Young Economist 2016: Sherwood Lam
01 Oct 2016
Should internet companies like Uber and Airbnb be regulated?
By Sherwood LamShun Hei
Fuelled by trust, reputation and efficiency, internet companies such as Uber and Airbnb are part of a bigger movement dubbed as ‘sharing economies’. The sharing economy resolves information gaps by using the internet to match consumer demand to spare capacity, and as such is able to compensate households for their idle resources while benefiting consumers in the form of lower prices, increased variety and convenience. Sharing economies also allow consumers to rent expensive goods for short periods of time instead of buying them. It is no wonder the industry is growing rapidly, with pioneers such as Lyft, Airbnb and Uber raising $680m, $1.5bn and $4.8bn in funds respectively in 2015. (Ronny Kerr, 2015) Consequently, the previously under-the-radar industry was brought into the spotlight, with many calling for its regulation on the basis of unfair competition to traditional industries,most notably the taxi industry, amongst other reasons. Government regulation however, is both costly and not designed for the sharing economy: regulations often cost millions to enforce, millions that could be used for infrastructure instead. Instead of traditional regulation, I believe a combination of self-regulation and compulsory introduction of a shared third-party company such as TrustCloud would be better suited and more cost effective for these internet-based companies. Meanwhile overregulated industries should be partly deregulated to encourage fairer competition.
One of the main criticisms of sharing economies is their apparent lack of quality control: as users provide products instead of a company, they may cheat customers to maximise their profits. However, this is not true, as users have an incentive to treat customers fairly. Most sharing economies employ a user-based rating system, where buyers can freely access a supplier’s rating before making a purchase, a user’s rating forms what many people call ‘reputation capital’ and it quickly becomes apparent that suppliers should treat customers fairly to maximise profits in the long term. If a supplier plans to sell repeatedly, we can model the process as a repeated game as drawn below. Consumers start by making the decision of whether to purchase from the supplier or take their business to another supplier, ceteris paribus the customer is much more likely to purchase the good if the supplier has a good rating. If the consumer decides to take their business elsewhere the supplier earns nothing, on the other hand, if the good/service is purchased the supplier then has a decision to make: should I exploit the customer or not?
On the one hand, the supplier would gain more in the short-term, but after being exploited the customer would leave a bad review, putting off future customers from buying especially since the internet makes this information easily accessible; an exploitative supplier should only expect to earn profits from the first few customers, after which the supplier will receive no business or be fired by the company itself. On the other hand, if the supplier decided to treat the customer fairly they would earn less in the short term, but positive reviews would ensure future business and hencemore profit in the long-term. No quality regulation is needed as producers are have an incentive to treat consumers fairly. In real life this translates to 93% of Uber users being satisfied compared to 52% of black cab users (Dan Taekema, 2015) and ‘EliteTaskers’ (TaskRabbit users with a high rating) earning three times more than their non-elite counterparts (TaskRabbit Support, 2016). However, there are some caveats to this. Firstly if a supplier believes that by exploiting the customer once they can make enough to outweigh the loss of future business on the platformthey may do so, this is particularly true for platforms such as Airbnb where a single exploit can make thousands. Secondly some sharing economies such as Airbnb have twoway marketplaces with non-anonymous rating systems where both consumers and producers rate each other non-anonymously. Customers with bad ratings find it hard to find suppliers, moreover customers who frequently give negative reviews are discriminated against. As the product is a sunk cost and consumers would be better offwith a good reviewthan a bad one, implicit collusion is encouraged between suppliers and customers. Consequently threats of bad reviews are ineffective as suppliers realize that it would not be in the customer’s interest to carry them out. Regardless of the quality of product producers continue to receive positive reviews, allowing producers to abuse their customers without retribution. Airbnb is a perfect example of this: the same properties listed on both TripAdvisor and Airbnb were 14% more likely to receive a 4.5 star rating on Airbnb (Zervas, G., Proserpio, D. and Byers, J., 2015).
Using quality regulation in the form of an inspection before registration would be expensive, whereas an anonymous complaint centre would fail to prevent exploitation until it occurred if suppliers believed the one-off profits were worth expulsion from the platform. In cases where the system is undermined, we should introduce a third-party company which will be more cost-effective, ensure fair treatment of consumers and increase revenue of suppliers and sharing economies alike: I will elaborate on this later. Otherwise, sharing economies can be trusted to self-regulate their quality.
