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

Chapter: Chapter 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice

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Suggested Citation:"Chapter 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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 5 - The Role of Attitudes Toward Long-Distance Trips in Mode Choice." 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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64 Introduction Attitudes, values, and preferences will affect the choice of mode for a full trip, and they will affect the choice of the airport of departure. This chapter presents the results of the 2017 ACRP Project 03-40 survey of such attitudes, values, and preferences. The chapter has three parts. In the first section, a wide variety of subject areas concerning attitudes toward transportation and specific modes is reviewed. Results are graphed to allow easy spotting of trends or consis- tencies in responses by gender, age, and income. Secondly, attitudes and preferences are used in the creation of five market segments, which can be used to better understand the wide variety of market reactions in the choice between air and automobile for making the long-distance trip. Finally, this chapter presents the results of an extensive attitude-based model that applies Structural Equation Modeling to better interpret the importance of factors beyond times and costs in the choice of the long-distance mode. Overall Attitude: People Still Want to Travel Americans seem to be somewhat positive about longer-distance trips. For instance, they agree with both the statement that there is something “exciting” about taking a trip by air and “appealing” about taking a long trip by car, with more positive feelings about the plane than about the automobile. Method In the ACRP Project 03-40 survey, respondents were shown a wide variety of statements (e.g., “For me, the process of going through airport security is stressful”) and offered seven possible levels of agreement ranging from Strongly Disagree (coded as −3) to Strongly Agree (coded as +3.) In the analysis that follows, the graphs show the mean level of agreement (scaled between 0 and +3) and mean level of disagreement (scaled between 0 and −3). Further, in Tables 5-1 through 5-5, the positive values are expressed as a blue horizontal bar, while the negative values are expressed as a red horizontal bar. Concerning long trips by car being “appealing,” in Figure 5-1 clear differences are revealed by gender and income level, where having less income is correlated with liking the car trip more. Attitudes Toward the Automobile Table 5-1 shows the variation in level of agreement with five statements, this time expressed as horizontal bars presented in two colors. Survey respondents generally report positive C H A P T E R 5 The Role of Attitudes Toward Long-Distance Trips in Mode Choice

The Role of Attitudes Toward Long-Distance Trips in Mode Choice 65 attitudes toward the car. Attitudes toward the freedom and independence that a car provides vary relatively little by demographic group. The one exception is age—Millennials are signifi- cantly less likely to attribute freedom and independence to owning a car. Importantly, none of these subgroups prefers to rent or borrow rather than own a car, but Millennials were more positive about renting or borrowing a car than the older groups: the scaling of agreement with the statement as presented here for the older groups on this question was twice as high as that of the Millennials. Males seem to be more open to the idea of renting/ borrowing than females, and the richer group was more open to the idea of renting/borrowing than the less rich group. Again, this must be seen in the context of a strong level of agreement from both groups about the preference to own the vehicle. This is reflected by the lack of differ- ence among groups in support for the statement “I need to drive a car to get where I need to go,” except that respondents with a lower income were more likely to endorse this statement than respondents with a higher income. To me, there is something appealing about taking a long trip by car I love the freedom and independence I get from owning one or more cars I would rather own a car than borrow or rent it (REV)* I need to drive a car to get where I need to go I feel I am less dependent on cars than my parents are/were Total 0.36 1.4 1.5 0.73 -0.41 Millennials 0.43 1.22 0.83 0.7 0.27 Older Groups 0.34 1.45 1.67 0.74 -0.58 Female 0.26 1.38 1.68 0.76 -0.53 Male 0.46 1.42 1.29 0.7 -0.27 Less Income 0.52 1.39 1.4 0.8 -0.41 More Income 0.14 1.42 1.63 0.64 -0.42 *REV = Reverse scored Table 5-1. Attitudes toward the automobile by age, gender, and income. 0 0.2 0.4 0.6 0.8 1 1.2 <35 >35 Female Male Less Income More Income In cr ea si ng L ev el o f A gr ee m en t Hedonic Reaction to Air and Car Trip by Age, Gender, and Income To me, there is something appealing about taking a long trip by car To me, there is something exciting about taking a trip by air Figure 5-1. Hedonic attitudes toward air and car trips by age, gender, and income.

