenue |
|
|
|
• Extended MLPI with DDF |
• Labor costs |
• Non-aeronautical revenue |
|
|
|
|
• Capital costs |
Undesirable output
|
|
|
|
|
Environmental factors
|
• Aircraft noise |
|
|
|
|
• Aircraft movements |
|
|
|
|
|
• Number of passengers |
|
|
Barros and Weber (2009BARROS C & WEBER W. 2009. Productivity growth and biased technological change in UK airports. Transportation Research Part E , 45: 642-653. Available at: https://doi.org/10.1016/j.tre.2009.01.004. https://doi.org/10.1016/j.tre.2009.01.00...
) |
27 UK airports, 2000-2005 |
DEA and MPI |
• Labor costs |
• Number of passengers |
|
|
|
|
• Capital costs |
• Cargo |
|
|
|
|
• Other costs |
• Aircraft movements |
|
Chi-Lok and Zhang (2009CHI-LOK A & ZHANG A. 2009. Effects of competition and policy changes on Chinese airport productivity: an empirical investigation. Journal of Air Transport Management , 15: 166-174. Available at: https://doi.org/10.1016/j.jairtraman.2008.09.003. https://doi.org/10.1016/j.jairtraman.200...
) |
25 Chinese airport, 1995-2006 |
Two-stage DEA model: |
• Runway length |
• Number of passengers |
(i) Airport localization program
|
|
|
1) DEA and MPI |
• Terminal size |
• Cargo |
(ii) Competition intensity
|
|
|
2) OLS and Tobit regression |
|
• Aircraft movements |
(iii) Public listing
|
|
|
|
|
|
(iv) Airport characteristics
|
|
|
|
|
|
• Airport hub status |
|
|
|
|
|
• Local economy |
|
|
|
|
|
• Coastal city |
|
|
|
|
|
• Tourist city |
|
|
|
|
|
• Population |
|
|
|
|
|
• Demand and supply shocks |
|
|
|
|
|
(v) Event variables
|
|
|
|
|
|
• Airline mergers |
|
|
|
|
|
• Open-skies agreements |
|
|
|
|
|
• Guangzhou new airport |
Lam et al. (2009LAM S, LOW J & TANG L. 2009. Operational efficiencies across Asia Pacific airports. Transportation Research Part E , 45: 654-665. Available at: https://doi.org/10.1016/j.tre.2008.11.003. https://doi.org/10.1016/j.tre.2008.11.00...
) |
11 major Asian Pacific airports, 2001-2005 |
DEA models: |
• Labor costs |
• Aircraft movements |
|
|
|
a) CCR |
• Capital costs |
• Number of passengers |
|
|
|
b) BCC |
• Soft cost input |
• Cargo |
|
|
|
c) SBM |
• Trade value |
|
|
|
|
d) Cost efficiency model |
|
|
|
|
|
e) Allocative efficiency model |
|
|
|
Tovar and Martín-Cejas (2009TOVAR B & MARTIN-CEJAS R. 2009. Are outsourcing and non-aeronautical revenues important drivers in the efficiency of Spanish airports? Journal of Air Transport Management , 15: 217-220. Available at: https://doi.org/10.1016/j.jairtraman.2008.09.009. https://doi.org/10.1016/j.jairtraman.200...
) |
26 Spanish airports, 1993-1999 |
SFA |
• Number of employees |
• Aircraft movements |
• Outsourcing |
|
|
|
• Land area |
• Average aircraft size |
• Non-aeronautical revenue |
|
|
|
• Number of gates |
• % of non-aeronautical revenue |
• Cargo |
Assaf (2010ASSAF A. 2010. Bootstrapped scale efficiency measures of UK airports. Journal of Air Transport Management , 16: 42-44. Available at: https://doi.org/10.1016/j.jairtraman.2009.03.001. https://doi.org/10.1016/j.jairtraman.200...
) |
27 UK airports, 2007 |
DEA and Bootstrapped DEA |
• Number of employees |
• Number of passengers |
|
|
|
|
• Airport area |
• Cargo |
|
|
|
|
• Number of runways |
• Aircraft movements |
|
Yang (2010YANG HH. 2010. Measuring the efficiencies of Asia-Pacific international airport - Parametric and non-parametric evidence. Computers & Industrial Engineering, 59: 697-702. Available at: https://doi.org/10.1016/j.cie.2010.07.023. https://doi.org/10.1016/j.cie.2010.07.02...
) |
12 international airports in Asia-Pacific region, 1998-2006 |
DEA and SFA (Cobb-Douglas production function) estimated using ML |
• Number of employees |
• Operating costs |
• Number of employees |
|
|
|
• Number of runways |
• Operating revenues |
• Number of runways |
|
|
|
|
|
• Operating costs |
|
|
|
|
|
• Time trend |
Tovar and Martín-Cejas (2010TOVAR B & MARTIN-CEJAS R. 2010. Technical Efficiency and Productivity Changes in Spanish Airports: A Parametric Distance Function Approach. Transportation Research Part E , 46: 249-60. Available at: https://doi.org/10.1016/j.tre.2009.08.007. https://doi.org/10.1016/j.tre.2009.08.00...
