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Ride Hailing in Emerging Markets Is More Than Transport
When Apple introduced the iPhone in 2007, only the most prescient of market observers would have prophesied that the smartphone would lead to a coming upheaval of urban transport. Just over a decade later, ride-hailing platforms rank as the most significant of the many revolutions the smartphone has wrought. In 2017, some 16 billion rides were taken worldwide, a number set to rise to 24 billion in 2018.1

In this, the third in our series of blogs on China/Asia innovation, we delve into a burgeoning technology segment that is increasingly intriguing in its vast potential for ubiquity: ride hailing and its adjacencies. It is an exciting area in which we envision extraordinary companies will outperform thanks to real options arising from idiosyncratic context unique to their geographies, including inequality and superior driver economics in the emerging world.

Emerging Market Size and Opportunity Are Much Larger

Over the past 5 to 10 years, technology has had a significant effect on economies across the globe, but the size and speed of the impact on emerging economies has been the most profound. In the case of ride hailing, underdevelopment in the physical transportation world has allowed for a leapfrog effect to the virtual world in emerging markets (EM). Of the 16 billion rides taken in 2017 globally, two-thirds were handled by Uber, China’s Didi, and Southeast Asia’s Grab.2 Adding India’s Ola, Go-Jek in Southeast Asia, and Careem in the Middle East, Asia alone took 70% of all ride-hailing trips in 2017.3 While Uber boasts 3 million drivers on its platform globally, Didi has onboarded 21 million, of which 5 to 6 million are active each month.4

This rapid adoption is a result of unique characteristics shared by many emerging markets: vast populations, coupled with social inequality, that have created a foundation for abundant driver supply and sustainable driver economics.  These characteristics have enabled ride-hailing leaders to offer pioneering services.

A Blessing in Disguise: Inequality and Driver Economics

Ultimately, the long-term profitability of the ride-hailing ecosystem hinges on the sustainability of platform economics and distribution. Our way of looking at this sector does not differ from our analysis of systemic ecosystem profitability for marketplaces, which is largely about a balance between the gross merchandise value and merchant take rates. Similar to Alibaba’s consistent emphasis on merchant and brand empowerment through technology infrastructure support, ride-hailing businesses will only be sustainable on a large scale if platforms can ensure drivers that the economics will work for them.

One way platforms accomplish this is by aggregating expenses to reduce driver unit costs. With the capacity to collect and analyze meaningful data from other high-frequency use cases, ride-hailing platforms can add value by providing route optimization and effective price segmentation through dynamic algorithms. The asset, in this case the vehicle, can operate during multiple shifts through creative methods such as co-ownership or financial firm ownership, which can reduce capital and operating unit costs.

As platforms experiment with ways to improve driver economics, be it through different tipping mechanisms, smarter customer segmentation, or dynamic routing and utilization, they are all seeking a more mature operational mode that supports systemic ecosystem profitability. In essence, it is the pursuit of a sustainable balance between enabling adequate driver incomes and maintaining a profitable take rate.

Full-time drivers generally experience a greater than median level of income across Asia. Exhibit 1.  At about $10 per ride, Uber drivers make about 2.7 times as much as those driving for Didi or Grab.5  But the cost of their time is also higher. The minimum wage per hour in the United States, at $8, is about 3.5 times the rate in China or Southeast Asia.6 This means that a driver in Asia is more likely to cover the minimum wage, and potentially make multiples of it by devoting more hours to driving. For example, Didi drivers who work eight hours a day can make a net income of RMB14,000 a month,7 about four times the salary of the typical taxi driver in Beijing. In contrast, only the most hard-working Uber drivers, and only in select high-density cities such as New York or San Francisco, clock annual earnings of $70,000,8 which would still be just over 2.3 times the income of the typical U.S. taxi driver.9

Exhibit 1: Driver Economics Underpinned Success of Ride Hailing in Asia

Ride-hailing companies need to focus constantly on improving driver economics as their single most critical mission, in our view. Platforms could also empower drivers by facilitating aggregation of equipment purchases and negotiating discounts for fleet purchasing. This concept would also apply to insurance shopping, fuel purchases, development of third-party asset ownership/lease, etc.

