Uber and Lyft

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pages: 265 words: 69,310

What's Yours Is Mine: Against the Sharing Economy by Tom Slee

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4chan, Airbnb, Amazon Mechanical Turk, asset-backed security, barriers to entry, Berlin Wall, big-box store, bitcoin, blockchain, citizen journalism, collaborative consumption, congestion charging, Credit Default Swap, crowdsourcing, data acquisition, David Brooks, don't be evil, gig economy, Hacker Ethic, income inequality, informal economy, invisible hand, Jacob Appelbaum, Jane Jacobs, Jeff Bezos, Khan Academy, Kibera, Kickstarter, license plate recognition, Lyft, Mark Zuckerberg, move fast and break things, natural language processing, Netflix Prize, Network effects, new economy, Occupy movement, openstreetmap, Paul Graham, peer-to-peer lending, Peter Thiel, pre–internet, principal–agent problem, profit motive, race to the bottom, Ray Kurzweil, recommendation engine, rent control, ride hailing / ride sharing, sharing economy, Silicon Valley, Snapchat, software is eating the world, South of Market, San Francisco, TaskRabbit, The Nature of the Firm, Thomas L Friedman, transportation-network company, Uber and Lyft, Uber for X, ultimatum game, urban planning, WikiLeaks, winner-take-all economy, Y Combinator, Zipcar

Uber is still privately owned at the time of writing, but the investments correspond to a market capitalization of $50 billion: more valuable than the three leading car rental companies (Hertz, Avis, and Enterprise) combined, and about two-thirds the value of Ford Motor Company. Uber is ambitious: it has explored many variants on its driving services from carpooling to high-end luxury services, as well as delivery and ­logistics, but for now UberX makes up the bulk of its business. It makes sense to talk of Uber and Lyft in the same breath, despite their different images, because they have ended up offering essentially the same service. When, after a campaign by Peers and others, California became the first state to create a separate set of rules for what it called Transportation Network Companies (TNCs), Uber and Lyft were the main beneficiaries.21 The TNC framework has since been adopted by Colorado, as well as Seattle, Minneapolis, Austin, Houston, and Washington. While there are differences,22 the basic principles are the same: the companies “provide prearranged transportation services for compensation using an online-enabled application or platform (such as smart phone apps) to connect drivers using their personal vehicles with passengers.” 23 The companies compete against each other for drivers, and some drivers drive for both platforms, keeping both companies’ apps in their car.

Second, Uber requires drivers to accept 90% of all rides that are sent their way, on pain of being removed from the service, so rejecting a potential ride comes at a cost. Racism manifests itself differently in different environments, and the better experience of black customers is an unintended side-effect of Uber’s system. Uber drivers are not told where to drive, so they may avoid what they consider as “sketchy” parts of town, and both Uber and Lyft have been accused of “redlining”: not providing services to poor and minority neighborhoods.68 Numerous comments on social media suggest that one of the appeals of Uber and Lyft to young and well-off early adopters was that the drivers matched their age, educational-level, and social background more than did taxi drivers. Instead of being driven by a middle-aged immigrant man who had 60 hours on the clock that week, you could be picked up by “a friend with a car,” more likely to be female, more likely to be well educated, and more likely to be white.69 As the companies have expanded, however, the driver population more closely matches taxi drivers and this opportunity to discriminate has faded.

But what comes out of this is that the real story is a long way from $90,000, even though that number is still out there (Guendelsberger refers to “that $90,000 a year figure that so many passengers asked about”). Uber drivers appear to take home about the same as a taxi driver once expenses are figured in, while Uber itself has stepped in and takes as much of the fare as do medallion holders. One of the complaints that taxi companies have against Uber and Lyft is that they are subject to different standards, and that the taxi standards are more onerous than those that the ridesharing companies have to follow. Uber maintains that its drivers are subject to a thorough screening process, but a series of assaults on the service has put this largely automated process under scrutiny. It has not held up well. Most dramatically, The Guardian worked with a whistleblower who applied for work as a driver with Uber UK.


pages: 375 words: 88,306

The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism by Arun Sundararajan

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3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, autonomous vehicles, barriers to entry, bitcoin, blockchain, Burning Man, call centre, collaborative consumption, collaborative economy, collective bargaining, corporate social responsibility, cryptocurrency, David Graeber, distributed ledger, employer provided health coverage, Erik Brynjolfsson, ethereum blockchain, Frank Levy and Richard Murnane: The New Division of Labor, future of work, George Akerlof, gig economy, housing crisis, Howard Rheingold, Internet of things, inventory management, invisible hand, job automation, job-hopping, Kickstarter, knowledge worker, Kula ring, Lyft, megacity, minimum wage unemployment, moral hazard, Network effects, new economy, Oculus Rift, pattern recognition, peer-to-peer lending, profit motive, purchasing power parity, race to the bottom, recommendation engine, regulatory arbitrage, rent control, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Coase, Second Machine Age, self-driving car, sharing economy, Silicon Valley, smart contracts, Snapchat, social software, supply-chain management, TaskRabbit, The Nature of the Firm, total factor productivity, transaction costs, transportation-network company, two-sided market, Uber and Lyft, Uber for X, universal basic income, Zipcar