) |
26 Spanish airports, 1994-1999 |
SFA and MPI |
• Number of employees |
• Aircraft movements |
|
|
|
|
• Number of gates |
• Average aircraft size |
|
|
|
|
• Airport area |
• % of non-aeronautical revenue |
|
Lozano and Gutiérrez (2011aLOZANO S & GUTIÉRREZ E. 2011a. Efficiency analysis and target setting of Spanish airports. Networks & Spatial Economics, 11: 139-157. Available at: https://doi.org/10.1007/s11067-008-9096-1. https://doi.org/10.1007/s11067-008-9096-...
) |
41 Spanish airports, 2006 |
Non-radial DEA models: |
• Runway area |
• Number of passengers |
|
|
|
a) RMOTE |
• Apron capacity |
• Aircraft movements |
|
|
|
b) CRS |
• Passenger throughput capacity |
• Cargo |
|
|
|
c) SE |
• Number of baggage claim belts |
|
|
|
|
d) NIRS |
• Number of check-in counters |
|
|
|
|
Target-setting DEA model |
• Number of boarding gates |
|
|
Lozano and Gutiérrez (2011bLOZANO S & GUTIÉRREZ E. 2011b. Slacks-based measure of efficiency of airports with airplanes delays as undesirable outputs. Computers & Operations Research, 38: 131-139. Available at: https://doi.org/10.1016/j.cor.2010.04.007. https://doi.org/10.1016/j.cor.2010.04.00...
) |
39 Spanish airports, 2006-2007 |
SBM model and DDF |
• Runway area |
Desirable outputs
|
|
|
|
|
• Apron capacity |
• Aircraft movements |
|
|
|
|
• Number of baggage claim belts |
• Number of passengers |
|
|
|
|
• Number of check-in counters |
• Cargo |
|
|
|
|
• Number of boarding gates |
Undesirable outputs
|
|
|
|
|
|
• % of delayed flights |
|
|
|
|
|
• Average delay time |
|
Tsekeris (2011TSEKERIS T. 2011. Greek airports: Efficiency measurement and analysis of determinants. Journal of Air Transport Management , 17: 140-142. Available at: https://doi.org/10.1016/j.jairtraman.2010.06.002. https://doi.org/10.1016/j.jairtraman.201...
) |
39 Greek airports, 2007 |
Two-stage DEA model: |
• Number of runways |
• Number of passengers |
• Location (island or mainland) |
|
|
1) DEA models; |
• Terminal and airplane parking area |
• Cargo |
• Size of operations |
|
|
2) SWBT regression and Bootstrapped censored quantile regression |
• Operating hours |
• Aircraft movements |
• Operating characteristics |
Assaf and Gillet (2012ASSAF A & GILLEN D. 2012. Measuring the joint impact of governance form and economic regulation on airport efficiency. European Journal of Operational Research, 220: 187-198. Available at: https://doi.org/10.1016/j.ejor.2012.01.038. https://doi.org/10.1016/j.ejor.2012.01.0...
) |
73 International airports across Europe, North America and Australia, 2003-2008 |
Two-stage DEA model: |
• Number of employees |
• Number of passengers |
• Ownership structure |
|
|
1) DEA and SFA; |
• Other operating costs |
• Aircraft movements |
• Economic regulation |
|
|
2) SWBT regression |
• Number of runways |
• Non-aeronautical revenue |
|
|
|
|
• Passenger terminal area |
|
|
Assaf et al. (2012ASSAF A & GILLEN D. 2012. Measuring the joint impact of governance form and economic regulation on airport efficiency. European Journal of Operational Research, 220: 187-198. Available at: https://doi.org/10.1016/j.ejor.2012.01.038. https://doi.org/10.1016/j.ejor.2012.01.0...
) |
27 UK airports, 1998-2008 |
SFA |
• Labor costs |
• Number of passengers |
|
|
|
|
• Capital costs |
• Aircraft movements |
|
|
|
|
• Materials costs |
• Cargo |
|
|
|
|
|
• Non-aeronautical revenues |
|
Chow and Fung (2012CHOW C & FUNG M. 2012. Estimating indices of airport productivity in Greater China. Journal of Air Transport Management , 24: 12-17. Available at: https://doi.org/10.1016/j.jairtraman.2012.04.004. https://doi.org/10.1016/j.jairtraman.201...
) |
30 Chinese airports, 2000-2006 |
MPI and SFA |
• Terminal area |
• Number of passengers |
|
|
|
|
• Runway length |
• Cargo |
|
|
|
|
• Time trend |
• Aircraft movements |
|
Gitto and Mancuso (2012GITTO S & MANCUSO P. 2012. Bootstrapping the Malmquist indexes for Italian airports. International Journal of Production Economics, 135: 403-411. Available at: https://doi.org/10.1016/j.ijpe.2011.08.014. https://doi.org/10.1016/j.ijpe.2011.08.0...