Ride Hailing Fills Transport Gap Across Asia

On the demand side, low levels of passenger car ownership, coupled with the inadequacies of public transportation alternatives, have provided significant catalysts for the widespread adoption of ride-hailing and its derivatives. Further, asset utilization levels for non-commercial automobiles are typically low. Developing countries, by definition, have low income levels, and thereby low discretionary capacity to own vehicles, which are, for most households, the single largest durable expenditure they are likely to make. Measured by National Gross Income per capita over average purchase price, new passenger cars are 50% less affordable in China versus the United States, and far less affordable in most developing economies in Southeast Asia and Latin America! Throw in fuel costs, maintenance, insurance, asset depreciation, and finance costs, and one can quickly see the lure of ride-hailing services among the poor. Moreover, in many large Asian metropolises, registration costs are high in an effort to curb congestion and pollution.

Despite significant infrastructure investment across Asia, investment in public transport has not kept pace with urbanization trends.  According to the United Nations, Asia is home to 54% of the world’s urban population. In China, 60% of the population lives in urban areas compared to just 26% in 1990.10 However, unlike developed Asian metropolises like Tokyo, Seoul, and Singapore, where 60% to 80% of inter-city mobility needs are fulfilled by a public transport system, urban cities in China have a public transport adoption rate of just 30% to 50%, thanks largely to less developed infrastructure.11  In Southeast Asia, the rate is below 30%.12

Ride-hailing platforms are filling these transport gaps. Platform companies are beginning to collaborate with public transport authorities to explore opportunities around carpooling and multi-mode transport.

Local Context Matters for Adjacent Businesses

Opportunities are emerging in many developing countries for ride-hailing platform monopolies beyond simply passenger transport. The greater relevance of ride-hailing to lower income countries, outlined above, is a function of historic context. Context also frames opportunities in adjacent businesses, which are relatively insignificant to Uber, its Western competitors, and even Didi in China. We see two big opportunities that the twin Southeast Asian giant platforms – Grab and Go-Jek – are tackling today. 

First, food delivery has the same inherent edge in the developing world as ride hailing (massive pools of low-cost labor) and is growing at rapid rates. In fact, food delivery literally rides on top of the inequality of ride hailing in every market, namely the large surplus of under-employed driver-entrepreneurs. In Jakarta, two-wheelers that can zip around town avoiding traffic (and quite often roads!) to complete trips dominate the ride-sharing segment. Drivers for Grab and Go-Jek minimize downtime by providing efficient food delivery services that operate using the same concept.

This opportunity is not as readily apparent in larger markets like China or the United States, where standalone companies already have achieved inherent natural advantages. For example, the aggressively competitive Chinese food delivery/local services market led by Meituan and constrains Didi’s horizontal expansion; in the United States, Uber Eats has found it difficult to gain critical mass against the established Grubhub.

Second, digital payments are a natural extension of high-frequency use cases like food delivery and ride hailing, bringing meaningful upside as it leads to the development of full-fledged fintech platforms. This dynamic is illustrated by Alibaba and its online payment platform, Alipay, in the context of e-commerce. Similar to how Alibaba created Alipay to encourage buyers on its e-commerce marketplace to trust third-party sellers (by allowing Alipay to hold payment in escrow until the buyer is satisfied with the product), both ride hailing and food delivery services are the intuitive high-frequency use cases that draw consumers to deposit money into bank accounts and e-wallets. Payment infrastructure not only helps platform companies like Grab and Go-Jek in pricing and take-rate standardization, but also ignites potential in areas such as credit intermediation, insurance, and wealth management. Exhibit 2. Southeast Asian markets are well positioned to leapfrog swiftly in this aspect, thanks to their historically underdeveloped offerings of payment options. With the exception of Malaysia and Singapore, most people in the region don’t own credit cards or even bank accounts.13

Exhibit 2: Opportunities Beyond Transport -- Interesting Optionality in SE Asia

Lumping together all of these unique, yet logical, scenarios beyond ride hailing, the industry leaders in geographies with underdeveloped technology infrastructure stand to gain the most. Ultimately, whoever owns the data reigns, as the more data a company aggregates through different service scenarios, the more it knows about individual users and the better it is able to cater to their needs. This data collection and analytics capability also feed back to the implementation of various efforts for driver economics improvement, such as customer segmentation and dynamic routing.