Historically the US taxicab industry was brought under regulation in the 1930’s in order to combat soaring taxi driver numbers brought about by the Depression Era which nearly doubled in the span of a few years (Rubenstein, 2014). In a prime example of the tragedy of the commons, rapid entry into the taxi driving market induced by low costs of entry and unemployment resulted in increased response times from congestion, and declining wages caused high turnover which in turn caused a decrease in service quality leading to even lower wages in a vicious cycle. To counter this the US introduced regulation on entry (medallion system), rates and finally service standards, after which there was ‘little or no entry into the industry except by the purchase of licences or permits fromexisting operators’ (Teal, R.F. and Berglund,M., 1987). Firms like Uber have been accused of providing unfair competition to their traditional counterparts, for instance, NewYork City yellow cab drivers have to pay for amedallionwhich costs $1.32m (Van Zuylen- Wood, 2015), London black cab drivers have to take a Knowledge of London test (TfL, 2016), and drivers in both cities face fixed rates, none of which Uber drivers have to do (Uber has surge pricing). This regulation asymmetry has led to widespread outrage amongst taxi drivers, with many calling for an outright ban on Uber. Most economists however, would argue that competition for the monopolistic taxi industry is welcome: since Uber’s debut there has been a decline in customer complaints per taxi trip (Wallsten, 2015), an increase in the net number of vehicles available for hire (Florida State University, 2014), and a lower cost alternative for consumers. Nowadays unemployment is much lower and there is a much bigger variety of jobs to choose from, society no longer requires the medallion system.
The issue therefore, lies within the onerous regulation ironically created by taxi firms themselves to monopolize the industry. In 1989, New Zealand deregulated their taxicab industry, leading to shorter waiting times, a decline in fares and a greater range of services (Morrison, P.S., 1997). Evidence from US states such as Seattle however, appear to contradict the claim that deregulation leads to an increase in consumer welfare: the mean fare increased by 145%in deregulated cities compared to 133% in regulated cities (Kang, C.H., 1998). The true reason behind this was the different type of deregulation underwent by the respective countries, while New Zealand only removed the quantitative limit on licences and kept fare control, Seattle removed fare control which led to a huge rate variation. Due to the nature of the non-radio dispatch industry customers have an incentive to take the first cab encountered and hence its price, since the waiting time and prices for the next cab are unknown, giving taxi drivers an unprecedented bargaining power to exploit riders with. This presents a question: should we regulate Uber’s pricing? Unlike Seattle taxis, Uber’s pricing is universal across all Uber drivers and prices are readily available on their website, the information costs associatedwith checking prices are much lower. Furthermore, regulations on pricing would disable Uber’s innovative surge pricing algorithm, an algorithm which applies a multiplier to fares to equilibrate market supply and demand. Although widely complained about by users, customers are forewarned and it ensures market clearing by motivating more drivers to work, whilst allocating rides to those who are the most willing and able to pay for them, in otherwords, the perfect price mechanism. Surge pricing maximises both consumer and producer welfare, during an Ariana Grade concert surge pricing ensured a 100% ride completion rate with an average waiting time of 2.6 minutes, without which driver’s would have made an estimated 13% less. In contrast, on New Year’s Eve (2014-2015) when surge pricing was not in effect completion rates fell to less than 20% (Hall, J., Kendrick, C. and Nosko, C., 2015). While high prices are bad, no service at all is worse, a price ceiling would eliminate the consistency afforded by Uber’s surge pricing algorithm, harming drivers and riders alike.
Instead of increasing regulation on sharing economies to make them less competitive, the government should increase traditional business’s competitiveness by removing unnecessary regulations which has been proven to increase consumer welfare; by undergoing similar deregulations to New Zealand such as wavering the application fee for taxi drivers (currently costs more than £1000 in total)we can ensure fairer competition between the industries.
