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Air Demand in a Dynamic Competitive Context with the Automobile (2019)

Chapter: Chapter 1 - Market Competition Between Airplane and Automobile Modes

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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
×
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
×
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
×
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
×
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
×
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
×
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
×
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
×
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
×
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
×
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
×
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Suggested Citation:"Chapter 1 - Market Competition Between Airplane and Automobile Modes." National Academies of Sciences, Engineering, and Medicine. 2019. Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25448.
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4 Over the past two decades, the role of the automobile in providing trips has risen, and the role of the airplane for shorter-distance trips has fallen considerably. Introduction The air travel system operates in competition with the automobile to a great extent. Most trips in the lower 48 states involve at least some level of competition between the automobile and airplane modes. Over the past two decades, the use of the automobile in providing trips has risen, and the use of air travel for shorter-distance trips has fallen consid- erably. Looking into the future, there is a wide variety of scenarios in which the role of the air transportation system in accommodating shorter trips could decrease dramatically. This may well occur both with the increase in the automobile share for the full long-distance trip and in the use of the automobile for access to less proximate airports—with a parallel decrease in the importance of the smaller airports providing feeder air services to hub air- ports. This report documents the finding that over the past two decades there has been a major increase in the use of the private automobile for trips more than 100 miles in distance, even during a period of relatively flat variation in the use of the automobile in the metro- politan context. This report explores the recent past and the present and speculates about the future role of the automobile in long-distance tripmaking. The implications for airport managers and all those involved in providing aviation services to the public are significant. Using market research methods never applied before to this subject, the research team for ACRP Project 03-40 has developed five separate illustrative futures for long-distance travel. They range from a scenario in which the automobile provides effortless services to its users to a scenario in which the public’s preference for air services increases to an extent not presently experienced. While one scenario assumes that the competitive position of the largest hub airports will increase significantly, two scenarios explore a combination of services and technology that would increase the relative importance of smaller airports, with more non-stop and direct flights between and among a wide variety of airport sizes and classifications. When compared with the base year of 1995 (the last year in which national long-distance travel survey data were collected on a systematic basis), the airlines are providing relatively fewer moderate-distance seat-miles, and more longer-distance seat-miles; the average distance of an air flight segment has grown by about 18%. While there have been instances of shorter- distance air trips moving to rail and bus, this occurs on a significant basis only on trips between New York and Boston and between New York and Washington D.C. Other than that, the decrease in the role of the airplane for making shorter-distance trips is paralleled by an increase in the role of the automobile. This pattern has significance for those charged with planning and managing the highway system just as it has significance for those operating smaller airports that do not host major transfer movements between flights. C H A P T E R 1 Market Competition Between Airplane and Automobile Modes

Market Competition Between Airplane and Automobile Modes 5 Report Structure This chapter is focused on the overall impact of various factors, both individually and assembled into larger scenarios, on the possible futures for travelers’ use of the automobile and/or air modes for long-distance trips. The purpose of this chapter is to establish an overall sense of scale for the range of possible futures that could reasonably be expected under a variety of assumptions. It is also important to examine how each of the impacting factors considered in this chapter separately influences long-distance travel behavior. Chapter 2 will document the history of the automobile and air modes, both separately and interacting together. Chapter 3 will examine the choice between these two modes, which is most significantly impacted by the factor of trip length in interaction with a set of independent variables. Chapter 4 focuses attention on the needs of smaller airports and explores the choice of the departure airport, which often involves market leakage from a local airport to a national one. Chapter 5 explores variation in attitudes and preferences toward the modes of the airplane and the automobile and the choice between them. Chapter 6 briefly reviews the methods used in the project, with reference to the technical appendix to this report, published as ACRP Web-Only Document 38 (available at http://www.trb.org/Main/Blurbs/179508.aspx), for those seeking more detail. The report concludes with a discussion of conclusions from the research in Chapter 7, including some early topics for further research. Highlights Highlights of the findings of this research (including the results of a survey conducted by the ACRP Project 03-40 research team in 2017) are the following: • Increased diversion of trips from air to automobile – The research has revealed a major shift in the use of automobiles for long-distance trip making, with particularly strong increases in market share for trips of less than 1,000 miles. – This shift is paralleled by a strong decrease in the supply of flights offered by the airlines for trips of less than 500 miles. – Project results suggest that the rate of growth of automobile use for long-distance trips is higher than the rate of growth of air travel, resulting in an increase in overall automobile mode share for long-distance trips since the base year. – Cost analysis suggests that airplane trips are cheaper per person than automobile trips for trips of 1,500 miles and more. – Although beyond the scope of this study, our research results suggest a significant shift in the makeup of the present generation of vehicle miles traveled (VMT), with trips of more than 100 miles making up as much as 29% of per capita VMT while metropolitan household travel seems generally flat. • Demographic differences – Data from the survey conducted showed that Millennials have a higher propensity than other age groups to choose air for shorter trips and a lower propensity to choose air for the longest trips. – The role of the automobile in the very long-distance (more than 1,500-mile) non-leisure trip needs to be examined further, as the automobile seems to play an important role in work-oriented multidestination tours which last several days. – Similarly, the need for the automobile for leisure trips with multiple children also explains why air is not chosen for some trips, even for trips of a very long distance. – The perceived need for a car at the trip destination is a powerful explanatory factor in the choice of mode, intertwined with both children and trip purpose. In the 2017 ACRP Project 03-40 survey, Millennials show a higher propensity than other age groups to choose air for shorter trips and a lower propensity to choose air for the longest trips.

