Ridehailing, uncertainty and sustainable transportation
Cite this dataset
Pike, Susan (2021). Ridehailing, uncertainty and sustainable transportation [Dataset]. Dryad. https://doi.org/10.25338/B87G9W
Abstract
This study investigates how stakeholders throughout the state of California view the potential impacts of ridehailing services such as Uber or Lyft, to transportation systems, and how to address such impacts. Ridehailing is one of several emerging shared use mobility alternatives, poised to impact transportation systems, for better or worse. For better if these new services catalyze the development and maturation of well-integrated multi-model transportation systems that serve all travelers and reduce vehicle miles travelled (VMT) and transportation emissions. For worse if these new services serve merely as a less expensive taxi, allowing more people to forego alternative modes of transportation like public transit and biking, thereby leading to increases in VMT and emissions and worsening congestion impacts. The high degree of uncertainty surrounding the impacts of these services presents challenges to stakeholders involved in transportation planning and policymaking. How transportation stakeholders view the potential positive and negative impacts of ridehailing and what to do about them is an open question, and one that warrants investigation as these services become more popular and their impacts begin to be understood. Through interviews, we investigate the viewpoints of 42 transportation stakeholders throughout the state of California. We find the diversity of interviewees is reflected in the sentiments they have about ridehailing, what issues are important and potential obstacles to achieving positive outcomes. Nonetheless, interviewees agree that regulations should balance local control with state level guidance.
Methods
This dataset consists of a portion of interview data collected in January through March of 2018; for each interviewee discussions related to perspectives on uncertainty have been identified and included in this dataset.
This data was collected through semi-structured interviews by phone with 42 stakeholders involved in transportataion planning or policy from state, regional and local agencies as well as public interest groups or non-profits. Each interview was recorded and transcribed, and then the content was coded using a confirmatory method.
The entire interview for each participant was coded, and the codes for each interview are entered into datasets in two ways. First, each interviewee is represented as a row, with columns included for every possible code and binary indicators (0 = not present, 1 = present) are used to denote whether or not each participant had a portion of their interview coded in that way. In addition, a second form of the dataset was produced, in which each row represents a single code from one interview; this format includes every code for each interview and each interview appears multiple times - one for each code assigned to a part of their interview. In addition to the list of codes, snippets of text are included that represent the portion of the interview for which the code was assigned.
Each interviewee is assigned an ID number which also indicates the type of participant; city, mpo, etc. The data is stripped of all identifiable information.
Usage notes
This data is the information from our interviews used in the preparation of one paper and one report for this project. Because this data was collected from interviews, it appears incomplete in the format attached here. The data included here was used in the analysis for a paper and related report. As we complete more analysis, additional portions of the data will be made available, and eventually the full dataset, along with complete or near complete transcriptions of the interviews.
Funding
California Department of Transportation, Award: Caltrans 65A0686 Task Order 013 USDOT Grant 69A3551747114