) |
28 Italian airports, 2000-2006 |
Bootstrapped MPI |
• Labor costs |
• Aircraft movements |
|
|
|
|
• Capital costs |
• Number of passengers |
|
|
|
|
• Soft cost input |
• Cargo |
|
|
|
|
|
• Aeronautical revenues |
|
|
|
|
|
• Non-aeronautical revenues |
|
Perelman and Serebrisky (2012PERELMAN S & SEREBRISKY T. 2012. Measuring the technical efficiency of airports in Latin America. Utilities Policy, 22: 1-7. Available at: https://doi.org/10.1016/j.jup.2012.02.001. https://doi.org/10.1016/j.jup.2012.02.00...
) |
21 Latin America airports, 2000-2007 |
DEA models and MPI |
• Number of employees |
• Number of passengers |
|
|
|
|
• Number of runways |
• Cargo |
|
|
|
|
• Terminal area |
• Aircraft movements |
|
Scotti et al. (2012SCOTTI D, MALIGHETTI P, MARTINI G & VOLTA N. 2012. The impact of airport competition on technical efficiency: a stochastic frontier analysis applied to Italian airport. Journal of Air Transport Management , 22: 9-15. Available at: https://doi.org/10.1016/j.jairtraman.2012.01.003. https://doi.org/10.1016/j.jairtraman.201...
) |
38 Italian airports, 2005-2008 |
SFA |
• Runway capacity |
• Aircraft movements |
• Airport competition |
|
|
|
• Number of aircraft parking positions |
• Number of passengers |
• Ownership structure |
|
|
|
• Terminal area |
• Cargo |
• Degree of dominance of the main airline in an airport |
|
|
|
• Number of check-in counters |
|
|
|
|
|
• Number of baggage claim belts |
|
|
|
|
|
• Number of employees |
|
|
Voltes-Dorta and Pagliari (2012VOLTES-DORTA A & PAGLIARI R. 2012. The impact of recession on airports’ cost efficiency. Transport Policy , 24: 211-222. Available at: https://doi.org/10.1016/j.tranpol.2012.08.012. https://doi.org/10.1016/j.tranpol.2012.0...
) |
194 Worldwide airports, 2007-2009 |
SCF (SR) |
(i) Variable costs
|
• Domestic-Schengen passengers |
|
|
|
|
• Labor costs |
• International passengers |
|
|
|
|
• Materials costs |
• Aircraft movements |
|
|
|
|
(ii) Fixed factors
|
• Maximum take-off weight |
|
|
|
|
• Terminal area |
• Cargo |
|
|
|
|
• Runway length |
• Non-aeronautical revenue |
|
|
|
|
• Number of boarding gates |
|
|
|
|
|
• Number of check-in counters |
|
|
|
|
|
• Number of baggage claim belts |
|
|
|
|
|
(iii) Other
|
|
|
|
|
|
• Time trend |
|
|
|
|
|
• Number of employees |
|
|
|
|
|
• % of dominant carrier |
|
|
|
|
|
• % of airline traffic |
|
|
|
|
|
• % of charter traffic |
|
|
|
|
|
• % of low-cost traffic |
|
|
|
|
|
• Ownership structure |
|
|
Wanke (2012aWANKE P. 2012a. Capacity shortfall and efficiency determinants in Brazilian airports: Evidence from bootstrapped DEA estimates. Socio-Economic Planning Sciences, 46: 216-229. Available at: https://doi.org/10.1016/j.seps.2012.01.003. https://doi.org/10.1016/j.seps.2012.01.0...
) |
65 Brazilian airports, 2009 |
Bootstrapped DEA and FDH model |
• Aircraft movements |
• Number of passengers |
|
|
|
|
|
• Cargo |
|
|
|
|
|
• Mail |
|
Wanke (2012bWANKE P. 2012b. Efficiency of Brazil’s airports: Evidences from bootstrapped DEA and FDH estimates. Journal of Air Transport Management , 23: 47-53. Available at: https://doi.org/10.1016/j.jairtraman.2012.01.014. https://doi.org/10.1016/j.jairtraman.201...
) |
63 Brazilian airports, 2009 |
DEA, Bootstrapped DEA, PCA, and CA |
• Airport area |
• Aircraft movements |
(Cluster analysis) |
|
|
|
• Apron area |
• Number of passengers |
• Regular flights |
|
|
|
• Number of runways |
• Cargo |
• Location |
|
|
|
• Runway length |
|
• International airport |
|
|
|
• Number of aircrafts parking positions |
|
• Airport hub status |
|
|
|
• Terminal area |
|
|
|
|
|
• Number of vehicles parking lots |
|
|
Adler et al. (2013ADLER N, LIEBERT V & YAZHEMSKY E. 2013. Benchmarking airports from a managerial perspective. Omega, 41: 442-458. Available at: https://doi.org/10.1016/j.omega.2012.02.004. https://doi.org/10.1016/j.omega.2012.02....
