How Do Taxi Drivers Terminate Their Shifts when Earnings Are Hard To Predict?

2020 ◽  
Author(s):  
Florian M. Artinger ◽  
Gerd Gigerenzer ◽  
Perke Jacobs
Keyword(s):  
Author(s):  
Yoshihiko Kadoya ◽  
Somtip Watanapongvanich ◽  
Mostafa Saidur Rahim Khan
Keyword(s):  

2021 ◽  
Vol 10 (2) ◽  
pp. 77
Author(s):  
Yitong Gan ◽  
Hongchao Fan ◽  
Wei Jiao ◽  
Mengqi Sun

In China, the traditional taxi industry is conforming to the trend of the times, with taxi drivers working with e-hailing applications. This reform is of great significance, not only for the taxi industry, but also for the transportation industry, cities, and society as a whole. Our goal was to analyze the changes in driving behavior since taxi drivers joined e-hailing platforms. Therefore, this paper mined taxi trajectory data from Shanghai and compared the data of May 2015 with those of May 2017 to represent the before-app stage and the full-use stage, respectively. By extracting two-trip events (i.e., vacant trip and occupied trip) and two-spot events (i.e., pick-up spot and drop-off spot), taxi driving behavior changes were analyzed temporally, spatially, and efficiently. The results reveal that e-hailing applications mine more long-distance rides and new pick-up locations for drivers. Moreover, driver initiative have increased at night since using e-hailing applications. Furthermore, mobile payment facilities save time that would otherwise be taken sorting out change. Although e-hailing apps can help citizens get taxis faster, from the driver’s perspective, the apps do not reduce their cruising time. In general, e-hailing software reduces the unoccupied ratio of taxis and improves the operating ratio. Ultimately, new driving behaviors can increase the driver’s revenue. This work is meaningful for the formulation of reasonable traffic laws and for urban traffic decision-making.


2020 ◽  
Vol 35 (5) ◽  
pp. 546-553 ◽  
Author(s):  
Canaan J. Hancock ◽  
Peter G. Delaney ◽  
Zachary J. Eisner ◽  
Eric Kroner ◽  
Issa Mahamet-Nuur ◽  
...  

AbstractIntroduction:The World Health Organization (WHO; Geneva, Switzerland) recommends lay first responder (LFR) programs as a first step toward establishing formal Emergency Medical Services (EMS) in low- and middle-income countries (LMICs) to address injury. There is a scarcity of research investigating LFR program development in predominantly rural settings of LMICs.Study Objective:A pilot LFR program was launched and assessed over 12 months to investigate the feasibility of leveraging pre-existing transportation providers to scale up prehospital emergency care in rural, low-resource settings of LMICs.Methods:An LFR program was established in rural Chad to evaluate curriculum efficacy, using a validated 15-question pre-/post-test to measure participant knowledge improvement. Pre-/post-test score distributions were compared using a Wilcoxon Signed-Rank test. For test evaluation, each pre-test question was mapped to its corresponding post-test analog and compared using McNemar’s Chi-Squared Test to examine knowledge acquisition on a by-question basis. Longitudinal prehospital care was evaluated with incident reports, while program cost was tracked using a one-way sensitivity analysis. Qualitative follow-up surveys and semi-interviews were conducted at 12 months, with initial participants and randomly sampled motorcycle taxi drivers, and used a constructivist grounded theory approach to understand the factors motivating continued voluntary participation to inform future program continuity. The consolidated criteria for reporting qualitative research (COREQ) checklist was used to guide design, analysis, and reporting the qualitative results.Results:A total of 108 motorcycle taxi participants demonstrated significant knowledge improvement (P <.001) across three of four curricular categories: scene safety, airway and breathing, and bleeding control. Lay first responders treated 71 patients over six months, encountering five deaths, and provided patient transport in 82% of encounters. Lay first responders reported an average confidence score of 8.53/10 (n = 38). In qualitative follow-up surveys and semi-structured interviews, the ability to care for the injured, new knowledge/skills, and the resultant gain in social status and customer acquisition motivated continued involvement as LFRs. Ninety-six percent of untrained, randomly sampled motorcycle taxi drivers reported they would be willing to pay to participate in future training courses.Conclusion:Lay first responder programs appear feasible and cost-effective in rural LMIC settings. Participants demonstrate significant knowledge acquisition, and after 12 months of providing emergency care, report sustained voluntary participation due to social and financial benefits, suggesting sustainability and scalability of LFR programs in low-resource settings.


2014 ◽  
Vol 68 ◽  
pp. 1-5 ◽  
Author(s):  
Sharon Newnam ◽  
Wondwesen Girma Mamo ◽  
Getu Segni Tulu

2014 ◽  
Vol 57 (12) ◽  
pp. 1377-1385 ◽  
Author(s):  
Barbara J. Burgel ◽  
Marion Gillen ◽  
Mary C. White
Keyword(s):  

2008 ◽  
Vol 198 (2660) ◽  
pp. 20-21
Author(s):  
Sue Chinn
Keyword(s):  

Sangyo Igaku ◽  
1989 ◽  
Vol 31 (3) ◽  
pp. 162-175 ◽  
Author(s):  
Teruko UEDA ◽  
Michiko HASHIMOTO ◽  
Issei YASUI ◽  
Masahiko SUNAGA ◽  
Toshio HIGASHIDA ◽  
...  

2011 ◽  
Vol 16 (1) ◽  
pp. 78-81 ◽  
Author(s):  
Xuan Du ◽  
Lixin Fu ◽  
Weihua Ge ◽  
Shaojun Zhang ◽  
Haikun Wang
Keyword(s):  

2021 ◽  
pp. 1-20
Author(s):  
Eva-Maria Griesbauer ◽  
Ed Manley ◽  
Daniel McNamee ◽  
Jeremy Morley ◽  
Hugo Spiers

Abstract Spatial boundaries play an important role in defining spaces, structuring memory and supporting planning during navigation. Recent models of hierarchical route planning use boundaries to plan efficiently first across regions and then within regions. However, it remains unclear which structures (e.g. parks, rivers, major streets, etc.) will form salient boundaries in real-world cities. This study tested licensed London taxi drivers, who are unique in their ability to navigate London flexibly without physical navigation aids. They were asked to indicate streets they considered as boundaries for London districts or dividing areas. It was found that agreement on boundary streets varied considerably, from some boundaries providing almost no consensus to some boundaries consistently noted as boundaries. Examining the properties of the streets revealed that a key factor in the consistent boundaries was the near rectilinear nature of the designated region (e.g. Mayfair and Soho) and the distinctiveness of parks (e.g. Regent's Park). Surprisingly, the River Thames was not consistently considered as a boundary. These findings provide insight into types of environmental features that lead to the perception of explicit boundaries in large-scale urban space. Because route planning models assume that boundaries are used to segregate the space for efficient planning, these results help make predictions of the likely planning demands of different routes in such complex large-scale street networks. Such predictions could be used to highlight information used for navigation guidance applications to enable more efficient hierarchical planning and learning of large-scale environments.


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