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Journal ArticleDOI

Modeling the Evolution of Ride-Hailing Adoption and Usage: A Case Study of the Puget Sound Region

TL;DR: In this article, the authors provide a basis to understand and quantify changes in ride-hailing services in cities around the world, using publicly available data sources that can be used for understanding and quantifying changes.
Abstract: Ride-hailing services have grown in cities around the world. There are, however, few studies and even fewer publicly available data sources that provide a basis to understand and quantify changes i...
Citations
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11 Feb 2010
TL;DR: The American Community Survey (ACS) as discussed by the authors has been conducted on an ongoing basis for the entire country since 2005 and has been shown to be more accurate than the traditional decennial census.
Abstract: Historically, most demographic data for states and substate areas were collected from the long version of the decennial census questionnaire. A “snapshot” of the characteristics of the population on the April 1 census date was available once every 10 years. The long form of the decennial census has been replaced by the American Community Survey (ACS) that has been conducted on an ongoing basis for the entire country since 2005. Instead of a snapshot in which all of the data are gathered at one time, the ACS aggregates data collected over time, making the results more difficult to interpret. However, the ACS data are updated annually.

691 citations

Journal ArticleDOI
TL;DR: In this paper , the authors examined the factors influencing the frequency of ride-hailing use and the demand for pooled and autonomous vehicle (AV) rides in Australia and found that there is a divide between factors affecting not only the use of using ridehailing in the status quo but also in the future adoption of new services of pooled and AV-based services.
Abstract: While ride-hailing has become ubiquitous in most metropolitan areas, it is still unclear how it prevails in the regional areas, especially after the emergence of new services of pooling or self-driving rides. This paper contributes to this knowledge gap by examining the regional/metropolitan dimension in the factors influencing the frequency of ride-hailing use and the demand for pooled and autonomous vehicle (AV) rides in Australia. Through individual-level survey data, we found that there is indeed a divide between factors affecting not only the frequency of using ride-hailing in the status quo but also in the future adoption of new services of pooled and AV-based services. Using the hybrid discrete choice model, we identify several latent psychological constructs that influence the use of ride-hailing services, namely being pro-technology, pro-pooling, pro-AV, anti-driving and security-cautious traits. Moreover, the results of multivariate models point to different observed and latent characteristics influencing the adoption of pooled and AV ride-hailing services for various trip purposes. In line with the literature, it was found that the socio-demographic characteristics that affect the frequency of use or adopting pooled and AV services in future include gender, age, income, education attainment, employment status, car ownership, and the current travel behaviour. We also found that ride-hailing in Australia has played more as a substitution role for public transport, private car and taxi than as a complementary role or feeder of the public transport system, both in the metropolitan and regional areas.

3 citations

Journal ArticleDOI
TL;DR: In this article , the authors examined the trip purposes, travel time, and origins and destinations of TNC trips recorded in the travel survey to explore how and why residents use TNC services, and explored the associations between TNC adoption, usage, and a series of demographic and socioeconomic variables.
Abstract: Due to the lack of data, there have been limited studies that link TNC (e.g., Uber and Lyft) usage and trips with demographic and socio-economic characteristics of individual customers, especially customers who might be financially vulnerable and lack car access. Using Chicago region’s 2018–19 household travel survey, this paper bridges the gap between TNC usage, trip characteristics, and individual's demographic and socio-economic characteristics. The first analysis examines the trip purposes, travel time, and origins and destinations of TNC trips recorded in the travel survey to explore how and why residents use TNC services. The second analysis uses zero-inflated negative binomial regression to explore the associations between TNC adoption, usage, and a series of demographic and socio-economic variables. Both analyses pay particular attention to financially disadvantaged residents who lack access to private cars. The analyses reveal that TNC use decreases with vehicle ownership. Compared to higher-income carless residents, lower-income carless residents use TNC services more for essential trips, especially during hours with infrequent transit services. For essential TNC trips, lower-income residents likely pay a bigger share of their income than higher-income residents do. The findings have implications on transit planning and transportation benefit programs that aim to integrate TNC services to enhance access for lower-income residents.