6 Air Demand in a Dynamic Competitive Context with the Automobile • Attitudes and preferences – The majority of respondents to the survey conducted for this research, in all demographic subgroups, disagree with the concept that they would rather share a car than own it, with Millennials being somewhat more open to the idea. – Attitudinal modeling shows that the decision between the two long-distance modes is largely one between the price of the air trip and the level of stress and distaste associated with the long automobile trip. – Younger people are more likely to agree that driving for more than a day is unpleasant and that they want to use a smart device while traveling. Younger respondents express more concern about personal safety, uncertainty, and costs in the long-distance trip than older respondents. – Women are more likely than men are to dislike driving for more than a day, and those with more income are more likely to dislike it than those with less income are. – Basic demographic preferences about air and automobile modes should be incorporated into marketing programs to encourage use of smaller airports. • Airport choice – Over 60% of survey respondents agreed with the premise that they would “prefer to drive to a larger airport than take a feeder flight from a closer airport.” – Stated Preference exercises revealed that travelers would add an extra hour of driving to save one-half hour of flying: these observations reflect the basic fact that time for the full trip by car is more direct than a car + air trip. – Extensive national modeling reveals the scale of possible loss for smaller American airports with evolving technology for the automobile. – A local airport typically commands the largest share of their passenger catchment market when it offers the option of flying directly to destinations; when passengers must connect to their final destination, they are much less likely to use their local airport. • Leakage to more distant airports – The overall leakage is estimated to be between 15% and nearly 32%, which suggests that a substantial amount of travel is spent on the ground accessing these major hub airports. – This report documents significant increases in Interstate roadway traffic attributable to leakage of markets away from smaller airports of departure to larger airports. – Across the study’s airport pairs, the percentage of traffic attributed to travelers driving to a substitute airport is generally between 0.05% and 12%. In sparsely populated airport environs, the percentage is higher; in built-up urban areas, the percentage is lower. • Possible alterations in airline service patterns and aircraft technologies – The research team concluded that there is a significant market for direct flights between smaller airports and that evolving aircraft technology might contribute to lowering the operating costs of such flights. – Energy and labor costs could reshape the commuter airline landscape. Lower cost commuter flights could supplement the declining frequencies of regional carriers as they shift from 50- to 70-seat planes. – Evolving aircraft technology could allow non-stop services on thin short-haul routes where only connecting service is currently available. – One scenario was created to examine additional flights, and a second scenario was created with additional flights and new short-/medium-distance aircraft technology. In the analysis of new trips, lowered costs are not as strong an explanatory factor as additional service. Establishing a Sense of Scale ACRP Project 03-40 has created a large-scale analytical framework that can help transporta- tion practitioners to understand the dynamic roles played by highways and aviation facilities in facilitating long-distance trips taken by North Americans. More than 8.5 million trips Younger people are more likely to agree that driving for more than a day is unpleasant and that they would like to use a smart device while traveling. Over 60% of survey respondents agreed with the premise that they would “prefer to drive to a larger airport than take a feeder flight from a closer airport.” New aircraft technologies reviewed in this study could supplement the declining frequencies of regional carriers as they shift from 50- to 70-seat planes and support non-stop services on thin short-haul routes where only connecting service is currently available.

Market Competition Between Airplane and Automobile Modes 7 with trip lengths of more than 100 miles are commenced every day in the United States. This equals more than 3.1 billion long-distance trips made by Americans every year. Of these trips, approximately 15% occur via air and approximately 82% occur via private vehicle, as shown in Table 1-1. This research project explores the process by which air competes with the automobile for the billions of such trips made in the United States each year. For trips between 100 miles and 500 miles, the automobile dominates, with more than 90% of the trips. However, air travel dominates for trips between 1,000 and 2,000 miles—the auto- mobile share of these trips is 20%. Research undertaken for the FHWA in 2016 concluded that the automobile is down to 2%–3% of the market for the smaller number of city pairs with 2,000 miles between the cities. Table 1-2 documents nearly 300,000 city pairs in which the split between automobile and air travel will vary sharply, influenced by several factors, for trips between 500 and 1,999 miles. Note that in this report, an “air trip” is defined as a trip from an origin airport to a destination airport that may include multiple flight segments in cases where transfers are made. This is different from “enplanements,” which are individual flight segments. The Base Case for Analysis of Alternative Scenarios While most definitions of a long-distance trip include trips of more than 100 miles, the ACRP Project 03-40 research team found that the most realistic competition between airplane trips and automobile trips occurs at distances of more than 200 miles. Thus, this research has created a new national air/automobile modeling process that simulates some 1,834,000,000 annual MODE AVERAGE DAILY TRIPS MORE THAN 100MILES IN DISTANCE SHARE FOR EACH MODE Automobile 6,985,000 82% Bus 195,000 2% Train 82,000 1% Air 1,267,000 15% Total 8,528,000 100% Source: RSG 2015b. Table 1-1. Overall mode of long-distance trips in 2011. DISTANCE (MILES) AIRPLANE AUTOMOBILE NUMBER OF CITY PAIRS 100–499 5% 91% 81,000 500–999 37% 61% 146,000 1,000–1,999 79% 20% 150,000 2,000–2,999 97% 2% 56,000 3,000+ 97% 3% 7,000 Source: FHWA 2015. Table 1-2. Airplane and automobile mode share and number of city pairs by distance.

