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

Chapter: CHAPTER 4. THE LOCATION OF AND FACTORS FOR COMPETITION AMONG AIRPORTS

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Suggested Citation:"CHAPTER 4. THE LOCATION OF AND FACTORS FOR COMPETITION AMONG AIRPORTS." National Academies of Sciences, Engineering, and Medicine. 2019. Technical Appendix to Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25642.
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Suggested Citation:"CHAPTER 4. THE LOCATION OF AND FACTORS FOR COMPETITION AMONG AIRPORTS." National Academies of Sciences, Engineering, and Medicine. 2019. Technical Appendix to Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25642.
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Suggested Citation:"CHAPTER 4. THE LOCATION OF AND FACTORS FOR COMPETITION AMONG AIRPORTS." National Academies of Sciences, Engineering, and Medicine. 2019. Technical Appendix to Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25642.
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Suggested Citation:"CHAPTER 4. THE LOCATION OF AND FACTORS FOR COMPETITION AMONG AIRPORTS." National Academies of Sciences, Engineering, and Medicine. 2019. Technical Appendix to Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25642.
×
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Suggested Citation:"CHAPTER 4. THE LOCATION OF AND FACTORS FOR COMPETITION AMONG AIRPORTS." National Academies of Sciences, Engineering, and Medicine. 2019. Technical Appendix to Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25642.
×
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Suggested Citation:"CHAPTER 4. THE LOCATION OF AND FACTORS FOR COMPETITION AMONG AIRPORTS." National Academies of Sciences, Engineering, and Medicine. 2019. Technical Appendix to Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25642.
×
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Suggested Citation:"CHAPTER 4. THE LOCATION OF AND FACTORS FOR COMPETITION AMONG AIRPORTS." National Academies of Sciences, Engineering, and Medicine. 2019. Technical Appendix to Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25642.
×
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Suggested Citation:"CHAPTER 4. THE LOCATION OF AND FACTORS FOR COMPETITION AMONG AIRPORTS." National Academies of Sciences, Engineering, and Medicine. 2019. Technical Appendix to Air Demand in a Dynamic Competitive Context with the Automobile. Washington, DC: The National Academies Press. doi: 10.17226/25642.
×
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31 CHAPTER 4. THE LOCATION OF AND FACTORS FOR COMPETITION AMONG AIRPORTS 4(A) VARIATION IN GROUND ACCESS DISTANCES TO AMERICAN AIRPORTS Chapter 4 of the Technical Appendix explores the location of American airports, in order to improve our understanding of the potential competition between and among them. A NEW SOURCE OF INTERREGIONAL TRAVEL DATA The trip tables used to create Figure 3-1, Figure 3-2, and Table 3-1 were based on data published by FHWA as part of its refined bus ridership estimate project, which was an extension of an earlier project, “Traffic Analysis Framework Multimodal Interregional Passenger Travel Origin Destination Data.” The following sections of this report utilize multiple data sources created in a separate FHWA project, “Foundational Knowledge to Support a Long-Distance Passenger Travel Demand Modeling Framework.” The research team has performed an analysis of input and output data for the “Foundational Knowledge” project, a national long-distance passenger demand forecasting model developed for FHWA. This project includes a synthesized population for the year 2010 for the full US population—a total sample of over 115 million household records. Key variables included in the household file are household size, household income, number of workers, presence/absence of children, and age of the head of household. A zonal system specific to the needs of long-distance trip-making was used, including over 4,400 transportation analysis zones for all 50 states (plus DC). The highway skims for the zone systems include connectors to all modeled airports and rail stations. The highway network that is used contains almost 200,000 links, including link-level information on tolls. Airport-to-airport matrices included in the model are based on the DB1B 10% sample of air coupon data, along with the published data of air route on-time performance, which provides estimates of air journey time, frequency of service (for direct and nondirect flights), and average transfers required. Zone-to-airport automobile access/egress matrices are used for all airports within 100 miles of each zone. All modal data are integrated using a new software tool, rJourneyTM, developed by RSG for the Foundational Knowledge project. DISTANCE TO AIRPORT, TRIP LENGTH DISTRIBUTION During the creation and calibration process of the rJourney model, national data was assembled for the ground access portion of long-distance air trips. The database includes highway distance from each Census tract in the United States to every airport within 100 miles of the tract centroid. The tracts and the US population can be categorized in terms of the access distance to airports of different sizes when these data are weighted by the population living in each Census tract. The analysis reported here was restricted to Census tracts within the 48 contiguous states (plus DC). Figure 4-1 shows that most US residents have one or more airports within 40 miles of home, with 34% of residents having the nearest airport between 20 and 30 miles from home.