) |
43 European airports (1998-2007) |
Two-stage network DEA model: |
• Staff costs |
• International passengers |
|
|
|
1) CA; |
• Other operating costs |
• Domestic passengers |
|
|
|
2) DEA models and PCA |
• Runway capacity |
• Cargo |
|
|
|
|
• Terminal capacity |
• Aircraft movements |
|
|
|
PCA |
• International passengers |
• Non-aeronautical revenues |
|
|
|
|
• Domestic passengers |
• Aeronautical revenues |
|
|
|
|
• Cargo |
|
|
|
|
|
• Aircraft movements |
|
|
Choo and Oum (2013CHOO Y & OUM T. 2013. Impacts of low cost carrier services on efficiency of the major U.S. airports. Journal of Air Transport Management , 33: 60-67. Available at: https://doi.org/10.1016/j.jairtraman.2013.06.010. https://doi.org/10.1016/j.jairtraman.201...
) |
63 US airports, 2007-2010 |
Two-stage model: |
• Number of employees |
• Number of passengers |
• % of LCC passenger |
|
|
1) VFP and SFA; 2) |
• Soft cost input |
• Aircraft movements |
• Airport output scale |
|
|
a) VFP regressions: |
|
• Non-aeronautical revenues |
• % of non-aeronautical revenue |
|
|
OLS, RE and FE; b) |
|
|
• % of international passengers |
|
|
SFA: Tobit regression |
|
|
• % of connecting passengers |
|
|
|
|
|
• % of cargo traffic |
|
|
|
|
|
• Runway utilization |
|
|
|
|
|
• Average aircraft size |
De Nicola et al. (2013NICOLA A, GITTO S & MANCUSO P. 2013. Airport quality and productivity changes: a Malmquist index. Transportation Research Part E , 58: 67-75. Available at: https://doi.org/10.1016/j.tre.2013.07.001. https://doi.org/10.1016/j.tre.2013.07.00...
) |
20 Italian-airports, 2006-2008 |
Two-stage model: |
• Labor costs |
• Work load units (WLU) |
Quality indicators
|
|
|
1) MPI; |
• Capital costs |
• Aircraft movements |
• % of delayed flights |
|
|
2) FA and Pooled-OLS regression |
• Soft cost input |
|
• Waiting time in queues at check-in |
|
|
|
|
|
• Baggage reclaim time |
|
|
|
|
|
• Mishandled bags |
Martini et al. (2013MARTINI G, MANELLO A & SCOTTI D. 2013. The influence of fleet mix, ownership and LCCs on airport’s technical / environmental efficiency. Transportation Research Part E , 50: 37-52. Available at: https://doi.org/10.1016/j.tre.2012.10.005. https://doi.org/10.1016/j.tre.2012.10.00...
) |
33 Italian-airports, 2005-2008 |
Two-stage DEA model: |
• Terminal area |
Desirable outputs
|
Aeronautical factors
|
|
|
1) DDF and DEA; |
• Runway length |
• Aircraft movements |
• Fleet mix |
|
|
2) Adapted SWBT regression |
• Number of baggage claim belts |
• Work load units (WLU) |
• Airport size |
|
|
|
• Number of aircraft parking positions |
Undesirable outputs
|
• Presence of low-cost-carriers |
|
|
|
|
• Total costs of local air pollution |
• Airline’s market power (degree of dominance of the main airline at each airport) |
|
|
|
|
• Noise levels |
Non-aeronautical factors
|
|
|
|
|
|
• Ownership structure |
Chang et al. (2013CHANG YC, YU MM & CHEN P. 2013. Evaluating the performance of Chinese airports. Journal of Air Transport Management , 31: 19-21. Available at: https://doi.org/10.1016/j.jairtraman.2012.11.002. https://doi.org/10.1016/j.jairtraman.201...
) |
41 Chinese-airports in 2008 |
Two-stage DEA model: |
• Business hour |
• Aircraft movements |
Airport service strategies
|
|
|
1) DEA-imposed quasi-fixed input constraints models; |
• Runway area |
• Number of passengers |
• Number of destinations |
|
|
2) SWBT regression |
• Terminal area |
• Mail/Cargo |
• Number of airlines served |
|
|
|
|
|
• Number of international routes |
|
|
|
|
|
Airport geographical characteristics
|
|
|
|
|
|
• City levels |
|
|
|
|
|
• Distance to Central Business District (CBD) |
|
|
|
|
|
• Flight area |
Ha et al. (2013HA HK, WAN Y, YOSHIDA Y & ZHANG A. 2013. Airline market structure and airport efficiency: evidence from major Northeast Asian airports. Journal of Air Transport Management , 33: 32-42. Available at: https://doi.org/10.1016/j.jairtraman.2013.06.008. https://doi.org/10.1016/j.jairtraman.201...