8 Air Demand in a Dynamic Competitive Context with the Automobile domestic trips in the lower 48 states with trip lengths of 200 miles and over. Most of these trips are made by automobile, with some 422,000,000 annual domestic air trips. The simulation process is presented in Chapter 6 of this report and is documented in more detail in a technical appendix to this report published as ACRP Web-Only Document 38. The modeling results in a simulation of long-distance tripmaking that utilizes some 70,000 analysis zones (Census tracts) for the calculation of airport access and egress trip segments. The model application leveraged the output of an existing national modeling framework for long-distance passenger travel, developed by RSG for the FHWA (RSG 2015b, Bradley et al. 2016). The mode/airport-choice models developed for ACRP Project 03-40 incorporate aspects of consumer preferences, attitudes, and values that are not in the current FHWA model. The new models have been applied using an extension of the FHWA model framework to develop scenarios to understand how different market developments are likely to affect demand for air and automobile modes. This process is designed to enhance practitioners’ understanding of the issues associated with automobile as an alternative mode to air travel. Table 1-3 shows the number of air trips modeled in the base case scenario, which resulted from calibration to recreate tripmaking conditions in 2011, a year for which FHWA has generated long-distance travel estimates for each major mode. Developing the Research Tools As part of the ACRP Project 03-40 research, a major national survey was conducted in 2017 in four metropolitan areas to collect information on long-distance travel behavior and attitudes as well as administer a series of Stated Preference experiments that deal with the choice between car and air. Survey Design and Questionnaire The objective of this research was to examine the choice to use car or air for long-distance travel in the United States. With this objective in mind, the sample for the survey was com- posed of travelers who had taken an automobile or air trip of more than 300 miles within the past year. Quota sampling, a technique that sets a minimum number of respondents for each DISTANCE (MILES) ANNUAL NUMBER OF AIRPLANE TRIPS AIRPLANE AS PERCENT OF AIRPLANE +AUTOMOBILE 200–400 45,934,525 5% 400–600 55,789,218 17% 600–800 54,936,454 28% 800–1,000 49,634,860 41% 1,000–1,200 50,415,726 56% 1,200–1,400 39,257,989 65% 1,400–1,600 20,678,987 72% 1,600–3,200 105,219,047 84% Total 421,866,806 23% Source: Project Scenario Testing Model Table 1-3. Number of air trips and mode share for the base case.

Market Competition Between Airplane and Automobile Modes 9 respective category, was used to establish a diverse sample of respondents. The resulting sample size was 4,223. A questionnaire was designed to collect information on present mode choice behavior and the sociodemographic characteristics of each survey respondent. The survey instrument also collected basic information concerning attitudes affecting the propensity to choose travel by car or airplane for trips of 300 miles or more. Three Kinds of Models The project developed three separate kinds of mathematical models to aid in understanding the choice between the automobile and airplane modes for long-distance trips. Attitudes were explored in the first model: the Structural Equations Model (SEM). The SEM was designed to emphasize the importance of “soft” variables, including values, preferences, and attitudes in the selection of modes for long-distance trips. The SEM, by design, does not emphasize trip-based times and costs. The second kind of model, for which there were two variations, was designed to emphasize the immediately relevant factors of travel time and cost, in addition to other traditional variables such as travel party size. The two variations on this kind of model are called the Multinomial Logit and Mixed Multinomial Logit Choice Models. The third model is designed to integrate all relevant factors into the prediction of (in this case) long-distance travel mode. The model takes the form of an Advanced Hybrid Choice Model, which is also described as an Integrated Choice Latent Variable Model. It was created to support the development of a nationwide travel demand modeling process, referred to here as the Scenario Testing Model. The models developed allowed the research team to explore five separate market futures that would influence the choice between air and automobile. The Five Overarching Scenarios The survey and model development process supported the development of the project’s Scenario Testing Model. In the application of this model, five overarching scenarios for the future of long-distance travel were created in addition to the base case simulation. They are the following: • Scenario 1: Automobile dominates the future. If, somehow, automobile trips become less stressful and somewhat less costly; long, multiday trips become less onerous; and riders could stay connected on automobile trips (as with automated vehicles); then, air demand would decrease by about 16%. • Scenario 2: An optimistic scenario for smaller airports. If the number of flights to non-hub airports increased, the number of direct flights from smaller airports increased, stress at larger airports increased, tickets became cheaper, the stress of driving increased, the relative cost of driving increased, and future generations are somewhat less automobile oriented, then air demand would increase by about 10%. • Scenario 3: Smaller airports benefit from new cheaper short-distance planes. This scenario is the same as Scenario 2, except only short-distance flights would have lower ticket prices; there would be more short-distance, direct flights; and there would be less stress at smaller airports. In this scenario, air demand would increase by about 14%. • Scenario 4: An aggressive scenario for hub airports. Hub airports lower their parking charges, decrease the amount of stress, and increase the frequency of direct flights. In this scenario, air demand would increase by 14%. The project created five overarching scenarios for the future of long- distance travel and, specifically, the market contest between aviation and the automobile.