32 Figure 4-1 also shows that only a small percentage of US residents live more than 80 miles from the nearest airport. FIGURE 4-1: DISTRIBUTION OF GROUND ACCESS TRIP DISTANCES Source: Federal Highway Administration, Foundational Knowledge Project. 4(B) AIRPORTS CATEGORIZED BY POTENTIAL COMPETITION WITH OTHER AIRPORTS SUMMARY OF NATIONAL AIRPORT LOCATIONS The analysis of airport access distance for US residents by Census tract was extended to distinguish major and minor airports, with the “major” airports being the top 60 in the United States in terms of annual enplanements. This distinction helps to better understand the proportion of potential long-distance travelers who have a choice of airports, often with larger airports available at longer distances from the residence location. Figure 4-2 shows that approximately 53% of residents are well served in relation to a major airport, with 45% of residents with a major airport being closest, and another 8% of residents with the major airport being the only option. Approximately 23% of residents have only a choice of a smaller airport. This leaves 24% of residents who have a choice of a minor airport and a more distant major airport—10% for whom the minor airport is at least 40 miles closer, and 14% where the major airport is almost as close as the smaller airport (within 40 miles). This suggests that airport choice is a major consideration for 24% of potential air travelers, and for people choosing the departing airport based on factors not influenced by geographic proximity.

33 FIGURE 4-2: FIVE CATEGORIES OF AIRPORT LOCATION FOR COMPETITION STUDIES AIRPORT LOCATION/COMPETITION CATEGORY, BY STATE The national aggregate data presented in Figure 4-2 is examined on a state-by-state basis in Table 4-1. This uses the same five categories, plus a sixth category—no airports within 100 miles of the Census tract—that was excluded from Figure 4-2 for graphic simplicity, as it includes less than one-half of one percent of continental US residents. However, 8.1% of residents of South Dakota and 10.2% of residents of Montana live in Census tracts with no airports within 100 miles. (Blank cells in Table 4-1, denoted with an en dash, are 0%.) TABLE 4-1: DISTRIBUTION OF RESIDENTS' AIRPORT LOCATION/POTENTIAL COMPETITION, BY STATE STATE ONLY MAJOR AIRPORT ONLY MINOR AIRPORT MAJOR AIRPORT IS CLOSER MAJOR AIRPORT IS ALMOST AS CLOSE MINOR AIRPORT IS AT LEAST 40 MILES CLOSER NO AIRPORTS TOTAL % AL – 79.9% .5% 4.8% 14.8% – 100.0% AR – 98.2% – – – 1.8% 100.0% AZ 50.8% 21.1% 17.2% 2.1% 5.3% 3.5% 100.0% CA 1.1% 9.2% 57.3% 26.5% 5.9% .1% 100.0% CO .1% 15.7% 63.6% 6.5% 12.6% 1.5% 100.0% CT – – 52.1% 47.9% – – 100.0% DC – – 100.0% – – – 100.0% DE – – 81.0% 19.0% – – 100.0% FL 28.2% 7.8% 46.6% 12.1% 5.3% – 100.0% only major airport, 8% major airport is closer, 45% major airport is almost as close, 14% minor airport is at least 40 miles closer, 10% only minor airport, 23%