That’s what I think is going to happen with hotels. I’m pretty close with some hotel executives; they don’t seem to be overly concerned.” Indeed, as Alison Griswold from Slate magazine documents, the hotel industry in 2014–15 enjoyed their highest-ever levels of occupancy and average daily room prices.29 The same is not true of Uber and Lyft’s impact on traditional taxicabs. The key difference is that, rather than being merely a differentiated service, Uber and Lyft also display higher quality across the board on most dimensions that customer value, except perhaps the ability to hail a car on the street. This does not negate the point I’m making—the increase in variety will increase consumption. However, the impact on the incumbents is likely to be negative more rapidly. Indeed, taxi drivers (most of whom in larger cities do not own their cars or “medallions”) switch to Uber every day; we have already seen evidence of a drop of about 30% in the price of a New York City yellow cab medallion.30 And in July 2015, Evgeny Freidman, the largest owner of yellow cab medallions in New York, filed a petition to put many of his medallion-owning companies into bankruptcy.31 And the eventual impact of on-demand transportation will likely be on the automobile industry as a whole, accelerated by autonomous cars becoming a mass-market commercial reality over the next decade.

Georgios Zervas, Davide Proserpio, and John Byers, “ The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry,” Boston University School of Management Research Paper No. 2013–16, May 7, 2015). http://dx.doi.org/10.2139/ssrn.2366898. 29. Alison Griswold, “Airbnb Is Thriving. Hotels Are Thriving. How Is that Possible?” Slate, July 6, 2015. http://www.slate.com/articles/business/moneybox/2015/07/airbnb_disrupting_hotels_it_hasn_t_happened_yet_and_both_are_thriving_what.html. 30. Jennifer Surane, “New York’s Taxi Medallion Business Is Hurting. Thanks to Uber and Lyft.” Skift, July 15, 2015. http://skift.com/2015/07/15/new-yorks-taxi-medallion-business-is-hurting-thanks-to-uber-and-lyft. 31. Josh Barro, “Taxi Mogul, Filing Bankruptcy, Sees Uber-Citibank Plot,” New York Times, July 22, 2015. http://www.nytimes.com/2015/07/23/upshot/taxi-mogul-filing-bankruptcy-sees-a-uber-citibank-plot.html?abt=0002&abg=1. 32. Andrey Fradkin, “Search Frictions and the Design of Online Marketplaces,” September 30, 2015. http://andreyfradkin.com/assets/SearchFrictions.pdf. 33.

See the full docket report for the case, O’Connor et al v. Uber Technologies, Inc. et al https://dockets.justia.com/docket/california/candce/4:2013cv03826/269290. Judge Chen’s decision (filing #251) is available at https://docs.justia.com/cases/federal/district-courts/california/candce/3:2013cv03826/269290/251. 4. Quoted in Dan Levine and Edward Chan, “Uber and Lyft Fail to Convince Judges,” Business Insider, March 2015. http://www.businessinsider.com/uber-and-lyft-fail-to-convince-judges-their-employees-are-independent-contractors-2015-3#ixzz3UIFTYbVy. 5. I have heard Teran discuss this at two separate events in the second half of 2015: the TAP Conference in New York on October 1, and the White House Summit on Worker Voice, October 7. See an op-ed by Sapone at http://qz.com/448846/the-on-demand-economy-doesnt-have-to-imitate-uber-to-win/. 6.


pages: 421 words: 110,406

Platform Revolution: How Networked Markets Are Transforming the Economy--And How to Make Them Work for You by Sangeet Paul Choudary, Marshall W. van Alstyne, Geoffrey G. Parker

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3D printing, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, Amazon Web Services, Andrei Shleifer, Apple's 1984 Super Bowl advert, autonomous vehicles, barriers to entry, big data - Walmart - Pop Tarts, bitcoin, blockchain, business process, buy low sell high, chief data officer, clean water, cloud computing, connected car, corporate governance, crowdsourcing, data acquisition, data is the new oil, discounted cash flows, disintermediation, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, financial innovation, Haber-Bosch Process, High speed trading, Internet of things, inventory management, invisible hand, Jean Tirole, Jeff Bezos, jimmy wales, Khan Academy, Kickstarter, Lean Startup, Lyft, market design, multi-sided market, Network effects, new economy, payday loans, peer-to-peer lending, Peter Thiel, pets.com, pre–internet, price mechanism, recommendation engine, RFID, Richard Stallman, ride hailing / ride sharing, Ronald Coase, Satoshi Nakamoto, self-driving car, shareholder value, sharing economy, side project, Silicon Valley, Skype, smart contracts, smart grid, Snapchat, software is eating the world, Steve Jobs, TaskRabbit, The Chicago School, the payments system, Tim Cook: Apple, transaction costs, two-sided market, Uber and Lyft, Uber for X, winner-take-all economy, Zipcar

YouTube employs a strong pull and deep understanding of the use of data in matching, while Vimeo differentiates itself through better hosting, bandwidth, and other tools for facilitating production and consumption. BEYOND THE CORE INTERACTION As we’ve seen, platform design begins with the core interaction. But over time, successful platforms tend to scale by layering new interactions on top of the core interaction. In some cases, the gradual addition of new interactions is part of the long-term business plan that platform founders had in mind from the beginning. In early 2015, both Uber and Lyft began experimenting with a new ride-sharing service that complements their familiar call-a-taxi business model. The new services, known as UberPool and Lyft Line, allow two or more passengers traveling in the same direction to find one another and share a ride, thereby reducing their cost while increasing the revenues enjoyed by the driver. Lyft cofounder Logan Green says that ride-sharing was always part of the Lyft idea.

