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Biography for William Swan Retired Chief Economist for Boeing Commercial Aircraft 1996-2005 Previous to Boeing, worked at American Airlines in Operations.

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Presentation on theme: "Biography for William Swan Retired Chief Economist for Boeing Commercial Aircraft 1996-2005 Previous to Boeing, worked at American Airlines in Operations."— Presentation transcript:

1 Biography for William Swan Retired Chief Economist for Boeing Commercial Aircraft 1996-2005 Previous to Boeing, worked at American Airlines in Operations Research and Strategic Planning and United Airlines in Research and Development. Areas of work included Yield Management, Fleet Planning, Aircraft Routing, and Crew Scheduling. Also worked for Hull Trading, a major market maker in stock index options, and on the staff at MIT’s Flight Transportation Lab. Education: Master’s, Engineer’s Degree, and Ph. D. at MIT. Bachelor of Science in Aeronautical Engineering at Princeton. (bill.swan@cyberswans.com)bill.swan@cyberswans.com © Scott Adams

2 Airline Route Developments The Unexpected Bill Swan, Chief Economist, Boeing Marketing

3 Airline Route Networks Change Over Time Outline of Discussion I. The History of Route Developments Similar patterns from all regions of the world II. Why Do These Patterns Dominate? Several reasons, which is most important? III. Implications for Airline Strategies Historical trends could change The burden of proof lies on explaining why

4 I. Growth is Served by More Airplanes, Not Bigger Jet Schedules Show Decreasing Seat Counts Data from August schedules

5 Average Capacities Are Static Or Down Growth is similar for all regions

6 Forecasters in 1983 Had a Really Hard Time

7 Forecasters in 1990 Were Still Confused

8 What We Missed: New Routes

9 Air Travel Growth Has Been Met By Increased Frequencies and Non-Stops

10 Seat Count is -4% of World ASK Growth New Markets 41% Added Frequency 50% Longer Ranges 13% Smaller Airplanes - 4%

11 Growth Patterns the Same at Closer Detail Similar patterns all over the world

12 Big Routes Do Not Mean Big Airplanes All Airport Pairs under 5000km and over 1000 seats/day

13 Size in 1990 Not a Forecast for Size in 2000

14 Small Airplanes Not on New Routes

15 Top 12 Markets in 12 World Regions Big Airports Do Not Mean Big Airplanes

16 Fast Growth Does not Mean Big Airplanes

17 a.Deregulation causes one-time move to smaller airplanes. Competition drives airlines to more routes and frequencies. b.Economic savings of larger airplanes diminish with size For new airplanes of similar missions. c.Cost savings come from avoiding intermediate stops. Connecting passengers pay a time and cost penalty. d.Natural network development. Route networks move from skeletal to highly-connected. e.Travelers’ priorities change as economies get richer. Higher value for timely services, less emphasis on lowest cost. II. Why Does Growth Add Frequency? Many expect more demand to lead to bigger airplanes

18 d. Networks Develop from Skeletal to Connected High growth does not persist at initial gateway hubs  Early developments build loads to use larger airplanes: Larger airplanes at this state means middle-sized Result is a thin network – few links A focus on a few major hubs or gateways In Operations Research terms, a “minimum spanning tree”  Later developments bypass initial hubs: Bypass saves the costs of connections Bypass establishes secondary hubs New competing carriers bypass hubs dominated by incumbents Large markets peak early, then fade in importance  Third stage may be non-hubbed low-cost carriers : The largest flows can sustain service without connecting feed High frequencies create good connections without hub plan

19 Skeletal Networks Develop Links to Secondary Hubs Early Skeletal Network Later Development bypasses Early Hubs

20 Consolidation Theory: A Story that Sounds Good Large markets will need larger airplanes Industry consolidation increases this trend Alliances increase this trend This trend is happening

21 Fragmentation Theory Large markets peak early Bypass flying bleeds traffic off early markets –Some connecting travelers get nonstops –Others get competitive connections –Secondary airports divert local traffic New airlines attack large traffic flows Frequency competition continues

22 Route Development Data: Measures What Really Happens Compare top 100 markets from Aug 1993 –Top 100 by seat departures –Growth to Aug 2003 Data from published jet schedules

23 Largest Routes are Not Growing as bypass flying diverts traffic

24 Large Long Routes are Not Growing as bypass flying diverts traffic

25 Very Largest Long Routes are Not Growing as bypass flying diverts traffic

26 JFK Gateway Hub Stagnant for 30 Years

27 JFK Gateway Hub Airplane Size Is Declining

28 Competition Rising in Long-Haul Flows

29 Networks Develop Beyond Early Airports  Decline of Long-Haul Gateway Hubs 1990-2000:

30 Congestion Has Not Slowed Route Developments Congestion is not driving seats per departure up Seat Counts at Top 5 Airports Show Little Congestion

