On-demand mobility services continue to evolve fast. New solutions are introduced constantly to address changes in consumer urban transportation tastes, or address shortcomings of existing offerings. Consumers demand for personalized transportation solutions that are affordable, convenient, and safe has led to the rapid growth of ride-hailing. But in cities where it is most popular, single passenger ride-hailing is a major contributor to traffic congestion and lengthening travel times leading to deteriorating passenger experience. We need to find solutions that increase the passenger throughput per mile and permanently remove vehicles from streets. Micromobility and new forms of ridesharing emerged in part to address these problems but also to provide lower cost transportation alternatives. They are now being combined with ride-hailing to offer multimodal transportation. Multimodal and shared on-demand mobility will have seven implications that will require careful analysis.
The congressional and European Parliament testimonies of Facebook’s CEO focused attention on Internet and ecommerce corporations and startups whose business models rely on the collection and exploitation of big data, with personal data being a major component. Legislators and the public at large came to realize a) the leverage such companies now possess through the dominant positions of the free and frequently personalized services they offer in exchange for the data they collect, b) the risks associated with not properly safeguarding this data, c) the legislators lack of detailed understanding about how the data is collected and used by these companies and their partners, and d) how difficult it will be to regulate the collection, processing, AI-based exploitation, and use of this data in a way that is agreeable to both consumers and businesses. These issues are re-emerging as more connected vehicles are shipped and will become more critical as companies using autonomous vehicles in a variety of services start to employ big data in insights-enabled business models. As we consider the monetization of transportation-related data it is necessary to understand who the main generators and users of this data are, who owns each type of generated data, the risks that may arise from mishandling the collected data, and whether existing and proposed regulations relating to autonomous vehicles and more broadly next-generation mobility suffice or need to be augmented.
In my book and previous posts I build a broad case for the key role big data and AI play in next-generation mobility, and provide several examples from transportation and logistics. Next-generation mobility is about intelligent, connected vehicles that utilize some form of electrified propulsion, and on-demand shared transport services of people and goods that will be offered through such vehicles. Many of these vehicles will be capable of autonomous movement. Next-generation mobility will help us address some of our biggest challenges, such as pollution and climate change, urbanization and congestion, aging population, and traffic fatalities, while enabling us to maintain economic prosperity by operating highly optimized supply chains that span the globe. It will give rise to a new value chain where big data and AI will play a key role. It is therefore important to identify the new monetization opportunities enabled by big data and AI in the context of this value chain.
In the previous post I described a new value chain that will connect companies providing on-demand personal mobility services and three emerging models for this value chain. This value chain is the result of the consumer shift from a car ownership-centric transportation model to a hybrid model that blends car ownership with vehicle access through a combination of on-demand mobility services and public transportation. It is also based on the stated intent by the providers of certain of these services to adopt Autonomous Connected Electrified (ACE) vehicles. Various acquisitions, partnerships, including the recently announced partnerships between Waymo and Avis, and Apple and Hertz, and investments by automotive industry incumbents and by companies offering, or intend to offer, on-demand mobility services point to new ecosystems that will be developed around this value chain. In this post I provide a deeper analysis of the emerging value chain and explore investment opportunities in startups that will participate in it.
This post first appeared on 4/27/17 in O’Reilly’s site. It has been revised since it first appeared.
In my book The Big Data Opportunity in Our Driverless Future I make two arguments. First, societal and urban challenges are accelerating the adoption of on-demand personal mobility services. Second, technology advances, including big data and AI, are making next-generation vehicles, and specifically Autonomous Connected and Electrified (ACE) vehicles a reality. I define Next-Generation Mobility as the movement of people and goods using a combination of ACE vehicles, and of transport services such as ride-hailing, car sharing, ridesharing, and others that are offered on a short-time, on-demand or as-needed basis. Next-Generation Mobility will cause three major shifts that can lead to the disruption of the automotive and transportation industries: a consumer shift, an automotive industry shift, and a mobility services shift.
In a series of posts, starting with this one, I examine what is causing these shifts, one of the value chains that is emerging as a result of these shifts, big data’s and AI’s key roles in the value chain, and the models being created around this value chain.