The evolution of Uber, Lyft, and LinkedIn illustrates several of the ways that new interactions may be layered on top of the core interaction in a given platform: • By changing the value unit exchanged between existing users (as when LinkedIn shifted the basis of information exchange from user profiles to discussion posts) • By introducing a new category of users as either producers or consumers (as when LinkedIn invited recruiters and advertisers to join the platform as producers) • By allowing users to exchange new kinds of value units (as when Uber and Lyft made it possible for riders to share rides as well as arranging solo pickups) • By curating members of an existing user group to create a new category of users (as when LinkedIn designated certain participants as “thought leaders” and invited them to become producers of informational posts) Of course, not every new interaction is successful. Jake McKeon founded the social network Moodswing as a place where people could share their emotional states, from elation to gloom.

They do this, in part, by developing rules, practices, and protocols that discourage multihoming. Multihoming occurs when users engage in similar types of interactions on more than one platform. A freelance professional who presents his credentials on two or more service marketing platforms, a music fan who downloads, stores, and shares tunes on more than one music site, and a driver who solicits rides through both Uber and Lyft all illustrate the phenomenon of multihoming. Platform businesses seek to discourage multihoming, since it facilitates switching—when a user abandons one platform in favor of another. Limiting multihoming is a cardinal competitive tactic for platforms. Here’s an example of how the effort to limit multihoming plays out in the new world of strategy. Adobe Flash Player is a browser app that delivers Internet content to users, including audio/video playback and real-time game play.


pages: 330 words: 91,805

Peers Inc: How People and Platforms Are Inventing the Collaborative Economy and Reinventing Capitalism by Robin Chase

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3D printing, Airbnb, Amazon Web Services, Andy Kessler, banking crisis, barriers to entry, bitcoin, blockchain, Burning Man, business climate, call centre, car-free, cloud computing, collaborative consumption, collaborative economy, collective bargaining, congestion charging, crowdsourcing, cryptocurrency, decarbonisation, don't be evil, Elon Musk, en.wikipedia.org, ethereum blockchain, Ferguson, Missouri, Firefox, frictionless, Gini coefficient, hive mind, income inequality, index fund, informal economy, Internet of things, Jane Jacobs, Jeff Bezos, jimmy wales, job satisfaction, Kickstarter, Lean Startup, Lyft, means of production, megacity, Minecraft, minimum viable product, Network effects, new economy, Oculus Rift, openstreetmap, optical character recognition, pattern recognition, peer-to-peer lending, Richard Stallman, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, self-driving car, shareholder value, sharing economy, Silicon Valley, six sigma, Skype, smart cities, smart grid, Snapchat, sovereign wealth fund, Steve Crocker, Steve Jobs, Steven Levy, TaskRabbit, The Death and Life of Great American Cities, The Nature of the Firm, transaction costs, Turing test, Uber and Lyft, Zipcar

Uber’s competitive advantage was once in the deals it had negotiated with local limo companies and individual drivers. But nothing prevents drivers from agreeing to drive for both companies or prospective passengers from having both apps on their smartphones. It is my experience with Zipcar and its competitors that customers choose based on a combination of convenience (the technology), price, and proximity. Both Uber and Lyft have business models and apps that appear to work; can the market sustain both? Buying (bribing) users too early in a company’s life cycle will just eat up a lot of money and won’t produce anything lasting. Doing so later is indeed possible, but it can be a very risky strategy depending on a company’s ability to defend that lead. I’ll talk more about the Uber/Lyft battle when I discuss the last phase, later in this chapter.

In Chapter 6 we talked about the range of possibilities when shaping a platform, from constrained to completely open, and how this defined how much innovation could happen. Right now, the Internet and GPS are wholly open platforms. It is this openness that has made for the infinite variation in applications. But some Inc platforms don’t want a lot of variation or creativity or innovation, and so they constrain the types of participation possible. Prosper wants to make loans to creditworthy borrowers. Uber and Lyft want safe drivers with clean cars. Twitter, on the other hand, doesn’t much care what you do with those 140 characters. The French precursor to the Internet was called Minitel and was widely used. It didn’t share these key characteristics. You needed a license to publish on it, and it was in every way a corporate and government walled garden. Almost nothing culturally interesting came from it.