66 Air Demand in a Dynamic Competitive Context with the Automobile Attitudes Toward Congestion and Stress All demographic categories strongly believe that the long-distance trip by air will be less stressful and tiresome than an equivalent trip by car (see Table 5-2). Individuals with higher income and Millennials especially agree with that statement. Congestion is of more concern to Millennials than to other subgroups in the sample, both for intra-city and intercity trips. Contrary to what might be expected, there was little endorsement of the statement that going through airport security is stressful. Compared to individuals with lower income, individuals with higher income reported being slightly less stressed at security and experiencing less dis- comfort with airport crowds. Table 5-3 shows that driving for several days is perceived as being more unpleasant by Millennials than by the other subgroups. Further, Millennials are more likely to say that even driving with family and friends is unpleasant, that finding a hotel and the costs of overnight stays are a concern, and that the level of uncertainty associated with a car trips makes them I feel really stressed when driving for a long time in congestion in and around big cities To me, getting stuck in traffic congestion on a long trip is a big concern Compared to driving a car for this trip, I would be less tired and stressed if I took the trip by air For me, the process of going through airport security is stressful Dealing with the crowds of people at the airport is uncomfortable for me Total 0.55 0.84 1.42 -0.01 -0.06 Millennials 0.75 1.04 1.53 0.05 0.06 Older Groups 0.5 0.78 1.4 -0.02 -0.09 Female 0.67 0.86 1.47 -0.14 -0.15 Male 0.41 0.81 1.37 0.14 0.05 Less Income 0.58 0.87 1.3 0.13 0.06 More Income 0.51 0.79 1.58 -0.18 -0.22 Table 5-2. Attitudes toward congestion and stress by age, gender, and income. The thought of driving for several days with family/friends is unpleasant To me, the basic idea of driving for more than a day is unpleasant When planning a long trip, finding a good hotel is a big concern When planning a long trip, the costs of staying overnight and meals along the way are a big concern The level of uncertainty associated with a multi-day auto trip tends to make me choose the plane Total -0.08 0.25 0.48 0.51 0.26 Millennials 0.34 0.74 0.72 0.96 0.65 Older Groups -0.18 0.13 0.42 0.4 0.16 Female -0.09 0.29 0.54 0.59 0.25 Male -0.07 0.21 0.41 0.42 0.28 Less Income -0.13 0.15 0.53 0.69 0.2 More Income -0.02 0.39 0.41 0.28 0.33 Table 5-3. Preferences regarding long-distance mode by age, gender, and income.

The Role of Attitudes Toward Long-Distance Trips in Mode Choice 67 choose the plane. By much smaller margins, females tend to evaluate trips by car more negatively than males, although they do not rise to the level of influencing the modal decision. Of all groups, the uncertainty associated with the multiday automobile trip seems to bother the older groups the least. Attitudes About Disturbing Behavior on the Trip Individuals are less concerned about crime and disturbing behavior when traveling by plane than when traveling by car (see Table 5-4). However, survey respondents were more concerned about the lack of privacy when traveling by plane, with most moderately agreeing with the idea the having people seated so close is unpleasant. Generally, there was little variation in endorsing this statement across subgroups, although individuals with less income tended to agree slightly more than did those with more income. Even though individuals evaluate the lack of privacy negatively, they perceive air travel as safe. This is reflected in the widespread endorsement of the statement that they do not worry about personal safety or disturbing behavior when on the plane. Even though individuals on the whole agree that a plane trip is safer than a trip by car, there are subgroups, such as Millennials and individuals with less income, who are less likely to agree. While they tend to agree that the plane trip has less risk for disturbing behavior, Millennials, males, and groups with less income are less likely to agree than older age groups, female respon- dents, and individuals with more income. Females are more likely than males to worry about traveling with people they do not know, as are individuals with less income. Millennials, compared to older individuals, are less worried about travel with people they do not know. Preferences and Choice of the Air Trip Most Americans would prefer to fly for trips of more than 300 miles, as shown in Table 5-5. This especially holds for females, those with more income, and younger individuals. These sub- group differences also emerge for the belief that people important in respondents’ lives would choose air travel over automobile travel, with the exception that there are no gender differences Having people so close to me in an airline seat is unpleasant to me I don't mind traveling with people I do not know To me, making a long-distance trip by car exposes me to MORE crime and disturbing behavior than going by air (REV) I would NOT worry about personal safety or disturbing behavior if I went by plane (REV) To me, taking a trip by air is MORE safe than taking that trip by car. (REV) Total 0.45 0.49 0.62 0.81 0.96 0 0 0 Millennials 0.49 0.7 0.48 0.53 0.66 Older Groups 0.44 0.44 0.65 0.88 1.03 0 0 0 Female 0.45 0.41 0.72 0.9 0.99 Male 0.45 0.59 0.5 0.71 0.92 0 0 0 Less Income 0.49 0.45 0.5 0.65 0.84 More Income 0.38 0.55 0.76 1.02 1.11 Note: Three statements shown in Table 5-4 regarding disturbing behavior and the safety of air travel were reverse scored (REV) to facilitate interpretation. Table 5-4. Concerns about the air trip by age, gender, and income.

