Mobility on Demand in the United States

The growth of shared mobility services and enabling technologies, such as smartphone apps, is contributing to the commodification and aggregation of transportation services. This chapter reviews terms and definitions related to Mobility on Demand (MOD) and Mobility as a Service (MaaS), the mobility marketplace, stakeholders, and enablers. This chapter also reviews the U.S. Department of Transportation’s MOD Sandbox Program, including common opportunities and challenges, partnerships, and case studies for employing on-demand mobility pilots and programs. The chapter concludes with a discussion of vehicle automation and on-demand mobility including pilot projects and the potential transformative impacts of shared automated vehicles on parking, land use, and the built environment

Synergies between app-based car-related shared mobility services for the development of more profitable business models

Purpose: Emerging shared mobility services are an opportunity for cities to reduce the number of car single trips to both improve traffic congestion and the environment. Users of shared mobility services, such as carsharing, ridesharing and singular and shared ride-hailing services, often need to be customers of more than one service to cover all their transport needs, since few mobility providers offer more than one of these services from a single platform. On the other hand, providers offering these services separately do not optimize costly resources and activities, such as the vehicles or the technology. Hence, the aim of this paper is to find synergies between the different app-based car-related shared mobility services that foster the development of new business models, to increase the profitability of these services. Design/methodology/approach: The research approach is built on the literature of car-related shared mobility services business models, supported by the review of certain outstanding services websites, and face-to-face interviews with users and drivers of these transport services. The analysis is presented by means of the Business Model Canvas methodology. Findings: Based on the synergies found, this paper suggests a few different approaches for services to share some resources and activities. Originality/value: This study identifies the common features of carsharing, ridesharing and singular and shared ride-hailing services to develop more profitable business models, based on providing the services in aggregated form, or outsourcing activities and resources. In addition, the implications of these proposals are discussed as advantages and drawbacks from a business perspectivePeer ReviewedPostprint (published version

Networking Transportation

Networking Transportation looks at how the digital revolution is changing Greater Philadelphia's transportation system. It recognizes several key digital transportation technologies: Artificial Intelligence, Big Data, connected and automated vehicles, digital mapping, Intelligent Transportation Systems, the Internet of Things, smart cities, real-time information, transportation network companies (TNCs), unmanned aerial systems, and virtual communications. It focuses particularly on key issues surrounding TNCs. It identifies TNCs currently operating in Greater Philadelphia and reviews some of the more innovative services around the world. It presents four alternative future scenarios for their growth: Filling a Niche, A Tale of Two Regions, TNCs Take Off, and Moore Growth. It then creates a future vision for an integrated, multimodal transportation network and identifies infrastructure needs, institutional reforms, and regulatory recommendations intended to help bring about this vision

Transportation for an Aging Population: Promoting Mobility and Equity for Low-Income Seniors

This study explores the travel patterns, needs, and mobility problems faced by diverse low-income, inner-city older adults in Los Angeles in order to identify solutions to their mobility challenges. The study draws information from: (1) a systematic literature review of the travel patterns of older adults; (2) a review of municipal policies and services geared toward older adult mobility in six cities; (3) a quantitative analysis of the mobility patterns of older adults in California using the California Household Travel Survey; and (4) empirical work with 81 older adults residing in and around Los Angeles’ inner-city Westlake neighborhood, who participated in focus groups, interviews, and walkabouts around their neighborhood

The Economic Impact of Transportation Network Companies on the Taxi Industry

Transportation Network Companies (TNC) are companies that use online-enabled platforms to connect passengers with drivers. In recent years, they have sparked controversy with the taxi industry, which accuses TNCs of operating unfairly. In my study, I look at taxi regulation, consumer transportation preferences, and costs and benefits of TNCs. I analyze data comparing three of these companies, Uber, Lyft, and Sidecar, with a traditional taxicab, and evaluate trends in taxi employment from the Bureau of Labor Statistics. I find that Transportation Network Companies generally have shorter wait times, cheaper prices, and increased convenience, aspects that appeal to consumer preferences. I also find that taxi driver employment tends to fluctuate with economic conditions, however cities that are more likely to use TNCs exhibit smaller growth. I predict that at current conditions, TNCs such as Uber and Lyft will overtake taxi services. Thus, the taxi industry must focus on increasing TNC regulation, creating innovative technology, and modifying its service to appeal to consumers

Incorporation of the Roadify API in Ride and Bike Sharing Systems

Ride and bike share companies have an interest in optimizing trips involving multi-modal transit. To make these services more user-friendly and efficient, we proposed that transit data should be integrated into them. Providing transit data to rideshare drivers in particular would increase their productivity and profits. To develop a plan for partnership between these companies and our sponsor, we developed pricing models and assessed how the APIs would work together. A tiered subscription model with a free trial base became the pricing structure of choice for a partnership with ridesharing company Uber, following research and discussions with our sponsor. Despite initial promise, we ruled out bike sharing as a possibility due to limited digital architecture and weaker financial incentives