In IT governance, this is the point at which the enterprise (the government, the business, the institution) competes against mission delivery (its own goals). As I looked at the graph, it became evident: having some rules (some structure) encourages me to participate, but having too many rules (too much structure) discourages me. Taxi regulations are full of outdated rules; hence the success of Uber and Lyft. Washington, D.C.’s Taxicab Commission chairman, Ron Linton, said that “Uber’s service is illegal because its drivers do not give passengers a receipt as they exit.”11 That’s true only if you define a receipt as a piece of paper. Everyone who uses these services pays by credit card from a preestablished online account and receives an email receipt in real time, pretty much as they close the door of the vehicle.


pages: 340 words: 92,904

Street Smart: The Rise of Cities and the Fall of Cars by Samuel I. Schwartz

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, active transport: walking or cycling, Affordable Care Act / Obamacare, American Society of Civil Engineers: Report Card, autonomous vehicles, car-free, City Beautiful movement, collaborative consumption, congestion charging, crowdsourcing, desegregation, Enrique Peñalosa, Ford paid five dollars a day, Frederick Winslow Taylor, if you build it, they will come, intermodal, invention of the wheel, lake wobegon effect, Loma Prieta earthquake, Lyft, Masdar, megacity, meta analysis, meta-analysis, moral hazard, Nate Silver, oil shock, Productivity paradox, Ralph Nader, rent control, ride hailing / ride sharing, Rosa Parks, self-driving car, skinny streets, smart cities, smart grid, smart transportation, the built environment, the map is not the territory, transportation-network company, Uber and Lyft, Uber for X, Unsafe at Any Speed, urban decay, urban planning, urban renewal, walkable city, Wall-E, white flight, Works Progress Administration, Yogi Berra, Zipcar

You don’t have to spend ten years learning the commuting ropes to know whether the train or bus you’re on is an express or a local, or even when it’s going to show up. You just need a smartphone. Smartphones are also all that’s needed to take advantage of other revolutionary new transportation options: ridesharing services like Via, car-sharing like Zipcar, and—especially—dispatchable taxi services like Uber and Lyft.c However, these and other cool new businesses didn’t create Millennial distaste for driving. They just exploited it. The question remains: why do Millennials find the automobile so much less desirable than their parents, grandparents, and great-grandparents did? Woodbridge, Virginia, is a small suburb about twenty miles south of Washington, DC. Many of the fifty-five thousand residents commute to Washington each day and return home to the leafy suburbs replete with cul-de-sacs and single-family homes.

In Los Angeles, the largest US market for the most popular service, uberX, drivers average less than $17 an hour before gas and tolls. However, even these aren’t the biggest concerns. If the goal is to improve mobility for city dwellers—to replace automobile dependency with active and multimodal transportation options—then it’s difficult to see how ride-matching can ever be more than a small part of the solution. That’s because the defining characteristic of the Ubers and Lyfts of the world (and of their very vocal cheerleaders) is hostility to regulation. For decades now, regulation has been getting very bad press, and not just from conservative politicians and libertarian economists. Everyone has a list of silly bureaucratic rules that have long outlived their usefulness, and I’m no exception. One of my favorites is the requirement that a car’s registration sticker be to the left of the inspection sticker or you’ll get a ticket.

Long before enough smartphone-carrying drivers hit the streets, the VIM tipping point will be reached. Beyond that point—that is, beyond the maximum carrying capacity of a particular city’s streets—the numbers won’t add up to more mobility, but less. This is an unavoidable fact of life. No matter how sophisticated the technology becomes, public streets will remain a public resource with finite capacity. When ride-matching services like Uber and Lyft treat city streets as a free good, they’re just repeating the same conceptual mistake that the original champions of motordom did during the 1920s—the argument that, while streetcars and trains were responsible for maintenance of “their” right-of-way, streets were free for everyone. Smart cities shouldn’t insist on stupid regulation. But that doesn’t mean they can do without regulation at all.


pages: 302 words: 73,581

Platform Scale: How an Emerging Business Model Helps Startups Build Large Empires With Minimum Investment by Sangeet Paul Choudary

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3D printing, Airbnb, Amazon Web Services, barriers to entry, bitcoin, blockchain, business process, Clayton Christensen, collaborative economy, crowdsourcing, cryptocurrency, data acquisition, frictionless, game design, hive mind, Internet of things, invisible hand, Kickstarter, Lean Startup, Lyft, M-Pesa, Mark Zuckerberg, means of production, multi-sided market, Network effects, new economy, Paul Graham, recommendation engine, ride hailing / ride sharing, shareholder value, sharing economy, Silicon Valley, Skype, Snapchat, social graph, social software, software as a service, software is eating the world, Spread Networks laid a new fibre optics cable between New York and Chicago, TaskRabbit, the payments system, too big to fail, transport as a service, two-sided market, Uber and Lyft, Uber for X, Wave and Pay

Imagine, in turn, a producer receiving a request and preparing to fulfill that request, only to find that the request is canceled. In both cases, the respective consumer or producer may become discouraged and decide to abandon the platform. In some of the largest cities, drivers drive for both Uber and Lyft, as well as other competitors. It’s not uncommon for these drivers to switch between the two platforms multiple times a day. With a limited supply of drivers in a city and the cost for a driver to connect to an additional platform being so small, drivers multihome on both Uber and Lyft. This has naturally led to intense competition between the two companies, and Uber infamously resorted to a playbook to create interaction failure on Lyft using questionable tactics. Uber decided to target interaction failure on Lyft by contracting third-party agents to use disposable phones to hail Lyft taxies.

This book explains the inner workings of these new business models and their ability to scale rapidly. The platform business model is powered by a new set of factors that determine value creation and competitive advantage. These factors are rapidly changing how entire industries operate. Upstarts are disrupting deeply rooted traditional industries by leveraging platforms. The decline of Nokia and Blackberry and the challenge of Uber and Lyft to the taxi industry worldwide bear testament to this shift. Meanwhile, individuals and niche brands are gaining rapid market access by leveraging platforms for global reach. Teenagers are building highly monetizable media empires on YouTube, while many freelancers make a better living on Upwork than they ever did or could at a traditional firm. My fascination with platforms emerged from a desire to understand business success and failure in the context of emerging digital business models.

