National Academies Press: OpenBook

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

Chapter: Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing Mode Choice

« Previous: Chapter 4. The Role of the Automobile in the Future of Smaller American Airports: Leakage from Smaller to Larger
Page 85
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 85
Page 86
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 86
Page 87
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 87
Page 88
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 88
Page 89
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 89
Page 90
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 90
Page 91
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 91
Page 92
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 92
Page 93
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 93
Page 94
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 94
Page 95
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 95
Page 96
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 96
Page 97
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 97
Page 98
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 98
Page 99
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 99
Page 100
Suggested Citation:"Chapter 5. Attitudes Toward the Long-Distance Trip and Their Role in Influencing 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.
×
Page 100

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

71 CHAPTER 5. ATTITUDES TOWARD THE LONG-DISTANCE TRIP AND THEIR ROLE IN INFLUENCING MODE CHOICE 5(A) INTRODUCTION AND STRUCTURE INTRODUCTION Attitudes, values and preferences will impact the choice of mode for the full trip, and they will impact the choice of the airport of departure. Chapter 5 now presents the results of the project’s 2017 survey of such attitudes, values and preferences. STRUCTURE Chapter 5 is presented in three parts. In the first section, we review a wide variety of subject areas concerning attitudes toward transportation and specific modes. Results are graphed to easily allow spotting trends or consistencies 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 market reactions in the choice between air and auto in the long-distance trip. Finally, Chapter 5 presents the results of an extensive attitude-based model which applies Structural Equation Modeling to better interpret the importance of factors beyond times and costs in the choice of the long-distance mode. 5(B) OVERALL ATTITUDE: PEOPLE STILL WANT TO TRAVEL FIGURE 5-1. HEDONIC ATTITUDES ABOUT THE LONG-DISTANCE TRIP, BY DEMOGRAPHIC ATTITUDES TOWARDS THE LONG-DISTANCE TRIP 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 0 0.2 0.4 0.6 0.8 1 1.2 <35 >35 Female Male Less Income More Income In cr ea sin g  Le ve l 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

72 “appealing” about taking a long trip by car, with more positive feelings about the plane than the automobile. Method In the project 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 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 Figures 5-2 through 5-8, 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 wealth is correlated with liking the car trip more. ATTITUDES TOWARD THE AUTO FIGURE 5-2 ATTITUDES TOWARD THE AUTO BY AGE, GENDER, AND INCOME Figure 5-2 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 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, such that Millennials are significantly less likely to attribute freedom and independence to owning a car. Importantly, none of these subgroups prefer to rent or borrow rather than own a car– but Millennials were more positive about the new forms 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, with richer group over 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 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

73 reflected by the lack of difference in support for the concept that ‘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. ATTITUDES TOWARD CONGESTION AND STRESS FIGURE 5-3. ATTITUDES TOWARD CONGESTION ON 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 (Figure 5-3). Individuals with higher income and Millennials especially agree with that statement. Congestion is of more concern to Millennials than to other sub-groups in the sample, both for intra- 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 or reporting discomfort with airport crowds. 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 airports 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

74 FIGURE 5-4. PREFERENCES ABOUT LONG-DISTANCE MODE In Figure 5-4 driving for several days is perceived as being more unpleasant by Millennials compared to 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 is a concern, and that the level of uncertainty associated with a car trips makes them choose the plane. By much smaller margins, females tend to evaluate trips by car more negatively than males, although they do not rise to level of influencing the modal decision. Of all groups, the uncertainty associated with the multi-day auto trip seems to bother the older groups the least. 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 is 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