) |
11 Northeast Asia airports, 1994-2011 |
Two-stage DEA model: |
• Runway length |
• Work load units (WLU) |
Governance structure
|
|
|
1) DEA models and SFA; |
• Terminal size |
|
• Ownership transition |
|
|
2) Tobit regression |
• Number of employees |
|
• Corporatization |
|
|
|
|
|
• Localization |
|
|
|
|
|
• State shares |
|
|
|
|
|
Competition User impacts
|
|
|
|
|
|
• Customer power |
|
|
|
|
|
• Dominant airline market share |
|
|
|
|
|
• Airline concentration |
|
|
|
|
|
Airport characteristics
|
|
|
|
|
|
• Input variable |
|
|
|
|
|
• Output variable |
|
|
|
|
|
• Open sky |
|
|
|
|
|
• New airport |
|
|
|
|
|
• Runway structure |
|
|
|
|
|
Hinterland characteristics
|
|
|
|
|
|
• Per capita GPD |
|
|
|
|
|
• Population |
|
|
|
|
|
Traffic composition
|
|
|
|
|
|
• International traffic |
|
|
|
|
|
• Cargo traffic |
Martín et al. (2013MARTÍN J, RODRÍGUEZ-DÉNIZ H & VOLTES-DORTA A. 2013. Determinants of airport cost flexibility in a context of economic recession. Transportation Research Part E , 57: 70-84. Available at: https://doi.org/10.1016/j.tre.2013.01.007. https://doi.org/10.1016/j.tre.2013.01.00...
) |
194 Worldwide airports, 2007-2009 |
Two-stage model: |
(i) Variable costs
|
• Domestic-Schengen passengers |
Ownership structure Outsourcing
|
|
|
1) SCF-SR; |
• Labor costs |
• International passengers |
• % of materials costs |
|
|
2) Linear regression |
• Materials costs |
• Aircraft movements |
Diversification
|
|
|
|
(ii) Fixed factors
|
• Average landed maximum take-off weight |
• % of non-aeronautical revenue |
|
|
|
• Check-in desks |
• Cargo |
Airline dominance and traffic mix
|
|
|
|
• Number of boarding gates |
• Non-aeronautical revenues |
• Airline traffic shares |
|
|
|
• Warehouse area |
|
• Share of charter traffic |
|
|
|
• Terminal area |
|
• Share of low-cost traffic |
|
|
|
• Runway length |
|
Other factors
|
|
|
|
(iii) Other
|
|
• Airport size |
|
|
|
• Time trend |
|
• Variation in passenger traffic between 2007 and 2009 |
|
|
|
• Number of employees |
|
• Pre-crisis efficiency level |
|
|
|
• Airline traffic shares |
|
• Localization |
|
|
|
• Share of charter traffic |
|
|
|
|
|
• Share of low-cost traffic |
|
|
|
|
|
• Ownership structure |
|
|
Wanke (2013WANKE P. 2013. Physical infrastructure and flight consolidation efficiency drivers in Brazilian airports: a two-stage network-DEA approach. Journal of Air Transport Management , 31: 1-5. Available at: https://doi.org/10.1016/j.jairtraman.2012.09.001. https://doi.org/10.1016/j.jairtraman.201...
) |
63 Brazilian airports, 2009 |
Two-stage network-DEA model and CA |
• Terminal area |
• Aircraft movements |
(Cluster analysis) |
|
|
|
• Number of aircraft parking positions |
|
• Location |
|
|
|
• Number of runways |
|
• International airport |
|
|
|
• Aircraft movements |
• Number of passengers |
• Airport hub status |
|
|
|
|
• Cargo |
• Regular flights |
Adler and Liebert (2014ADLER N & LIEBERT V. 2014. Joint impact of competition, ownership form and economic regulation on airport performance and pricing. Transportation Research Part A, 64: 92-109. Available at: https://doi.org/10.1016/j.tra.2014.03.008. https://doi.org/10.1016/j.tra.2014.03.00...
) |
51 European and Australian airports, 1998-2007 |
Two-stage DEA model: |
• Staff costs |
• Number of passengers |
Airport characteristics and management strategies
|
|
|
1) DEA (WA-I); |
• Other operating costs |
• Cargo |
• % of non-aeronautical revenue |
|
|
2) Robust cluster and RE regression |
• Runway capacity |
• Aircraft movements |
• High levels of delay |
|
|
|
|
• Non-aeronautical revenues |
• Runway capacity utilization |
|
|
|
|
|
• Aircraft movements |
|
|
|
|
|
• Average aircraft size |
|
|
|
|
|
Ownership, regulation and competition
|
|
|
|
|
|
• Ownership structure |
|
|
|
|
|
• Economic regulation |
|
|
|
|
|
• Regional competition |
|
|
|
|
|
Time trend
|
|
|
|
|
|
• Year 1999 |
|
|
|
|
|
. |
|
|
|
|
|
. |
|
|
|
|
|
. |
|
|
|
|
|
• Year 2009 |
Ahn and Min (2014AHN YH & MIN H. 2014. Evaluating the multi-period operating efficiency of international airports using data envelopment analysis and the Malmquist productivity index. Journal of Air Transport Management, 39: 12-22. Available at: https://doi.org/10.1016/j.jairtraman.2014.03.005. https://doi.org/10.1016/j.jairtraman.201...
