Beyond the dichotomy: How ride-hailing competes with and complements public transport.
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SUBMITTER: Cats O
PROVIDER: S-EPMC8759690 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundAlcohol consumption is associated with a wide range of adverse health consequences and a leading cause of preventable deaths. Ride-hailing services such as Uber have been found to prevent alcohol-related motor vehicle fatalities. These services may, however, facilitate alcohol consumption generally and binge drinking in particular.ObjectiveThe goal of the research is to measure the impact of ride-hailing services on the extent and intensity of alcohol consumption. We allow these associations to depend on population density as the use of ride-hailing services varies across markets.MethodsWe exploit the phased rollout of the ride-hailing platform Uber using a difference-in-differences approach. We use this variation to measure changes in alcohol consumption among a local population following Uber's entry. Data are drawn from Uber press releases to capture platform entry and the Behavioral Risk Factor Surveillance Systems (BRFSS) Annual Survey to measure alcohol consumption in 113 metropolitan areas. Models are estimated using fixed-effects Poisson regression. Pre- and postentry trends are used to validate this approach.ResultsRide-hailing has no association with the extent of alcohol consumption in high (0.61 [95% CI -0.05% to 1.28%]) or low (0.61 [95% CI -0.05% to 1.28%]) density markets, but is associated with increases in the binge drinking rate in high-density markets (0.71 [95% CI 0.13% to 1.29%]). This corresponds to a 4% increase in binge drinking within a Metropolitan Statistical Area.ConclusionsRide-hailing services are associated with an increase in binge drinking, which has been associated with a wide array of adverse health outcomes. Drunk driving rates have fallen for more than a decade, while binge drinking continues to climb. Both trends may be accelerated by ride-hailing services. This suggests that health information messaging should increase emphasis on the direct dangers of alcohol consumption and binge drinking.
| S-EPMC7875688 | biostudies-literature
Project description:Despite the potential of ride-hailing services to democratize the labor market, they are often accused of fostering unfair working conditions and low wages. This paper investigates the effect of algorithm design decisions on wage inequality in ride-hailing platforms. We create a simplified city environment where taxis serve passengers to emulate a working week in a worker's life. Our simulation approach overcomes the difficulties stemming from both the complexity of transportation systems and the lack of data and algorithmic transparency. We calibrate the model based on empirical data, including conditions about locations of drivers and passengers, traffic, the layout of the city, and the algorithm that matches requests with drivers. Our results show that small changes in the system parameters can cause large deviations in the income distributions of drivers, leading to an unpredictable system that often distributes vastly different incomes to identically performing drivers. As suggested by recent studies about feedback loops in algorithmic systems, these short-term income differences may result in enforced and long-term wage gaps.
| S-EPMC7162900 | biostudies-literature
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.
| S-EPMC8377752 | biostudies-literature
Project description:This article examines the impact of the COVID-19 pandemic on ride-hailing drivers in Africa. It argues that though ride-hailing offers paid-work to some African workers, the commodified and informalised nature of this work results in poor job quality. The effects of which are greatly amplified during the pandemic. Drawing on a mixed methods approach: in-depth interviews with ride-hailing drivers in Nairobi and digital ethnography, it also provides a narrative of 'hustle' to outline strategies of resilience, reworking, and resistance among informal workers. It concludes by highlighting the need for adequate regulatory frameworks and on-the-ground solidarity networks to ensure decent working conditions and to push back against precarity in the gig economy.
| S-EPMC9111704 | biostudies-literature
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.
| S-EPMC8259384 | biostudies-literature
Project description:IntroductionThis study aimed to explore the factors influencing people's utilization of ride-hailing services, particularly in the context of the COVID-19 pandemic.MethodsA two-stage survey was conducted among the same group of passengers pre and post COVID-19 pandemic, resulting in a total of 670 valid samples. Exploratory factor analysis (EFA) was applied to the data, followed by the ordered probit and ordered logit models to identify the motivational factors behind passengers' frequency of using ride-hailing.ResultsThe findings indicated that trust and loyalty were the most influential factors in determining passengers' frequency of using ride-hailing services. However, passengers' perception of the COVID-19 pandemic did not have a significant effect on the frequency of using ride-hailing.DiscussionThis research provides empirical evidence and policy implications for understanding people's usage of the ride-hailing services in the context of public-health emergency.
| S-EPMC9909234 | biostudies-literature
Project description: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.