68 Air Demand in a Dynamic Competitive Context with the Automobile in this regard. When respondents were asked the more abstract question about whether they would continue to travel by air if driverless cars were to become reality, most responded affir- matively, with the exception of Millennials, who stated that they would be less likely to choose air travel over travel in autonomous vehicles. Implications of the Attitudinal Data While the prior discussion of results focused on the differences among demographic sub- groups, it is important to keep the overarching similarities in mind: all subgroups would rather fly than drive, show some agreement that the air trip is safe, and are not majorly concerned about the issue of disturbing behavior with air travel. Attitudes toward getting through airport security and crowding at airports are not statistically relevant either way. On the other hand, sitting too close to others in airplanes is almost universally disliked. Even though the “basic idea of driving more than 1 day” is perceived as moderately unpleasant by most, all but one subgroup (Millennials) reported liking driving with friends and family— with all groups finding some level of “appeal” in a road trip. Some demographic patterns were consistent: males were more positive about driving than were females; respondents with less income were less worried about the long-distance trip than were respondents with more income. Within an overall pattern of trip approval, younger indi- viduals tend to worry more about personal safety and disturbing behavior than older individuals do. Young individuals were also more worried about the details of finding lodging on the way and paying for it. Consistent with expectations, younger respondents also reported a higher usage and need for information and communication technologies, and Millennials consistently agreed less with statements expressing automobile dependence and automobile need. Market Segmentation by Attitude and Behavior Purpose and Method The potential markets for long-distance travel (including air and automobile) can be ana- lyzed in terms of their demographic similarity, their geographic similarity, and their similarity in market preferences. Market segmentation is a key strategy in market research; it allows To me, there is something exciting about taking a trip by air When I have a choice, I would really prefer to fly (REV) People important in my life would choose the plane over the drive by car I would definitely consider taking the plane for a trip to <destination> If driverless cars were to become a reality, I would NOT be less likely to travel by plane Total 0.72 0.48 1.18 1.6 0.33 Millennials 1.13 0.53 1.36 1.8 -0.18 Older Groups 0.61 0.46 1.14 1.55 0.46 Female 0.8 0.61 1.15 1.65 0.44 Male 0.62 0.32 1.22 1.54 0.19 Less Income 0.74 0.35 1.04 1.44 0.26 More Income 0.69 0.63 1.36 1.81 0.41 Table 5-5. Preference for flying by age, gender, and income.

