US Airline Business Models 2006-2015

126 Pages·2017·2.07 MB·English

U.S. Airline Business Models 2006-2015:
Trends and Key Impacts
by
Alexander R. Bachwich
B.S., Mechanical Engineering
South Dakota School of Mines & Technology, 2015
Submitted to the Department of Civil and Environmental Engineering
in partial fulfillment of the requirements for the degree of
Master of Science in Transportation
at the
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
June 2017
(cid:13)c Massachusetts Institute of Technology 2017. All rights reserved.
Author..............................................................................................................
Department of Civil and Environmental Engineering
May 12, 2017
Certifiedby........................................................................................................
Peter P. Belobaba
Principal Research Scientist of Aeronautics and Astronautics
Thesis Supervisor
Acceptedby.......................................................................................................
Jesse Kroll
Professor of Civil and Environmental Engineering
Chair, Graduate Program Committee
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U.S. Airline Business Models 2006-2015: Trends and Key Impacts
by Alexander R. Bachwich
Submitted to the Department of Civil and Environmental Engineering on
May 12, 2017 in partial fulfillment of the requirements for the degree of
Master of Science in Transportation.
Abstract
This thesis focuses on the evolution of U.S. airline business models from 2006-
2015, and the impacts of these changes on other stakeholders in the U.S. air trans-
portationsystem. TheU.S.airlineindustryhasbeenaffectedbyincreasinglyvolatile
profit cycles since its deregulation in 1978. This volatility has led to major changes
in the industry, including cost convergence between traditional Low Cost Carriers
(LCCs)andNetworkLegacyCarriers(NLCs), multipleroundsofconsolidation, and
mostrecentlyaperiodof“CapacityDiscipline”wherehighfuelpricesandareduced
number of competitors led to slower-than-average capacity growth.
The combined effects of these changes led to the emergence of a new business
model: the“UltraLowCostCarrier”(ULCC).Inthisthesis,weconductananalysis
of ULCCs in the U.S. and demonstrate how these carriers’ business models, costs,
and effects on air transportation markets differ from those of the traditional LCCs.
We also explore how the network and fleet strategies of airlines using all three
business models have changed, highlighting key trends such as the decline in 50 seat
jet use by NLCs and the varying network strategies of ULCCs.
Inthesecondhalfofthethesis, weexaminehowthesechangesinairlinebusiness
models have affected other stakeholders in the U.S. transportation system. We
describe how average fares have changed from 2006-2015 in the top U.S. markets.
Then,usingeconometricmodels,weexaminetheeffectsofULCCandLCCpresence,
entry, and exit on base airfares, and how these effects have changed over time.
Wealsoexplorehowevolvingairlinebusinessmodelshaveimpactedcommunities
and their local airports. We find that seat capacity has grown at large hub airports
from 2006-2015, whereas smaller airports have all seen declines in service levels
to varying degrees. In particular, we examine how secondary airports in major
metro areas have been affected by changing LCC strategies, and how the smallest
airports have experienced significant declines in NLC service, yet some gains in
ULCC service. Finally, we discuss the public policy implications of these service
changes, and what policy options airports and communities have at both a local
and national level to improve their level of commercial air service.
Thesis Supervisor: Peter Belobaba
Title: Principal Research Scientist of Aeronautics and Astronautics
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Acknowledgements
First and foremost, I would like to thank my advisor Dr. Peter Belobaba.
From the very first time I met with him, two years before I even entered the
M.S.T. program, Peter has been willing to share his extensive knowledge of
and passion for the airline industry with me. His insight into the research
problems I faced, his continuous support of my research and academic goals,
and most of all his unfailing patience with me as a student and researcher have
all been invaluable during my time at MIT. I can’t thank him enough.
I would also like to thank Mike Wittman for being an amazing mentor,
colleague, and friend. Thanks for always listening to my thoughts about the
aviation industry and sharing your stories from the field. Without your col-
laboration on ULCC research, this thesis wouldn’t be possible.
This thesis was also made possible in part by all my colleagues at Hawaiian
Airlines, especially those on the Network Strategy team: Chris Keen, Angela
Tseng, and Ken Lieber. During my time in HNL this past summer, I learned
how airline analysis works in practice, and cemented my passion for this fasci-
nating and dynamic industry. I’d be remiss not to also thank William Swelbar,
who not only inspired me to begin work on ULCCs, but provided excellent ca-
reer and life advice, and connected me with the team at Hawaiian.