) |
23 major international airports, 2006-2011 |
DEA (CCR, BCC, SE, both input and output oriented) and MPI |
• Land area |
• Aircraft movements |
|
|
|
|
• Runway length |
• Number of passengers |
|
|
|
|
• Passenger terminal area |
• Cargo |
|
|
|
|
• Cargo terminal area |
|
|
Coto-Millán et al. (2014COTO-MILLÁN P, CASARES-HORTANÓN P, INGLADA V & AGÜEROS M. 2014. Small is beautiful? The impact of economic crisis, low cost carriers and size on efficiency in Spanish airports (2009-2011. Journal of Air Transport Management , 40: 34-41. Available at: https://doi.org/10.1016/j.jairtraman.2014.05.006. https://doi.org/10.1016/j.jairtraman.201...
) |
35 Spanish airports, 2009-2011 |
Two-stage DEA approach: |
• Labor costs |
• Number of passengers |
• Airport size |
|
|
1) DEA and MPI; |
• Capital costs |
• Cargo |
• Share of LCC (low-cost carriers) passengers |
|
|
2) Tobit regression |
• Other operating costs |
• Aircraft movements |
|
Li (2014LI SL. 2014. The cost allocation approach of airport service activities. Journal of Air Transport Management , 38: 48-53. Available at: https://doi.org/10.1016/j.jairtraman.2013.12.018. https://doi.org/10.1016/j.jairtraman.201...
) |
Magong airport, 1991-2000 |
Two-stage DEA model: |
• Number of employees |
• Airport Service Costs |
• Number of employees |
|
|
1) DEA; |
• Labor costs |
|
• Labor costs |
|
|
2) Regression analysis |
• Apron area |
|
• Apron area |
|
|
|
• Cargo terminal area |
|
• Cargo terminal area |
|
|
|
• Passenger terminal area |
|
• Passenger terminal area |
|
|
|
• Scheduled flight numbers |
|
• Scheduled flights numbers |
|
|
|
• Number of passengers |
|
|
|
|
|
• Arrival passenger numbers |
|
|
|
|
|
• Departure passenger numbers |
|
|
|
|
|
• Passenger capacity of peak hour |
|
|
|
|
|
• Cargo |
|
|
Merkert and Mangia (2014MERKERT R & MANGIA L. 2014. Efficiency of Italian and Norwegian airports: a matter of management or of the level of competition in remote regions? Transportation Research Part A , 62: 30-48. Available at: https://doi.org/10.1016/j.tra.2014.02.007. https://doi.org/10.1016/j.tra.2014.02.00...
) |
35 Italian and 46 Norwegian airports, 2007-2009 |
Two-stage DEA model: |
Technical inputs
|
• Aircraft movements |
• Classification of the airports |
|
|
1) Bootstrapped DEA; |
• Terminal area |
• Number of passengers |
• Military aviation |
|
|
2) Tobit regression |
• Apron area |
• Cargo |
• Italy or Norway |
|
|
|
• Number of runways |
|
• Population |
|
|
|
• Runway length |
|
• Profitability |
|
|
|
• Runway area |
|
• Competition |
|
|
|
• Airport area |
|
|
|
|
|
• Number of employees |
|
|
|
|
|
Financial inputs
|
|
|
|
|
|
• Operating costs |
|
|
|
|
|
• Staff costs |
|
|
|
|
|
• Material costs |
|
|
Scotti et al. (2014SCOTTI D, DRESNER M, MARTINI G & YU C. 2014. Incorporating negative externalities into productivity assessments of US airports. Transportation Research Part A , 62: 39-53. Available at: https://doi.org/10.1016/j.tra.2014.02.008. https://doi.org/10.1016/j.tra.2014.02.00...
) |
44 US airports, 2005-2009 |
Two-stage model: |
• Land area |
Desirable outputs
|
• Fleet mix |
|
|
1) DDF approach; |
• Terminal area |
• Number of passengers |
• Airport size |
|
|
2) Tobit Regression |
• Runway length |
• Aircraft movements |
• Percentage of night flights |
|
|
|
• Number of boarding gates |
• Cargo |
• Multiple airport system |
|
|
|
• Operating costs |
Undesirable outputs
|
• % of international passengers |
|
|
|
|
• Flight delays |
|
|
|
|
|
• Noise |
|
|
|
|
|
• Local air pollution |
|
Tsui et al. (2014aTSUI W, BALLI H, GILBEY A & GOW H. 2014a. Operational efficiency of Asia - Pacific airports. Journal of Air Transport Management , 40: 16-24. Available at: https://doi.org/10.1016/j.jairtraman.2014.05.003. https://doi.org/10.1016/j.jairtraman.201...