| S-EPMC5993247 | biostudies-literature
Project description:Even though our knowledge of the cause of disease and disability has grown, stigma still exists. Weiner, Perry, and Magnusson's seminal study on attributions of stigma has been cited over 500 times since its publication in 1988. The current research sought to replicate and expand this literature in two studies. We used the 10 stigmas from the original study and we added six more (representing common psychological and physical stigmas). In the first study, we examined the classification of stigmas using cluster analysis. We found that instead of dichotomizing stigmas into either psychological or physical, attributions of controllability and stability together resulted in four distinct clusters. Although these were mostly consistent with past literature, the fourth cluster included both psychological and physical stigmas and was rated as moderately controllable and moderately stable. In the second study, we examined how information about responsibility shifts causal attributions, emotional responses, and helping behaviors. Information that an individual was responsible for their stigma led to greater attributions of controllability, less positive emotions, and less help compared to information that an individual was not responsible. More interestingly, the no-information control condition was similar to the responsibility information condition for stigmas that fell into the controllable clusters whereas the control condition was similar to the not responsible information condition for stigmas that fell into the uncontrollable clusters. While parsimony is valued, the psychological/physical dichotomy is not nuanced enough to fully capture the variation in stigmas, which in turn has implications for future research on stigma reduction.
| S-EPMC5221656 | biostudies-literature
Project description:The outbreak of the COVID-19 pandemic challenged urban public transport systems to maintain accessibility and service for daily users while adapting to local health and safety regulations. Developing sustainable and resilient urban policies under such crisis conditions requires understanding the different feelings, experiences and expectations of passengers and how these relate to socio-economic inequalities. Drawing on a mixed-method study in Berlin (Germany), Brussels (Belgium), Stockholm (Sweden) and Tallinn (Estonia), we show how the pandemic outbreak has changed both who uses public transport and how users experience their journeys. Challenging the narratives that portray public transport as a place of fear, we find that remaining passengers assess the risk of contagion lower than those who avoided it completely. We argue that promoting resilient public transport requires policies that address the needs of passengers relying on public transport services. Therefore, we question the current policies under the sustainable mobility paradigm for not taking sufficient account of the feelings, experiences and emotions and particularly of transport-dependent users.
| S-EPMC9637532 | biostudies-literature
Project description:BackgroundWe hypothesized that the absence of P25 and the N20-P25 amplitude in somatosensory evoked potentials (SSEPs) have higher sensitivity than the absence of N20 for poor neurological outcomes, and we evaluated the ability of SSEPs to predict long-term outcomes using pattern and amplitude analyses.MethodsUsing prospectively collected therapeutic hypothermia registry data, we evaluated whether cortical SSEPs contained a negative or positive short-latency wave (N20 or P25). The N20-P25 amplitude was defined as the largest difference in amplitude between the N20 and P25 peaks. A good or poor outcome was defined as a Glasgow-Pittsburgh Cerebral Performance Category (CPC) score of 1-2 or 3-5, respectively, 6 months after cardiac arrest.ResultsA total of 192 SSEP recordings were included. In all patients with a good outcome (n = 51), both N20 and P25 were present. Compared to the absence of N20, the absence of N20-P25 component improved the sensitivity for predicting a poor outcome from 30.5% (95% confidence interval [CI], 23.0-38.8%) to 71.6% (95% CI, 63.4-78.9%), while maintaining a specificity of 100% (93.0-100.0%). Using an amplitude < 0.64 μV, i.e., the lowest N20-P25 amplitude in the good outcome group, as the threshold, the sensitivity for predicting a poor neurological outcome was 74.5% (95% CI, 66.5-81.4%). Using the highest N20-P25 amplitude in the CPC 4 group (2.31 μV) as the threshold for predicting a good outcome, the sensitivity and specificity were 52.9% (95% CI, 38.5-67.1%) and 96.5% (95% CI, 91.9-98.8%), respectively. The predictive performance of the N20-P25 amplitude was good, with an area under the receiver operating characteristic curve (AUC) of 0.94 (95% CI, 0.90-0.97). The absence of N20 was statistically inferior regarding outcome prediction (p < 0.05), and amplitude analysis yielded significantly higher AUC values than did the pattern analysis (p < 0.05).ConclusionsThe simple pattern analysis of whether the N20-P25 component was present had a sensitivity comparable to that of the N20-P25 amplitude for predicting a poor outcome. Amplitude analysis was also capable of predicting a good outcome.
| S-EPMC6582536 | biostudies-literature