3 citations

Journal ArticleDOI
TL;DR: In this article , the authors compared three types of choice-set structures in the context of urban travel mode choice by estimating standard logit and nested logit models to test six hypotheses on the associations of RHS adoption with its determinants.
Abstract: The ride-hailing service (RHS) has emerged as a major form of daily travel in many Southeast Asian cities where motorcycles are extensively used. This study aims to analyze the local context in motorcycle-based societies, which may affect the establishment of travelers’ choice set after the appearance of RHSs. In particular, it empirically compares three types of choice-set structures in the context of urban travel mode choice by estimating standard logit and nested logit models to test six hypotheses on the associations of RHS adoption with its determinants. Revealed preference data of 449 trips from both RHS users and non-RHS users were collected through a face-to-face interview-based questionnaire survey in Hanoi, Vietnam, in December 2020. The results of model estimations revealed: (1) a substitutional effect for two-wheelers but not for four-wheelers, (2) a significant positive influence of car ownership on car RHS adoption but not on motorcycle RHS adoption, (3) significantly high sensitivity to travel time of motorcycle RHS but not of car RHS, (4) a significant negative effect of traffic congestion on car RHS adoption but an insignificant one on motorcycle RHS adoption, and (5) a significant positive association of an individual’s experience in using a smartphone with car RHSs but insignificant association with motorcycle RHSs. Our findings suggest that transportation policies of RHS motorcycles should be different from those of RHS cars because of the heterogeneity in travel behaviors of RHS users between them. They also indicate that the transition from motorcycles to cars as well as the difference in service availability among different types of RHSs should be incorporated into the development of transportation policies in Southeast Asian cities.

2 citations

References
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Journal ArticleDOI
TL;DR: The Unified Theory of Acceptance and Use of Technology (UTAUT) as mentioned in this paper is a unified model that integrates elements across the eight models, and empirically validate the unified model.
Abstract: Information technology (IT) acceptance research has yielded many competing models, each with different sets of acceptance determinants. In this paper, we (1) review user acceptance literature and discuss eight prominent models, (2) empirically compare the eight models and their extensions, (3) formulate a unified model that integrates elements across the eight models, and (4) empirically validate the unified model. The eight models reviewed are the theory of reasoned action, the technology acceptance model, the motivational model, the theory of planned behavior, a model combining the technology acceptance model and the theory of planned behavior, the model of PC utilization, the innovation diffusion theory, and the social cognitive theory. Using data from four organizations over a six-month period with three points of measurement, the eight models explained between 17 percent and 53 percent of the variance in user intentions to use information technology. Next, a unified model, called the Unified Theory of Acceptance and Use of Technology (UTAUT), was formulated, with four core determinants of intention and usage, and up to four moderators of key relationships. UTAUT was then tested using the original data and found to outperform the eight individual models (adjusted R2 of 69 percent). UTAUT was then confirmed with data from two new organizations with similar results (adjusted R2 of 70 percent). UTAUT thus provides a useful tool for managers needing to assess the likelihood of success for new technology introductions and helps them understand the drivers of acceptance in order to proactively design interventions (including training, marketing, etc.) targeted at populations of users that may be less inclined to adopt and use new systems. The paper also makes several recommendations for future research including developing a deeper understanding of the dynamic influences studied here, refining measurement of the core constructs used in UTAUT, and understanding the organizational outcomes associated with new technology use.

27,798 citations

Journal ArticleDOI
TL;DR: In this paper, the authors explore who uses ridesourcing and for what reasons, how the ridesourcing market compares to that of traditional taxis, and how ridesourcing impacts the use of public transit and overall vehicle travel.

833 citations


"Modeling the Evolution of Ride-Hail..." refers background in this paper

  • ...In terms of behavioral survey-based studies, initial work has reported that ride-hailing users are generally younger, more educated, live in urban areas, earn higher incomes, and own fewer cars than the general population (1, 6-9)....

    [...]