Consolidation Power Behind the Global Ride-Hailing Consortium

Didi, along with its investor SoftBank, has been ramping up global ride-hailing consolidation through investment. The Chinese ride-hailing giant has invested in Lyft, Uber, Grab, India’s Ola, and the Middle East’s Careem. Meanwhile, Softbank runs a $100 billion tech fund, which has enabled the investment powerhouse to bypass its peers, as well as Chinese and U.S. tech giants, to strike deals with startups under the overarching thesis of Artificial Intelligence. Having tightened its grip over the global ride-hailing sphere, with estimated stakes of 15% in Didi, 17% in Uber, 27% in Ola, and 20% in Grab, Softbank is poised to loom large over the global ride-hailing landscape. Its influence on these companies can be inferred by the recent Grab-Uber merger in Southeast Asia. Betting on the disruptive impact of autonomous vehicles (AV), Softbank has also been making a number of investments related to changes in mobility: NVIDIA, a key provider for companies looking to add automated driving; Arm, a key chip designer enabling AV; and GM Cruise, an autonomous driving operator, to name a few.

Alongside the overheating ride-hailing competition in Asia and much of the developed world, companies in Russia, India, and Brazil are also poised for superlative growth while taking advantage of similar geographic advantages.We particularly like Yandex. A Russian company, it enjoys a host of real options unifying the characteristics mentioned above. Additionally, because of the antagonistic relationship that has evolved between the United States and Russia, Yandex has a feature that most tech companies with glittering success don't have: an extremely attractive share price.

Significant Challenges Remain

It is important to realize that recent numbers across almost all regions are being adversely impacted by the embryonic stage of market development in the form of driver and consumer subsidies. In Asia, discounts to consumers remain high, at around 6% of gross revenue, whereas Uber has reduced these to under 2%.14 Aside from competition-induced market development, regulatory attention in China has ramped up after some unfortunate crimes involving Didi drivers. Growing new businesses in food delivery and fintech are likely to take a toll on Grab’s profitability, even as its ride-hailing business improves after the exit of Uber from the region. Even so, Grab enjoys a full suite of optionality that very few other platforms can access.

The story of ride hailing is indeed a global one. As consolidation continues to take place amid the evolving global competitive topography and technological advancement in areas like artificial intelligence and data analytics, we are confident about the multitude of real options lying ahead, and believe that truly audacious companies that are able to grasp these opportunities will be able to leapfrog global peers.

Oppenheimer Developing Markets Fund Top 10 Stock Holdings by Issuer

Alibaba Group Holding Ltd.6.0%
Taiwan Semiconductor Manufacturing5.4
Novatek OAO4.5
Glencore Plc4.1
Tencent Holdings Ltd.4.1
Housing Development Finance Corp.3.2
Kotak Mahindra Bank Ltd.2.8
AIA Group Ltd.2.7
LVMH Moet Hennessy Louis Vuitton2.4

All holdings are as of 10/31/18, subject to change.


作者:Justin Leverenz、Bhavtosh Vajpayee、Menghan Li

当 Apple 于 2007 年推出 iPhone 的时候,只有最有先见之明的市场观察者能够预料到智能手机会给城市交通带来巨大变化。短短十几年的时间,网约车服务平台便成为智能手机引发的最为重要的革命之一。2017 年全球网约车单量约 160 亿,到 2018 年这个数字将上升至 240 亿 1。


在过去 5 至 10 年间,技术对全球经济产生了巨大的影响,但其对新兴经济体的影响范围和速度最为深远。就网约车服务来说,在新兴市场 (EM),实体交通服务的落后促使虚拟交通服务的飞跃式发展。在 2017 年全球 160 亿单网约车服务订单中,三分之二由优步、中国的滴滴出行和东南亚的 Grab 包揽 2。加上印度的 Ola、东南亚的 Go-Jek 和中东的 Careem,亚洲占据 2017 年所有网约车服务出行量的 70% 3。优步的平台在全球共拥有 300 万名司机,滴滴出行则拥有 2100 万名司机,其中每月活跃人数为 500 至 600 万 4。





一般来说,在整个亚洲,全职司机的收入在收入中位水平以上。表 1。优步司机每次接单可赚取 10 美元左右,大约是滴滴出行或 Grab 司机的 2.7 倍 5。但是他们的时间成本更高。美国最低工资为每小时 8 美元,大概是中国或东南亚国家的 3.5 倍 6。这意味着亚洲国家的司机更可能超过该最低工资水平,并且有可能通过工作更长的时间来赚取几倍于最低工资的收入。例如,滴滴出行司机每天工作八小时,每月便可赚取人民币 14000 元的净收入 7,大约是北京普通出租车司机薪水的四倍。相反,只有最勤劳的优步司机,而且只有在像纽约或旧金山之类人口密度高的城市,其年收入才能达到 70000 美元 8,这仍然仅仅是美国普通出租车司机收入的 2.3 倍 9。

