2016年经济学人 车费的变动 寻找出租车供需平衡解决方法(下)

（单词翻译）

Surge pricing also boosts supply, at least locally. The extra money is shared with drivers, who therefore have an incentive¹ to travel to areas with high demand to help relieve the crush.

至少在局部地区动态价格策略增加了供给。司机们可平分额外费用，这使得他们愿意开车到需求高的地方拉客，这有助于缓解交通拥堵。

A recent analysis published by Uber illustrates³ how the system is intended to work. Jonathan Hall, head of economic research at Uber, Cory Kendrick, a data scientist at the firm, and Chris Nosko, of the University of Chicago, compared two high-demand cases in New York city to illustrate² how surge pricing is intended to work. In March 2015 it kicked in after a sold-out concert by Ariana Grande, a singer, in an arena⁴ in the middle of Manhattan. As the show came to an end, the number of people in the area opening the Uber app quadrupled in just a few minutes. Uber's algorithm swiftly applied⁵ surge pricing; the average waiting time for a car rose only modestly, while the “completion rate”—the share of requests for rides that are met—never fell below 100%. On New Year's Eve in 2014, in contrast, Uber's surge-pricing algorithm broke down for 26 minutes, leaving New York without surge pricing. The average wait time for a car soared from about two minutes to roughly eight, while the completion rate dropped below25% (see chart).

优步最近的一项分析解释了峰时价格工作的机制。优步的经济研究部主管约翰逊·霍尔、数据研究员科里·肯德里克还有芝加哥大学的克里斯·诺斯克比较了纽约两个高需求的案例以说明峰时价格的作用机制。2015年3月，爱莉安娜·格兰德在曼哈顿中央举办了一场演唱会，在这场门票销售一空的演唱会之后，峰时价格机制开始起作用。当演唱会接近尾声，仅几分钟内这个地区打开优步app的人数就是之前的四倍。优步的计算程序很快地启动了峰时价格机制；每辆车的平均等待时长只增长了少许，然而完成率——打的份额的完成度从没降到100%以下。相比之下，2014年新年除夕夜峰时价格机制崩溃了整整26分钟，致使纽约处于无峰时价格状态。每辆车的平均等待时长从两分钟涨到了八分钟，而完成率降到了25%以下。（见表格）

The comparison may overstate the power of surge pricing. Even without the help of algorithms, cab drivers know to converge⁶ on a venue⁷ as an event finishes; more Uber drivers than normal were surely in the area at the end of Ms Grande's concert in expectation of the extra business. Yet the possibility of earning a surge fare may also strengthen drivers' incentives⁸ to anticipate and respond pre-emptively to high demand. Ironically, the better Uber's surge-pricing algorithm works, the less the company will need to use it, since drivers' pre-emptive responses will tend to eliminate the demand imbalances that make surge pricing necessary in the first place.

这个对比可能夸大了峰时价格机制的作用。即使没有程序的帮助，司机们也知道如何在一场盛事结束后自行往利益靠拢；格兰德的演唱会结束时，冲着生意比以往多，这个地区的司机也比以往更多。趁价格处于峰时来赚取更高利润的机会激发司机们对高需求做出预测并先下手为强。讽刺的是，优步的峰时价格机制的作用越好，公司对其需求却越少，因为司机会先下手为强，这样就会消除供需不平衡，而峰时价格机制只有在供需不平衡时才会起作用。

There are tantalising hints that Uber hopes to follow this logic⁹ to its conclusion. Mr Schneider noted¹⁰ that clever machine-learning tools could process Uber's piles of data and determine when and where demand is likely to outstrip¹¹ the supply of cars. There would be no need to wait until demand starts to rise, nor for drivers to scan concert schedules. The ability to anticipate demand would be of some use to Uber today: it could tell drivers where they are likely to be needed. But they would presumably not respond as rapidly as they do to the inducement of surge fares. Eventually, however, Uber hopes to replace its human drivers with autonomous¹² vehicles, which could be directed around the city by the company's computers without any pecuniary¹³ incentives. (The company still has an incentive to maximise earnings¹⁴, though, so it might opt¹⁵ to keep surge pricing even if technology made it redundant¹⁶, at the risk of further public rage.)

但是总会有一些似有若无的暗示表明优步希望继续采用这样的机制。施耐德就指出过精明的机器研究工具能够处理优步的数据堆并且能够预测出乘车需求大于供给的时间和地点。无需等待需求上涨亦无需司机查看演唱会的日程。对如今的优步来说预测需求的能力是极有用的，因为司机可以知道哪些地方需求比较大。但是他们对于需求的反应可能没有对价格上涨的诱惑反应快。然而优步的最终目标是用自动驾驶来取代人类司机，这样的话公司便可以通过计算程序来操控，这样就不用受到金钱诱因的影响了。（然而公司还是有可以使利润最大化的激励机制，所以它还会保留峰时价格机制，即使这个机制会在技术的发展下变的多余，而且还会引起众怒。）

Apps and downs

应用软件的起伏变动

Whether Uber remains¹⁷ a big part of the transport network in future, and whether it retains surge pricing, depends in part on how well local governments manage the transport system as a whole. In districts or cities where travellers have appealing alternatives, in the form of good public transport or private competitors to Uber, users will be more sensitive to price. Surge pricing will therefore not generate a big financial windfall for Uber (or its drivers). But where public transport is thin on the ground, or where Uber has little private competition, it is a different story. In other words, surge pricing is really only as painful as local officials allow it to be.

未来优步是否能保持网络交通巨头之一的地位，是否继续保留峰时价格机制，都部分取决于当地政府能否统筹交通系统。在那些出行者可以有替代出行方式的街道和城市，比如运作良好的公共交通系统和像优步这样的私营竞争者，他们对价格也更加的敏感。因此峰时价格并不会让优步（或者其司机）坐享其成。但是在那种公共交通不发达地区或者优步的竞争者很少的地方，将会是另一番景象。换句话说，峰时价格机制的可恨程度取决于当地政府。