Cologne Business School 21.03.2012 Airport capacity constraints & air travellers airport choice behaviour from global constraints to local effects Dr. Marc C. Gelhausen
Cumulative distribution of global ATMs on airports in 2008 100 90 Top 1,000 Airports (41%) handle about 52 m ATMs (95%) 80 Share of ATMs Worldwide (n = 55,043,014) 70 60 50 40 30 20 Top 100 Airports (4.1%) handle nearly 28 m ATMs (51%) Gini Coefficient = 0.8033 50% of the global air traffic is handled by less than 5% of 2,500 airports 10 0 0,04 2,5 4,96 7,42 9,89 12,3 14,8 17,3 19,7 22,2 24,7 27,1 29,6 32 34,5 37 39,4 41,9 44,3 46,8 49,3 51,7 54,2 56,6 59,1 61,6 64 66,5 68,9 71,4 73,9 76,3 78,8 81,3 83,7 86,2 88,6 91,1 93,6 96 98,5 Share of Airports Worldwide in % (n = 2,438) Reichmuth/Berster/Gelhausen (2011), CEAS Aeronautical Journal 2 (1-4), pp. 21 Slide 1
Why consider capacity constraints in airport choice? Limited airport infrastructure: Runways Terminals Night curfews Noise/emissions/political restrictions Affects available airport capacity to handle air passenger demand Slide 2
Hourly variation of flight movements at Frankfurt Airport Frankfurt Intl Airport: Peak Week 2008: 22-28 September 2008 (9,459 ATMs) 100 90 80 ATMs per Hour 70 60 50 40 30 20 10 0 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 Monday Tuesday Wednesday Thursday Friday Saturday Sunday Total Arrival Departure Source: OAG, DLR Slide 3
Development of air traffic volume 2000 2010 at LHR & FRA 125 120 120 117 Europe 116 Year 2000 = 100 115 110 111 110 111 111 113 Frankfurt 110 106 105 103 103 103 London Heathrow 102 100 2006 2007 2008 2009 2010 100 Europe Frankfurt London Heathrow Reichmuth/Berster/Gelhausen (2011), CEAS Aeronautical Journal 2 (1-4), pp. 21 Slide 4
Traffic ranking by hours of operation of the year 2008 at London Heathrow Airport; CUI = 0.85 Flight Movements at London Heathrow in 2008 100 90 355th Hour or 5% Peak Hour: 86 5060th or Average Hour: 73 (77% of Hours with ATMs/Hour > 5) 80 70 ATMs per Hour 60 50 40 30 20 10 Capacity Utilization Index: Introduced by DLR in the global analysis as the ratio of average day time demand to 5% peak hour demand, as a proxy of capacity in the absence of comparable capacities of airports world wide, for airports with high traffic volumes. 0 1 281 561 841 1,121 1,401 1,681 ATMs in 2008: 479,294 1,961 2,241 2,521 2,801 3,081 3,361 3,641 3,921 4,201 4,481 4,761 5,041 Hours of the Year 5,321 5,601 5,881 6,161 6,441 6,721 7,001 7,281 7,561 7,841 8,121 8,401 8,681 Source: OAG, DLR Slide 6 Slide 5
CUI analysis of airports worldwide Reichmuth/Berster/Gelhausen (2011), CEAS Aeronautical Journal 2 (1-4), pp. 21 Slide 7 Slide 6
General model structure of the capacity constraints forecast and hypothesis about interdependencies Attitude of Population towards Air Transport Government and social Values Welfare Level Age Structure Tourism... Location and Size of an Airport Noise Number of Flights Airport Category... Democracy Ministry of Environment... Intermodal Substitution Railway Km Country Size... Acceptance & speed to improve airport capacities +: Positive wrt Improvement -: Negative wrt Improvement Slide 7
Main questions in modelling capacity constraints How is the individual air passenger affected: Given his chosen destination... Does he change his departure airport ( he is crowded out)? or Does he pay a higher price at his favourite airport ( other passengers are crowded out)? or Does he cancel his air trip altogether ( he is crowded out)? Slide 8
