Uber Price Quotes

That bidding process pushes prices higher, giving rise to inflationary pressures. To mitigate that risk, the tax needs to offset enough current spending to free up the real resources the government is trying to hire. The problem is that because this particular tax is levied on a tiny cadre of uber-rich people, it won’t open up much (if any) fiscal space.

the ride-sharing service Uber is the hottest, most valuable technology start-up on the planet. It is also one of the most controversial. The company, which has been the target of protests across Europe this week, has been accused of a reckless attitude toward safety, of price-gouging its customers, of putting existing cabbies out of work and of evading regulation. And it has been called trivial. In The New Yorker last year, George Packer huffed that Uber typified Silicon Valley’s newfound focus on “solving all the problems of being 20 years old, with cash on hand.” It is impossible to say whether Uber is worth the $17 billion its investors believe it to be; like any start-up, it could fail.

FREE EXCHANGE Pricing the surge The microeconomics of Uber’s attempt to revolutionise taxi markets 1014 words

Uber’s algorithm (which it has been refining since 2011) is the company’s greatest asset and most significant innovation, allowing it to find the price that will attract drivers—whom, as independent contractors, it can’t order onto the road—without alienating customers.

Flywheel, which provides an app for users to summon taxicabs with their smartphones, will offer a flat $10 rate for all Flywheel-summoned cab rides within San Francisco from 8 p.m. Wednesday to 3 a.m. Thursday. The same price will apply in Seattle and Flywheel’s new markets of San Diego and Sacramento. “Uber can charge 30 times (normal) or whatever they hell they want to do, but we want to make sure anyone who takes a taxi pays a flat fee,” said Flywheel CEO Rakesh Mathur. (He clarified that the 30-times number was “just made up.”) That promotion will cost Flywheel a pretty penny. The startup will pay cabbies double what the metered rates would have been — so in effect, they receive surge pricing, without passengers having to pay it. While Flywheel doesn’t have the massive war chest of Uber, which has raised about $3 billion, it has a respectable $30 million in venture backing, including a recent $12 million round.

Rather than taking supply and demand as a given, the new breed of microeconomist helps nudge the two into line. In the early days of Airbnb, an online market for home rentals, its economists pored over customer data to spot market weaknesses. Costly enhancements, including professional photographs of every listing, are rigorously tested to make sure they work before being rolled out. The company also guides users uncertain about the right rate to charge for a listing. At Uber, a taxi service, prices surge during peak hours, pulling more drivers onto the road. At Poynt, a Silicon Valley startup offering a new type of cashless

Thiel wrote in his 2014 book, Zero to One: Great companies can be built on open but unsuspected secrets about how the world works. Consider the Silicon Valley startups that have harnessed the spare capacity that is all around us but often ignored. Before Airbnb, travelers had little choice but to pay high prices for a hotel room, and property owners couldn’t easily and reliably rent out their unoccupied space. Airbnb saw untapped supply and unaddressed demand where others saw nothing at all. The same is true of private car services Lyft and Uber.

all of its paths to reduce its losses—charging higher prices, paying its workers less—would destroy the advantages that it has built. So it sits there, widely regarded as one of the defining success stories of the Internet era, a unicorn unlike any other, with billions in losses and a plan to become profitable that involves vague promises to somehow monetize all its user data and a specific promise that its investment in a different new technology—the self-driving car, much ballyhooed but as yet not exactly real—will square the circle and make the math add up. That’s the story of Uber—so far. It isn’t a pure Instagram fantasy like the Fyre Festival or a naked fraud like Theranos; it managed to go public and maintain its outsize valuation, unlike its fellow money-losing unicorn WeWork, whose recent attempt at an IPO hurled it into crisis. But like them, it is, for now, an example of a major twenty-first-century company invented entirely out of surplus, less economically efficient so far than the rivals it is supposed to leapfrog, sustained by investors who believe its promises in defiance of the existing evidence, floated by the hope that with enough money and market share, you can will a profitable company into existence, and goldwashed by an “Internet company” identity that obscures the weakness of its real-world fundamentals. Maybe it won’t crash like the others; maybe the tens of billions in investor capital won’t be wasted; maybe we won’t be watching a documentary on its hubris five or ten years hence. But Uber’s trajectory to this point, the strange unreality of its extraordinary success, makes it a good place to begin a discussion of economic

As a result, platforms that offer these commoditized services should focus on matching consumers with available producers as seamlessly as possible. And the best ones do exactly that. For example, Uber’s automatic matching and even its controversial surge pricing are all about facilitating the most transactions. Compare Uber’s commoditized services to a noncommoditized service, such as renting an apartment on Airbnb. In this example, many additional characteristics matter to consumers, such as where the apartment is located, how large it is, what different amenities it offers,

