First, fulfillment is greater among those in households with at least one car but still fewer cars than adults compared to those with no cars. Their lower average trip-making levels than
households with more cars are accounted for entirely by other demographic differences, such as age and residential location, on average, suggesting that this group is able to fulfill their needs despite owning fewer cars. By contrast, about 70% of the diminished trip-making observed among those in no-car households can be accounted for by demographics, but the rest is unexplained. This potentially reflects unfulfilled desire to engage in activities outside the home, though it may also be related to unmeasured preferences for fewer activities that are not reflected in demographics.
Policy implication: People still need cars, but lower ownership levels may be able to provide sufficient mobility.
Among non-owners, fulfillment is generally greatest among those living in environments consonant with a car-free lifestyle: “urban” community types and the highest-density Census tracts, where (though not measured explicitly) alternatives such as walking and transit and proximate destinations are likely to be richest. This is expected. Interestingly, however, there is little difference in fulfillment between any of the other community types: suburban areas, second cities (which have densities similar to suburban areas but distinctly function as a population and/or employment center within the local area), and truly low-density
town/country areas. This suggests that all of these places are failing (or succeeding) to the same degree as one another in accommodating no-car households. Vehicle use is no less, and actually slightly greater, on average, among non-car-owners living in second cities than in suburban areas (though it is even greater among those in town/country areas).
Policy implication: More places with more of the features of the higher density urban areas are needed in order to make car-free lifestyles truly feasible.
Although which “urban” features would make a difference is beyond the scope
of this research, “second city” community types appear to offer no meaningful improvement over suburban areas for non-car-owners.
Policy implication: The potential importance of vehicle-sharing in enabling incremental reduction in vehicle dependence may be greatest outside of the highest-density urban areas.
As a group, the elderly appear most at risk for transportation-related hardship, with low measures of mobility fulfillment and greater vehicle use — seemingly dissonant from their ownership status. Women also have lower fulfillment, but seemingly only among the elderly and those with children.
Policy implication: Services or policies targeting the mobility of the elderly and children could have particular social benefit.
Vehicle sharing is also especially high among the very young (age 18-24), among whom mobility fulfillment is also high. This suggests successful use of vehicles outside of the traditional model of vehicle ownership, perhaps specific to the typical activities, sociability, technology-use, or cultural orientation of this age group. This is particularly interesting in light of the overall trend toward decreased licensing, ownership, and use among the younger generation (Davis, Dutzik, &
Baxandall, 2012).
Policy implication: The habits of non-owning youth (and perhaps all youth) may serve as a model of the future. Some aspects of their current practices may help inform the design of innovative sharing-enabling services, whether targeting the young or old.
Policy implication: The young may be the most likely early adopters of some types of innovative services, though they might also have access to the greatest array of alternative sources of rides through informal channels and therefore more discriminating about services offered.
Some of the surprising results may reflect people whose living situations or other life
circumstances have not yet adjusted to their vehicle-ownership (or driver) status, or vice versa.
For instance, among non-vehicle-owners, home-ownership is associated with more vehicle use, even after taking into account the residential environment, housing type, ages, and income
levels of the occupants, on the face of it suggesting more access to tangible resources
(apparently leading to rides in cars) than their other demographic attributes would predict. But this group also has less fulfillment, on average, perhaps an indication that ownership (and reluctance to move) have resulted in a living situation that is no longer consonant with their transportation needs. Conversely non-car-owners with limiting medical conditions apparently enjoy greater mobility than expected, perhaps reflecting longer-term adjustment to their circumstances, compared with medically limited car-owners.
Policy implication: Policies designed to ease or accelerate adjustment to car-free living, such as financial incentives that favor leaving a detached single-family home in a low-density environment and moving to a more
accommodating environment, are needed.
Policy implication: Policies designed to help elderly “age in place” may be at odds with this approach, though they could also ameliorate the consequences of living in an otherwise dissonant situation.
Despite the hypothesis that income itself would be an indicator of choice, both for vehicle-ownership level and complementary life circumstances, the results suggest that within ownership strata (which are already related to income but have heterogeneity within them), income has little correspondence to either vehicle use or mobility fulfillment, once residential environment (and other relevant demographic attributes such as age) have been accounted for.
This suggests an equalizing effect of car-free lifestyles for those who are able to live in
consonant built environments. However, other factors emerged as potential indicators of choice versus necessity: Non-car-owners with less educational attainment use vehicles more (seemingly dissonant with their ownership status) and those who cannot drive also use vehicles more with less mobility fulfillment (even after accounting for factors such as age, disability, income, and residential location). This suggests that although not reflected in income per se, there may be
other constraints among non-driving non-owners that affect mobility, which may be an equity concern.
Policy implication: Educational attainment and driving ability are the best indicators of “choice” (versus necessity) among non-owners. Highly educated drivers might be the most likely early adopters of any innovative sharing-enabling services — whether or not they require driving.
Table 51. Summary of the correlates of vehicle use and fulfillment among non-owners
Attribute Vehicle use Mobility fulfillment
Household income Less as income increases, on average, but no difference after accounting for residential location
No difference
Educational attainment Less No difference
Home-ownership More Less
Driver status Less More
Limiting medical conditions More More
Female gender More Less
Age More among 18-24 and 60+ Diminishing with age among 50+
Children No difference Less
Employment No difference No difference
Household size No difference Less if alone, More if 3+ adults
Density Less as increases More as increases
Community type
MSA-level transit score Less More
Modes used
Results regarding the extent and nature of the vehicle-sharing and ride-sharing that is already occurring provide two types of conclusions for policy and marketing. On the one hand, the types of occasions in which vehicle-sharing already occurs point to the circumstances most ripe for innovative services or policies designed to further promote sharing. On the other hand, the types of occasions in which vehicle-sharing is absent point to circumstances in which services or policies might contribute the most value — with potential for profit (if a willing market exists)