75 ATTITUDES ABOUT DISTURBING BEHAVIOR IN THE TRIP FIGURE 5-5. CONCERNS ABOUT THE AIR TRIP Note: Three questions in Figure 5-5 regarding disturbing behavior and the safety of air travel were reverse-scored to facilitate interpretation, noted with capital letters Individuals are less concerned about crime and disturbing behavior when traveling by plane compared to by car (Figure 5-5). 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, though individual with lower incomes tended to agree slightly more than those with higher incomes. 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 a whole agree that a plane trip is safer than a trip by car, there are subgroups such as Millennials and individuals with lower income who are less likely to agree. While they tend to agree that the plane trip has less disturbing behavior, Millennials, males and lower income groups are less likely to agree than older age groups, female respondents, and individuals with higher income. Females are more likely than males to worry about traveling with people they do not know, as are individuals with lower income. Millennials, compared to older individuals, are less worried about travel with people they do not know. 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 I would NOT worry  about personal  safety or  disturbing  behavior if I went  by plane To me, taking a trip  by air is MORE safe  than taking that  trip by car.  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

76 PREFERENCES AND CHOICE OF THE AIR TRIP FIGURE 5-6. PREFERENCES FOR FLYING Most Americans would prefer to fly for their trips over 300 miles, as shown in Figure 5-6. This especially holds for females, those with higher income, and for younger individuals compared to males, those with lower income, and those over 35. These subgroup differences also emerge for the belief that peers would choose air travel, with the exception that there are no gender differences in this regard. When asked the more abstract question about whether they would continue to travel by air if driverless cars were to become reality, most individuals respond affirmatively, with the exception of Millennials, who state that they would be less likely to choose air over autonomous cars. IMPLICATIONS FROM THE ATTITUDINAL DATA While the prior discussion of results focused on differences between demographic subgroups, it is important to keep the overarching similarities in mind: all subgroups would rather fly than drive, and all groups show some agreement that the air trip is safe, and that the issue of disturbing behavior is not a major concern with air travel. Getting through airport security and the issue of crowding at airports does not rise to be 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 one day” is perceived as moderately unpleasant by most, all but one subgroups (Millennials) reported liking driving with friends and family— with all groups finding some level of ‘appeal’ about a road trip. Some demographic patterns were consistent, with males more positive about driving than females, with lower income respondents less worried about the long-distance trip than respondents with higher income. Within an overall pattern of trip approval, younger individuals tend to worry more about personal safety and disturbing behavior than those older individuals. Young individuals were also more worried about the details of finding lodgings on the way and paying for it. Consistent with expectations, younger respondents also reported a higher usage and 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

77 need for information and communication technologies, and Millennials consistently gave lower ratings to the various concepts of auto dependence and auto need. 5(C) MARKET SEGMENTATION BY ATTITUDE AND BEHAVIOR PURPOSE AND METHOD The potential markets for long-distance travel, (including air and auto), can be analyzed 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 marketers to understand different motivations for market behavior by different segments. This section of Chapter 5 now summarizes the market segmentation process, presents the five groups revealed in the process, and summarizes the groups’ characteristics. Market segmentation 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 categories 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 personality 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 more strongly by a particular set of attitudes toward, for example, 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 this case, the preference for choosing the car or the plane as a mode 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. In order to find the most appropriate number of segments, which variables to include in the model, and model fit, standard statistical tests are applied. 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 represent “building blocks” of attitudes, values, and preferences, which might influence an individual’s propensity to choose an 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 which defied clear categorization. Of the five clear segments, over 50%

78 of the sample ended up in essentially pro-air travel categories, about 25% in essentially pro-auto choice, with a conflicted group in between. Figure 5-7 shows the relative size of these five market segment groups. FIGURE 5-7. THE FIVE MARKET SEGMENTS REVEALED IN THE LATENT CLASS CLUSTERING