The Role of Attitudes Toward Long-Distance Trips in Mode Choice 69 marketers to understand different motivations for market behavior by different segments. This section of Chapter 5 summarizes the market segmentation process, presents the five groups revealed in the segmentation process, and summarizes the groups’ characteristics. The behaviors, attitudes, and values of any given population are hugely variable. For the purposes of discussion and analysis, it is often useful to group a population into discrete cate- gories that can be characterized and compared to one another. Many commonly used cluster analysis methods achieve this by using an a priori segmentation approach based on demographic variables such as income, gender, or age; however, the goal of Latent Class Cluster (LCC) analysis is to identify groups based on latent variables such as attitudes, preferences, values, or person- ality differences. For example, differences among individuals in their preference for air travel might be due in part to travelers’ household incomes; however, perhaps the differences are not driven by income at all but are instead driven by a particular set of attitudes toward privacy, the environment, or convenience when traveling. As a data-driven analysis method based on latent variables, LCC allows researchers to identify subgroups that are based on distinct psychological profiles as they relate to travel preferences—in the case of this research, the preference for traveling by car or plane for medium- to long-distance trips. LCC uses a “finite mixture model” to identify unique groups. This model assumes that a population can be segmented into a finite number of groups, or classes, by “unmixing” the data to identify the number and characteristics of the populations, or latent classes. The result of this method is that, for each individual, the model assigns probabilities for membership in each class and groups individuals in such a manner that they share similar characteristics but are dissimilar from those in other groups. Standard statistical tests are applied to find the most appropriate number of segments, which variables to include in the model, and model fit. Once classes are defined, members of the classes can then be profiled by other variables. For example, researchers can see the income distribution of all classes and see whether high income is associated with a particular segment. Each of these classes represents the “building blocks” of attitudes, values, and preferences, which might influence an individual’s propensity to choose automobile or air travel for medium- or long-distance trips. Results: Five Market Segments Revealed The market segmentation modeling process revealed five clearly identifiable market segments, and an additional group that defied clear categorization. Of the five clear segments, over 50% of the sample ended up in essentially pro-air-travel categories and about 25% ended up in essen- tially pro-automobile-choice categories, with a conflicted group in between. Figure 5-2 shows the relative size of these five market segment groups. The following descriptions and characteristics of the segments are for illustrative purposes only and are probabilistic rather than deterministic, meaning that the descriptions do not necessarily apply to all members of a cluster. For instance, even though the Ardent Plane Adherents segment contains a large portion of employed individuals, not all members of this segment are employed. Likewise, even though the Ardent Automobile Lovers includes a disproportionally sizeable percentage of respondents who chose a car for their trips in the past years, not all did. Ardent Plane Adherents (29%) The largest segment identified in the sample are Ardent Plane Adherents. This group of travelers includes many employed, high-earning, and single individuals with no children for whom being connected to their smartphone or laptop is of greater importance than access to their car. Ardent Plane Adherents report a high ratio of business (as compared to leisure) trips.

70 Air Demand in a Dynamic Competitive Context with the Automobile As a group that travels primarily alone for business, flying is second nature and the go-to mode for their travel needs. As seasoned flyers, they are comfortable on the plane and “true believers” in air travel. They perceive it to be easy to get to and from the airport, are satisfied with the schedules offered by the airlines, and are not particularly concerned about safety or lack of privacy when flying. Their friends, family, and colleagues reinforce their preference for traveling by plane, as it is also the go-to mode for people in their social circles. Along with this acceptance of air travel comes a deep-seated rejection of and aversion to traveling by car, which has few, if any, redeeming features for them. This group of travelers hates traffic and congestion, finds longer drives unpleasant, thinks that car travel is more exhausting than flying, and rejects any idealistic notion about making a road trip with friends or family members that might be evoked in other people’s minds. Given their attitudes toward traveling by car and plane, it is not surprising that 100% of this group states that they would consider taking a plane for a future trip, and 0% would consider taking a car. Rational Air Travelers (23%) The second largest cluster, Rational Air Travelers, includes high earners and is almost evenly split between men and women. Members of this segment tend to be of middle age and have no children in the household. Rational Air Travelers are likely to travel alone and tend to be the primary decision-makers for their trips. As a group that does not need to accommodate the wishes or needs of fellow travelers, their mode choice is clear: like Ardent Plane Adherents, they strongly prefer to take the plane to driving for their travel needs. Attitudinally, this group shares many views with the Ardent Plane Adherents in that they perceive flying as safe, are familiar with it, are comfortable on the plane, and think that their travel needs are being met by airline schedules. Nonetheless, Rational Air Travelers differ in important ways from Ardent Plane Adherents, most notably in that they lack the deep-seated aversion to the car. In fact, the exact opposite is true: they are the least likely out of all groups to agree that the idea of driving for several days with family friends is unpleasant and, unlike several other groups, they are not Note: Percentages do not add up to 100% because 6% of the sample did not fall into any cluster. Ardent Plane Adherents Rational Air Travelers Rational Car Travelers Ardent Automobile Lovers Ambivalent Adapters Figure 5-2. The five market segments revealed in the latent class clustering.