) |
11 New-Zealand airports, 2010-2012 |
Two-stage model: |
• Operating costs |
• Operating revenues |
• Population around the airport |
|
|
1) SBM model and MPI; |
• Number of runways |
• Number of passengers |
• Airport hub status |
|
|
2) SWBT regression |
|
• Aircraft movements |
• Airport operating hours |
|
|
|
|
|
• Airport ownership structure |
|
|
|
|
|
• Christchurch earthquakes |
|
|
|
|
|
• Rugby World Cup 2011 |
Tsui et al. (2014bTSUI W, GILBEY A & BALLI H. 2014b. Estimating airport efficiency of New Zealand airports. Journal of Air Transport Management , 35: 78-86. Available at: https://doi.org/10.1016/j.jairtraman.2013.11.011. https://doi.org/10.1016/j.jairtraman.201...
) |
21 Asia-Pacific airports, 2002-2011 |
Two-stage DEA approach: |
• Number of employees |
• Number of passengers |
• Time trend |
|
|
1) DEA; |
• Number of runways |
• Cargo |
• GPD per capita |
|
|
2) SWBT and RE |
• Runway length |
• Aircraft movements |
• % of international passengers |
|
|
Tobit regression |
• Passenger terminal area |
|
• Airport hub status |
|
|
|
|
|
• Airport ownership structure |
|
|
|
|
|
• Airport operating hours |
|
|
|
|
|
• Airport hinterland population |
|
|
|
|
|
• Alliance membership of dominant airline |
Lai et al. (2015LAI PL, POTTER A, BEYNON M & BERESFORD A. 2015. Evaluating the efficiency performance of airports using an integrated AHP/DEA-AR technique. Transportation Policy, 42: 75-85. Available at: https://doi.org/10.1016/j.tranpol.2015.04.008. https://doi.org/10.1016/j.tranpol.2015.0...
) |
24 major international airports, 2010 |
DEA and AHP/DEA-AR |
• Number of employees |
• Number of passengers |
|
|
|
|
• Number of gates |
• Cargo and mail |
|
|
|
|
• Number of runways |
• Aircraft movements |
|
|
|
|
• Terminal area |
• Aeronautical and non-aeronautical revenues |
|
|
|
|
• Runway length |
|
|
|
|
|
• Operating costs |
|
|
Merkert and Assaf (2015MERKERT R & ASSAF A. 2015. Using DEA models to jointly estimate service quality perception and profitability - Evidence from international airports. Transportation Research Part A , 75: 42-50. Available at: https://doi.org/10.1016/j.tra.2015.03.008. https://doi.org/10.1016/j.tra.2015.03.00...
) |
30 international airports, 2013 |
Two-stage DEA model: |
• Runway length |
Profitability
|
• % of non-aeronautical revenue |
|
|
1) DEA and bootstrapped DEA; |
• Terminal size |
• Profit margin |
• Ownership structure |
|
|
2) SWBT Regression |
• Number of employees |
Perceived service quality
|
• % of LCC airlines |
|
|
|
|
• Skytrax (ranking determined by industry body) |
• Asia-Pacific localization |
|
|
|
|
• Pax reviews (ranking determined by costumers) |
• % of international passengers |
|
|
|
|
Other common outputs
|
• Number of gates |
|
|
|
|
• Number of passengers |
|
|
|
|
|
• Cargo |
|
|
|
|
|
• Aircraft movements |
|
Zou et al. (2015ZOU B, KAFLE N, CHANG YT & PARK K. 2015. US airport financial reform and its implications for airport efficiency: An exploratory investigation. Journal of Air Transport Management , 47: 66-78. Available at: https://doi.org/10.1016/j.jairtraman.2015.05.002. https://doi.org/10.1016/j.jairtraman.201...
) |
42 US airports, 2009-2012 |
Two-stage DEA model: |
• Labor costs |
Desirable outputs
|
Funding sources used by US airports
|
|
|
1) DEA; |
• Capital costs |
• Number of passengers |
• Passenger facility charges |
|
|
2) RE regression |
• Material costs |
• Aircraft movements |
• Airport improvement program grants |
|
|
|
|
• Cargo |
Runway utilization factors
|
|
|
|
|
• Non-aeronautical revenue |
• Passengers per runway |
|
|
|
|
Undesirable output
|
• Cargoes per runway |
|
|
|
|
• Total flight arrival delay |
• Delay per runway |
|
|
|
|
|
Year
|
|
|
|
|
|
• 2010 |
|
|
|
|
|
• 2011 |
|
|
|
|
|
• 2012 |
|
|
|
|
|
Hub size
|
|
|
|
|
|
• Medium |
|
|
|
|
|
• Small |
|
|
|
|
|
• Non-hub |
See and Li (2015SEE K & LI F. 2015. Total factor productivity analysis of the UK airport industry: a HicksMoorsteen index method. Journal of Air Transport Management , 43: 1-10. Available at: https://doi.org/10.1016/j.jairtraman.2014.12.001. https://doi.org/10.1016/j.jairtraman.201...