Possible consequences of capacity constraints at airports Low Redistribution of demand among neighbouring airports Mixed strategy Travel disutility Restricted growth of local demand Airport capacity expansion High / No Airport capacity expandable? Yes Gelhausen (2009), Journal of Airport Management 3(4), pp. 366 Slide 9
Forecasting philosophy of a nested logit-model Traveller: Which alternative is the best for me? Evaluation of alternatives by means of utility Lack of observability, measurement errors, Forecaster: Which alternative is most likely the best for him? Choice probabilities Summing up over homogenous populations Market segment specific market shares of all alternatives Gelhausen (2008), Journal of Airport Management 2(4), pp. 355 Slide 10
Modelling capacity constraints in airport choice - conceptual Idea: The higher the loss in personal welfare (utility) from alternative to alternative, the higher the efforts to get a slot for the best alternative, e.g. by early booking or paying higher prices. Realisation: Increase so-called synthetic price to reduce airport attractiveness and thus redistribute excess demand until capacity constraints are met. Slide 11
Modelling capacity constraints in airport choice (I) 1 P i e e j V i V j P i σ A <σ B σ A σ B 0 0 V i max(v j ), i j Slide 12
Modelling capacity constraints in airport choice (II) 1 P i MS1 Reduction of P i depends on level of P i and MSi MS1 MS2 MS1 > MS2 MS2 0 0 P i e e j V sp i V sp j V b x x sp sp i k k,i i k V i max(v j ), i j Decrease of V i to meet capacity constraints Slide 13
Example: Airport choice in the Cologne region Gelhausen (2008), Journal of Airport Management 2(4), pp. 355 Slide 14
Willingness-to-pay by market segment Market segment 1 Euro equals... DOM Leisure 17.40 DOM Business 2.74 EUR Short stay 19.75 EUR Holiday 21.55 EUR Business 1.00 INT Leisure 5.39 INT Business 4.45 Slide 15
Total market share of DUS wrt capacity constraints 0.9 0.8 0.7 Market share per airport 0.6 0.5 0.4 0.3 FRA DUS CGN DTM HHN NRN 0.2 0.1 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Share of unsatisfied demand potential at DUS due to limited capacity Gelhausen (2009), Journal of Airport Management 3(4), pp. 366 Slide 16
Market shares by segment at DUS wrt capacity constraints Market share of DUS per market segment 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 DOM L - Berlin DOM B - Berlin EUR S - Barcelona EUR H - Barcelona EUR B - Barcelona INT L - Dallas INT B - Dallas 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Share of unsatisfied demand potential at DUS due to limited capacity Gelhausen (2009), Journal of Airport Management 3(4), pp. 366 Slide 17
Market shares by segment at STR wrt capacity constraints Gelhausen (2011), Journal of Air Transport Management 17, pp. 116 Slide 18
Effects of capacity deficit at DUS on market segments at CGN Market share of CGN per market segment 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 DOM L - Berlin DOM B - Berlin EUR S - Barcelona EUR H - Barcelona EUR B - Barcelona INT L - Dallas INT B - Dallas 0.2 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 Share of unsatisfied demand at DUS due to limited capacity Gelhausen (2009), Journal of Airport Management 3(4), pp. 366 Slide 19
Conclusions Capacity constraints at one airport affect the whole airport system Demand is distributed among more airports, benefiting remote airports However, spill-over effects may lead to further capacity-constrained airports Welfare of air travellers is reduced due to higher prices and crowding out effects Slide 20
Thank you for your attention Contact: Dr. Marc C. Gelhausen DLR - German Aerospace Center Institute of Air Transport and Airport Research Linder Höhe 51147 Cologne/Germany Marc.Gelhausen@dlr.de Tel: +49 2203 601 2463