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

Chapter: CHAPTER 6. DATA COLLECTION, SAMPLING PLAN, AND DESCRIPTION OF 2017 SURVEY

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Suggested Citation:"CHAPTER 6. DATA COLLECTION, SAMPLING PLAN, AND DESCRIPTION OF 2017 SURVEY." 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 6. DATA COLLECTION, SAMPLING PLAN, AND DESCRIPTION OF 2017 SURVEY." 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 6. DATA COLLECTION, SAMPLING PLAN, AND DESCRIPTION OF 2017 SURVEY." 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 6. DATA COLLECTION, SAMPLING PLAN, AND DESCRIPTION OF 2017 SURVEY." 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 6. DATA COLLECTION, SAMPLING PLAN, AND DESCRIPTION OF 2017 SURVEY." 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 6. DATA COLLECTION, SAMPLING PLAN, AND DESCRIPTION OF 2017 SURVEY." 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 6. DATA COLLECTION, SAMPLING PLAN, AND DESCRIPTION OF 2017 SURVEY." 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 6. DATA COLLECTION, SAMPLING PLAN, AND DESCRIPTION OF 2017 SURVEY." 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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41 CHAPTER 6. DATA COLLECTION, SAMPLING PLAN, AND DESCRIPTION OF 2017 SURVEY 6(A) INTRODUCTION In 2017, the research team conducted a major national survey for this study in four metropolitan areas to collect data on travelers’ long-distance travel behavior and attitudes. As part of this work, the research team administered a series of stated preference (SP) experiments to examine the choice between car and air. This chapter describes the survey methodology for this effort. 6(B) SURVEY METHODOLOGY SAMPLING PLAN The objective of this study 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 study comprised travelers who had taken an automobile or air trip of greater than 300 miles within the past year. The research team used quota sampling, a technique that sets a minimum number of respondents for each respective category, to establish a diverse sample of respondents. Respondents were recruited through Research Now, a major online sample provider. To be eligible to take the online survey, respondents were required to have lived in a qualifying region and be over the age of 18. The overall goal for the survey was to obtain 4,000 respondents. Invitations to the online survey were emailed to respondents who resided within the Combined Statistical Area centered on each of the study’s four target regions. Minimum quotas were set for each metropolitan area and combinations of reference trip distance, purpose, and mode. Soft quotas were used to ensure an equal representation of gender and a range of incomes and ages in the sample. In practice, this meant the sample was targeted proportionally along these dimensions and was monitored during the data collection process, but exact minimum quotas were not set in this instance. Geographic Quotas The sampling plan targeted respondents living in one of four metropolitan areas: Washington, DC; Boston; Chicago; and Denver. Minimum quotas were set for each region, to ensure a large enough sample. TABLE 6-1 GEOGRAPHIC QUOTAS METROPOLITAN AREA MINIMUM QUOTA Washington, DC 800 Boston 800 Chicago 800 Denver 800

42 Trip Quotas Each respondent was required to describe a recent medium- or long-distance trip by airplane or car to act as a reference trip for the SP experiments. To collect enough sample from multiple reference trip types, the research team set quotas for each combination of trip distance, trip purpose, and mode. “Medium” distance trips were defined as having a destination within a 300– 500-mile radius of the center of the metropolitan area. Long-distance trips were defined as having a destination farther than 500 miles from the center of the metropolitan area. TABLE 6-2: DISTANCE, PURPOSE, AND MODE QUOTAS DISTANCE X PURPOSE X MODE MINIMUM QUOTA Medium Business Air Trip 200 Medium Business Car Trip 200 Medium Personal Air Trip 200 Medium Personal Car Trip 200 Long Business Air Trip 200 Long Business Car Trip 200 Long Personal Air Trip 200 Long Personal Car Trip 200 Total Medium Distance 1,500 Total Long Distance 1,500 QUESTIONNAIRE A questionnaire helped understand 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 traveling by car or plane for trips of 300 miles or more. The survey questionnaire was drafted and reviewed with the Panel. Once the questionnaire content was finalized, the research team programmed the web-based survey. The survey first asked a few demographic questions for screening purposes (to ensure the sample was in the geographic areas of interest and determine which quota cells respondents fell into). Then respondents were asked to enter the total number of round trips they have made within the last year. These totals were collected separately for medium-distance trips (300–500-miles from the metropolitan area) and long-distance trips (over 500 miles) and categorized by mode (car or plane) and primary purpose (business or leisure). The survey also asked respondents if they had taken any multi-destination or one-way long-distance trips within the past year. Each question included an interactive map so that respondents could see which destinations fell into each distance category.

43 FIGURE 6-1: SCREENSHOT OF MEDIUM-DISTANCE TRIPS QUESTION FOR CHICAGO-AREA ORIGINS

44 FIGURE 6-2: SCREENSHOT OF LONG-DISTANCE TRIPS QUESTION FOR CHICAGO-AREA ORIGINS Following this section of the survey, respondents were assigned a trip distance, purpose, and mode where they had entered at least one round trip and asked to provide further details about their most recent trip in this category. Trip details included origin and destination, party size, trip duration, trip costs, and specific questions relating to air trips or car trips. This information was used to construct a series of eight SP trade-off experiments where respondents were asked to choose driving or one of three air options with varying characteristics for similar trip they had described. Attributes that varied for the air options were departure airport, number of stops, airfare, travel time, airport access mode, and access travel time. Airport parking and access gas costs were also included, if applicable. Attributes that varied for the car option were door-to-door driving time, gas costs, and if the trip was made with an autonomous vehicle. A screenshot of an example SP experiment is pictured in Figure 6-3.