The Role of Attitudes Toward Long-Distance Trips in Mode Choice 71 particularly irritated by traffic congestion. Thus, this group does not reject driving or traveling by car in general terms—they just do not perceive it as a good option for this trip, that is, their preference for taking the plane is based on the pragmatic realization that taking the plane for medium- or long-distance trips is a more relaxing, faster choice. Ambivalent Adapters (18%) The youngest, most diverse group among the identified groups is Ambivalent Adapters. As a whole, this segment has high employment rates but also the most minors in the household; they are caught between the competing demands of their work lives and their home lives. Perhaps as a result, they are the group most likely to adapt their mode choice to a situation and are most likely to consider both the car and the plane. However, the choice between flying and driving can best be described as “picking the lesser of two evils,” as they perceive plenty of negatives with both modes. For instance, they perceive themselves to be less dependent on automobiles than their parents; they have little emotional attachment to the car; and they like the idea of borrowing, sharing, or renting a car rather than buying one. They also do not find day trips by car with friends and family particularly appealing and have a strong dislike for traffic congestion. Again, this is not to say that they are unabashed fans of air travel—quite the contrary. They worry about personal safety when flying, do not like going through security at the airport, and dislike the lack of privacy on airplanes. Ambivalence about taking the car versus the plane is reflected in this group’s actual mode choices over the past year. Approxi- mately 46% of all the trips they report were taken by plane. This segment is in the middle, between Ardent Plane Adherents (who took the plane for 76% of their trips) and Ardent Automobile Lovers (who only took 18% of their trips by plane). Rational Car Travelers (16%) Rational Car Travelers tend to drive rather than fly. Their choice is determined by the perceived advantages of driving and pragmatism rather than by an aversion to flying. These individuals are not particularly bothered by the downsides of flying that other people asso- ciate with this mode. For instance, they are the least likely to be worried about security and disturbing behavior on a plane and do not particularly mind going through airport security or experiencing crowds at the airport. However, the specific needs of their trip make the car the more logical choice. Rational Car Travelers tend to travel with other people rather than alone, are the most likely to have a car available for their trips, and think that they need the flexibility of a car at their destinations. In addition, this group enjoys taking road trips with others and is the least likely to be bothered by traffic, all of which make driving the logical choice for their travel needs. Ardent Automobile Adherents (8%) Ardent Automobile Adherents are an older group of individuals on a fixed income; the group includes a high percentage of retirees and few currently employed individuals relative to the other groups. The travel needs of this group tend to be focused on longer trips with other people for leisure. The choice for how they get to their destination is clear to them; they cannot imagine living without a car, enjoy taking road trips with family members, and think that they need a car once they are at their destination. To them, taking the car is the only option because, unlike the Rational Car Travelers, they have a strong aversion to flying and reject air travel. This group hates going through security, does not like the crowds in airports, worries about personal safety and disturbing behavior on planes, laments the lack of privacy on planes, and generally thinks that driving exposes them to less crime and disturbing behavior.

72 Air Demand in a Dynamic Competitive Context with the Automobile An Attitude-Based Model of the Choice Between the Car Trip and the Air Trip Defining the ACRP Project 03-40 SEM for Long-Distance Mode Choice The SEM for Long-Distance Mode Choice has four basic elements. First, it is hypothesized that transportation behavior is influenced by long-term values that may influence the location of the traveler, may influence shorter term attitudes, and may directly influence the choice of long-distance mode. For example, some basic attitudes toward the ownership of a car might influence one’s location decision, might influence short-term attitudes toward a specific trip, and influence the choice or rejection of the automobile for the trip. Location is the second element of the SEM. Higher levels of “urbanity” of a location often imply that a major airport is close by. The “ruralness” of a location is correlated with a longer driving distance to a sizeable airport. In the third element of the model, shorter term attitudes are formed at a time closer to making the modal decision. The idea of finding satisfactory en route lodging for a given multiday automobile trip might be unpleasant for some, while others might not be bothered by it. Some people might feel that “people like me” would always choose to travel by air, while others feel the opposite. The fourth element of the model is the modal choice itself. Figure 5-3 presents a schematic diagram of how the three explanatory elements are hypothesized to relate to the outcome factor, “Propensity to Choose Car Trip.” Figure 5-3. Conceptual diagram of the attitude-based choice model.

