Dataset Information

An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective.

ABSTRACT: Using data provided by a ride-hailing platform, this paper examines the factors that affect taxi driver response behavior to ride-hailing requests. The empirical investigation from a driver's perspective is of great importance for ride-hailing service providers, given that approximately 40% of the hailing requests receive no response from any driver. To comprehensively understand taxi driver response behavior, we use a rich dataset to generate variables related to the spatio-temporal supply-demand intensities, the economic incentives, the requests' and the drivers' characteristics. The results show that drivers are more likely to respond to requests with economic incentives (especially a firm subsidy), and those with a lower spatio-temporal demand intensity or a higher spatio-temporal supply intensity. In addition, drivers are more likely to respond to requests involving rides covering a greater geographical distance and to those with a smaller number of repeated submissions. The drivers' characteristics, namely, the number of requests received and the number of requests responded, however, have relatively little impacts on their response probability to the current request. Our findings contribute to the related literature and provide managerial implications for ride-hailing service providers.

SUBMITTER: Xu K

PROVIDER: S-EPMC5993247 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective.

Xu Ke K Sun Luping L Liu Jingchen J Wang Hansheng H

PloS one 20180608 6

Using data provided by a ride-hailing platform, this paper examines the factors that affect taxi driver response behavior to ride-hailing requests. The empirical investigation from a driver's perspective is of great importance for ride-hailing service providers, given that approximately 40% of the hailing requests receive no response from any driver. To comprehensively understand taxi driver response behavior, we use a rich dataset to generate variables related to the spatio-temporal supply-dema ...[more]

PMID: 29883478

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Project description:ObjectiveNightclub patrons who consume alcohol and drugs in these venues would appear to be an important population to target with on-demand ride hailing app (RHA) services to reduce drunk/drugged driving (DUI). The present study is an exploratory examination of RHA use to avoid DUI behavior, as well as the perceived barriers and benefits of such RHA use, among young adult nightclub patrons in Miami who use drugs.MethodsCompleters of a 2011-2015 randomized controlled trial of brief interventions to reduce health risk behaviors among young adult nightclub patrons were recruited to participate in a single self-administered computer-assisted interview about health risks, driving behaviors, and RHA perceptions and use. Recruitment (N = 123) began in June 2016 and ended in July 2017. Bivariable logistic regression and ANOVA models examined group differences between: (a) those who had used an RHA to avoid DUI vs. not; and (b) those who used RHAs as their primary mode of transportation to nightclubs vs. not.ResultsAbout half were female (52.8%); median age was 29; 59.4% Hispanic, 31.7% Black, 8.1% white, 0.8% other race/ethnicity. Recent alcohol and marijuana use were almost universally endorsed, and more than half reported recent use/misuse of cocaine (72.4%), MDMA (63.4%), and prescription benzodiazepines (62.6%) and opioids (56.9%). More than 80% reported driving under the influence of alcohol and/or drugs in the past 12 months, and 17.1% experienced a DUI arrest in the prior two years. Almost two-thirds (65.9%) of participants had used an on-demand RHA to avoid DUI, but self-driving or riding in another's car were the most common (76.4%) primary modes of transportation to clubs. RHAs were the primary mode of travel to clubs for 21 (17.1%) respondents. Participants whose friends strongly disapproved of DUI were more than twice as likely to have used RHAs for this reason compared to those who had not done so. Those reporting RHA use to avoid DUI were less likely than others to have driven under the influence in the past 12 months and were somewhat more likely to endorse DUI-related risks. Those who used alternate modes of transportation were more likely than those who used RHAs as their primary mode of transportation to clubs to endorse the expense of RHAs and the lack of RHA drivers near their favorite clubs as barriers to RHA use to travel to nightclubs.ConclusionsThis novel study among a high-risk population points to the potential for on-demand RHAs to reduce DUI behaviors and arrests among young adult nightclub patrons who consume alcohol and/or drugs in the context of the club experience. Our findings point to key educational, peer support, and structural targets for intervention to increase the use of RHAs among this population, specifically, club-based incentives for increasing RHA availability and affordability. Research is needed to fully elucidate the findings of this exploratory study, including potential differences in intervention approaches depending on the location-specific public transportation options.

Project description:BackgroundOnline ride-hailing is a fast-developing new travel mode. However, tobacco control policies on its drivers remain underdeveloped. This study aims to reveal the status and determine the influencing factors of ride-hailing drivers' smoking behaviour to provide a basis for the formulation of tobacco control policies.MethodsWe derived our cross-sectional data from an online survey of full-time ride-hailing drivers in China. We used a survey questionnaire to collect variables, including sociodemographic and work-related characteristics, health status, health behaviour, health literacy and smoking status. Finally, we analysed the influencing factors of current smoking by conducting chi-square test and multivariate logistic regression.ResultsA total of 8990 ride-hailing drivers have participated in the survey, in which 5024 were current smokers, accounting to 55.9%. Nearly one-third of smokers smoked in their cars (32.2%). The logistic regression analysis results were as follows: male drivers (OR = 0.519, 95% CI [0.416, 0.647]), central regions (OR = 1.172, 95% CI [1.049, 1.309]) and eastern regions (OR = 1.330, 95% CI [1.194, 1.480]), working at both daytime and night (OR = 1.287, 95% CI [1.164, 1.424]) and non-fixed time (OR = 0.847, 95% CI [0.718, 0.999]), ages of 35-54 years (OR = 0.585, 95% CI [0.408, 0.829]), current drinker (OR = 1.663, 95% CI [1.526, 1.813]), irregular eating habits (OR = 1.370, 95% CI [1.233, 1.523]), the number of days in a week of engaging in at least 10 min of moderate or vigorous exercise ≥3 (OR = 0.752, 95% CI [0.646, 0.875]), taking the initiative to acquire health knowledge occasionally (OR = 0.882, 95% CI [0.783, 0.992]) or frequently (OR = 0.675, 95% CI [0.591, 0.770]) and underweight (OR = 1.249, 95% CI [1.001, 1.559]) and overweight (OR = 0.846, 95% CI [0.775, 0.924]) have association with the prevalence of current smoking amongst online ride-hailing drivers.ConclusionThe smoking rate of ride-hailing drivers was high. Sociodemographic and work-related characteristics and health-related factors affected their smoking behaviour. Psychological and behavioural interventions can promote smoking control management and encourage drivers to quit or limit smoking. Online car-hailing companies can also establish a complaint mechanism combined with personal credit.

Dataset Information

An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective.

Publications

An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective.

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