Ridesharing as an Alternative to Ambulance Transport for Voluntary Psychiatric Patients in the Emergency Department

Introduction: Emergency department (ED) crowding is a growing problem. Psychiatric patients have long ED lengths of stay awaiting placement and transportation to a psychiatric facility after disposition.Methods: Retrospective analysis of length of ED stay after disposition for voluntary psychiatric patients before and after the use of Lyft ridesharing services for inter-facility transport.Results: Using Lyft transport to an outside crisis center shortens time to discharge both statistically and clinically from 113 minutes to 91 minutes (p = 0.028) for voluntary psychiatric patients. Discharge time also decreased for involuntary patients from 146 minutes to 127 minutes (p = 0.0053).Conclusion: Ridesharing services may be a useful alternative to medical transportation for voluntary psychiatric patients

Uber Effort: The Production of Worker Consent in Online Ride Sharing Platforms

The rise of the online gig economy alters ways of working. Mediated by algorithmically programmed mobile apps, platforms such as Uber and Lyft allow workers to work by driving and completing rides at any time or in any place that the drivers choose. This hybrid form of labor in an online gig economy which combines independent contract work with computer-mediated work differs from traditional manufacturing jobs in both its production activity and production relations. Through nine interviews with Lyft/Uber drivers, I found that workers’ consent, which was first articulated by Michael Burawoy in the context of the manufacturing economy, is still present in the work of the online gig economy in post-industrial capitalism. Workers willingly engage in the on-demand work not only to earn money but also to play a learning game motivated by the ambiguity of the management system, in which process they earn a sense of self-satisfaction and an illusion of autonomous control. This research points to the important role of technology in shaping contemporary labor process and suggests the potential mechanism which produces workers’ consent in technology-driven workplaces

Transportation network companies as cost reduction strategies for paratransit

Paratransit service is an auxiliary type of public transportation provided for people with disabilities and older adults. Federal ADA regulations require all transit agencies receiving federal funding to provide paratransit service, but the per trip cost to transit operators is extremely expensive. Many transit agencies are looking for ways to reduce costs without limiting services. For many agencies, this results in providing the minimum services as required by ADA regulations. However, Boston’s Massachusetts Bay Transit Authority (MBTA) has taken a different approach to cost reduction by entering into one of the first partnerships with transportation network companies. In September 2016, MBTA’s paratransit service, The Ride, began a partnership with both Uber and Lyft as a cost reduction strategy for paratransit provision. Since the beginning of the partnership, MBTA has been able to reduce costs of providing paratransit while maintaining the same level of service. This report will examine the benefits and limitations of such partnerships between transit agencies and transportation network companies, using MBTA’s The Ride partnership as an example for potentially successful partnerships throughout the United States.Community and Regional Plannin

Chapter 13 - Sharing strategies: carsharing, shared micromobility (bikesharing and scooter sharing), transportation network companies, microtransit, and other innovative mobility modes

Shared mobility—the shared use of a vehicle, bicycle, or other mode—is an innovative transportation strategy that enables users to gain short-term access to transportation modes on an “as-needed” basis. It includes various forms of carsharing, bikesharing, scooter sharing, ridesharing (carpooling and vanpooling), transportation network companies (TNCs), and microtransit. Included in this ecosystem are smartphone “apps” that aggregate and optimize these mobility options, as well as “courier network services” that provide last mile package and food delivery. This chapter describes different models that have emerged in shared mobility and reviews research that has quantified the environmental, social, and transportation-related impacts of these services

Spartan Daily, March 7, 2017

Volume 148, Issue 17https://scholarworks.sjsu.edu/spartan_daily_2017/1016/thumbnail.jp

What Does the Gig Economy Mean for Workers?

[Excerpt] Technological advancement and the proliferation of the smartphone have reshaped the commercial landscape, providing consumers new ways to access the retail marketplace. On-demand companies are one such innovation, and underpinning on-demand commerce is the gig economy, the collection of markets that match service providers to consumers of on-demand services on a gig (or job) basis. Flagship on-demand companies such as Uber (driver services) and Handy (home cleaners and household services) have garnered significant media attention both for their market success and recent legal challenges, particularly concerning the classification of gig workers. Broader questions about the pros and cons of the gig economy have emerged as on-demand markets grow and the gig economy expands into new sectors. By some accounts, workers’ willingness to participate in the gig economy provides evidence that gig work is a beneficial arrangement. Indeed, gig jobs may yield benefits relative to traditional employment in terms of the ease of finding employment and greater flexibility to choose jobs and hours. The gig economy may facilitate bridge employment (e.g., temporary employment between career jobs or between full-time work and retirement) or provide opportunities to generate income when circumstances do not accommodate traditional full-time, full-year employment. At the same time, however, the potential lack of labor protections for gig workers and the precarious nature of gig work have been met with some concern. The nationwide reach of gig work and its potential to impact large groups of workers, and their livelihoods, have attracted the attention of some Members of Congress. These Members have raised questions about the size and composition of the gig workforce, the proper classification of gig workers (i.e., as employees or independent contractors), the potential for gig work to create work opportunities for unemployed or underemployed workers, and implications of gig work for worker protections and access to traditional employment-based benefits. In support of these policy considerations, this report provides an overview of the gig economy and identifies legal and policy questions relevant to its workforce

Investigating the Influence of Dockless Electric Bike-share on Travel Behavior, Attitudes, Health, and Equity

Cities throughout the world have implemented bike-share systems as a strategy for expanding mobility options. While these have attracted substantial ridership, little is known about their influence on travel behavior more broadly. The aim of this study was to examine how shared electric bikes (e-bikes) and e-scooters influence individual travel attitudes and behavior, and related outcomes of physical activity and transportation equity. The study involved a survey in the greater Sacramento area of 1959 households before (Spring 2016) and 988 after (Spring 2019) the Summer 2018 implementation of the e-bike and e-scooterservice operated by Jump, Inc., as well as a direct survey of 703 e-bike users (in Fall 2018 & Spring 2019). Among householdrespondents, 3–13% reported having used the service. Of e-bike share trips, 35% substituted for car travel, 30% substituted for walking, and 5% were used to connect to transit. Before- and after-household surveys indicated a slight decrease in self-reported (not objectively measured) median vehicle miles traveled and slight positive shifts in attitudes towards bicycling. Service implementation was associated with minimal changes in health in terms of physical activity and numbers of collisions. The percentages of users by self-reported student status, race, and income suggest a fairly equitable service distribution by these parameters, but each survey under-represents racial minorities and people with low incomes. Therefore, the study is inconclusive about how this service impacts those most in need. Furthermore, aggregated socio-demographics of areas where trips started or ended did not correlate with, and therefore are not reliable indicators of, the socio-demographics of e-bike-share users. Thus, targeted surveying of racial minorities and people with low-incomes is needed to understand bike-share equity

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