The defensibility and competitive advantage of a platform business are very closely related to the multihoming costs that its producers and consumers incur. Multihoming costs vary for different platforms. When developers co-develop for the Android and iOS platforms, they incur high multihoming costs. Multihoming costs are high for consumers as well because of the cost of mobile phones. Most consumers will own only one phone. However, multihoming costs for drivers to co-exist on Uber and Lyft are relatively low. Many drivers participate on both platforms. Given the ease of booking rides, multi-homing costs are very low for travelers/riders on these platforms as well. This is an important consideration for on-demand platforms. With a limited supply of service providers available, multihoming may lead to a strong, ongoing competition between platforms for access to service providers.


pages: 168 words: 50,647

The End of Jobs: Money, Meaning and Freedom Without the 9-To-5 by Taylor Pearson

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Airbnb, barriers to entry, Black Swan, call centre, cloud computing, Elon Musk, en.wikipedia.org, Frederick Winslow Taylor, future of work, Google Hangouts, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, loss aversion, low skilled workers, Lyft, Mark Zuckerberg, market fragmentation, means of production, Oculus Rift, passive income, passive investing, Peter Thiel, remote working, Ronald Reagan: Tear down this wall, sharing economy, side project, Silicon Valley, Skype, software as a service, software is eating the world, Startup school, Steve Jobs, Steve Wozniak, Stewart Brand, telemarketer, Thomas Malthus, Uber and Lyft, unpaid internship, Watson beat the top human players on Jeopardy!, web application, Whole Earth Catalog

A market opportunity that would have been available to a few thousand people that could afford to build a hotel is now available to a few million people that may have a spare bedroom. There are not many more houses now in the U.S. than there were 5 years ago, but AirBnB has created more inventory (extra rooms to stay in) without creating more supply (building hotels). Uber and Lyft have done for the taxi industry what AirBnB has done for the hotel industry—anyone with a car can become a taxi driver by signing up online to drive for the service. In the past it was difficult and expensive to become a taxi driver. Some cities require drivers to invest tens of thousands of dollars to buy a medallion just to drive a taxi. Uber and Lyft now let anyone do the work by instead going through a background check. A lot of people use this as supplemental income when making a job transition. They don’t have to invest thousands of dollars—they can just sign up on the website and make a few thousand bucks a month between jobs.


pages: 366 words: 94,209

Throwing Rocks at the Google Bus: How Growth Became the Enemy of Prosperity by Douglas Rushkoff

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3D printing, Airbnb, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, bank run, banking crisis, barriers to entry, bitcoin, blockchain, Burning Man, business process, buy low sell high, California gold rush, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, centralized clearinghouse, citizen journalism, clean water, cloud computing, collaborative economy, collective bargaining, colonial exploitation, Community Supported Agriculture, corporate personhood, crowdsourcing, cryptocurrency, disintermediation, diversified portfolio, Elon Musk, Erik Brynjolfsson, ethereum blockchain, fiat currency, Firefox, Flash crash, full employment, future of work, gig economy, Gini coefficient, global supply chain, global village, Google bus, Howard Rheingold, IBM and the Holocaust, impulse control, income inequality, index fund, iterative process, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joseph Schumpeter, Kickstarter, loss aversion, Lyft, Mark Zuckerberg, market bubble, market fundamentalism, Marshall McLuhan, means of production, medical bankruptcy, minimum viable product, Naomi Klein, Network effects, new economy, Norbert Wiener, Oculus Rift, passive investing, payday loans, peer-to-peer lending, Peter Thiel, post-industrial society, profit motive, quantitative easing, race to the bottom, recommendation engine, reserve currency, RFID, Richard Stallman, ride hailing / ride sharing, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, shareholder value, sharing economy, Silicon Valley, Snapchat, social graph, software patent, Steve Jobs, TaskRabbit, trade route, transportation-network company, Turing test, Uber and Lyft, Uber for X, unpaid internship, Y Combinator, young professional, Zipcar

Feeding more activity to the ledger simply cedes more of humanity and business alike to a growth-centric industrial model that was invented to thwart us to begin with. That’s the problem with any of the many new ways we have of earning income through previously off-the-books activities. On the one hand, they create thrilling new forms of peer-to-peer commerce. eBay lets us sell our attic junk. Web site Airbnb lets us rent out our extra bedrooms to travelers. Smartphone apps Uber and Lyft let us use our vehicles to give people rides, for money. Unlike many of the other platforms we’ve looked at so far, these opportunities don’t lead to power-law distributions, because a car or home can be hired only by one person at a time. As long as you’re listed on the network and have decent reviews, you should do as well as anyone else. From the consumer’s side, these apps are amazing. If you need a ride, you can open Uber and see a map of the area along with tiny icons for the available cars.

