'There is No Future in it': Pandemic and Ride Hailing Hustle in Africa.
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ABSTRACT:
SUBMITTER: Anwar MA
PROVIDER: S-EPMC9111704 | biostudies-literature | 2022 Apr
REPOSITORIES: biostudies-literature
Publications
'There is No Future in it': Pandemic and Ride Hailing Hustle in Africa.
Anwar Mohammad Amir MA Odeo Jack Ong'Iro JO Otieno Elly E
International labour review 20220422
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 ...[more]
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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: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:Since ride-hailing has become an important travel alternative in many cities worldwide, a fervent debate is underway on whether it competes with or complements public transport services. We use Uber trip data in six cities in the United States and Europe to identify the most attractive public transport alternative for each ride. We then address the following questions: (i) How does ride-hailing travel time and cost compare to the fastest public transport alternative? (ii) What proportion of ride-hailing trips do not have a viable public transport alternative? (iii) How does ride-hailing change overall service accessibility? (iv) What is the relation between demand share and relative competition between the two alternatives? Our findings suggest that the dichotomy-competing with or complementing-is false. Though the vast majority of ride-hailing trips have a viable public transport alternative, between 20% and 40% of them have no viable public transport alternative. The increased service accessibility attributed to the inclusion of ride-hailing is greater in our US cities than in their European counterparts. Demand split is directly related to the relative competitiveness of travel times i.e. when public transport travel times are competitive ride-hailing demand share is low and vice-versa.
| S-EPMC8759690 | 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:A precise, scalable, and computationally efficient mathematical framework is proposed for region-wide autonomous electric vehicle (AEV) fleet management, sizing and infrastructure planning for urban ride-hailing services. A comprehensive techno-economic analysis in New York City is conducted not only to calculate the societal costs but also to quantify the environmental and health benefits resulting from reduced emissions. The results reveal that strategic fleet management can reduce fleet size and unnecessary cruising mileage by up to 40% and 70%, respectively. This alleviates traffic congestion, saves travel time, and further reduces fleet sizes. Besides, neither large-battery-size AEVs nor high-power charging infrastructure is necessary to achieve efficient service. This effectively alleviates financial and operational burdens on fleet operators and power systems. Moreover, the reduced travel time and emissions resulting from efficient fleet autonomy create an economic value that exceeds the total capital investment and operational costs of fleet services.
| S-EPMC10879127 | biostudies-literature
Project description:Pure self-management model, pure aggregation business model and Self-support + aggregation model are three commonly used business modes on ride-hailing platforms. We use an analytical model to study these three business models and give the optimal business model decision of the platform. The research shows that the heterogeneity ratio of drivers, the cost of the platform under the Self-support model, the franchise fee received by the platform under the aggregation model and the dissatisfaction of the original users on the platform play a key role in the selection of the platform's business model. When the difference between the franchise fee under the aggregation mode and the platform cost under the Self-support mode fails to generate positive feedback on the platform profit, the platform should choose the pure Self-support mode. When riders are more sensitive to the heterogeneity of service quality of the platform and user stickiness can be ensured, the platform should choose the pure aggregation business model. When user stickiness can be guaranteed and the cost of the platform under the self-run model is controllable, the platform should choose the Self-support + aggregation business model.
| S-EPMC11369292 | 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: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:IntroductionEmerging and re-emerging infectious diseases continue to pose a severe threat to public health in Sub-Saharan Africa (SSA) and globally. Community-related interventions, such as community e-Health literacy, can contribute to the preparedness to respond effectively to emerging and re-emerging infectious diseases. This study investigated the relationship between e-Health literacy and SSA countries' perceptions of the importance of readiness for potential pandemics.MethodThis cross-sectional study was conducted in sub-Saharan African countries (Nigeria, Rwanda, Burundi, and South Africa) among adults aged 18 years and above between July 2020 and August 2021, respondents were recruited through a non-probability sampling technique. Participants were asked to self-report the perceived importance of 13 items on future pandemic preparedness scored on a 5 Likert-point scale. The four key dimensions of pandemic preparedness were online medical consultation, online courses, messaging for healthcare, and shopping. E-Health literacy was the key exposure. The questionnaire was adapted from a previously validated e-Health literacy scale. Data was collected through a self-administered questionnaire online. Data analysis was done using Stata and descriptive statistics including frequency, proportions, means, and standard deviation were used to summarize variables. Inferential statistics including chi-square and logistic regressions were used to test the significance of association between e-health literacy and pandemic preparedness setting the level of significance at 5%.ResultsA total of 1295 people participated in this study. Roughly half of all participants, 685 (52.90%), were aged between 18 and 29 and 685 (52.90%) were females. The standardised average (SE) e-Health literacy score was 29.55 (0.19). Shopping was perceived as the most important dimension of pandemic preparedness across participating countries (mean (SE) of 3.32 (0.06) and above across all countries for online shopping), while online medical consultation was the least perceived as important (mean (SE) of 2.88 (0.08) or less in two countries for instant health advice from chatbot). In the fully adjusted model, e-Health literacy was associated with 8 out of 13 items of the perceived importance of the pandemic preparedness questionnaire. Those include online consultation with doctors (OR = 1.11, 95% CI 1.02-1.21), telephone health advice (OR = 1.07, 95%CI 1.00-1.15), medicine delivery (OR = 1.04, 95% CI 1.03-1.06), getting medicine prescribed in a hospital visit/follow-up in a community pharmacy (OR = 1.07, 95% CI 1.05-1.10), receiving health information via email (OR = 1.08, 95% CI 1.01-1.17) and via social media (OR = 1.08, 95% CI 1.03-1.14), online shopping (OR = 1.07, 95% CI 1.03-1.11) and instant streaming courses (OR = 1.09, 95% CI 1.02-1.16).ConclusionsThe higher e-Health literacy scores were associated with a higher perception of most elements as important in future pandemic readiness. Strengthening e-Health literacy can be a key element of the preparation for pandemics in SSA countries.
| S-EPMC11681008 | biostudies-literature