79 Note: Percentages do not add up to 100% because 6% of the sample did not fall into any cluster. 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 Devoted Car Adherents comprises a disproportionally sizable 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 (compared to leisure) trips. 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” of 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 the preference for taking the plane, as it is also the go-to mode for 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: They hate traffic and congestion, find longer drives unpleasant, think that car travel is more exhausting than flying, and reject any idealistic notion that making a road trip with friends or family members might evoke 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 the plane for a future trip, and 0% would consider taking the car. Rational air travelers (23%) The second largest cluster, Rational Air Travelers, includes high earners, almost evenly split between men and women, and tend to be of middle age with 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 wishes or needs of fellow travelers, their mode choice is clear: like Ardent Plane Adherents, they strongly prefer to take the plane over driving for their travel needs. Attitudinally, this group shares many views with the first cluster in that they perceive flying as a safe, are familiar with it, are comfortable on the plane, and think that their travel needs are being met by airline schedules. However, 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

80 days with family friends is unpleasant and, unlike several other groups, they are also not particularly irritated by traffic congestion, either. 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%) Ambivalent Adapters is the youngest, most diverse group among the identified groups. As a whole, this segment has high employment rates but also the most minors in the household; they are caught between competing demands of balancing their work lives with 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 and have little emotional attachment to the car as they like the idea of borrowing sharing or renting are 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. The ambivalence about taking the car versus the plane is reflected in their actual mode choices over the past year: approximately 46% of all the trips they report were in a plane. This segment is in the middle, between devoted plane Adherents (who took the plane for 76% of their trips) and devoted car Adherents (who only took 18% of their trips by plane). Rational auto travelers (16%) Rational Auto 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 associate 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 the crowds at the airport. However, the specific needs of their trip make the car the more logical choice: Rational Auto 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, they enjoy taking road trips with others and are the least likely to be bothered by traffic, all of which make driving the logical choice for their travel needs. Ardent auto adherents (8%) Ardent Auto Adherents are an older group of individuals on a fixed income; the group

81 includes a high percentage of retirees and few currently employed individuals relative to the other groups. Their travel needs tend to center around longer trips with other people for leisure and 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 the car once at the destination. To them, taking the car is the only option because, unlike the Rational Auto Travelers, they have a strong aversion to flying and reject air travel: They hate going through security, do not like the crowds in airports, worry about their personal safety and disturbing behavior on plane, lament the lack of privacy on planes, and generally think that driving exposes them to less crime and disturbing behavior. 5(D) AN ATTITUDE-BASED MODEL OF THE CHOICE BETWEEN THE CAR AND THE AIR THE ACRP STRUCTURAL EQUATION MODEL FOR LONG-DISTANCE MODE CHOICE Defining the model The Structural Equations Model of Long-Distance Mode Choice has four basic elements. It is hypothesized transportation behavior is influenced by long-term values, which may influence the location of the traveler; they may influence the 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 the specific trip, and influence the choice or rejection of the auto for the trip. Location is the second element of the SEM model. Higher levels of ‘urbanity’ of a location often imply that a major airport is close by; the ‘ruralness’ of a location is correlated with 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. For a given trip, the idea of finding satisfactory en-route lodging for the multi-day auto trip might be unpleasant for some, while others might not be bothered by it. Some people might feel that ‘people-like-them’ would always choose the air, while others feel the opposite. The fourth element of the model is the modal choice itself. Figure 5-8 presents a schematic diagram of how the three explanatory elements are hypothesized to relate to the outcome factor, “Propensity to Choose Car Trip.” 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, shown in Figure 5-8. CONCEPTUAL DIAGRAM OF THE ATTITUDE-BASED CHOICE MODEL

82 The three categories here have been developed and applied in other CRP studies including NCRRP Report 4,29 and TCRP Research Report 201.30 Longer term values 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. Auto Orientation. A latent auto factor was created representing hedonic considerations (e.g., love for the auto); 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. FIGURE 5-8. CONCEPTUAL DIAGRAM OF THE ATTITUDE-BASED CHOICE MODEL 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. 29 NCRRP Report 4, Intercity Passenger Rail in the Context of Dynamic Travel Markets, National Cooperative Rail Research Program, Transportation Research Board, Washington DC, 2016. 30 TCRP Research Report 201, Understanding Changes in Demographics, Preferences, and Markets for Public Transportation, Transportation Research Board, Washington DC, 2018

