Surge pricing also boosts supply, at least locally.The extra money is shared with drivers, whotherefore have an incentive to travel to areas withhigh 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 illustrates how the system is intended to work. JonathanHall, head of economic research at Uber, Cory Kendrick, a data scientist at the firm, and ChrisNosko, of the University of Chicago, compared two high-demand cases in New York city toillustrate how surge pricing is intended to work. In March 2015 it kicked in after a sold-outconcert by Ariana Grande, a singer, in an arena in the middle of Manhattan. As the show cameto an end, the number of people in the area opening the Uber app quadrupled in just a fewminutes. Uber's algorithm swiftly applied surge pricing; the average waiting time for a car roseonly modestly, while the “completion rate”—the share of requests for rides that are met—neverfell below 100%. On New Year's Eve in 2014, in contrast, Uber's surge-pricing algorithm brokedown for 26 minutes, leaving New York without surge pricing. The average wait time for a carsoared 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 ofalgorithms, cab drivers know to converge on a venue as an event finishes; more Uber driversthan normal were surely in the area at the end of Ms Grande's concert in expectation of theextra business. Yet the possibility of earning a surge fare may also strengthen drivers'incentives to anticipate and respond pre-emptively to high demand. Ironically, the betterUber'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 pricingnecessary 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 logic to its conclusion. Mr Schneidernoted that clever machine-learning tools could process Uber's piles of data and determinewhen and where demand is likely to outstrip the supply of cars. There would be no need towait until demand starts to rise, nor for drivers to scan concert schedules. The ability toanticipate demand would be of some use to Uber today: it could tell drivers where they arelikely to be needed. But they would presumably not respond as rapidly as they do to theinducement of surge fares. Eventually, however, Uber hopes to replace its human driverswith autonomous vehicles, which could be directed around the city by the company's computerswithout any pecuniary incentives. (The company still has an incentive to maximise earnings,though, so it might opt to keep surge pricing even if technology made it redundant, at therisk 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 remains a big part of the transport network in future, and whether it retainssurge pricing, depends in part on how well local governments manage the transport system asa whole. In districts or cities where travellers have appealing alternatives, in the form of goodpublic transport or private competitors to Uber, users will be more sensitive to price. Surgepricing will therefore not generate a big financial windfall for Uber (or its drivers). But wherepublic transport is thin on the ground, or where Uber has little private competition, it is adifferent story. In other words, surge pricing is really only as painful as local officials allow it tobe.
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。
姓名:李娜
加入一诺留学前,曾任职于太傻咨询北京总部,多年来在法律、教育、传媒、经济等文商类专业申请方面积累了丰富的经验,熟知美国、英国、香港、新加坡、澳洲等国家留学申请以及签证细节。
帮助数十名学生拿到几个国家的顶级院校录取,包括:芝加哥、康奈尔、杜克大学、宾夕法尼亚大学、西北大学、范德堡大学、南加州大学、波士顿大学、新加坡国立大学、巴斯大学、UCL等世界名校。曾帮助学生凭借88分托福斩获Purdue University, Indiana University(Bloomington)教育技术学PHD offer, 89分托福成功拿到南加州大学LLM录取。引领学生挖掘自身最大潜力,量身定做最佳留学方案。
版权所有@2012-2016 一诺留学网 京ICP备12034294号-1
联系电话:400-003-6508 010-62680991 传真:010-82483329 邮箱:service.bj@yinuoedu.net