Context-based access control for ridesharing service

The paper describes a context-based access control model for a ridesharing service. Ridesharing is a shared use of a car by the driver and one or more passengers for a joint trip. The service is based on the smart space concept. For this purpose the Smart-M3 platform is used. Currently the Smart-M3 platform doesn't have an appropriate access control mechanism meeting the following requirements: supporting a flexible, descriptive and well-defined policy language and taking into consideration the context information. Therefore, the usage of the context-based access control model has been proposed. This model is built as a combination of the role-based and attribute-based access control models. It uses roles, which are assigned dynamically based on the user's context, and meets the requirements to the access control in the smart space. An analysis of information transfer through the ridesharing service modules is used for defining the user's context. The model has been implemented within an access control broker, which controls the access to the smart space resources

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

Why continue sharing: determinants of behavior in collaborative economy services

La economía colaborativa está revolucionando la forma en que los consumidores utilizan los bienes y servicios. En nuestro estudio modificamos y ampliamos el modelo de confirmación de expectativas para determinar los factores motivacionales que impulsan la satisfacción y la intención de continuar usando los servicios de viajes colaborativos. Más importante aún, agregamos el valor social como un factor adicional. En este estudio fueron encuestados usuarios españoles experimentados de BlaBlaCar. La calidad del servicio, la utilidad percibida, la confianza y el valor social son determinantes de la satisfacción de los usuarios experimentados y, a través de ella, de la intención de continuar usando; mientras que no es el caso para el impacto ambiental ni para los beneficios económicos. Además, la confianza afecta directamente a la intención de continuar. Estos resultados tienen implicaciones gerenciales relevantes, mostrando que los usuarios de algunos servicios colaborativos están motivados por otros factores además de los económicos.The sharing economy is revolutionizing the way consumers use goods and services. In our study we modify and extend the expectation confirmation model to determine the motivational factors which drive the satisfaction and continue intention to use ridesharing services. Most importantly, we add social value as an additional factor to those previously studied in the literature. We apply our model in a survey among experienced Spanish users of BlaBlaCar. Service quality, perceived usefulness, trust and social value are determinants of satisfaction of experienced users and through it, of intention to continuance; while it is the case neither for environmental impact nor for economic benefits. Additionally, trust affects directly continuance. These results have relevant managerial implications, showing that users of some sharing services are motivated by other factors than purely economic

A dynamic ridesharing dispatch and idle vehicle repositioning strategy with integrated transit transfers

We propose a ridesharing strategy with integrated transit in which a private on-demand mobility service operator may drop off a passenger directly door-to-door, commit to dropping them at a transit station or picking up from a transit station, or to both pickup and drop off at two different stations with different vehicles. We study the effectiveness of online solution algorithms for this proposed strategy. Queueing-theoretic vehicle dispatch and idle vehicle relocation algorithms are customized for the problem. Several experiments are conducted first with a synthetic instance to design and test the effectiveness of this integrated solution method, the influence of different model parameters, and measure the benefit of such cooperation. Results suggest that rideshare vehicle travel time can drop by 40-60% consistently while passenger journey times can be reduced by 50-60% when demand is high. A case study of Long Island commuters to New York City (NYC) suggests having the proposed operating strategy can substantially cut user journey times and operating costs by up to 54% and 60% each for a range of 10-30 taxis initiated per zone. This result shows that there are settings where such service is highly warranted