Their ads show people sharing an extra bedroom and a place at the family table, but the statistics reveal that the vast majority (87 percent) of hosts leave their homes in order to rent them.37 Homes become amateur hotels, as the original residents try to live off the arbitrage between the rent they pay, the rent they earn, and the cost of living somewhere other than home. Even if you are having trouble finding work in the digital economy, you no longer have an excuse for being entirely off the books. Just don’t let the landlord find out what you’re doing. Likewise, the amateur taxi networks of Uber and Lyft are great ways for otherwise “underemployed” vehicle owners to make a few extra bucks. There’s no reason now to leave a worthwhile asset or hour off the books—even if the underemployed are really underpaid freelancers working a whole lot of hours already. These apps are not about sharing space in a vehicle—like driving a friend to the train station—they’re about monetizing unemployed people’s time and stuff.


pages: 457 words: 128,838

The Age of Cryptocurrency: How Bitcoin and Digital Money Are Challenging the Global Economic Order by Paul Vigna, Michael J. Casey

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3D printing, Airbnb, altcoin, bank run, banking crisis, bitcoin, blockchain, Bretton Woods, California gold rush, capital controls, carbon footprint, clean water, collaborative economy, collapse of Lehman Brothers, Columbine, Credit Default Swap, cryptocurrency, David Graeber, disintermediation, Edward Snowden, Elon Musk, ethereum blockchain, fiat currency, financial innovation, Firefox, Flash crash, Fractional reserve banking, hacker house, Hernando de Soto, high net worth, informal economy, Internet of things, inventory management, Julian Assange, Kickstarter, Kuwabatake Sanjuro: assassination market, litecoin, Long Term Capital Management, Lyft, M-Pesa, Mark Zuckerberg, McMansion, means of production, Menlo Park, mobile money, money: store of value / unit of account / medium of exchange, Network effects, new economy, new new economy, Nixon shock, offshore financial centre, payday loans, peer-to-peer lending, pets.com, Ponzi scheme, prediction markets, price stability, profit motive, RAND corporation, regulatory arbitrage, rent-seeking, reserve currency, Robert Shiller, Robert Shiller, Satoshi Nakamoto, seigniorage, shareholder value, sharing economy, short selling, Silicon Valley, Silicon Valley startup, Skype, smart contracts, special drawing rights, Spread Networks laid a new fibre optics cable between New York and Chicago, Steve Jobs, supply-chain management, Ted Nelson, The Great Moderation, the market place, the payments system, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, tulip mania, Turing complete, Tyler Cowen: Great Stagnation, Uber and Lyft, underbanked, WikiLeaks, Y Combinator, Y2K, Zimmermann PGP

David Johnston is a senior board member at the Mastercoin Foundation, the body that coordinates the funding for the Mastercoin project, which offers a special software platform for developers to design special decentralized applications that can run on top of the bitcoin blockchain. He says blockchain technology “will supercharge the sharing economy,” that emerging trend in which apartment owners use Airbnb.com to rent out quasi hotel rooms and car owners sign up as self-employed taxidrivers for smartphone-based Uber and Lyft. The idea is that if we can decentralize the economy and foster multiple forms of peer-to-peer exchanges, people will figure out profitable ways to turn much of what they own or control into a marketable service. Johnston is known for having coined the term DApp, for “decentralized autonomous application,” to describe the kind of specialized software programs that could thrive in blockchain-based settings.

Got some extra computing power sitting on your desktop? Share it with those who need it. Got a car sitting idle in your driveway? Share that. Got a big idea? Share it online and raise the money online to fund it. Business symbols of this era so far include the personal-apartment rental site Airbnb, the crowdfunding site Kickstarter, the peer-to-peer lending network Lending Club, and the taxi services controlled by individual car owners Uber and Lyft. In some respects these new business models are extensions of a process that began far earlier with the advent of the Internet. While no self-respecting bitcoiner would ever describe Google or Facebook as decentralized institutions, not with their corporate-controlled servers and vast databases of customers’ personal information, these giant Internet firms of our day got there by encouraging peer-to-peer and middleman-free activities.


pages: 527 words: 147,690

Terms of Service: Social Media and the Price of Constant Connection by Jacob Silverman

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23andMe, 4chan, A Declaration of the Independence of Cyberspace, Airbnb, airport security, Amazon Mechanical Turk, augmented reality, Brian Krebs, California gold rush, call centre, cloud computing, cognitive dissonance, correlation does not imply causation, Credit Default Swap, crowdsourcing, don't be evil, Edward Snowden, feminist movement, Filter Bubble, Firefox, Flash crash, game design, global village, Google Chrome, Google Glasses, hive mind, income inequality, informal economy, information retrieval, Internet of things, Jaron Lanier, jimmy wales, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, late capitalism, license plate recognition, life extension, Lyft, Mark Zuckerberg, Mars Rover, Marshall McLuhan, meta analysis, meta-analysis, Minecraft, move fast and break things, national security letter, Network effects, new economy, Nicholas Carr, Occupy movement, optical character recognition, payday loans, Peter Thiel, postindustrial economy, prediction markets, pre–internet, price discrimination, price stability, profit motive, quantitative hedge fund, race to the bottom, Ray Kurzweil, recommendation engine, rent control, RFID, ride hailing / ride sharing, self-driving car, sentiment analysis, shareholder value, sharing economy, Silicon Valley, Silicon Valley ideology, Snapchat, social graph, social web, sorting algorithm, Steve Ballmer, Steve Jobs, Steven Levy, TaskRabbit, technoutopianism, telemarketer, transportation-network company, Turing test, Uber and Lyft, Uber for X, universal basic income, unpaid internship, women in the workforce, Y Combinator, Zipcar