I’m extremely grateful for the personal friendship and professional support
of all my ICAT colleagues, including Adam, Ben, German, JP, Matt, Oren,
and Tamas. All of the airline geek banter exchanged at our lunches has been
one of my favorite aspects of the MIT experience.
I’d also like to thank all of my other MIT and Boston friends, including
Alex, Andrea B, Andrea S, Caralyn, Eli, Eytan, Henry, Jack, Joanna, John,
Katie, Kim, Nate, Nick, Sid, Taylor, and numerous others (including all my
TSG and Asymptones friends!) Without you, my experience at MIT would be
incomplete, and I certainly wouldn’t have been able to grow as a person and a
researcher nearly as much as I did. I’m equally grateful to my South Dakota
friends for years of support, including Patrick, Scott, Beth, Paul, and Reed.
Finally, I owe much gratitude to my wonderful family, especially my sister
Emily and my parents Dale and Vera. Thank you for supporting my love
of aviation throughout life, for always sharing your wisdom and love, and
especially for always trusting me to make our family travel plans.
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Contents
1 Introduction 15
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.2 Motivation for Research . . . . . . . . . . . . . . . . . . . . . 16
1.3 Outline of Thesis . . . . . . . . . . . . . . . . . . . . . . . . . 17
2 Evolution of U.S. Airline Business Models 21
2.1 A Cyclic Industry . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.2 Cost Convergence . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.3 Consolidation . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.4 Capacity Discipline . . . . . . . . . . . . . . . . . . . . . . . . 32
2.5 The Emerging ULCC . . . . . . . . . . . . . . . . . . . . . . . 34
2.5.1 Characteristics of the ULCC model . . . . . . . . . . . 37
3 Evolution of U.S. Airline Network and Fleet Structures 43
3.1 Background and Methods . . . . . . . . . . . . . . . . . . . . 43
3.1.1 Connectivity Model . . . . . . . . . . . . . . . . . . . . 45
3.2 Aggregate Fleet and Capacity Statistics . . . . . . . . . . . . . 47
3.3 Network Legacy Carriers (NLCs) . . . . . . . . . . . . . . . . 54
3.4 Hybrid Low Cost Carriers (LCCs) . . . . . . . . . . . . . . . . 61
3.5 Ultra Low Cost Carriers (ULCCs) . . . . . . . . . . . . . . . . 67
4 Key Impacts on Traffic and Fares 75
4.1 Capacity and Traffic Trends . . . . . . . . . . . . . . . . . . . 75
4.2 Unit Revenue and Fare Trends . . . . . . . . . . . . . . . . . . 78
4.3 Impact of the Emerging ULCC on Fares . . . . . . . . . . . . 83
4.3.1 Models . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
4.3.2 Data Sources and Processing . . . . . . . . . . . . . . . 85
4.3.3 Descriptive Statistics . . . . . . . . . . . . . . . . . . . 87
4.3.4 Results: Market Presence . . . . . . . . . . . . . . . . 89
4.3.5 Results: Entry/Exit . . . . . . . . . . . . . . . . . . . 91
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5 Key Impacts on Airports, Communities, and Public Policy 95
5.1 Overview of Seat Capacity Trends by
Airport Type . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
5.2 LCCs and Secondary Airports . . . . . . . . . . . . . . . . . . 100
5.3 Impacts on Smaller Airports . . . . . . . . . . . . . . . . . . . 105
5.3.1 NLCs and Decline of the 50 Seat Jet . . . . . . . . . . 105
5.3.2 ULCCs and Growth in Service to Small Airports . . . 108
6 Conclusions 113
6.1 Evolution of U.S. Airline Business Models . . . . . . . . . . . 113
6.2 Impacts on Fares and Communities . . . . . . . . . . . . . . . 116
6.3 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
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List of Figures
2.1 Classification of select major U.S. carriers in 2006 . . . . . . . 21
2.2 U.S. Airline Industry Net Income Since 1978 - Source: Airlines
for America . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.3 Cost per equivalent available seat mile, excl. transport-related
expenses, by carrier type, 2006-2015 . . . . . . . . . . . . . . . 25
2.4 Labor cost per equivalent seat mile by carrier type, 2000-2015 26
2.5 Year-over-yearchangeinavailabledomesticseatmilesbycarrier
