A joint report by LightStream Research & Henry Kwon
Ride hailers pitch themselves to investors and regulators as disruptive P2P technology platforms which serve to link passengers with both commercially licensed and unlicensed vehicles using mobile apps. These services closely resemble services offered by dispatchers in the taxi dispatch service segment. However, because ride hailers are free from fixed fare and fleet size limitations imposed on the taxi industry in virtually all jurisdictions around the world, they have been able to utilise surge pricing to dramatically reduce the response time to customers at peak hours. During non-peak times, ride hailers tend to undercut traditional taxi pricing and, in our view, these two factors have provided greatest growth drivers for ride hailers over the past several years.
In our report conducted jointly by Henry Kwon and Lightstream Research for Smartkarma, we have analysed a large variety of markets in North America, Latin America, Europe, Asia (East, SouthEast and South), the Middle East and Africa to attempt to discern the characteristics which will determine the long-term winners in this industry and understand their true nature as businesses. As part of this process, we interviewed the dominant ride-hailing application in Sri Lanka (where many of the LSR team are based). The company, known as PickMe is unusual in that it is profitable at the EBITDA margin despite being constrained to an extremely small market with very low ASPs. By conducting this detailed research, we identified the following broad patterns in the ride-hailing markets around the world:
The question of whether ride hailers are taxis, private hire vehicles or P2P technology platforms, are in the process of being worked out by each jurisdiction that we have analysed, each with its own set of priorities (traffic congestion, public safety and/or service quality). In the end, we believe that ride hailers will come to be regulated one way or another just as the taxi industry was placed under regulation in the early part of the 20th century in the U.S. that closely resembles the current moves to regulate ride hailers. This means that ride hailers will have to pay taxes, answer to any pricing/licensing/fleet size regulations that authorities may impose based on their perception of ride hailers’ role in public welfare, and as NYC and London are imposing, certain wage and quasi-employee status requirements will have to be met. This is likely to result in long term cost pressures for ride hailers that may not be reflected in current consensus analyst forecasts, despite disclaimers from both Uber and Lyft that increased regulations will likely lead to higher cost pressures and/or the need to increase their prices.
Current equity market valuations have likely priced in these factors based on the post-IPO price performances of Uber (UBER US) and Lyft Inc (LYFT US), but the notion that ride hailers are taxi companies may not have sunk in completely, and it is this risk that we believe investors should keep in mind. Based on our observations, we further believe that localized EM ride hailers are better positioned competitively against developed market players based on business model sustainability.
Global Players | EM/Local Players | |
Knowledge of Home Market Rules? | 5 | 5 |
Under-developed/Deteriorating Home Market Public Transit systems? | 3 | 5 |
Accommodative government regulators? | 2 | 4 |
Drivers ability to make a living as independent contractors to ride hailers under current pricing? | 0 | 4 |
Total | 10 | 18 |
Scale: O (Lowest) - 5 (Highest) |
Source: Henry Kwon & Lightstream Research
We favour the emerging markets partly because we believe local knowledge is a key competitive advantage that has been demonstrated repeatedly, mostly through instances of local players beating out global major Uber and forcing its exit. Consumer customs are key to attracting riders and examples of their importance include Didi offering e-cashback rewards whereas Uber offered its standard discounts for fees, early offerings of three and two-wheeled options by local operators around South and South East Asia whereas Uber was slow to offer these same services, and Ola offering the booking of rides and information updates through SMS for India where smartphone penetration is lower than many other regions.
This need for localisation allows emerging market players to more than offset potential scale advantages generated by players like Uber on the cost side, particularly on server fees due to volume purchasing. Emerging markets also typically have an under-developed public transport system and taxi operators. As such, the overall competitive situation is less intense even if market sizes can be much smaller and penetration rates could be difficult to raise quickly with lower-income customers. In addition to reduced competition, the situation also typically makes regulators more welcoming of these services in order to address transport infrastructure deficiencies. The national loyalty and pride in a locally sourced “tech” company should also not be underestimated.
This situation potentially can allow these operators, not to displace incumbents, because they barely exist, but instead to focus on developing their ecosystem and build out the services already available in developed markets with lower up-front costs while also creating moderately well-paying jobs. The extension into other services such as food delivery may be similar to developed markets but financial services are an area where there is again often no incumbent to replace due to low levels of banking and loan penetration. Taxi operators in these regions typically do not have a real empire to protect and are more likely to be enticed by the potential to grow the pie than by the idea of defending their share of it.
For all these reasons we believe this industry is likely to generate the most value in emerging markets rather than in developed ones. In a nutshell, we believe the true change in economics that these models bring are not so much in running costs but in up-front costs (no need to invest in a massive taxi fleet, safety can be complemented with tracking rather than just background checks and driver screening and professionalism can be maintained through ratings rather than expensive training and reinforcement). As such we view them as poor versions of disruptive tech companies but as potentially very attractive tech companies if their role is to accelerate development (although valuations may or may not be justified).
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