First Advisor

Kelly J. Clifton

Term of Graduation

Summer 2020

Date of Publication


Document Type


Degree Name

Master of Science (M.S.) in Civil & Environmental Engineering


Civil and Environmental Engineering




Scooters -- Public opinion, Choice of transportation, Commuting, Urban transportation, City planning



Physical Description

1 online resource (xi, 241 pages)


In just three years, e-scooters have substantially disrupted and altered the urban mobility landscape. Throughout this period, they have been commonly touted as part of a larger micromobility solution that promises to erase equity barriers and solve the first-mile/last-mile problem. However, few studies in the nascent e-scooter literature have considered these claims. In this study, we surveyed students at Portland State University (n = 1,968) about the role that e-scooters, among other modes, played in meeting their general and university-related travel needs. We then estimated models that incorporated demographics, travel behavior, and latent attitudes distilled using exploratory factor analysis (EFA). These models were used to assess the current performance of e-scooters in meeting equity and mode-shift goals.

We first estimated ordinal logit models to understand the relationship of these factors to the stated number of trips taken in the 7 days prior to the survey by e-scooter, car, bike, and MAX light rail. Perceived propensity to switch to using e-scooter, car, bike, or MAX light rail modes for commuting to the university should their present primary commute mode became unavailable. We also designed and implemented a stated choice experiment (SCE) consisting of several hypothetical scenarios of a commute to PSU. In the SCE, students were given a three-mode labelled set consisting of car, bike, and e-scooter + MAX choices. The experiment choice sets were designed using a D-Efficient method. In order to understand the relationship of travel time and cost in addition to the other covariates on mode choice, we estimated a multinomial logit (MNL) model from the experiment data. We used this model to perform a thorough sensitivity analysis to uncover the most impactful factors that encourage first-mile/last-mile e-scooter usage. Additionally, we used the model to generate catchment area maps for e-scooter/MAX multimodal trips in the Portland area based on the most probable mode choice at every point in the city.

In addition to the models, we asked students to indicate barriers that actively prevented them from using non-auto modes more often. We mapped out barrier "hot-spots" in order to understand the current travel realities of the city.

Results were mixed in indicating that e-scooters bring about racial and gender equity in transportation. Additionally, we found that there was no place in the city where taking an e-scooter to connect with MAX to travel to PSU was more preferable (utilitarian) than taking a bike or private car, on average. This suggests that e-scooters are currently not a practical solution to the first-mile/last-mile problem. However, our findings revealed "dials" that can be tweaked through policy measures in order to promote this kind of use. Overall, our critical analysis of the implementation of e-scooters suggests that their promise is overstated, at least without substantial policy changes to encourage desired use cases.


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