31 Congestion: Solutions From History Congestion has been a cost, not a constraint  Solutions favored by airports: 1.Redefining measurement of capacity movements 2.Technical improvements to raise capacity 3.Added runways 4.Building replacement airport  Solutions provided by the airline market: 5.Using un-congested times of day 6.By-passing congested gateways with new nonstop markets 7.Building frequencies and connections at secondary hubs 8.Using secondary airports at congested cities  Solutions beginning to be used: 9.Reducing smaller, propeller aircraft movements 10.Moving small, short-haul jet movements to larger aircraft

32 Congestion Affects Short & Small Flights

33 Chicago Airplane Sizes Do Not Show Congestion

34 Congestion is Not Driving 747 Shares UP

35  Plan for growth: 70%-100% of it in added frequencies  Plan for flexibility: Long-term commitments should not hang on one specific future  Plan to have more routes: Growth will include new nonstop markets  Plan to have more frequencies: Growth will include more flights at more times of day  Plan to face competition: Competitors will by-pass your hub  Plan to discuss history: Leaders may imagine growth patterns different from history Implications of History for Airlines Route strategy should respect history

36 Hubs: The Whys and Wherefores Just over half of trips are connecting Thousands of small connecting markets Early hubs are Gateways Later hubs bypass Gateways –One third of bypass loads are local—saving the connection –One third of bypass loads have saved one connect of two –One third of bypass loads are merely connecting over a new, competitive hub Growth is stimulated by service improvements –Bypass markets grow faster than average

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38 Half of Travel is in Connecting Markets

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40 Half the Trips are Connecting

41 Connecting Share of Loads Averages about 50%

42 Long-Haul Flights are from Hubs, and carry mostly connecting traffic

43 Hub Concepts Hub city should be a major regional center –Connect-only hubs have not succeeded –Early hubs are centers of regional commerce Early Gateway Hubs get Bypassed –Early International hubs form at coastlines –Interior hubs have regional cities on 2 sides Later hubs duplicate and compete with early hubs –Many of the same cities served –Which medium cities become hubs is arbitrary –Often better-run airport or airline determines success –Also the hub that starts first stays ahead

44 Three Kinds of Hubs International hubs driven by long-haul –Gateway cities –Many European hubs: CDG, LHR, AMS, FRA –Some evolving interior hubs, such as Chicago –Typically one bank of connections per day Regional hubs connecting smaller cities –Most US hubs, with at least 3 banks per day –Some European hubs, with 1 or 2 banks per day High-Density hubs without banking –Continuous connections from continuous arrivals and departures –American Airlines at Chicago and Dallas –Southwest at many of its focus cities

45 ORD ATL DFW DEN JFK LAX MIA SFO Regional and Gateway Hubs in US

46 ORD ATL DFW DEN JFK LAX MIA SFO Secondary Hubs in US STL SLC CVG PHX IAH MSP DTW PIT EWR SEA

47 Why Secondary Hubs? Airlines Hate Competition Avoid “head-to-head” whenever possible –Preferred carrier wins big Gets first choice of premium fare demand Gets full loads during off peaks Leaves 2 nd choice carrier low yield, high peaking –Result: Lots of new routes

48 Minot, N. D., USA, is served over one Hub

49 Minot Feeds to Minneapolis Hub MOT MSP

50 18:00 Bank Gives Minot 38 Destinations Inbound Bank Outbound Bank

51 Minot Connects to the World

52 Value Created by Hubs The idea in business is to Create Value Do things people want at a cost they will pay Hubs make valuable travel options Feeder city gets “anywhere” with one connection Feeder city can participate in trade and commerce Hubs are cost-effective Most destinations attract less than 10 pax/day Connecting loads use cost-effective airplanes

53 Hubs Build Loads First, then Frequency

54 Hubs Give Competitive Advantages Less peaking of demands, as variations in different markets average out Dominate feeder legs –Connect loads allow dominant frequency –Connect loads avoid small, expensive airplanes –Feeder cities can be “owned” Dominant airline will get 15% market share advantage Dominant airline can control sales channels Control of feeder cities makes airline attractive to alliances

55 Hubs Compete with Other Hubs Compete on quality of connection –Does the airport “work?” Short connecting times Reasonable walking distances Reliable baggage handling Few delayed flights Recovery from weather disruptions Later flights for when something goes wrong

56 Hubs Develop Pricing Mixes Higher fares in captive feeder markets Low discount fares in selected connecting markets to fill up empty seats –Low connecting fares compete against nonstops –Select low fare markets against competition –It pays to discount and fill Unless you discount your own high-fare markets

57 Hubs Win The dominant form of airline networks is hubs and connections This is because networks are “thin” –Meaning only a few, larger city pairs are nonstop As networks grow, secondary hubs develop –Competing with early hubs Hubs dominate because they create good travel –Save time over un-coordinated connections –Avoid the use of small, expensive airplane sizes