10 Air Demand in a Dynamic Competitive Context with the Automobile • Scenario 5: Air dominates the future. Congestion on the highways means longer travel times for automobile trips. The price of gas goes up. As youth grow older, their concerns about long-distance highway trips remain, and preference for private vehicle ownership goes down. The price of air trips goes down and flight frequencies increase. In this scenario, air demand would increase by about 16%. Although the magnitude of the overall effects of the five scenarios are similar, they have very different effects when analyzed along dimensions such as trip distance, airport size, travel purpose, and region of the country. Such differences are highlighted in the following section. Understanding the Five Possible Futures for Long-Distance Travel The five scenarios reflect a wide range of possible roles for airplanes and automobiles in the long-distance trips of the future. When examined in terms of futures designed purposefully to illustrate possible trends (rather than to predict any specific future), the impact of possible changes in the technology of the automobile jumps from the data. One of the five future scenarios was designed to explore the possible impacts of autonomous vehicles on the selection of mode for long-distance trips. The Sheer Range of Futures Examined The forecast range of possible outcomes for air demand is graphed in Figure 1-1, which compares the most automobile-oriented scenario (Scenario 1: Automobile dominates the future) with the four scenarios that are more optimistic for the airport community. For the national system as a whole, the impacts range from a decrease in air travel of 16% to an increase of 16%. Looking at the results as a whole, the smallest airports would suffer most from a dramatic change in automobile technology in Scenario 1 (−34%) and would benefit most from the hypothesized new services to smaller airports in Scenario 3 (+55%). As noted, the scenarios are purposefully designed to examine extreme changes in input assumptions and should not be considered travel forecasts. The smallest airports would suffer most from a dramatic change in automobile technology and benefit most from the hypothesized new services to smaller airports. -16% 10% 14% 14% 16% Scenario 1. Auto dominates the future Scenario 2. Optimistic for smaller airports Scenario 3. New short distance planes Scenario 4. Aggressive for the hub airports Scenario 5. Air dominates the future Ch an ge in A ir T ri ps Change in National Air Trips Figure 1-1. Change in air trips in the national system in five scenarios.

Market Competition Between Airplane and Automobile Modes 11 Understanding the Implications of a Very Automobile-Oriented Future (Scenario 1) As shown in Figure 1-2, a hypothetical scenario with autonomous vehicles shows impacts on air travel that vary by the length of the long-distance trip. While the average impact on the number of air trips is a decrease of about 16%, there is considerable variation of impact by trip length. For example, a decrease of 24% is shown for trips between 600 and 800 miles in length. For the model inputs and simulation results, airports were segmented along four size classes according to their ranking in terms of the number of origin-destination (O-D) air passenger trips taken in 2011: • Large hubs: The 30 largest airports • Smaller hubs: Airports ranked 31 to 60 • Smaller airports: Airports ranked 61 to 120 • Regional (smallest) airports: Airports ranked lower than 120th In the most pessimistic future for air travel, Scenario 1 shows that decreases in air passengers at the 30 largest airports might be as small as 12%, while decreases at the smallest airports might be as high as 34%, as shown in Figure 1-3. Both Figures 1-1 and 1-2 show how the relative desirability of the automobile mode varies widely by trip distance. Repeatedly in this research, the air travel market showed vulnerability and instability for shorter-distance trips, but not for the longest distance trips. The choice of whether to travel by car or airplane is overwhelmingly determined by trip distance, which emerges as more important than factors such as age, income, education level, or details of services provided. Figure 1-4 shows the U.S. Census divisions. Based on Figure 1-4, Figure 1-5 shows that different parts of the nation would react differently to a massive change in the technology of the private automobile. While the Pacific, Mountain, and New England divisions show the smallest decreases in percentage of air trips, the East South Central and East North Central divisions would be most vulnerable to change in mode away from aviation. One reason for such differences is the range of trip distances seen in different divisions—people in the Mountain 200- 400 400- 600 600- 800 800- 1000 1000- 1200 1200- 1400 1400- 1600 1600- 3200 -17.7% -15.0% -24.1% -22.3% -18.4% -15.8% -12.8% -8.4% -25.0% -20.0% -15.0% -10.0% -5.0% 0.0% % D ec re as e in A ir T ri ps Trip Distance (miles) Decrease in Air Trips from Autonomous Vehicles Figure 1-2. Impacts of Scenario 1 on air trips by length of long-distance trip. In Scenario 1, decreases in air passengers at the 30 largest airports might be as small as 12%, while decreases at the smallest airports might be as high as 34%.