Exhibit 1: Driver Economics Underpinned Success of Ride Hailing in Asia



尽管亚洲对基础设施进行了大量投资,但是对公共交通的投资仍跟不上城市化趋势的步伐。根据联合国数据,亚洲拥有全球 54% 的城镇人口。中国的城镇人口比例为 60%,而 1990 年时仅为 26%10 。但是,在东京、首尔和新加坡等亚洲发达城市,公共交通系统便可满足 60% 至 80% 的城际出行需求,与之不同的是,中国的城市的公共交通采用率仅为 30% 至 50%,这很大程度上归因于不太发达的基础设施 11。在东南亚,这个数字低于 30% 12。


不仅仅在客运行业,在很多发展中国家其他行业均出现了网约车平台垄断的机遇。网约车服务与低收入国家的极大关联,如上所述,是历史性背景的作用。这种背景同样也为其邻近产业带来机遇,相对而言,这对其西方竞争者优步,甚至是中国的滴滴出行来说无关紧要。我们可以看到两大亚洲巨头平台 - Grab 和 Go-Jek - 正在抢夺的两大机遇。

首先,在发展中国家,外卖和网约车服务一样具有内在优势(大量的低成本劳动力),而且正以高速增长。实际上,外卖可以说是在各市场网约车服务不均的基础上发展起来的,即未充分就业的司机-企业家大量过剩。在雅加达,骑双轮车的人可以避开交通拥堵(和高峰路段)在城镇快速穿行,在网约车行业中大行其道。Grab 和 Go-Jek 的司机通过提供有效率的外卖服务(以相同的概念运作)以最大限度减少停工时间。

这种机遇在一些例如中国或美国的大型市场并不明显,在这些市场一些独立的公司已经取得了内在的自然优势。例如,由美团和饿了么领导的中国外卖/本地服务市场竞争激烈,限制了滴滴出行的横向扩张;在美国,Uber Eats 发现很难从知名的 Grubhub 公司夺取临界量。

其次,数字化支付是外卖和网约车等高频使用场景的自然延伸,它不仅促进了成熟的金融科技平台的发展,还带来了富有意义的积极影响。在电商背景下,阿里巴巴及其线上支付平台支付宝将这一动力发挥得淋漓尽致。如同阿里巴巴创造支付宝来鼓励其电商市场的买家信任第三方卖家一样(在买家确认收到合格货物前,由支付宝替买卖双方保存支付款),网约车和外卖服务都是吸引消费者将资金存在银行账户或电子钱包中的直观高频使用场景。支付基础设施不仅有助于 Grab 和 Go-Jek 等平台公司对定价与转化率进行标准化,还激发了信贷中介、保险和财富管理等领域的潜力。表 2。由于东南亚的支付服务的发展程度相对落后,因此该市场在这一方面具备飞跃式发展的潜力。除马来西亚与新加坡以外,该区域的多数人没有信用卡,甚至连银行账户也没有 13。

Exhibit 2: Opportunities Beyond Transport -- Interesting Optionality in SE Asia


通过投资,滴滴出行与其投资方软银集团一起促进了全球网约车服务的整合。作为中国网约车巨头,滴滴出行投资了 Lyft、优步、Grab、印度的 Ola 和中东的 Careem。与此同时,软银集团成立了一只千亿美元技术资金,用来投资专注研究人工智能技术的初创公司。这家投资帝国凭借该基金将同行和中美技术巨头甩在身后。软银集团加强了对全球网约车领域的掌控,预计持有滴滴出行 15% 的股权、优步 17% 的股权、Ola 27% 的股权、Grab 20% 的股权,覆盖了全球网约车格局。从近期东南亚 Grab 和优步的合并便可推测它对这些公司的影响力。考虑到无人驾驶汽车 (AV) 带来的颠覆性影响,软银集团也曾在出行产业变革方面进行了大量投资:例如,自动驾驶技术的主要提供商英伟达 (NVIDIA);实现 AV 的主要芯片设计商 Arm;无人驾驶运营商 GM Cruise。

