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Understanding Use of Transport Network Companies(TNC) in Virginia

This study deals with a) Understanding familiarity with transportation network companies (TNCs) and their use frequency b) Understanding travel choices in alcohol-related situations in Virginia. Ordered logistic regression models were used to identify factors associated with the respondents perceived familiarity with transportation network companies (TNCs) and use frequency. Based on the two models, the consistent factors were using a mobile wallet, a cell phone for entertainment, an app for taxi services, or an app for hotel booking/air transport arrangements, living in Northern Virginia, normally using multiple transportation modes for a single trip, higher education levels, and higher household income which were associated with increased TNC familiarity and use frequency. Self-identifying as White/Caucasian was also associated with increased TNC use frequency. Increased age was associated with decreasing TNC familiarity and use frequency.

Subsequently, travel choices in alcohol related situations were studied with the objective of understanding the role of Transportation Network Companies (TNCs) in these situations and whether they have an impact on DUIs. For this objective, this study analyzes travel-choices associated with three scenarios alcohol related situations: (a) the last time the respondent consumed alcohol, (b) when avoiding driving after drinking, and (c) when avoiding riding with a driver who had been drinking. Multinomial Logistic Regression models were developed for all the three scenarios. For model (a), significant factors included use of a personal vehicle to arrive at the location where last consuming alcohol, being comfortable with having a credit card tied to a cell phone app, age, income, travelling alone when leaving the location where last consuming alcohol, having the highest educational attainment of high school graduate (GED), consumption of alcohol at bar/tavern/club, consumption of alcohol at home of friends/acquaintance place, and transportation network company (TNC – e.g., Uber, Lyft) weekly use frequency. For (b), use of a personal vehicle to arrive at the location where last consuming alcohol, consumption of alcohol at a bar/tavern/club, consumption of alcohol at the home of friends/acquaintance place, comfort with tying of credit card to apps, age, gender, income, multi-modal travel for a regular trip, TNC weekly use frequency, and use of an app for hotel reservations and/or air transportation arrangements are significant factors. For (c), use of a personal vehicle to arrive at the location where last consuming alcohol, walking to the location where last consuming alcohol, consumption of alcohol at a bar/tavern/club, comfort with tying a credit card to apps, age, income, TNC weekly use frequency, previously riding in a car with a driver who may have drunk too much to drive safely, and being employed full time are the significant factors. / Master of Science / The study intends to improve understanding of the characteristics of early adopters of TNC services and contribute towards understanding travel choices made by individuals in alcohol-related situations. Data for this study came from a telephone survey of just over 3000 respondents across three metropolitan regions of Virginia; Northern Virginia, Hampton Roads/Tidewater and the Richmond urban area.

This study deals with a) Understanding familiarity with transportation network companies (TNCs) and their use frequency b) Understanding travel choices in alcohol-related situations in Virginia. Based on the surveys, ordinal logit models were developed to predict the degree of familiarity and use frequency of TNCs. The results showed that income was significantly associated with both increased familiarity and increased use frequency of TNCs. Educational attainment was also significant and positively associated with familiarity and use frequency. Age was significantly and negatively associated with TNC familiarity and use frequency. This may be important in understanding TNC use in locations with older populations. Individuals located in Northern Virginia were associated with increased TNC familiarity and use frequency. Individuals who used multiple modes to commute had a higher likelihood of being familiar with and using TNCs more frequently. Use of an app for sourcing taxi services was associated with increased TNC familiarity and use frequency. Similarly, using an app for hotel reservations and/or air transportation arrangements was associated with increased TNC use frequency. In addition, individuals using their phone for entertainment were more likely to be familiar with and use TNCs. Use of mobile wallet was associated with increased TNC familiarity and use frequency. Employment status “student” was significantly associated with TNC familiarity which suggests that information is easily accessible for this group of people. Also, individuals self-identifying their race as white had a higher probability of using TNCs.

The second part of the research analysis included multinomial logistic regression models which identified factors associated with respondents’ travel choices in alcohol-related situations: (1) the last time the respondent consumed alcohol, (2) when avoiding driving after drinking, and (3) when avoiding riding with a driver who had been drinking. From the model results, it was found v that consumption of alcohol at a bar was statistically associated with use of TNC services in all three alcohol-related situations. TNCs were more likely to be used by younger people in all three alcohol-related situations examined in this study. Older people were more likely to ride with designated drivers than to use TNCs when avoiding driving after drinking and the last instance of consuming alcohol. Familiarity with, and regular use of TNCs increased the likelihood of using TNCs in all three alcohol-related situations in this study.

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/83896
Date09 July 2018
CreatorsLahkar, Paranjyoti
ContributorsCivil and Environmental Engineering, Hancock, Kathleen L., Murray-Tuite, Pamela Marie, Heaslip, Kevin Patrick
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
Detected LanguageEnglish
TypeThesis
FormatETD, application/pdf
RightsIn Copyright, http://rightsstatements.org/vocab/InC/1.0/

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