12 Air Demand in a Dynamic Competitive Context with the Automobile Smallest Airports Smaller Larger Largest 30 Airports -34% -25% -17% -12% -40% -35% -30% -25% -20% -15% -10% -5% 0% % C ha ng e in A ir P as se ng er s Airport Size Impact of Autonomous Vehicles on Air Demand, by Airport Size Figure 1-3. Impacts of Scenario 1 on air trips by airport size. Source: census.gov Figure 1-4. U.S. Census divisions. ES Cent EN Cent WN Cent WS Cent Mid Atl Sou Atl New Eng Mountn Pacific Decrease -25% -20% -19% -18% -17% -17% -15% -12% -9% -25% -20% -19% -18% -17% -17% -15% -12% -9% % D ec re as e in A ir T ri ps U.S. Census Divisions Decrease in Air Demand in Autonomous Vehicle Scenario, by U.S. Census Division Figure 1-5. Impacts of Scenario 1 on air trips by U.S. Census division.

Market Competition Between Airplane and Automobile Modes 13 and Pacific divisions tend to make more trips in the longer-distance ranges where the car is a less competitive option. The results presented show that Scenario 1 will affect airports of different sizes very differ- ently. The results support the conclusion that the shortest flights and the smallest airports experience the most volatility and uncertainty in their futures. By way of example, Table 1-4 allows the direct comparison of the two extreme conditions (Scenario 1 and Scenario 3) for the short-distance air trip (between 200 and 400 miles), resulting a range between 18% decline and 25% growth associated with the two extreme futures. The same comparison of futures is presented by size of airport in Table 1-5 where, again, the smallest airports are associated with the widest variation of possible futures; in this case, varying from a future with a loss of more than 30%, to a future with a gain of more than 50%. More Optimistic Scenarios for Airports Although the ACRP Project 03-40 research team concluded that the smallest airports are most vulnerable to loss of demand for air trips from changes in automobile technology, the team also examined what factors might come together to improve the fate of smaller airports in PERCENT CHANGE IN AIR DEMAND VS. BASE CASE TRIP DISTANCE (MILES) SCENARIO 1: AUTOMOBILE DOMINATES THE FUTURE SCENARIO 2: OPTIMISTIC FOR SMALLER AIRPORTS SCENARIO 3: NEW SHORT- DISTANCE PLANES SCENARIO 4: AGGRESSIVE FOR THE HUB AIRPORTS SCENARIO 5: AIR DOMINATES THE FUTURE 200–400 −17.7% 15.2% 25.4% 42.4% 34.0% 400–600 −15.0% 12.6% 19.7% 25.7% 24.6% 600–800 −24.1% 12.1% 17.7% 16.8% 19.3% 800–1,000 −22.3% 13.1% 18.6% 11.9% 15.9% 1,000–1,200 −18.4% 10.6% 14.7% 7.9% 12.4% 1,200–1,400 −15.8% 9.4% 12.7% 5.8% 10.4% 1,400–1,600 −12.8% 7.6% 9.9% 4.1% 8.3% 1,600–3,200 −8.4% 4.0% 4.5% 2.2% 5.6% Total −16.1% 9.9% 14.4% 13.8% 15.6% Table 1-4. Percent change in air demand vs. base scenario by trip distance band (Scenarios 1–5). PERCENT CHANGE IN AIR DEMAND VS. BASE CASE AIRPORT SIZE SCENARIO 1: AUTOMOBILE DOMINATES THE FUTURE SCENARIO 2: OPTIMISTIC FOR SMALLER AIRPORTS SCENARIO 3: NEW SHORT- DISTANCE PLANES SCENARIO 4: AGGRESSIVE FOR THE HUB AIRPORTS SCENARIO 5: AIR DOMINATES THE FUTURE Largest 30 Hubs −12.2% 5.2% 8.6% 18.4% 14.2% Larger −16.8% 6.8% 10.1% 13.2% 15.4% Smaller −25.0% 25.9% 31.0% −2.7% 13.5% Smallest Airports −34.3% 35.8% 54.7% 4.4% 35.6% Table 1-5. Percent change in air demand vs. base scenario by airport size (Scenarios 1–5).

14 Air Demand in a Dynamic Competitive Context with the Automobile Scenarios 2 and 3. Figure 1-6 shows the percent increase in air trips by trip length for Scenario 3, which includes optimistic assumptions about how new shorter-distance aircraft technology might lower operating costs (and thus ticket prices) and the number of short-distance, direct flights that would be operated by the airlines. Air trips of less than 600 miles are shown to increase by 20% to 25% in the scenario that includes new smaller aircraft technology. Comparing the Five Scenarios Table 1-4 shows the percent change in air tripmaking versus the base case, by trip distance, for all five scenarios. Table 1-6 shows the impact of the five scenarios by U.S. Census division. In Table 1-4, it perhaps seems counter-intuitive that Scenario 4 gains the most air trips in the shorter-distance classes. The explanation is that the hub airports already dominate the market for longer air trips, but in this scenario, lower prices, lower stress, and more direct flights make using hub Air trips of less than 600 miles are shown to increase by 20% to 25% in the scenario that includes new smaller aircraft technology. PERCENT OF CHANGE IN AIR DEMAND U.S. CENSUS DIVISION SCENARIO 1: AUTOMOBILE DOMINATES THE FUTURE SCENARIO 2: OPTIMISTIC FOR SMALLER AIRPORTS SCENARIO 3: NEW SHORT-DISTANCE PLANES SCENARIO 4: AGGRESSIVE FOR THE HUB AIRPORTS SCENARIO 5: AIR DOMINATES THE FUTURE New England −12.8% 6.9% 10.7% 17.9% 14.7% Mid-Atlantic −17.0% 9.1% 13.7% 22.0% 20.2% East North Central −18.6% 10.8% 16.2% 17.2% 18.3% West North Central −21.2% 13.3% 18.8% 11.8% 18.4% South Atlantic −19.0% 10.7% 15.3% 15.3% 17.4% East South Central −26.9% 19.8% 27.6% 9.8% 20.4% West South Central −17.6% 11.3% 16.1% 11.3% 16.3% Mountain −13.1% 8.0% 10.5% 7.2% 9.6% Pacific −6.7% 6.1% 9.6% 10.3% 9.2% Table 1-6. Percent change in air demand by U.S. Census division (Scenarios 1–5). 25% 20% 18% 19% 15% 13% 10% 5% 200-400 400-600 600-800 800-1000 1000-1200 1200-1400 1400-1600 1600-3200 % In cr ea se in A ir T ri ps Trip Distance (miles) Optimistic Future for Smaller Airport with New Aircraft Technology, by Distance Figure 1-6. Percent increase in air trips for smaller airports by distance (Scenario 3).