If you live in New York City, like I do, a taxi that picks you up in Manhattan is legally obliged to take you wherever you want to go, including to one of the other boroughs (with the meter running the whole time, of course). Unless you are violent, disruptive, or otherwise problematic, the driver can’t refuse you a ride based on your skin color or some star rating you’ve accumulated. You can also expect to pay a standard fare, unlike with Uber and Lyft, which are known to institute surge pricing to leverage high demand. Uber claims that surge pricing represents a market-based solution and offers a fair price based on availability. Except that Uber controls the market. They decide how many cars are on the road—the company has been caught asking drivers to stay off the road in order to drive up rates. At the same time, Uber has presented itself as a populist operation with a low threshold for entry.

It also allows one to refuse to do business with the other without suffering great consequences—unlike, for example, the TaskRabbit worker who was almost fired from the service after complaining about a misleading job listing involving piles of laundry covered in cat diarrhea. If I approached a laundry service with such a task, they’d either laugh at me or demand a hefty price to do the work, and understandably so. Some of these companies have helped to spur establishment players toward needed reforms. Taxi services, often seen as resisting innovation, have begun adopting smartphone apps and e-hailing systems to keep up with Uber and Lyft. Airbnb has shown that many people are interested in renting out their homes, despite laws that prevent doing so, and that cities may have to work to accommodate this need. But in the spirit of disruption, these companies tend to show up in a new city promising to lead a revolution, only to be forced—by court order, political pressure, or the realization that existing regulations do some good and are unlikely to be overturned—to start negotiating with political leaders and abide by local laws.


pages: 179 words: 43,441

The Fourth Industrial Revolution by Klaus Schwab

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3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, Buckminster Fuller, call centre, clean water, collaborative consumption, conceptual framework, continuous integration, crowdsourcing, disintermediation, distributed ledger, Edward Snowden, Elon Musk, epigenetics, Erik Brynjolfsson, future of work, global value chain, Google Glasses, income inequality, Internet Archive, Internet of things, invention of the steam engine, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, life extension, Lyft, megacity, meta analysis, meta-analysis, more computing power than Apollo, mutually assured destruction, Narrative Science, Network effects, Nicholas Carr, personalized medicine, precariat, precision agriculture, Productivity paradox, race to the bottom, randomized controlled trial, reshoring, RFID, rising living standards, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, smart cities, smart contracts, software as a service, Stephen Hawking, Steve Jobs, Steven Levy, Stuxnet, The Spirit Level, total factor productivity, transaction costs, Uber and Lyft, Watson beat the top human players on Jeopardy!, WikiLeaks, winner-take-all economy, women in the workforce, working-age population, Y Combinator, Zipcar

These have reduced the transaction costs and friction in the system to a point where it is an economic gain for all involved, divided in much finer increments. Well-known examples of the sharing economy exist in the transportation sector. Zipcar provides one method for people to share use of a vehicle for shorter periods of time and more reasonably than traditional rental car companies. RelayRides provides a platform to locate and borrow someone’s personal vehicle for a period of time. Uber and Lyft provide much more efficient “taxi-like” services from individuals, but aggregated through a service, enabled by location services and accessed through mobile apps. In addition, they are available at a moment’s notice. The sharing economy has any number of ingredients, characteristics or descriptors: technology enabled, preference for access over ownership, peer to peer, sharing of personal assets (versus corporate assets), ease of access, increased social interaction, collaborative consumption and openly shared user feedback (resulting in increased trust).


pages: 323 words: 90,868

The Wealth of Humans: Work, Power, and Status in the Twenty-First Century by Ryan Avent

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3D printing, Airbnb, American energy revolution, autonomous vehicles, Bakken shale, barriers to entry, Bernie Sanders, BRICs, call centre, Capital in the Twenty-First Century by Thomas Piketty, Clayton Christensen, cloud computing, collective bargaining, computer age, dark matter, David Ricardo: comparative advantage, deindustrialization, dematerialisation, Deng Xiaoping, deskilling, Dissolution of the Soviet Union, Donald Trump, Downton Abbey, Edward Glaeser, Erik Brynjolfsson, eurozone crisis, everywhere but in the productivity statistics, falling living standards, first square of the chessboard, first square of the chessboard / second half of the chessboard, Ford paid five dollars a day, Francis Fukuyama: the end of history, future of work, gig economy, global supply chain, global value chain, hydraulic fracturing, income inequality, indoor plumbing, industrial robot, interchangeable parts, Internet of things, inventory management, invisible hand, Jacquard loom, James Watt: steam engine, Jeff Bezos, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph-Marie Jacquard, knowledge economy, low skilled workers, lump of labour, Lyft, manufacturing employment, means of production, new economy, performance metric, pets.com, price mechanism, quantitative easing, Ray Kurzweil, rent-seeking, reshoring, rising living standards, Robert Gordon, Ronald Coase, savings glut, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, single-payer health, software is eating the world, supply-chain management, supply-chain management software, TaskRabbit, The Nature of the Firm, The Spirit Level, The Wealth of Nations by Adam Smith, Thomas Malthus, trade liberalization, transaction costs, Tyler Cowen: Great Stagnation, Uber and Lyft, Uber for X, very high income, working-age population