type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.6 Types of partnerships between airlines organized by level of in-
tegration and profitability improvement . . . . . . . . . . . . . 29
2.7 Comparison between changes in GDP and changes in U.S. do-
mestic capacity (ASMs) 2006-2016 . . . . . . . . . . . . . . . . 33
2.8 Changes in U.S. domestic capacity by carrier type 2010-2015,
indexed to 2010 . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.9 Allegiant and Spirit traffic and capacity, in billions of RPMs
and ASMs, 2005-2015 . . . . . . . . . . . . . . . . . . . . . . . 36
2.10 System CASM ex transport-related expenses & fuel vs. mean
stage length (2014) . . . . . . . . . . . . . . . . . . . . . . . . 38
2.11 Average cost per enplaned passenger among select ULCCs and
LCCs, 3Q15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
2.12 Ticket vs. ancillary revenue per passenger segment for Spirit
and Allegiant, 2014 . . . . . . . . . . . . . . . . . . . . . . . . 40
2.13 Total system RASM ex transport-related revenues vs. mean
stage length (2014) . . . . . . . . . . . . . . . . . . . . . . . . 40
3.1 Key network and fleet questions with associated metrics . . . 43
3.2 Example schematic of Airport Connectivity Quality Index (1) 46
3.3 Example schematic of Airport Connectivity Quality Index (2) 46
3.4 Fleet size and composition of Major U.S. airlines, 2006 . . . . 48
3.5 Fleet size and composition of Major U.S. airlines, 2015 . . . . 49
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3.6 Averagedailynarrowbodyblockhourutilizationbyairlinetype,
2006-2015 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.7 Average domestic stage length by airline type, 2006-2015 . . . 52
3.8 Evolution of the combined fleet of NLCs by equipment type . 54
3.9 Average narrowbody block hour utilization of NLC-operated
flights, 2006-2015 . . . . . . . . . . . . . . . . . . . . . . . . . 55
3.10 Average stage length of NLC-marketed domestic flights, 2006-
2015 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.11 Seat departures at top 10 AA/US/HP stations by seats, 2006 . 57
3.12 Seat departures at top 10 DL/NW stations by seats, 2006 . . . 58
3.13 Seat departures at top 10 UA/CO stations by seats, 2006 . . . 59
3.14 Share of flights at major U.S. NLC hubs by mainline and re-
gional aircraft, 2006 vs. 2015 . . . . . . . . . . . . . . . . . . . 60
3.15 Percentage of total connectivity lost without NLCs by airport
hub type, 2015 . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.16 Evolution of LCC narrowbody fleets 2006-2015 by carrier . . . 62
3.17 Average narrowbody block hour utilization of LCC-operated
flights, 2006-2015 . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.18 AveragestagelengthofLCC-marketeddomesticflights,2006-2015 64
3.19 Seat departures at top 10 WN/FL stations by seats, 2006 . . . 64
3.20 Seat departures at top 10 B6 stations by seats, 2006 . . . . . . 65
3.21 Seat departures at top 10 AS stations by seats, 2006 . . . . . . 66
3.22 Percentage of total connectivity lost without LCCs by airport
hub type, 2015 . . . . . . . . . . . . . . . . . . . . . . . . . . 67
3.23 Evolution of ULCC narrowbody fleets 2006-2015 by carrier . . 67
3.24 Average narrowbody block hour utilization of ULCC-operated
flights, 2006-2015 . . . . . . . . . . . . . . . . . . . . . . . . . 68
3.25 Average stage length of ULCC-marketed domestic flights, 2006-
2015 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.26 Seat departures at top 10 F9 stations by seats, 2006 and 2015 70
3.27 Seat departures at top 10 G4 stations by seats, 2006 and 2015 71
3.28 Seat departures at top 10 NK stations by seats, 2006 and 2015 72
3.29 Number of destinations by carrier among ULCCs by daily fre-
quency of service, 2015 . . . . . . . . . . . . . . . . . . . . . . 73
3.30 Percentage of total connectivity lost without ULCCs by airport
hub type, 2015 . . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.1 PercentageoftotalU.S.domesticcapacitybycarriertype, 2006-
2015 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
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