Market Competition Between Airplane and Automobile Modes 15 airports more competitive with using an automobile for the shorter trips as well. Conversely, a reason that improving service from small airports increases air demand in the longer-distance ranges is that more attractive flights from these airports can also be used to reach hub transfer airports for long air trips. Implications for Airports by Size The extensive modeling of possible futures for the relationship between the automobile system and the air system has revealed a very clear and consistent pattern of travel behavior: it is the smaller airports, and more generally the shorter trip segments, that are most intensively intertwined with the future of automobile travel. This report will examine the impact of various scenarios and futures on smaller airports in two ways. First, the overall change in boardings will be presented. Second, the impacts of changes in the selection of the first airport of departure (the airport used from the home end of a round-trip journey) will be analyzed separately. Chapter 4 will further explore the concept of leakage from closer, smaller airports to larger airports that are farther away—usually by substituting an automobile trip for the first leg of a total trip. To explore the choice of traveling from the closer airport or from the larger airport, the research team modeled several geographic areas covered in the survey conducted for this research that had a dominant airport and smaller airports at various distances from it. As an example, Table 1-7 shows how each of the five scenarios might influence the dominant airport in Boston, [Boston Logan International Airport (BOS)] and the two smaller (subdominant) national airports, T. F. Green Airport (PVD) in Providence, Rhode Island, and Manchester- Boston Regional Airport (MHT) in Manchester, New Hampshire. MHT is revealed as very susceptible to supply side changes in BOS, reflected in Scenario 4, while PVD is less so. MHT suffers a 26% loss under the Scenario 4 assumptions, with PVD declining by only 4%. This same pattern of high volatility to supply side assumptions finds MHT far more likely to benefit from a national pattern of new short-distance flights than PVD. Table 1-8 examines two major airports in the North Carolina air market, one serving Charlotte, Charlotte Douglas International Airport (CLT), and one serving Raleigh/Durham, Raleigh Durham International Airport (RDU), and a smaller airport serving Greensboro, commonly known as the Piedmont Triad International Airport (GSO). Table 1-8 shows that at GSO the market would evidently benefit from a national pattern of increased numbers of short-distance, and (possibly) cheaper flight segments (Scenario 3), with around a 60% increase Smaller airports and shorter trip segments are most intensively intertwined with the future of automobile travel. PERCENT CHANGE IN AIR DEMAND AIRPORT (BY CODE) SCENARIO 1: AUTOMOBILE DOMINATES THE FUTURE SCENARIO 2: OPTIMISTIC FOR SMALLER AIRPORTS SCENARIO 3: NEW SHORT-DISTANCE PLANES SCENARIO 4: AGGRESSIVE FOR THE HUB AIRPORTS SCENARIO 5: AIR DOMINATES THE FUTURE BOS −12% 3% 7% 23% 14% PVD −14% 5% 10% −4% 16% MHT −16% 24% 27% −26% −7% BOS, PVD, & MHT −12% 5% 8% 18% 13% Table 1-7. Percent change in air demand in a region with a dominant airport and subdominant ones (Scenarios 1–5).