34 STATE ONLY MAJOR AIRPORT ONLY MINOR AIRPORT MAJOR AIRPORT IS CLOSER MAJOR AIRPORT IS ALMOST AS CLOSE MINOR AIRPORT IS AT LEAST 40 MILES CLOSER NO AIRPORTS TOTAL % GA 5.9% 19.0% 57.4% 9.1% 8.6% – 100.0% IA – 84.1% 6.9% 3.2% 5.2% .6% 100.0% ID – 98.9% – .4% – .7% 100.0% IL .5% 13.4% 72.4% 6.3% 7.4% – 100.0% IN 6.5% 15.8% 49.5% 13.2% 15.0% – 100.0% KS 21.9% 51.8% 15.9% 6.1% 1.8% 2.6% 100.0% KY .9% 34.2% 16.9% 9.3% 38.7% – 100.0% LA .1% 43.9% 32.8% 9.0% 14.2% – 100.0% MA – – 69.6% 29.4% 1.0% – 100.0% MD .3% .2% 97.7% 1.8% – – 100.0% ME – 68.9% – 4.0% 22.3% 4.8% 100.0% MI – 26.3% 40.9% 12.0% 20.9% – 100.0% MN 2.1% 19.2% 65.0% 6.9% 5.7% 1.1% 100.0% MO 25.9% 30.1% 35.7% 5.1% 2.0% 1.2% 100.0% MS – 82.7% – 6.6% 10.2% .5% 100.0% MT – 89.8% – – – 10.2% 100.0% NC – 13.6% 46.5% 16.7% 23.2% – 100.0% ND – 99.4% – – – .6% 100.0% NE – 20.6% 42.2% 9.6% 20.8% 6.9% 100.0% NH – 10.5% – 55.1% 34.3% .2% 100.0% NJ – – 70.3% 27.4% 2.3% – 100.0% NM 2.2% 37.0% 43.0% 3.0% 8.4% 6.4% 100.0% NV 71.9% 24.2% 1.0% .4% 1.4% 1.0% 100.0% NY .5% 12.6% 57.2% 17.7% 12.1% – 100.0% OH – .8% 58.7% 30.3% 10.2% – 100.0% OK 1.2% 95.3% .5% 1.3% .1% 1.6% 100.0%

35 STATE ONLY MAJOR AIRPORT ONLY MINOR AIRPORT MAJOR AIRPORT IS CLOSER MAJOR AIRPORT IS ALMOST AS CLOSE MINOR AIRPORT IS AT LEAST 40 MILES CLOSER NO AIRPORTS TOTAL % OR 17.6% 32.8% 39.6% 5.3% 4.2% .5% 100.0% PA 9.6% 7.4% 41.9% 23.0% 17.9% .2% 100.0% RI – – – 57.0% 43.0% – 100.0% SC – 46.4% 8.2% 9.3% 36.1% – 100.0% SD – 91.0% – – .9% 8.1% 100.0% TN 15.0% 58.2% 19.6% 5.2% 2.1% – 100.0% TX 10.0% 23.2% 56.4% 4.0% 6.2% .1% 100.0% UT 82.6% 9.8% 4.6% .2% – 2.7% 100.0% VA – 42.7% 34.8% 5.9% 16.6% – 100.0% VT – 84.5% .7% 11.8% 3.0% – 100.0% WA 31.5% 19.8% 40.0% 4.2% 3.7% .8% 100.0% WI – 27.5% 38.2% 10.6% 23.7% – 100.0% WV 9.0% 54.4% 24.4% 10.2% 2.0% – 100.0% WY 1.2% 80.7% 1.4% 1.2% 14.7% .9% 100.0% Total USA 8.0% 22.9% 45.5% 13.6% 9.7% .5% 100.0% No Data: – Source: rJourney database. Competition from Major Airports in Minor Airport Catchment Area Arguably, the issue of “leakage” from one airport to another is of most concern to the managers of smaller airports. Using the rJourney database, Figure 4-3 looks only at residents living within 40 miles of a minor airport, a distance chosen to represent a logical catchment area for such an airport. That chart shows that over 35% of people who live close to a small airport live farther than 100 miles from a major competing airport. On the other hand, over 20% of these people have access to a major airport within 20 miles of their residential location.