The Role of Attitudes Toward Long-Distance Trips in Mode Choice 73 The Latent Factors Developed in the Model Using the application of factor analysis and the published literature in this area, four latent factors were developed to represent preferences on issues with a longer term time frame than those concerning the evaluation of a transit trip and its attributes, as shown in Figure 5-3. The three categories here have been developed and applied in other research (RSG et al. 2016, Coogan et al. 2018). Longer Term Values Longer term values include values urbanism, automobile orientation, and values information technology. These are discussed in text that follows. Values urbanism. A latent factor representing preferences for the attributes of “valuing urbanism” in neighborhoods was created with the use of three questions about the importance of walking to a commercial district, being outside with people, and having a mix of people from different backgrounds. Automobile orientation. A latent automobile factor was created representing hedonic considerations (e.g., love for the automobile); an observed variable representing the desire to control one’s own space in the car; and the statement that he/she needs a car to get where he/she needs to go. Values information technology. Finally, the importance of being productive, and staying connected all day was explored in one latent factor based on the two related attitudes, and the level of ownership of devices. Location A latent factor was created with the use of two observed variables: one reflecting the density of intersections (“design”) and one about the distance to the preferred airport. Shorter-Term Attitudes About the Trip—Four Factors Seven latent factors were created in the model to reflect shorter term attitudes and trip conditions. Nineteen variables were used in development of the seven latent factors. Four of the seven factors are discussed below. Cost. A latent factor dealing with the perceived additional cost of the air trip was created with three observed variables. The first sought agreement with the estimate that this trip would be more expensive by plane. The second two were based on (1) the actual airfare per mile and (2) the airfare per hour of driving. Stress due to air travel. Reported attitudes were used for seats on planes being too close, dealing with crowds at the airport, and stress from the airport security procedures, to create the latent factor. Stress due to driving. A latent factor was created from two concerns about roadway congestion. Safety and disturbing behavior were reflected in a latent factor, based on three survey questions, each of which was scaled so that higher values represent higher levels of concern with air travel.

74 Air Demand in a Dynamic Competitive Context with the Automobile Shorter-Term Attitudes About the Trip—Factors from the Theory of Planned Behavior In addition, three more factors were created, which were influenced by (but do not exactly operationalize) the Theory of Planned Behavior, a theory commonly used in the adaptation of principles of social psychology to the subject area of transportation. Affective attitudes toward trip. The first represents the concept of whether a behavior (e.g., choosing to travel by car) is in the interest of the participant and is seen as a pleasant experience. These attitudinal questions are similar to how “Attitude Toward the Behavior” in the Theory of Planned Behavior is usually operationalized. This latent factor was created from three observed variables, two of which concerned the unpleasantness of the drive, and one concerned with the level of uncertainly associated with it. Social support. The next latent factor was created to help explore the influence of normative factors, that is, the extent to which important others would support the participant’s modal decision and whether they travel by that mode. In the Theory of Planned Behavior, this factor is called a subjective norm (and sometimes, a social norm). Control—perceived inconvenience of the trip. The final latent factor was created to reflect the concept that choosing to travel by air might be difficult or even impossible, that is, something that one would not have the control to do. For this latent factor, three observed variables were used that reflect the perceived difficulty or impossibility of going by air, including “the airlines just do not go where I need to go.” Needing a car at the destination and difficulty in getting to the airport are also included in the creation of the latent factor. In the Theory of Planned Behavior, the concept that one may not be able to carry out a behavior is called “Perceived Behavioral Control.” The Outcome Factor: Choice of Mode A latent factor was developed to reflect “The Propensity to Choose Car Trip” (as shown in Figure 5-3), based on a combination of mode selection for the reference trip, for the short- distance trip, and for a summary of all trips mentioned by the survey participant. A complete description of how the observed variables were used in the creation of the latent factors is presented in ACRP Web-Only Document 38. Running the Model The model was run as a SEM, using AMOS Version 22 software, which is part of the SPSS set of modeling software packages. The sample included 4,232 respondents. The final model shows the relationships between and among the 12 latent factors of the model, based on the application of 33 observed variables, as shown in detail in ACRP Web-Only Document 38. The Long-Distance Mode Choice SEM has positive overall evaluative characteristics: the model has a Root Mean Square Error of Approximation of 0.04, where any value below 0.05 is considered a good fit. It has a comparative fit index and a Tucker Lewis Index of 0.95 and 0.93, where values above 0.90 are considered to reflect a good model fit. The model has 33 coefficients, whose unstandardized and standardized coefficients and p values are presented in ACRP Web-Only Document 38. All the coefficients in the model were found to be significant with p values of less than or equal to 0.01, except one, which is under 0.02. Interpreting the Results of the Long-Distance Mode Choice SEM The model is not designed primarily to predict behavior, but rather to contribute to under- standing the relationship between and among factors, given the relationships hypothesized