随着亚洲和大部分发达国家的网约车竞争进入白热化阶段,俄罗斯、印度和巴西的企业也开始发挥相似的地理优势,准备好迎接巨大发展。我们尤其欣赏 Yandex。Yandex 是一家俄罗斯企业,拥有大量集上述特性于一体的实物期权。此外,由于美国与俄罗斯之间的敌对关系,Yandex 拥有一个多数成功企业所没有的特质:极具吸引力的股票价格。

我们需要了解的是,由于市场仍处于萌芽期,司机和消费者补贴高昂,近期几乎所有地区的数据都受到不利影响。亚洲的消费者补贴居高不下,约为总收入的 6%,而优步则将它们削减至 2% 以下 14。除了市场发展受竞争驱动,在滴滴司机涉嫌数宗不幸的犯罪案件后,中国加大了对网约车服务的监管力度。即使在优步退出中国网约车市场后,Grab 的网约车服务得以发展,但外卖和金融科技领域中不断发展的新兴业务可能会给其盈利能力造成重大不利影响。尽管如此,Grab 拥有多数其他平台难以企及的完整选择权。







所有所持股份的截止日期为 2018 年 10 月 31 日,可能会有所变动。

奥本海默基金的股票不是任何银行的存款或债务,没有任何银行提供担保,未受到 FDIC 或任何其他机构的保障,涉及包括可能损失所投资本金金额在内的投资风险。

在投资任何奥本海默基金前,投资者应谨慎考虑基金的投资目标、风险、费用和开支。基金招募说明书和摘要说明均包含上述信息和有关基金的其他信息;您可咨询您的理财顾问,或可访问 或致电 1 800 CALL OPP (225 5677) 获取。在投资前,请仔细阅读基金说明书和摘要说明。

  1. a, bSource: ABI Research, 9/4/18.
    资料来源:ABI Research,2018 年 9 月 4 日。
  2. a, bNote: Uber, Didi and Grab are averaging 15 million, 25.5 million, and 5.3 million rides a day, respectively, as per company disclosures and media reports, as of 2018.
    注:截至 2018 年,根据公司披露数据和媒体报道,优步、滴滴出行和 Grab 的日均网约车服务单量分别为 1500 万、2550 万和 530 万。
  3. a, bSource: ABI Research, 9/4/18.
    资料来源:ABI Research,2018 年 9 月 4 日。
  4. a, bSource: Company disclosures and media reports, as of 2018.
    资料来源:公司披露数据和媒体报道,截至 2018 年。
  5. a, bNote: Based on disclosed financials for Uber, and industry discussions for Didi and Grab, mid-2018 data.
    注:根据所披露的优步的财务数据以及关于滴滴出行和 Grab 的行业讨论,2018 年年中数据。
  6. a, bSource: World Bank figures, 2017.
  7. a, bSource: South China Morning Post, Didi Chuxing says it employs 3.9 million retired soldiers as drivers, easing China’s jobless veterans problem, 7/30/18.
    资料来源:《南华早报》,滴滴出行表示该公司雇用了 390 万名退休军人作为司机,缓解了中国退伍军人失业问题,2018 年 7 月 30 日。
  8. a, bSource: RideGuru,, accessed 11/18.
    资料来源:RideGuru,,访问时间为 2018 年 11 月。
  9. a, bSource: PayScale,, accessed 11/18.
    资料来源:PayScale,,访问时间为 2018 年 11 月。
  10. a, bSource:  United Nations, Department of Economic and Social Affairs, Population Division, 2018.
    . 资料来源:联合国经济和社会事务部人口部,2018 年。
  11. a, bSource: World Economic Forum for Developed Asia Metropolises and Local Government Reports for China, 2018.
    资料来源:世界经济论坛关于亚洲发达城市的报告和中国地方政府报告,2018 年。
  12. a, bSource: Boston Consulting Group, Unlocking Cities – The impact of ridesharing in Southeast Asia and beyond, 11/17.
    资料来源:波士顿咨询公司,开放城市 - 共享出行在东南亚和其他地区的影响,2017 年 11 月。
  13. a, bSource: KPMG research, 2016.
    资料来源:毕马威会计师事务所的研究,2016 年。
  14. a, bSource: Uber disclosures and media reports.