Today’s labour victories, when they occur, tend to come from straightforward issues for which it is easy to muster broad, passionate electoral support: policies such as a rise in the minimum wage or a reduction in immigration. The more complex negotiations that occurred a generation or two ago, when labour had a seat at the political table, tend not to occur any longer. That could change. Drivers for car-sharing firms, such as Uber and Lyft, are battling to unionize. Unionization could eventually come to other sectors of the economy in which large pools of on-demand labour sell their time through market-making apps as well. Unionization would yield uncertain direct benefits to workers within these firms, though. Short-run concessions wrung from ownership might simply accelerate the pace of automation: troublesome labour tends to encourage the deployment of robots, whether the setting is a factory in Shenzhen or a car on California streets.


pages: 598 words: 134,339

Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World by Bruce Schneier

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23andMe, Airbnb, airport security, AltaVista, Anne Wojcicki, augmented reality, Benjamin Mako Hill, Black Swan, Brewster Kahle, Brian Krebs, call centre, Cass Sunstein, Chelsea Manning, citizen journalism, cloud computing, congestion charging, disintermediation, Edward Snowden, experimental subject, failed state, fault tolerance, Ferguson, Missouri, Filter Bubble, Firefox, friendly fire, Google Chrome, Google Glasses, hindsight bias, informal economy, Internet Archive, Internet of things, Jacob Appelbaum, Jaron Lanier, Julian Assange, Kevin Kelly, license plate recognition, linked data, Lyft, Mark Zuckerberg, Nash equilibrium, Nate Silver, national security letter, Network effects, Occupy movement, payday loans, pre–internet, price discrimination, profit motive, race to the bottom, RAND corporation, recommendation engine, RFID, self-driving car, Silicon Valley, Skype, smart cities, smart grid, Snapchat, social graph, software as a service, South China Sea, stealth mode startup, Steven Levy, Stuxnet, TaskRabbit, telemarketer, Tim Cook: Apple, transaction costs, Uber and Lyft, urban planning, WikiLeaks, zero day

We used to buy things with cash at a store; now we use credit cards over the Internet. We used to pay with coins at a tollbooth, subway turnstile, or parking meter. Now we use automatic payment systems, such as EZPass, that are connected to our license plate number and credit card. Taxis used to be cash-only. Then we started paying by credit card. Now we’re using our smartphones to access networked taxi systems like Uber and Lyft, which produce data records of the transaction, plus our pickup and drop-off locations. With a few specific exceptions, computers are now everywhere we engage in commerce and most places we engage with our friends. Last year, when my refrigerator broke, the serviceman replaced the computer that controls it. I realized that I had been thinking about the refrigerator backwards: it’s not a refrigerator with a computer, it’s a computer that keeps food cold.


pages: 515 words: 126,820

Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World by Don Tapscott, Alex Tapscott

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Airbnb, altcoin, asset-backed security, autonomous vehicles, barriers to entry, bitcoin, blockchain, Bretton Woods, business process, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, clean water, cloud computing, cognitive dissonance, corporate governance, corporate social responsibility, Credit Default Swap, crowdsourcing, cryptocurrency, disintermediation, distributed ledger, Donald Trump, double entry bookkeeping, Edward Snowden, Elon Musk, Erik Brynjolfsson, ethereum blockchain, failed state, fiat currency, financial innovation, Firefox, first square of the chessboard, first square of the chessboard / second half of the chessboard, future of work, Galaxy Zoo, George Gilder, glass ceiling, Google bus, Hernando de Soto, income inequality, informal economy, interest rate swap, Internet of things, Jeff Bezos, jimmy wales, Kickstarter, knowledge worker, Kodak vs Instagram, Lean Startup, litecoin, Lyft, M-Pesa, Mark Zuckerberg, Marshall McLuhan, means of production, microcredit, mobile money, Network effects, new economy, Oculus Rift, pattern recognition, peer-to-peer lending, performance metric, Peter Thiel, planetary scale, Ponzi scheme, prediction markets, price mechanism, Productivity paradox, quantitative easing, ransomware, Ray Kurzweil, renewable energy credits, rent-seeking, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, seigniorage, self-driving car, sharing economy, Silicon Valley, Skype, smart contracts, smart grid, social graph, social software, Stephen Hawking, Steve Jobs, Steve Wozniak, Stewart Brand, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, The Wisdom of Crowds, transaction costs, Turing complete, Turing test, Uber and Lyft, unbanked and underbanked, underbanked, unorthodox policies, X Prize, Y2K, Zipcar

We have faster supply chains, new approaches to marketing, and peer-to-peer collaborations like Linux and Wikipedia on a massive scale, with many innovative new business models. Blockchain technology will accelerate this process. As the Internet of Things takes hold, these trends will go into hyperdrive. THE FUTURE: FROM UBER TO SUBER We’ve covered a lot of ground in this chapter. Now let’s pull all the strands of innovation together in just one scenario. Consider service aggregators like Uber and Lyft. Uber is an app-based ride-sharing network of drivers who are willing to give other people a lift for a fee. To use Uber, you download the Uber app, create an account, and provide Uber with your credit card information. When you use the app to request a car, it asks you to select the type of car you want and marks your location on a map. The app will keep you posted on the availability and whereabouts of your prospective driver.