16 Air Demand in a Dynamic Competitive Context with the Automobile in trips commencing here. The volatility factor is also reflected in the finding that loss of air demand in Scenario 1 would be much more severe for GSO than for a dominant airport like CLT. The changes in enplanements presented in Table 1-8 are influenced by two kinds of travel behavior change: (1) the replacement of a full air trip (involving all segments) by a car trip and (2) an increase in use of a car for the first segment of a trip that will continue by airplane. Changes in the selection of the airport of origin are addressed extensively in Chapter 4. Change from Major Component Factors Used in Scenarios As noted earlier, each of the five overarching scenarios was assembled by inclusion of key input variables to describe a future assumption. At the same time, the input factors were examined separately. A range of initial component factors was run to gauge the sensitivity of the model to various types of changes in the input assumptions. The base scenario was run along with several input variables, some of which are summarized here: • Airfares up 25%: Fares for all routes are increased by 25% over 2011 levels. This includes both Economy and Business/First Class fares. For the whole population, this results in a decrease in air trips of about 6%, with the business travel purpose less sensitive than other travel purposes. • Car operating cost up 25%: For all O-Ds, the perceived automobile operating cost for the car mode is increased by 25% over 2011 levels, from 20 cents/mile to 25 cents per mile. This resulted in an average increase in air trips by 3%. • All incomes up 25%: The household income for each tour is increased by 25%. This resulted in an increase in air trips of 1%. • Smaller airport flight frequencies down 50%: For any airports smaller than the largest hubs, the frequencies for both direct and connecting flights are reduced by 50% on all routes. This resulted in a decrease in air trips of 1%. • Smaller airport flight frequencies up 100%: For any airports smaller than the largest hubs, the frequencies for both direct and connecting flights are doubled on all routes. This resulted in systemwide increase in air trips of 3%. • More direct flights to/from smaller airports: For flights between the second rank of airports (here labeled as “larger airports”), and flights between the smallest airports and all other airports within 1,000 miles, the minimum frequency for direct flights is two flights per day. This resulted in a systemwide increase in air trips of 3%. PERCENT CHANGE IN AIR DEMAND AIRPORT (BY CODE) SCENARIO 1: AUTOMOBILE DOMINATES SCENARIO 2: OPTIMISTIC FOR SMALLER AIRPORTS SCENARIO 3: NEW SHORT-DISTANCE PLANES SCENARIO 4: AGGRESSIVE FOR THE HUB SCENARIO 5: AIR DOMINATES THE FUTURE THE FUTURE AIRPORTS CLT −19% 4% 7% 23% 17% RDU −20% 4% 6% 16% 16% GSO −28% 58% 64% −11% 18% CLT, RDU, & GSO −20% 8% 11% 18% 16% Table 1-8. Percent changes in air demand in a region with two larger hubs and a smaller airport (Scenarios 1–5). A range of separate component factors was run to gauge the sensitivity of the model to various types of changes in the input assumptions.

Market Competition Between Airplane and Automobile Modes 17 • Large airports more stressful: For airports on each end that are large hubs, the latent variable for “Airport Stress” is shifted 0.5 units toward higher stress. For the group of airports here labeled “larger,” the latent variable for “Airport Stress” is shifted 0.25 units toward higher stress. Thus, the maximum shift is 1.0, which is the standard deviation of the random com- ponent of the latent variables. This resulted in a decrease in air trips of 7%. • Stressful long-distance driving and automobile orientation: An increase of 1.0 in the latent variable for stress in driving would result in an increase in air trips of 4.5%; a 1-unit shift in the latent variable for reliance on the private car is associated with a 6% increase in air trips. • All people adopt “under-35” attitudes: For computing the latent variables, all people are treated as if they are in the under-35 age group, reflecting a future scenario where everyone has the attitudes of today’s younger people—at least as far as the five latent variables are con- cerned. This resulted in an increase in air trips of 5%. Examples of three of the component factors are discussed in the following sections. Impact of New Direct Flights by U.S. Census Division A hypothetical increase in direct flights between and among smaller airports affects air trips differently in different U.S. Census geographic divisions. Figure 1-7 shows that the smallest change in travel pattern (less than 1% increase in air trips) is predicted for the Pacific, where, presumably, a good selection of direct flights already exists. By contrast, it appears that there is an unmet need for direct short flights in the East South Central U.S. Census division, where an increase of 8% in air trips is predicted by the new model under the assumption of increased direct flights. Attitudinal Variation by Age As discussed in Chapter 5 of this report, travel preferences vary depending on the age of the traveler. Travelers under 35 years old have a greater distaste for multiday automobile trips than do travelers over 35. No one knows how the attitudes and preferences of travelers younger than 35 will change as they age. A scenario was built to reflect the idea that, as they age, they will retain the preferences they expressed in their youth. Figure 1-8 shows how air travel 8.1% 5.1% 3.7% 3.4% 3.1% 2.4% 1.6% 1.6% 0.7% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0% 9.0% ES CENT WN CENT EN CENT SOU ATL WS CENT MID ATL MOUNTN NEW ENG PACIFIC % Increase in Air Trips U .S . C en su s D iv is io ns Increase in Air Trips from Hypothesized Increase in Direct Flights, by U.S. Census Division Figure 1-7. Percent increase in air trips from increased direct service by U.S. Census division.