Book
17 May 2010
TL;DR: Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives as discussed by the authors, and have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance.
Abstract: It is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on choice

691 citations


"Modeling the Evolution of Ride-Hail..." refers methods in this paper

  • ...We refer the reader to Greene and Hensher (39) for estimation details, which is relatively straightforward using the maximum likelihood inference approach....

    [...]

11 Feb 2010
TL;DR: The American Community Survey (ACS) as discussed by the authors has been conducted on an ongoing basis for the entire country since 2005 and has been shown to be more accurate than the traditional decennial census.
Abstract: Historically, most demographic data for states and substate areas were collected from the long version of the decennial census questionnaire. A “snapshot” of the characteristics of the population on the April 1 census date was available once every 10 years. The long form of the decennial census has been replaced by the American Community Survey (ACS) that has been conducted on an ongoing basis for the entire country since 2005. Instead of a snapshot in which all of the data are gathered at one time, the ACS aggregates data collected over time, making the results more difficult to interpret. However, the ACS data are updated annually.

691 citations

Posted Content
TL;DR: Clewlow et al. as discussed by the authors presented findings from a comprehensive travel and residential survey deployed in seven major U.S. cities, in two phases from 2014 to 2016, with a targeted, representative sample of their urban and suburban populations.
Abstract: Author(s): Clewlow, Regina R.; Mishra, Gouri S. | Abstract: The rapid adoption of ride-hailing poses significant challenges for transportation researchers, policymakers, and planners, as there is limited information and data about how these services affect transportation decisions and travel patterns. Given the long-range business, policy, and planning decisions that are required to support transportation infrastructure (including public transit, roads, bike lanes, and sidewalks), there is an urgent need to collect data on the adoption of these new services, and in particular their potential impacts on travel choices. This paper presents findings from a comprehensive travel and residential survey deployed in seven major U.S. cities, in two phases from 2014 to 2016, with a targeted, representative sample of their urban and suburban populations. The purpose of this report is to provide early insight on the adoption of, use, and travel behavior impacts of ride-hailing.

421 citations


"Modeling the Evolution of Ride-Hail..." refers background in this paper

  • ..., 2018; Dias et al. 2019; and Komanduri et al., 2018). Dias et al. (2019) fused secondary land use and census data to the RideAustin data to draw inferences about the characteristics of frequent ride-hailing users and ride-hailing trip purposes....

    [...]

  • ..., 2018; Dias et al. 2019; and Komanduri et al., 2018). Dias et al. (2019) fused secondary land use and census data to the RideAustin data to draw inferences about the characteristics of frequent ride-hailing users and ride-hailing trip purposes. Wenzel et al. (2019) explored the RideAustin trip data to analyze energy implications of ride-hailing; they estimated that empty trips between servicing rides accounts for 26% of total ride-hailing VMT and the net effect of ride-hailing on energy use is a 41–90% increase compared to baseline, pre-TNC, personal travel....

    [...]

  • ..., 2018; Dias et al. 2019; and Komanduri et al., 2018). Dias et al. (2019) fused secondary land use and census data to the RideAustin data to draw inferences about the characteristics of frequent ride-hailing users and ride-hailing trip purposes. Wenzel et al. (2019) explored the RideAustin trip data to analyze energy implications of ride-hailing; they estimated that empty trips between servicing rides accounts for 26% of total ride-hailing VMT and the net effect of ride-hailing on energy use is a 41–90% increase compared to baseline, pre-TNC, personal travel. The studies mentioned above provide rich insights on the nature of ride-hailing trips and empty VMT. However, to our knowledge, no study has explored the temporal behavioral dynamics of ride-hailing use. Of course, the study of changes in traveler behavior over time relates to considerations of temporal stability (or not) of behaviors, which has been examined extensively within the broad context of temporal transferability of travel demand models (see NASEM, 2012 for an exhaustive review of such temporal transferability studies). Some other studies examine travel behavior variability without necessarily tying to transferability, including Marchetii (1994), Meyer (1999), Wu et al. (2013), Miller and Shalaby (2003), Sharaby and Shiftan (2012), Zhao et al....

    [...]