83 Location A latent factor was created with the use of two observed variables: one reflecting the density of intersections (‘design’), one about the distance to the preferred airport. Shorter term attitudes about the trip Seven latent factors were created in the model to reflect shorter term attitudes and trip conditions. A total of 19 variables were used in development of the seven latent factors. 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 a) 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. 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 this behavior (e.g. choosing the 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 about 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, to what extent 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 Subjective Norm (and sometimes, 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 which 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 of getting to the airport are also included in the creation of the latent factor. In the Theory of

84 Planned Behavior, the concept that one may not be able to carry out the 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 used in Figure 5-8, which was 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 the Technical Appendix. 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 the Technical Appendix. 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 the Technical Appendix. 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 STRUCTURAL EQUATION MODEL The model is not primarily designed to predict behavior, but to contribute to understanding of the relationship between and among factors, given the relationships hypothesized in Figure 5-8. 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 Standardize Total Effect, the AMOS software program states: “The standardized total (direct and indirect) effect of Auto Orientation on Car Chosen is - .449. That is, due to both direct (unmediated) and indirect (mediated) effects of Auto Orientation on Car Chosen, when Auto 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, it becomes clear that the factor concerning the issue of the comparative “expense” of the two modes has the highest STE (at .72), as shown graphically in Figure 5-9 in horizontal bar chart format, where the explanatory factors are ordered by the scale of their absolute values.

85 FIGURE 5-9. TOTAL STANDARDIZED EFFECT ON MODE CHOICE, RANK ORDERED BY ABSOLUTE VALUE (ICT = INFORMATION AND COMMUNICATIONS TECHNOLOGY) INTERPRETING THE SEM FORMAT The data shown in Figure 5-9 can be interpreted in several ways. While the standardized total effect 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. For example, the table shows that:  A 10% increase in the value of the factor “Auto 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 long-term values held by the traveler concerning his/her love of, and need for, cars emerge as the second strongest predictor of mode choice. 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 our interpretation, the SEM model shows that the dominant characteristic of air travel is its cost – attributes about stress at the airport, or poor coverage of destinations (“inconvenient”) simply did not emerge as explanatory factors the way that price does; an increase in air price is strongly associated with an increase in auto mode share. The horizontal bar chart format of Figure 5-9 reveals the positive and negative characteristics of the STE data. It shows that ‐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 Standarized Total Effect

86 attitudes toward the auto are more nuanced: survey responses about one’s love for the freedom and independence from auto 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 auto seem therefore to be more ambivalent, simultaneously receiving both positive and negative evaluations. In sum, the SEM modeling process suggests that the choice of the long-distance 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 perceived level of unpleasantness of the long-distance auto trip. The cost of the air trip is expressed in the highest horizonal bar in Figure 5-9, while the pluses and minuses of the auto 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.

Next: Chapter 6. Methods We Used in This Project »
Air Demand in a Dynamic Competitive Context with the Automobile Get This Book
×
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

TRB’s Airport Cooperative Research Program has released a pre-publication version of ACRP Research Report 204: Air Demand in a Dynamic Competitive Context with the Automobile. The report establishes a new approach to the analysis of future consumer demand for shorter distance air travel in comparison with travel by automobile.

According to the report, future demand for shorter-range airline trips is both volatile and unstable, affected by changes in technology as well as consumer preferences. Through application of new research tools that support scenario analysis, the report suggests that evolving automobile technology could diminish demand for shorter-range air trips, both in terms of distance to ultimate destination as well as access to larger airports.

Alternatively, changes in aircraft technology could increase demand for short-distance air travel by creating improvements that decrease operating cost of short flights. Most probably, the future will bring changes affected by both emerging trends.

The report may 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 larger airport versus a longer automobile drive bypassing the smaller airport, traveling directly to a larger airport.

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!