Aduana de Destino

Gender was found to be insignificant in the adoption (or non-adoption) decisions concerning autonomous vehicles under a benefits-dominated market segment. From the marginal effect estimates shown in Table 4-7, Hispanic/black respondents in this market segment are more

extremely likely to adopt autonomous vehicle when they become available in the market, relative

to everyone else. Comparing across generations, belonging to the great generation (1 if respondent is of 65 years or above, 0 otherwise) in a benefits-dominated market segment increases the probability of being unlikely or extremely unlikely to adopt autonomous vehicles when they became available in the market, relative to Gen-X-ers (1 if respondent is between the ages of 35 and 49 years, 0 otherwise).

On the other hand, being a millennial (1 if respondent is under the age of 35 years, 0 otherwise) or a baby boomer (1 if respondent is between the ages of 50 and 64 years, 0 otherwise) in this market segment increases the probability of being extremely likely to adopt an autonomous vehicle when they become available in the market. However, all three of these variables mentioned above vary across the population indicating considerable heterogeneity among Hispanics/blacks, millennials, and baby boomers in a benefits-dominated market segment. These results are interesting to the analyst. Millennials are a significant demographic in determining the course of future technology adoption as they are the largest living generation (Fry, 2016) and are set to dominate the future discussions and discourse on adoption of emerging technologies.

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Table 4-7 Marginal Effects for Significant Parameters in the Benefits-Dominated Market Segment

Variable Description

Marginal Effects Extremely

Unlikely Unlikely Unsure Likely

Extremely Likely Millennial Indicator (1 if respondent is

classified as a millennial, 0 otherwise) -0.0000002 -0.000005 -0.003 -0.055 0.059 Baby Boomer Indicator (1 if respondent is

classified as baby boomer, 0 otherwise) -0.0000004 -0.00011 -0.008 -0.162 0.170 Great Generation Indicator (1 if respondent is

classified as belonging to the great generation, 0 otherwise)

0.000003 0.0005 0.025 0.211 -0.236

Hispanic/Black Respondent Indicator (1 if respondent is classified as Hispanic/black, 0 otherwise) Standard deviation of parameter

-0.000004 -0.00012 -0.010 -0.345 0.355

High Income Household Indicator (1 if respondent belongs to a household that earns an annual income more than $100,000, 0 otherwise) Standard deviation of parameter

-0.0000004 -0.00012 -0.009 -0.152 0.161

Non-Commuter Indicator (1, if respondent

does not commute to work, 0 otherwise) -0.0000003 -0.00009 -0.007 -0.134 0.141 Short Commute Distance Indicator (1 if

respondent travels a one-way distance less than 5 miles for their commute, 0 otherwise)

0.000001 0.00022 0.012 0.129 -0.141

Long Commute Time Indicator (1 if respondent travels 45 minutes or more one- way for their commute, 0 otherwise)

0.0000003 -0.00009 -0.008 -0.197 0.205

Low Parking Time Indicator (1 if respondent spends 5 minutes or less in order to park their vehicle, 0 otherwise)

0.0 0.000002 0.0002 0.003 -0.003

Vehicle Ownership Indicator (1 if respondent is a member of a household that owns more than one vehicle, 0 otherwise)

-0.0000006 0.00017 0.012 0.214 -0.226

Recent Vehicle Purchase Indicator (1 if respondent recently purchased or leased a new vehicle, 0 otherwise)

-0.000001 -0.00033 -0.019 -0.246 0.266

Crash Indicator (1 if respondent has been involved in a traffic crash in the past, 0 otherwise)

-0.0000004 -0.00011 -0.007 -0.09 0.097

The baby boomers, on the other hand, are a generation of respondents who equate owning a car to independence (Ross, 2014). Previous studies have established their relative aversion towards new technologies (Rainie & Perrin, 2016). Therefore, the heterogeneity observed in a benefits-dominated market segment could be significant indicators for the need to avoid

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generalizations across generations. Annual household income was found to be an important indicator on adoption (or non-adoption) decisions regarding autonomous vehicles. High-income households (1 if respondent belongs to a household that earns an annual income more than $100,000, 0 otherwise) in benefits-dominated market segment are more extremely likely to adopt autonomous vehicles when they become available in the market (as shown in Table 4-7).

Several model results show the influence of current travel characteristics on consumers’ adoption (or non-adoption) decisions of autonomous vehicles. For instance, it is interesting to note that respondents who do not commute to work are more extremely likely to adopt autonomous vehicles when they become available in the market. Likewise, respondents traveling 45 minutes or more one-way, on average, for their commute are more extremely likely to adopt autonomous vehicles. However, this behavior is not echoed by respondents who travel a one-way distance of 5 miles or less for their commute trips. Respondents who travel, on average, 5 miles or less for their commute in a benefits-dominated market segment are less extremely likely to adopt autonomous vehicles, relative to those that travel higher commute distances. There is considerable heterogeneity among observations as the variables depicting current travel characteristics in a benefits-dominated market segment are random parameters thereby indicating that not all commuters’ adoption (or non-adoption) behaviors are similar.

Parking seems to have a complex effect on respondents’ adoption (or non-adoption) of autonomous vehicles. Respondents in a benefits-dominated market segment, who spend 5 minutes or less in order to park their vehicle, are less extremely likely to adopt autonomous vehicles when they become available in the market. However, this parameter varies across observations showing considerable heterogeneity among the respondents. Vehicle ownership has an interesting influence on intended adoption of autonomous vehicles in a benefits-dominated market segment. If

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respondent belongs to a household that owns two or more vehicles, they are less extremely likely to adopt autonomous vehicles when they become available in the market. At the outset, these results look counter-intuitive. On closer look, however, it is likely that respondents in households that own a large number of vehicles are likely entrenched in a driving culture. Therefore, they are less likely to be enthused about adopting a technology that takes the pleasure of driving away the driver.

Additionally, respondents in a benefits-dominated, who recently purchased or leased a new vehicle are more extremely likely to adopt an autonomous vehicle when they become available in the market. Most new cars are fitted with advanced safety/automation features that make driver safer, and it’s perhaps an influencing factor for such respondents to invest further in technologies that could potentially reduce crashes by 90% (NHTSA, 2014). Lastly, previous crash experience made respondents more extremely likely to adopt autonomous vehicles when they became available in the market – perhaps indicating an increased emphasis on safety in their driving.