) |
45 UK airports, 2001-2009 |
Two-stage model: 1) |
• Labor costs |
• Aeronautical revenue |
• Ownership structure |
|
|
Hicks-Moorsteen |
• Capital costs |
• Non-aeronautical revenue |
• Airport size (number of passengers) |
|
|
TFP index; |
• Other operating costs |
|
• First lag of TFP level |
|
|
2) FGLS and |
|
|
• Economic regulation |
|
|
continuous updated |
|
|
|
|
|
GMM regression |
|
|
|
|
|
|
|
|
• Weekly opening hours |
|
|
|
|
|
• Ownership structure |
|
|
|
|
|
• % of international traffic |
|
|
|
|
|
• Airport size (WLU) |
|
|
|
|
|
• Population density around the airport |
|
|
|
|
• Number of passengers |
• Level of seasonality |
|
|
Two-stage DEA model: |
• Staff costs |
• Aircraft movements |
• Joint military-civil airport |
|
|
1) DEA; |
• Other operating costs |
• Cargo |
• Spain or Turkey |
Ülkü (2015ULKÜ T. 2015. A comparative efficiency analysis of Spanish and Turkish airports. Journal of Air Transport Management , 46: 56-68. Available at: https://doi.org/10.1016/j.jairtraman.2015.03.014. https://doi.org/10.1016/j.jairtraman.201...
) |
41 Spanish and 32 Turkish airports, 2009-2011 |
2) OLS and Tobit regression |
• Runway area |
• Non-aeronautical revenues |
• Year (2009, 2010 or 2011) |
Örkcü et al. (2016ORKCÜ H, BALIKÇI C, DOGAN M & GENÇ A. 2016. An evaluation of the operational efficiency of turkish airports using data envelopment analysis and the Malmquist productivity index: 2009-2014 case. Transport Policy, 48: 92-104.) |
21 Turkey airports, 2009-2014 |
Two-stage DEA model: |
• Number of runways |
• Aircraft movements |
• Population around the airport |
|
|
1) DEA and Malmquist productivity index; |
• Runway units |
• Number of passengers |
• Airport hub status |
|
|
2) SWBT Regression |
• Passenger terminal area |
• Cargo |
• Airport operating hours |
|
|
|
|
|
• Joint military-civil airport |
|
|
|
|
|
• Percentage of international traffic |
Chaouk et al. (2020CHAOUK M, PAGLIARI R & MOXON. 2020. The impact of national macro-environment exogenous variables on airport efficiency. Journal of Air Transport Management , 82: 1-11. Available at: https://doi.org/10.1016/j.jairtraman.2019.101740. https://doi.org/10.1016/j.jairtraman.201...
) |
59 European and Asia-Pacific airports |
Two-stage DEA model: |
• Number of runways |
• Number of passengers |
• Air transport output |
|
|
1) DEA; |
• Number of gates |
• Aircraft movements |
• Institutions |
|
|
2) SWBTRegression |
• Terminal area |
• Cargo |
• Infrastructure |
|
|
|
• Number of employees |
• Non-aeronautical revenues |
• Macro-economic environment |
|
|
|
|
|
• Health and primary education |
|
|
|
|
|
• Higher education and training |
|
|
|
|
|
• Goods market efficiency |
|
|
|
|
|
• Labour market efficiency |
|
|
|
|
|
• Financial market development |
|
|
|
|
|
• Technological readiness |
|
|
|
|
|
• Market size |
|
|
|
|
|
• Business sophistication |
|
|
|
|
|
• Innovation |
|
|
|
|
|
• Safety and security |
|
|
|
|
|
• Corruption perception |
|
|
|
|
|
• Human development |
|
|
|
|
|
• Travel and tourism |
Huynh et al. (2020HUYNH T, KIM G & HA HK. 2020. Comparative analysis of efficiency for major Southeast Asia airports: A two-stage approach. Journal of Air Transport Management , 89: 1-9. Available at: https://doi.org/10.1016/j.jairtraman.2020.101898. https://doi.org/10.1016/j.jairtraman.202...
) |
9 major Southeast Asia Airports |
Two-stage DEA model: |
• Runway length |
• Passenger movement |
• Airport characteristics |
|
|
1) DEA; |
• Terminal area |
• Cargo |
• Governance structure |
|
|
2) Tobit Regression |
• Apron capacity |
• Aircraft movements |
• Competition |
|
|
|
|
|
• User impact |