SoftBank, however, had invested more than $10 billion into WeWork and gotten nothing in return. The Vision Fund was down nearly $2 billion in the most recent quarter, during which Uber’s stock had slipped. SoftBank shares were down 10 percent since Wingspan’s release. Both WeWork and SoftBank executives were coming to grips with the realization that its IPO might be priced at a level far below its $47 billion valuation. While SoftBank’s preferred shares gave it some protection—it could get its money out before the company’s employees—a valuation below what SoftBank paid for its shares would mean that the firm’s investment was underwater, much as

For consumers, most of these problems are invisible. That is by design. You’re not supposed to know that the trending topics on Twitter were sifted through by a few destitute people making pennies. You’re not supposed to realize that Facebook can process the billions of photos, links, and shareable items that pass through its network each day only because it recruits armies of content moderators through digital labor markets. Or that these moderators spend hours numbly scrolling through grisly photos that people around the world are trying to upload to the network. Uber’s selling point is convenience: press a button on your phone and a car will arrive in minutes, maybe seconds, to take you anywhere you want to go. As long as that’s what happens, what do consumers have to complain about? Now joined by a host of start-up delivery services, ride-sharing companies are in the business of taking whomever or whatever from point A to point B with minimal fuss or waiting time. That this self-indulgent convenience ultimately comes at the expense of others is easily brushed off or shrouded in the magical promise that anything you want can be produced immediately.

Over the last generation, journalism has slowly been swallowed. The ascendant media companies of our era don’t think of themselves as heirs to a great ink-stained tradition. Some prefer to call themselves technology firms. This redefinition isn’t just a bit of fashionable branding. Silicon Valley has infiltrated the profession, from both within and without. Over the past decade, journalism has come to depend unhealthily on Facebook and Google. The big tech companies supply journalism with an enormous percentage of its audience—and therefore a big chunk of revenue. This gives Silicon Valley influence over the entire profession, and it has made the most of its power. Dependence generates desperation—a mad, shameless chase to gain clicks through Facebook, a relentless effort to game Google’s algorithms. It leads media to ink terrible deals, which look like self-preserving necessities, but really just allow Facebook and Google to hold them even tighter. Media will grant Facebook the right to sell advertising or give Google permission to publish articles directly on its fast-loading server. What makes these deals so terrible is the capriciousness of the tech companies. They like to shift quickly in a radically different direction, which is great for their bottom line, but terrible for all the media companies dependent on the platforms. Facebook will decide that its users prefer video to words, or that its users prefer ideologically pleasing propaganda to hard news. When Facebook shifts direction like this or when Google tweaks its algorithm, they instantly crash Web traffic flowing to media, with all the rippling revenue ramifications that follow. Media know they should flee the grasp of Facebook, but dependence also breeds cowardice. The prisoner lies on the cot dreaming of escape plans that will never hatch. Dependence on the big tech companies is increasingly the plight of the worker and the entrepreneur. Drivers maintain erratic patterns of sleep because of Uber’s shifting whims. Companies that manufacture tchotchkes sold on Amazon watch their businesses collapse when Amazon’s algorithms detect the profitability of their item, leading the giant to manufacture the goods itself at a lower price. The problem isn’t just financial vulnerability. It’s the way in which the tech companies dictate the patterns of work, the way in which their influence can shift the ethos of an entire profession to suit their needs—lowering standards of quality, eroding ethical protections. I saw this up close during my time at the New Republic. I watched how dependence on the tech companies undermined the very integrity of journalism. At the very beginning of that chapter in my career, I never imagined that we would go down that path.

Curious about what separated the successful companies from those that failed, we examined dozens of cases and found that the failures mostly relied on price or brand effects. By contrast, the successes hit on an idea that really worked—driving traffic from one user group in order to drive profits from another user group. We described our findings in a paper that analyzed the mathematics of two-sided network effects.10 Today, such successful platform businesses as eBay, Uber, Airbnb, Upwork, PayPal, and Google exhibit this model extensively.11

Up-front investment to try to professionalize the supply side early on in a network’s development inevitably comes with risk. In a well-publicized misstep for Uber, the company sought to expand its supply side by financing vehicles to provide cars to potential drivers who didn’t own vehicles, a program called XChange Leasing. The hypothesis was that this should push these drivers into power-driver territory quickly. Payments could be automatically deducted from their Uber earnings, and their driver ratings and trip data could be used to underwrite the loans. XChange Leasing unfortunately lost $525 million and failed to professionalize the driver side of the market. The problem was, it attracted drivers highly motivated by money—usually a positive—but who didn’t have high credit scores for good reason. They often failed to make payments, using their Uber-provided car to drive for competitors and avoid the automatic deductions. They would steal the cars and sell them for, say, half price. They would drive for Lyft instead of Uber, as a way to avoid the automatic payment deductions—they would try to have their cake and eat it, too. Uber needed to organize a massive repossession effort to get the cars back, but it was too late—many had been sold illegally, some finding themselves as far away as Iraq and Afghanistan, GPS devices still attached and running. This is a colorful example of how scaling the supply side, when a lot of capital is involved, can be tricky.

