Small regional airport sustainability: Lessons from benchmarking

Transcription

1 mall regioal airport sustaiability: Lessos from bechmarkig JATM, 2013 Nicole Adler, Tolga Ülkü ad Ekateria Yazhemsky Hebrew Uiversity of Jerusalem, Israel. Humboldt Uiversity of Berli, Germay. Hebrew Uiversity of Jerusalem, Israel. Weblik for the Paper: DOI:

2 Outlie Motivatio Methodologies Efficiecy Measuremet airport observatios variables Results DEA break-eve poit secod stage regressio Coclusios Page 2

3 Outlie Motivatio Methodologies Efficiecy Measuremet airport observatios variables Results DEA break-eve poit secod stage regressio Coclusios Page 3

4 Motivatio A efficiet airport provides importat ecoomic catalysts that eable the local ad regioal ecoomy to thrive ad improve the quality of life i the regio. (Oum et al., 2008) Page 4

5 Motivatio mall ad regioal airports frequetly suffer from: limited traffic fixed ifrastructure requiremets isufficiet reveues to cover their costs ubsidize loss-makig airports 1. Direct subsidies from local or federal govermet 2. Cross-subsidizatio Questio: how should such airports be structured, maaged ad fiacially supported i order to survive? Page 5

6 Regioal accessibility ad social developmet i Europe Page 6

7 Motivatio mall regioal airports should ot be uderestimated I Europe*, i 2007, 340 out of 491 airports < 1,5 millio PAX *The EU, Croatia, Turkey, Icelad, Norway ad witzerlad (ource: EUROTAT) Airport bechmarkig literature focuses o: Mai large hubs Coutry level Page 7

8 Aims of research to estimate relative efficiecies of regioal airports across Europe to aalyze efficiecy chages over time to examie reasos for poor performace to provide recommedatios to airport maagers, airport operators, civil aviatio authorities ad govermets Page 8

9 Outlie Motivatio Methodologies Efficiecy Measuremet airport observatios variables Results DEA break-eve poit secod stage regressio Coclusios Page 9

10 DEA model Max, s.t. 1 Q = 1 m s = 1 = 1 = 1 = 1 = 1 x x y y i r ND k ND p y = 1 io x ro io ro = ND ko ND po = m x io y L i= 1 r = 1 io ro io s U ro ro i = 1,..., m k = 1,..., l r = 1,..., p = 1,..., s q 0 = 1,..., 0 i = 1,..., m 0 r = 1,..., s BAM(Cooper et al., 2011) lack-based (additive) No-radial No-orieted No-discretioary variables Variable Returs to cale Page 10

11 DEA model Max, s.t. 1 Q = 1 m s = 1 = 1 = 1 = 1 = 1 x x y y i r ND k ND p y = 1 io x ro io ro = ND ko ND po = m x io y L i= 1 r = 1 io ro io s U ro ro i = 1,..., m k = 1,..., l r = 1,..., p = 1,..., s q 0 = 1,..., 0 i = 1,..., m 0 r = 1,..., s BAM(Cooper et al., 2011) DMU specific rages L = x x i i = 1,..., io io U = y y r = 1,..., ro r r 0 Ideal poit m { x, } x = mi = 1..., i i { y, } y = max = 1..., r r s Page 11

12 Determiatio of break-eve poit PAX Page 12

13 ecod stage regressios OL Regressio Trucated Regressio Robust results (Cesored) Tobit Regressio Page 13

14 Outlie Motivatio Methodologies Efficiecy Measuremet airport observatios variables Results DEA break-eve poit secod stage regressio Coclusios Page 14

15 Regioal ad small airport dataset 85 airports from 6 coutries: Austria, Frace, Germay, Italy, Norway ad UK (Avior) (icl. HIAL) Betwee 3,000-1,600,000 passegers aually Time Period: Page 15

16 Iputs: labor costs other operatig costs total ruway legth (ND) Iput ad output variables Moetary values: PPP ad iflatio adusted 16 Outputs: o-aeroautical reveues the umber of passegers served (ND) commercial air traffic movemets (ND) tos of cargo (ND) ND: No-discretioary

17 Outlie Motivatio Methodologies Efficiecy Measuremet airport observatios variables Results DEA break-eve poit secod stage regressio Coclusios Page 17

18 Percetage reductios / icreases at coutry ad airport group level 18 Coutry / Airport Group Number of Airports Percetage Reductio i taff Costs Percetage Reductio i Other Operatig Costs Percetage Reductio i Total Costs Percetage Icrease i No-aviatio Reveues Avior 41 31% 56% 43% 23% HIAL 9 58% 74% 65% 134% UK 2 37% 28% 32% - Group 52 36% 58% 46% 41% Austria 1 36% 12% 24% - Frace 22 47% 42% 45% 4% Germay 2 72% 41% 58% - Italy 5 43% 42% 43% 6% UK 3 59% 46% 52% 5% tadaloe 33 49% 41% 46% 4% Average 41% 51% 46% 27%

19 Break-eve poit Critical level of passeger throughput 200, , , ,233

20 ecod stage regressio 20

21 Outlie Motivatio Methodologies Efficiecy Measuremet airport observatios variables Results DEA Malmquist break-eve poit secod stage regressio Coclusios Page 21

22 Coclusios Reduce costs & icrease commercial reveues Potetial for some airports eve to achieve break-eve poit (144 out of 696 obs.) Operatioal costs icreasig i Europe over decade Need to further aalyze security maagemet Airport groups are less efficiet Idividual maagemet better utilizes resources accordig to regioal eeds ubsidies should be performace based Improve icetives for productive efficiecy Outsource all groud hadlig activities Need for cotiuous bechmarkig 22

23 Thak you for your attetio. Page 23