18 Air Demand in a Dynamic Competitive Context with the Automobile would increase if all age groups were to adopt such attitudes and young people (younger than 35) were, as they grow older, to retain their present negative attitudes and behavior toward the multiday automobile trip. In this case, air trips in the future would increase, and they would increase most dramatically for shorter-distance trips. As previously stated, travelers younger than 35 report a much higher level of dislike for multiday automobile trips than do travelers older than 35; tolerance for long automobile trips increases by age group at this point. If all age groups had this distaste for long automobile trips, air trips would increase by about 4%. Perhaps surprisingly, if all age groups were to have the same diminished reliance on the car as the young, no significant change in air trips is simulated in the model. In a parallel result, if all age groups had the same desire to remain electronically connected during long-distance as travelers younger than 35, no significant change in air use is predicted. Perceptions of Automobile Travel As explored in Chapter 5, some groups feel that long-distance automobile trips cause more stress than other groups do. A forecast was made of the implications of all market groups becoming less dissatisfied with the amount of stress perceived to be involved in automobile trips. Figure 1-9 shows that changing only this one attribute of the comparative experience could result in a 10% decline in air trips for the highly vulnerable 200- to 400-mile trip range. This is particularly important as automobile manufacturers make incremental improvements leading to the ultimate acceptance of autonomous vehicles, perhaps somewhat later. Such advanced concepts as connected-vehicle technology combined with the present pattern of providing increasing levels of comfort and entertainment in private vehicles could have significant impacts on the choice between the car trip and the air trip. Consistent with the major conclusions of this study, however, driving even the most “stress-free” automobile would not greatly affect the modal decision for trips longer than 1,600 miles. At the other end of the spectrum of possible changes in attitudes toward the automobile, if, over time, the population has a decrease in its belief that automobile ownership is essential for personal mobility, then automobile trips of less than 1,000 miles might divert to air, while trips 9.9% 7.6% 5.8% 4.6% 3.9% 3.1% 2.3% 1.2% 200-400 400-600 600-800 800-1000 1000-1200 1200-1400 1400-1600 1600-3200 % In cr ea se in A ir T ri ps Trip Distance (miles) Increase in Air Trips if All Had the Attitudes of the Young, by Trip Distance Figure 1-8. Percent increase in air trips by trip distance if all age groups had the attitudes of the Millennials. The perception that automobile trips are less stressful would result in a 10% decline in air trips between 200 and 400 miles in length.

Market Competition Between Airplane and Automobile Modes 19 of more than 1,000 miles are less volatile. Such a shift away from the car would affect smaller airports more than larger airports (not pictured). Figure 1-10 shows that less than a 4% change is forecast for trips of 1,000 miles and longer. Implications from the Scenario Testing Exercise This chapter has focused primarily on the results of the scenario testing process developed in this research. The scenario testing process was just one aspect of the larger research effort, but several policy implications can be drawn from this element of the work program. What Travel Patterns Are Most Vulnerable? It is clear from the results of several parallel research approaches that the impact of changes in the automobile system will have greater impact on overall air travel patterns than any other isolatable phenomenon examined in this study. The competition from the automobile of the future will have more impact on smaller airports than on larger ones and more impact on shorter-distance trips than on longer-distance trips. 200-400 400-600 600-800 800-1000 1000- 1200 1200- 1400 1400- 1600 1600- 3200 -10.00% -7.40% -5.60% -4.70% -3.70% -2.90% -2.20% -1.20% % D ec re as e in A ir T ri ps Trip Distance (miles) Decrease in Air Trips if Car Trips Are Less Stressful Figure 1-9. Percent decrease in air trips by trip distance if the car is perceived as less stressful than it is at present. 17.8% 9.9% 6.8% 5.2% 3.4% 2.5% 1.8% 1.0% 200-400 400-600 600-800 800-1000 1000-1200 1200-1400 1400-1600 1600-3200 % In cr ea se in A ir T ri ps Trip Distance (miles) Increase in Air Trips with Decrease in Orientation to the Private Car, by Trip Distance Figure 1-10. Percent increase in air trips by trip distance with decrease in private car orientation.

20 Air Demand in a Dynamic Competitive Context with the Automobile The Importance of Leakage It is also clear that the issue of leakage, as perceived by the managers of smaller airports, will not go away. As discussed in Chapter 4, the research team’s exploration of “willingness to pay” reveals that the average traveler would spend an extra hour in a car to avoid an extra half hour in an air trip. Travelers on average are willing to pay an additional $17 on their airfare to save an hour of access time but are willing to spend about double that amount to avoid an hour of in-flight time. This confirms results from other research that flight time is considered more onerous than ground access time. At the same time, the level of comfort in private cars and vans is increasing sharply (e.g., offering separate electronic screens for each seat). In short, longer trips in the automobile may become less stressful, and increased travel time in an automobile to divert to a more distant airport will become less onerous. It remains to be seen whether air- craft designed to provide cheaper service over short distances will be developed and successfully deployed, thereby improving the fortunes of the smaller airports.

Next: Chapter 2 - Trends and Changes in Automobile and Air Markets over Two Decades »
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Future demand for shorter-range airline trips is unstable, affected by changes in technology as well as consumer preferences. Through application of new research tools that support scenario analysis, the TRB Airport Cooperative Research Program's ACRP Research Report 204: Air Demand in a Dynamic Competitive Context with the Automobile explores the potential effects of evolving automobile and aircraft technology and shifting consumer preferences on demand for shorter-range air trips.

While previous methods of demand forecasting have tended to see aviation in a vacuum relative to its key domestic competitor, the automobile, the analytic framework presented in this report facilitates comparison of the two competing modes under changing technology and demographic conditions as well as consumer choice.

The report is designed to help managers of smaller airports develop a better understanding of how consumers choose between flying out of a smaller hometown airport to connect to a flight at a larger airport and taking a longer automobile drive, bypassing the smaller airport, to fly directly from a larger airport.

Also see the accompanying ACRP Web-Only Document 38: Technical Appendix to Air Demand in a Dynamic Competitive Context with the Automobile.

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