Finding the Competitive Levers When there’s a battle between two networks, there are competitive levers that shift users from one into the other—what are they? The best place to focus in the rideshare market was the hard side of the network: drivers. More drivers meant that prices would be lower, attracting valuable high-frequency riders that often comparison shop for fares. Attract more riders, and it more efficiently fills the time of drivers, and vice versa. There was a double benefit to moving drivers from a competitor’s network to yours—it would push their network into surging prices while yours would lower in price. Uber’s competitive levers would combine financial incentives—paying up for more sign-ups, more hours—with product improvements to improve Acquisition, Engagement, and Economic forces. Drawing in more drivers through product improvements is straightforward—the better the experience of picking up riders and routing the car to their destination, the more the app would be used. Building a better product is one of the classic levers in the tech industry, but Uber focused much of its effort on targeted bonuses for drivers. Why bonuses? Because for drivers, that was their primary motivation for using the app, and improving their earnings would make them sticky. But these bonuses weren’t just any bonuses—they were targeted at quickly flipping over the most valuable drivers in the networks of Uber’s rivals, targeting so-called dual apping drivers that were active on multiple networks. They were given large, special bonuses that compelled them to stick to Uber, and every hour they drove was an hour that the other networks couldn’t utilize. There was a sophisticated effort to tag drivers as dual appers. Some of these efforts were just manual—Uber employees who took trips would just ask if the drivers drove for other services, and they could mark them manually in a special UI within the app. There were also behavioral signals when drivers were running two apps—they would often pause their Uber session for a few minutes while they drove for another company, then unpause it. On Android, there were direct APIs that could tell if someone was running Uber and Lyft at the same time. Eventually a large number of these signals were fed into a machine learning model where each driver would receive a score based on how likely they were to be a dual apper. It didn’t have to be perfect, just good enough to aid the targeting.

Why can’t I just subscribe to transportation the same way I subscribe to electricity and internet access? But wait, you might say. Uber isn’t a subscription service—there are no monthly fees. I disagree. It sure looks and feels like a digital subscription service to me. Uber has your ID and all your payment particulars, and it employs usage-based pricing so that you pay for only what you use. It knows your usage history (your home, your work, your common destinations) and uses that information to customize its service for you. And thanks to its partnership with Spotify, it even knows your favorite music. Oh, and guess what? Uber does in fact offer monthly subscriptions. Right now Uber is testing a flat-rate subscription service in several cities. Users can pay a monthly fee in exchange for bundles of reduced-rate trips with no surge pricing. In other words, Uber will cut you a deal on rides in exchange for steady business. The company may take a short-term profitability hit, but the goal is to gain long-term customer loyalty in a very young and turbulent market—and this customer loyalty is becoming more and more important as ridesharing becomes a commodity.

Third, the idea that venture capitalists get into deals on the strength of their brands can be exaggerated. A deal seen by a partner at Sequoia will also be seen by rivals at other firms: in a fragmented cottage industry, there is no lack of competition. Often, winning the deal depends on skill as much as brand: it’s about understanding the business model well enough to impress the entrepreneur; it’s about judging what valuation might be reasonable. One careful tally concluded that new or emerging venture partnerships capture around half the gains in the top deals, and there are myriad examples of famous VCs having a chance to invest and then flubbing it.[6] Andreessen Horowitz passed on Uber. Its brand could not save it. Peter Thiel was an early investor in Stripe. He lacked the conviction to invest as much as Sequoia. As to the idea that branded venture partnerships have the “privilege” of participating in supposedly less risky late-stage investment rounds, this depends from deal to deal. A unicorn’s momentum usually translates into an extremely high price for its shares. In the cases of Uber and especially WeWork, some late-stage investors lost millions. Fourth, the anti-skill thesis underplays venture capitalists’ contributions to portfolio companies. Admittedly, these contributions can be difficult to pin down. Starting with Arthur Rock, who chaired the board of Intel for thirty-three years, most venture capitalists have avoided the limelight. They are the coaches, not the athletes. But this book has excavated multiple cases in which VC coaching made all the difference. Don Valentine rescued Atari and then Cisco from chaos. Peter Barris of NEA saw how UUNET could become the new GE Information Services. John Doerr persuaded the Googlers to work with Eric Schmidt. Ben Horowitz steered Nicira and Okta through their formative moments. To be sure, stories of venture capitalists guiding portfolio companies may exaggerate VCs’ importance: in at least some of these cases, the founders might have solved their own problems without advice from their investors. But quantitative research suggests that venture capitalists do make a positive impact: studies repeatedly find that startups backed by high-quality VCs are more likely to succeed than others.[7] A quirky contribution to this literature looks at what happens when airline routes make it easier for a venture capitalist to visit a startup. When the trip becomes simpler, the startup performs better.[8]