36 FIGURE 4-3: DISTANCE TO MAJOR AIRPORT FOR THOSE LIVING WITHIN 40 MILES OF MINOR AIRPORT Source: rJourney database. Competition from Minor Airports in Major Airport Catchment Area There is little temptation to choose a smaller airport—at least based on proximity—for most travelers living in the logical catchment area of a major airport. Over 50% of people living within 40 miles of a major airport do not have a competing smaller airport located within 60 miles. On the other hand, approximately 10% of people have a second airport within 20 miles of their residences. For people living within 20 miles of a major airport, a similar pattern emerges, which is observable by examining the blue (lower) portions of the vertical bars in Figure 4-4. FIGURE 4-4: DISTANCE TO MINOR AIRPORT FOR TRAVELERS WITHIN 40 MILES OF A MAJOR AIRPORT Source: rJourney database. 0% 5% 10% 15% 20% 25% 30% 35% 40% 0- 20 miles 20-40 miles 40-60 miles 60-80 miles 80-100 miles Over 100 miles Pe rc en t i n di st an ce c at eg or y to m aj or a ip or t Distance to competing major airport for those within 40 miles of minor airport 0% 5% 10% 15% 20% 25% 30% Under 20 20-40 40-60 60-80 80-100 Over 100 Pe rc en t i n D is ta nc e C at eg or y Distance to Minor Airport in Miles Major Airport within 20 miles Major Airport 20 - 40 miles

37 4(C) AIRPORT SELECTION IN AND BETWEEN MULTI-AIRPORT REGIONS The ACRP 03-40 project has examined the process by which travelers choose between candidate airports in regions where competition exists. Larger and more dominant airports are preferred for long-distance airline trips and are less frequently used in shorter-distance air travel. This section presents examples of these alternative choices, with one example for the East Coast and one example for the West Coast. This analysis is based on the air trips simulated from the rJourney long-distance model. The simulated air trips are not based on observed data (such as the DB1B ticket data), but these trips distinguish the home (production) end of air trips from the nonhome (attraction) end. (One of the objectives of the current project will be to improve the modeled choices between competing airports, but the current model produces reasonable results.) ROLE OF DOMINANT AIRPORTS IN TRIPS FROM NEW ENGLAND For those living in the Boston region—defined broadly for this research project to include Bradley/Harford, Connecticut; Providence, Rhode Island; Manchester, New Hampshire; and Portland, Maine—the dominant airport (Boston Logan International Airport) is selected overwhelmingly over the smaller regional airports for trips to the San Francisco Bay Area, claiming 82% of the region-to-region market. Given that there are three important airports in the Bay Area, the dominant pair of airports (BOS/SFO) captures 71% of the region-to-region market. The dominant-to-dominant airport share for the shorter-distance trips to the Washington/Baltimore region within the East Coast is smaller—comprising only 32% of the market. TABLE 4-2: SELECTION OF AIRPORTS FOR LONG- AND SHORT-DISTANCE TRIPS FROM NEW ENGLAND LONG-DISTANCE CORRIDOR SHORT-DISTANCE CORRIDOR FROM/TO SFO SJC OAK FROM/TO DCA BWI IAD BOS 71% 8% 3% BOS 32% 21% 9% BDL 7% 1% 1% BDL 3% 7% 1% PVD 3% 1% 1% PVD 3% 9% 1% MHT 2% 0% 1% MHT 2% 8% 0% PWM 2% 0% 0% PWM 2% 3% 0% Source: rJourney database.

38 Role of Dominant Airports in Trips from California TABLE 4-3: SELECTION OF AIRPORTS FOR LONG- AND SHORT-DISTANCE TRIPS FROM CALIFORNIA LONG-DISTANCE CORRIDOR SHORT-DISTANCE CORRIDOR FROM/TO SFO SJC OAK FROM/TO SFO SJC OAK BOS 71% 8% 3% LAX 28% 8% 8% BDL 7% 1% 1% SNA 8% 7% 6% PVD 3% 1% 1% LGB 3% 0% 4% MHT 2% 0% 1% PSP 2% 0% 0% PWM 2% 0% 0% BUR 1% 5% 10% ONT 1% 3% 5% Source: rJourney database. Table 4-3 contains the same long-distance corridor model run outcomes as Table 4-2, but this time compared to a shorter-distance corridor in California, from the Los Angeles region to the Bay Area. Transcontinental trips to New England from the San Francisco Bay Area are more likely to use both dominant airports, compared to shorter-distance trips in California; for which only 28% of the trips use both dominant airports.

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This technical appendix from the TRB Airport Cooperative Research Program, ACRP Web-Only Document 38: Technical Appendix to Air Demand in a Dynamic Competitive Context with the Automobile, supplements ACRP Research Report 204: Air Demand in a Dynamic Competitive Context with the Automobile with more detailed documentation of the research effort, including greater technical detail on the analytical models created for the research and their application.

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