Millennials are the largest generation in the current U.S. population. Their travel preferences and choices have profound implications for the travel industry and transportation policy making. The existing literature, however, has presented mixed findings on whether Millennials differ from their preceding generations in vehicle usage, walking or biking, and transit riding. Furthermore, the majority of the existing studies investigated generational travel at the national level; few have explored the spatial variation of generational travel at the subnational scale. This study examines individuals’ modal shares in daily travel by Millennials, Generation X, and Baby Boomers across megaregions. A unique dataset is assembled with national travel surveys from 1977 to 2017, covering the age spectrum from five years to 71 years for the three generations. The study applies multilevel modeling to capture the dynamic effects associated with generational, megaregional, and period variations on individuals’ modal share. Results of the study show the varying trends of modal shares in different life stages between generations. Millennials in adulthood maintain the highest walk/bike share and the lowest share of vehicle travel among all generations. Megaregional variations exert differentiated influences on individuals’ mode share patterns across generation subgroups. The varying trends of modal shares over the age spectrum across generations highlight the importance of having cohort-tailored initiatives to achieve sustainable transportation objectives. The study’s quantification of megaregional and generational variations on modal shares provides useful information for modal split analysis and other transportation planning practices at the level between states and metropolitan areas.


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    Title :

    Generational Patterns of Modal Shares Across Megaregions


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    Li, Yang (author) / Zhang, Ming (author)


    Publication date :

    2022-02-02




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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