THE SCHOOL OF CITY AND REGIONAL PLANNING

GEORGIA INSTITUTE OF TECHNOLOGY

Under the provisions of the regulations for the degree

DOCTOR OF PHILOSOPHY 

on Thursday, July 28, 2016
1:00 – 3:00 PM
in Economic Development Building 235 (next to CGIS/CQGRD)

will be held the

DISSERTATION PROPOSAL DEFENSE
 
for
 
Yongsung Lee

"Will Millennials Stay in Cities and Live without Cars? An Analysis of Current and Future Choices of Residential Location and Travel Behavior"

The Examiners Are:

Dr. Subhro Guhathakurta, Chairperson
Dr. Tim Welch, School of City and Regional Planning

Dr. Giovanni Circella, School of Civil and Environmental Engineering

Dr. Patricia Mokhtarian, School of Civil and Environmental Engineering

Faculty and students are invited to attend this examination.

Abstract:

The Millennial generation, which comprises young adults who were born between the early 1980s and 2000, is increasingly reported to prefer residential locations in cities, or denser suburban neighborhoods, own fewer cars, and make more non-motorized trips than older cohorts. In addition, millennials tend to postpone marriage, childbearing, and homeownership, tend to pursue more high education and often struggle in positioning themselves in the job market. What is less clear, to date, is what factors are behind these trends. Previous studies suggest that millennials’ behaviors might be explained by either economic factors (and temporary struggles) or cultural/attitudinal differences from previous generations. According to the “economy-centered” theories, it is likely that millennials would move to lower-density auto-oriented suburban neighborhoods, once they pay back their student loans, improve their economic conditions, and move on with their stages of life. In contrast, other researchers have highlighted that the trends in declining auto use and increasing walking, biking and use of transit of young adults predate the recent economic recession of several years, and therefore may be mainly attributable to non-economic factors. Accordingly, the “culture-centered” theories predict that even when Millennials reached economic stability, they would continue to make different decisions from the members of the previous generations in terms of their residential location choices, and dependency on automobiles. Since these two explanations provide policy implications in different directions, planners are seeking to understand better whether Millennials’ urban resurgence will be transformative in the future.

The literature offers few clues about the future choices of Millennials: in particular, qualitative characteristics such as attitudes and preferences are often attributed an important role in explaining millennials’ behavior. Unfortunately, information about these variables is often missing in most travel surveys, including the National Household Travel Survey (NHTS) data used in many studies. A relatively small number of academic papers employed focus group interviews and data collected through in-depth surveys with questions on values, perceptions, and preferences of Millennials on automobiles and driving. However, the samples in these papers are often quite small, and not representative of the target population.

This study addresses these gaps in the literature by employing a rich set of sociodemographic, economic, and attitude/preference data that was collected from 2,400 millennials and members of the previous Generation X in California with a comprehensive online survey during fall 2015. A quota sampling approach was employed to obtain enough cases from each region (including the less dense and rural areas) of California. For additional information on the survey content and data collection efforts for this project, see Circella et al. (2015). This study attempts to understand (1) the reasons for the “current” residence type and travel patterns, (2) any lagging effects of living in cities on later choices on residential locations and travel mode choice via updating attitudes and preferences, and (3) the aspiration for the “future” residential location (neighborhood type) and expected levels of travel (by mode).