The Role of Attitudes Toward Long-Distance Trips in Mode Choice 75 in Figure 5-3. SEM models allow the ability to look at the combination of direct and indirect effects of one factor upon another, called the “Standardized Total Effect” (STE). For example, to explain the meaning of the STE, the AMOS software program states: The standardized total (direct and indirect) effect of Automobile Orientation on Car Chosen is −.449. That is, due to both direct (unmediated) and indirect (mediated) effects of Automobile Orientation on Car Chosen, when Automobile Orientation goes up by 1 standard deviation, Car Chosen goes down by 0.449 standard deviations. Focusing on the effects of various factors on the model’s key outcome, choice of mode, shows that the factor concerning the issue of the comparative “expense” of the two modes has the highest STE (at .72). This is shown graphically in Figure 5-4 in horizontal bar chart format, where the explanatory factors are ordered by the scale of their absolute values. Interpreting the SEM Format The data shown in Figure 5-4 can be interpreted in several ways. While the STE is usually expressed in the scale of a 100% increase in the independent factor, a more realistic interpretation can be stated in terms of a 10% increase in the independent explanatory factor. Conclusions include the following: • A 10% increase in the value of the factor “Automobile Orientation” would be associated with a 4.5% increase in the Outcome Factor, “Car Chosen.” • A 10% increase in the value of the factor “(Car) Attitude Unpleasant” would be associated with a 2.6% decrease in the Outcome Factor, “Car Chosen.” • A 10% increase in the value of the factor “Air Trip Stressful” would be associated with 2.2% increase in the Outcome Factor, “Car Chosen.” Comparing the Role of the Factors While the dominance of expense of the modes (expressed in the question as the expense of air) is totally expected, the roles of other factors are noteworthy. The second strongest (ICT = Information and communications technology) -0.4 -0.2 0 0.2 0.4 0.6 0.8 Air Expensive Auto Orientation Car Unpleasant Likes ICT Car Trip Stressful Air Trip Stressful Social Support for Air Air Inconvenient Location More Rural Crime on Air Trip Pro Urbanism Expressed as Standardized Total Effect Figure 5-4. Total standardized effect on mode choice, rank ordered by absolute value.

76 Air Demand in a Dynamic Competitive Context with the Automobile predictor of mode choice is long-term values held by the traveler concerning his/her love of cars and need for one. Beyond the concern for costs, attitudes about the car seem to be more powerful explainers of the outcome than are attitudes about the air trip—with measurement of trips being unpleasant and stressful given higher ranking than equivalent questions about the air experience. In the research team’s interpretation, the SEM shows that the dominant characteristic of air travel is its cost—attributes such as stress at the airport, or poor coverage of destinations (“inconvenient”) simply did not emerge as explanatory factors the way that price did; an increase in air price is strongly associated with an increase in automobile mode share. The horizontal bar chart format of Figure 5-4 reveals the positive and negative characteristics of the STE data. It shows that attitudes toward the automobile are more nuanced: survey responses about one’s love for the freedom and independence provided by automobile ownership emerge as strong factors in the explanation of variance in mode share. At the same time, statements that long trips are unpleasant are part of a factor with strong negative explanatory power. Attitudes toward the automobile seem therefore to be more ambivalent, simultaneously receiving both positive and negative evaluations. In sum, the SEM process suggests that the choice of a long-distance travel mode is the result of a trade-off in the mind of the traveler, in which the price of the air trip is compared with the perceived level of unpleasantness of a long-distance automobile trip. The cost of the air trip is expressed in the top horizontal bar shown in Figure 5-4, while the pluses and minuses of the automobile trip are expressed in the four horizontal bars immediately below. Compared with the explanatory power of these factors, other considerations modeled are revealed to be relatively unimportant.

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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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