Take Into Account Divergent Consumer Segments Across Markets and Privacy Protection to Increase the Likelihood of Adopting Shared Mobility Services.
Impact of Emerging Transportation Technologies and Digital Services on Travel Behavior Is Explored Across Individuals With Varying Socio-Demographic Characteristics in California.
Made Public Date

Panel Study of Emerging Transportation Technologies and Trends in California: Phase 2 Findings


Transportation demand and travel-related decision-making among individuals can be greatly influenced by emerging transportation technologies, changes in sociodemographic composition along with increased availability of modern communication devices like smartphones and access to shared mobility services. This study investigated the relationships among different factors such as individual attitudes and lifestyles, residential location, vehicle ownership, travel behavior, the adoption of shared mobility and attitudes towards adoption of emerging transportation technologies and mobility services in California. In the first phase of this study conducted in 2015, 1,975 residents of California, individuals born in 1980s and 1990s and Generation X (individuals born between 1965 and 1980) were recruited through an online opinion panel. For this second phase of the study the longitudinal component of the research was added through a second wave of data collection by including (i) a total of 1,992 survey respondents (1,620 via mail and 372 online) using stratified sampling by six regions in California (ii) a total of 1,833 survey respondents recruited based on quota sampling by six California regions and neighborhood types (urban, rural, etc.) and (iii) A total of 246 of the 1,975 survey respondents from phase 1. The combined dataset was used to analyze the impacts of emerging technologies and trends, the role of life stages in affecting changes in travel behavior, vehicle ownership, adoption of technology and user responsiveness to introduction of mobility services. The study also highlighted attitudinal and mode-choice differences across generations, for example between Millennials and Generation X.

Lessons Learned

  • Take into consideration divergent consumer segments within the markets for alternative fuel vehicles, automated vehicles and shared mobility. The uniqueness of these customer segments in their choices of vehicle-ownership, residential location and daily travel patterns were characterized by their socio-demographics, latent attitudes, built-environment, local/regional policies and their level of familiarity with emerging technologies. For example, people who were pro-environment, tech-savvy and car utilitarian were more likely to choose Alternative Fuel Vehicles (AFVs) in the future.
  • Consider built environment and employment characteristics of the population while offering shared mobility services. It was found that residents of urban neighborhoods with high employment entropy were more likely to use ride-hailing services compared to those from suburban and rural areas. Safeguarding privacy concerns and a decrease in travel time can increase the likelihood of individuals in such neighborhoods to adopt ride-hailing over individual car ownership.
  • Improve Electric Vehicle (EV) network in neighborhoods to remove people’s psychological barriers. It was found that residents were more likely to adopt AFVs in neighborhoods with higher density of electric vehicles. Moreover, individual’s current user experience in AFV had positive effect on their future interest in AFV. Increasing people’s knowledge and experience of EV, especially those that never used EV before, could be a critical strategy for higher market adoption.
  • Employ pricing strategies to discourage short-distance ride-hailing trips if the goal is to discourage ride-hailing from replacing active modes. The study found that mode-share of ride-hailing services was higher when people were making trips to locations within walkable distance from their homes and individuals living in vibrant and walkable neighborhoods replaced possibly active modes with ride-hailing.
  • Make policies and initiatives targeted towards customers that are Automated-Vehicle (AV) curious. A small nudge instead of massive investments would be required for this group of customers to overcome their initial skepticism towards embracing AVs unlike AV hesitant customers.
Goal Areas
System Engineering Elements