58 Industry Growth is Small Markets Virtuous Circle: –Better services: More Value Faster connections (add 15% demand for online) Fewer Stops (add 15% for each lost stop) Higher frequencies (add 15% for full-day schedule) –Lower Costs: Lower Prices Higher traffic volumes mean lower costs Competitive choices eliminate monopoly pricing New “small” markets get new services –Smaller towns, secondary city airports –Grow network from “below”

59 Why Hubs Work Revenue Benefits for Hubbing Spring 2005 Research Working Paper

60 Hubs Work Fare Rise Linearly with Distance Fares decline Linearly with Market Size Hubs serve Smaller Connecting Markets Hubs get premium revenues for connects Low Cost Carriers price Connections High –Tend to charge sum of local fares –Prices match Hub Carriers’ prices

61 Hub Cost Carriers’ (HCCs) Fare Trend is Linear with Distance O-D Markets Without Low-Cost (LCC) Competition

62 Low-Cost Carriers’ (LCCs) Fares are Linear With Distance

63 Hub Cost Carriers’ (HCCs) Fares Match Low-Cost (LCC) Competition

64 HCC Fares Decline with Market Size

65 LCC Fares Decline with Market Size

66 Fares Decline with Market Size

67 HCC Fares are Slightly Higher Than LCC Fares, adjusted for Market Size

68 The Real Difference is Hubs Serve Many more Small Markets US HCCs have “given up” local markets –Nonstop markets to hub city –Used to gain premium revenues –Now required to match LCCs –Revenues no longer cover union labor costs –HCCs have given up most traffic to LCCs Hubs serve connecting markets –Share of HCC revenues in small markets high –Share of LCC revenues in small markets low –Fares in small markets higher –More small market revenues mean higher HCC fares

69 Hubs Emphasize Smaller Markets

70 LCCs Share of Small Markets is 5% Share of Larger Nonstop Markets is 25%

71 HCCs Raise Average Fare By Emphasizing Connecting Markets Average Fare for All Passengers: $146 Average Fare for HCC Passengers: $166 Average Fare for LCC Passengers: $102

72 HCC Revenues are 1/3 Small Markets LCC Revenues are 10% Small Markets

73 Hubs Make Travel Possible Hubs exist to serve small markets For US domestic network –25% of revenues are from small markets –Over 30% of HCC revenues –Under 10% of LCC revenues International “small markets” add to this US has higher share nonstop than world

74 Economics of “Small Markets” Half of world-wide loads are connecting Small cities have small markets Small Markets pay more Value is there –Small cities have lower living costs Lower housing costs Higher air travel costs –Air Travel connects small cities to trade

75 Fares are Linear With Distance Average Fare = $153 + $0.043 * Dist –R-square = 0.13 –All US domestic markets with valid data –Excluding Hawaii –Mix of HCC and LCC markets –18,000 data points (Airport Pair O-Ds)

76 Fares are Higher for Small Markets (Includes both Small and LCC Presence Effects) For Pax < 10/day Fare = $117 + 0.046 * Distance 257 data points; R-square = 0.42 For 10/day < Pax < 100/day Fare = $106 + 0.037 * Distance 758 data points; R-square = 0.37 For Pax > 100/day Fare = $98 + 0.035 * Distance 671 data points; R-square = 0.34

77 HCC Fares are Higher for Small Markets For Pax < 10/day Fare = $127 + 0.042 * Distance R-square = 0.24 For 10/day < Pax < 100/day Fare = $110 + 0.036 * Distance R-square = 0.30 For Pax > 100/day Fare = $115 + 0.031 * Distance R-square = 0.22

78 LCC Fares are Higher for Small Markets For Pax < 10/day Fare = $111 + 0.0442 * Distance R-square = 0.33 For 10/day < Pax < 100/day Fare = $100 + 0.034 * Distance R-square = 0.31 For Pax > 100/day Fare = $83+ 0.032 * Distance R-square = 0.38

79 LCCs Price Close to HCCs in Very Small Markets Pax < 10/day HCC fare = $127 + 0.042 * Distance LCC fare = $111 + 0.044 * Distance

80 LCCs Price Connections Close to HCCs 10/day < Pax < 100/day HCC fare = $100 + 0.036 * Distance LCC fare = $100 + 0.034 * Distance

81 LCCs Fares In Nonstop Markets are Low HCC fares are a mix of all-HCC and with-LCC Markets Pax > 100/day HCC fare = $115 + 0.031 * Distance LCC fare = $83 + 0.032 * Distance

82 Full Model Includes 3-4 Variables Fare = $102 + 0.040* Distance (R2 = 0.36) Fare = $131 + 0.038* Distance – 6.4 * Ln(Pax) (R2 = 0.36) Fare = $153 + 0.037* Distance – 6.9 * Ln(Pax) - $23 if LCC presence (R2 = 0.48) Fare = $151 + 0.037* Distance – 7.0 * Ln(Pax) - $20 if LCC presence + $26 if HCC only (R2 = 0.48)

83 William Swan: Data Troll Story Teller Economist


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