45 FIGURE 6-3: SCREENSHOT OF AN EXAMPLE SP EXPERIMENT Respondents were then put through a battery of approximately 50 attitudinal questions in eight sets to understand general attitudes toward the various aspects of medium- and long-distance air and automobile travel. Respondents were asked to what extent they agreed or disagreed with each statement on a seven-point scale (Figure 6-4). The survey concluded with an additional set of demographic questions.

46 FIGURE 6-4: SCREENSHOT OF ONE SET OF ATTITUDINAL QUESTIONS SURVEY ADMINISTRATION Pretest On February 17, 2017, the survey was pretested with a group of 100 respondents. RSG analyzed the pretest data and ran preliminary SP models to ensure everything was working as planned. Once it was confirmed that respondents understood the SP section and that reasonable coefficients could be obtained from the design, the survey was launched in full. Full Field The full field effort occurred between February 21, 2017 and March 8, 2017. Prior to beginning analysis, the research team reviewed records to identify potentially bad data. Three criteria were used to identify bad data:  The respondent had taken the survey in an unreasonably quick time (under 8 minutes).  The respondent had indicated that they made an unreasonable number of long-distance trips (over 200 trips in a year).  The respondent straight-lined (provided the same response) for at least four out of the eight sets of attitudinal questions. Respondents meeting these criteria were removed from the dataset and new respondents were recruited to complete data collection. The tables and charts that follow provide an information about the sample makeup.

47 6(C) FINAL DATASET The field effort resulted in a total of 4,223 valid responses, exceeding the goal of 4,000. Table 6-3 shows the number of completed surveys, by metro area and by region, with the targeted sample sizes included for reference. The research team aimed to collect 800 completed surveys in each metro area to provide enough sample for analysis; it exceeded that goal in all four metro areas. The final sample was split evenly among the four metro areas. TABLE 6-3: SAMPLE QUOTAS AND COMPLETED SURVEYS, BY GEOGRAPHY METROPOLITAN AREA MINIMUM QUOTA ACTUAL # SURVEYS % SURVEYS Washington, DC 800 1,050 24.9% Boston 800 1,039 24.6% Chicago 800 1,078 25.5% Denver 800 1,056 25.0% Total 4,000 4,223 100% In addition, the research team aimed to collect a minimum of 200 completed surveys from each of the eight combinations of trip distance (medium or long), trip purpose (business or personal), and mode (car or air). Again, these numbers were exceeded in each category and each accounted for somewhere between 7% and 20% of the sample (Table 6-4). Car trips of greater than 500 miles for business were, unsurprisingly, the least common. TABLE 6-4: SAMPLE QUOTAS AND COMPLETED SURVEYS, BY TRIP TYPE DISTANCE X PURPOSE X MODE MINIMUM QUOTA ACTUAL # SURVEYS % SURVEYS # SURVEYS BY DISTANCE % SURVEYS BY DISTANCE Medium Business Air Trip 200 366 8.7% 1,887 44.7% Medium Business Car Trip 200 331 7.8% Medium Personal Air Trip 200 529 12.5% Medium Personal Car Trip 200 661 15.7% Long Business Air Trip 200 531 12.6% 2,336 55.3% Long Business Car Trip 200 291 6.9% Long Personal Air Trip 200 844 20.0% Long Personal Car Trip 200 670 15.9% DEMOGRAPHICS Although the research team did not set hard quotas for demographics, it aimed to obtain a good mix of ages and incomes along with a balanced gender ratio. Table 6-5 shows a balanced age profile that might be slightly skewed toward older respondents with 21% of the sample in the 65-

48 or-over age category and another 21% between 55 and 64. The sample is 53% female (Table 6-6). Finally, the household income category of each respondent is shown in Table 6-7. This shows a balance among the higher-income categories, but a smaller proportion (7% of the sample) of those who make less than $35,000 per year. This can be partially attributed to the likelihood that potential low-income respondents are less likely to have made a long-distance trip in the past year and thus would not have qualified to take the survey. TABLE 6-5: AGE CATEGORY OF COMPLETED SURVEYS AGE CATEGORY # SURVEYS % OF SAMPLE 18–34 847 20% 35–44 783 19% 45–54 794 19% 55–64 892 21% 65 and older 907 21% Column n -- 4,223 TABLE 6-6: GENDER OF COMPLETED SURVEYS GENDER # SURVEYS % OF SAMPLE Female 2,257 53% Male 1966 47% Column n -- 4,223 TABLE 6-7: HOUSEHOLD INCOME OF COMPLETED SURVEYS INCOME CATEGORY # SURVEYS % OF SAMPLE Less than $35,000 307 7% $35,000–$74,999 1,199 28% $75,000–$99,999 864 20% $100,000–$149,999 922 22% $150,000 or more 931 22% Column n -- 4,223

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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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