A quick search of ‘Uber driver satisfaction’ on google yields a host of negative reviews from previous drivers (Google, 2016), low employee satisfaction rate in the sharing economy isn’t exclusive to Uber, with Taskrabbit receiving a 2.2/5 rating on GlassDoor with many employees accusing the company of exploitation (GlassDoor, 2016). However, the term ‘employee’ is a poor choice of word, as ‘contractors’ for these firms are not legally considered employees and as such are not eligible for insurance, sick pay, the national minimum wage or protection against unfair dismissal. While the argument ‘If you don’t like it, work for somebody else’ usually applies to independent contractors, sharing economies are different in that they are platform providers. In 1998 Microsoft was sued for making switching between operating platforms diffucult, effectively locking consumers into their system and overcharging them (The United States Department of Justice, 1999). Similarly, the complex registration process for sharing economies makes it relatively hard to switch between employers, in addition employees lose their ‘reputation capital’ after leaving; unlike other independent contractors workers face entry and exit costs and can hence be exploited to a greater extent before they quit. Nevertheless, changing their legal status from independent contractors to employees would harm employer and employee alike, in an Uber spokesperson’s own words:
‘As employees, drivers would drive set shifts, earn a fixed hourly wage, and lose the ability to drive using other ride-sharing apps as well as the personal flexibility they most value’ (Alison Moodie, 2015) With 42% of female Uber driver’s claiming that the primary reason they worked with Uber was to work a flexible schedule and 51% of drivers working less than 15 hours a week compared to 4% of taxi drivers (Hall, J.V. and Krueger, A.B., 2015), it is obvious that flexibility is indeed an important factor and rebranding them as employees is not a good solution. A better solution would be to encourage competition between sharing economy firms in the labour market. Although there are several platforms to choose from, barriers to switching prevent workers from changing platforms, granting firms a degree of monopsony. Unlike traditional monopsonys in the labour market information failure is not an issue: there is an abundance of information available as firms have an incentive to advertise themselves, furthermore information costs are low compared to traditional businesses thanks to the internet.
Instead of government regulation, we should force users to sign up to sharing economies through a third party company such as TrustCloud to facilitate the transfer of reputation capital between platforms which would otherwise be lost. Moreover, the threat of having a permanent negative reputation combined with being banned from multiple platforms would deter most suppliers from exploiting customers, addressing the issue of exploitation in the sharing economy. Letting users sign up through TrustCloud would also remove the need to pay the background check fees and go through the application process more than once. Workers would benefit from lower costs of entry and exit, and as a result sharing economy firms would be forced to offer competitive working conditions without extra regulation. Additionally, letting a third-party handle applications would increase the revenue of sharing economies and its suppliers as well by increasing consumer confidence. Firstly, suppliers would be detered from exploiting consumers. Secondly, a third-party company would have no incentive to allow dangerous or underqualified individuals to work in the industry, even if they offered lower wages.
The sharing economy is an economic innovation made possible by 21st century technology, it represents an extra source of income for workers, lower prices for consumers and reduced wastage for society as a whole. Rather than trying to extend government regulations to cover something it wasn’t designed for, we should pursue a more cost-effective, better adapted approach by trust reputation to replace regulation and allow the sharing economy and its members to regulate themselves with the mandatory help of third-party businesses such as TrustCloud. Meanwhile to ensure fairer competition, we should follow New Zealand’s example and partly deregulate overregulated industries such as the taxicab industry.
Alison Moodie (2015) Hillary Clinton criticises the Uber business model for exploiting workers, Available at: https://www.theguardian.com/sustainable-business/2015/jul/14/hillary-clinton-criticises-the-uberbusiness-model-for-exploiting-workers (Accessed: 3rd July 2016).
Dan Taekema (2015) Poll finds rising Uber ridership — and satisfaction, Available at:https://www.thestar.com/news/gta/2015/12/30/poll-finds-rising-uber-ridership-andsatisfaction.html (Accessed: 1st July 2016).
Google (2016), Available at: https://www.google.co.uk/?gws_rd=ssl&sourceid=chrome&ie=UTF-8&q=uber+rating&safe=active&ssui=on#q=uber+driver+satisfaction&safe=active&ssui=on (Accessed: 2nd July 2016).
GlassDoor (2016) TaskRabbit Reviews, Available at: https://www.glassdoor.co.uk/Reviews/Taskrabbit-Reviews-E595166.htm?countryRedirect=true (Accessed: 2nd July 2016).
Hall, J., Kendrick, C. and Nosko, C., 2015. The Effects of Uber’s Surge Pricing: A Case Study. The University of Chicago Booth School of Business.
Hall, J.V. and Krueger, A.B., 2015. An Analysis of the Labor Market for Uber’s Driver-Partners in the United States. Princeton University Industrial Relations SectionWorking Paper, 587.
Jonathan Hall (2015) In the Driver’s Seat: A Closer Look at the Uber Partner Experience, Available at: https://newsroom.uber.com/in-the-drivers-seat-understanding-the-uber-partner-experience/ (Accessed: 3rd July 2016).
Kang, C.H., 1998. TAXI DEREGULATlON: lNTERNATIONAL COMPARISON. Institute for Transport.
Morrison, P.S., 1997. Restructuring effects of deregulation: the case of the New Zealand taxi industry. Environment and planning A, 29(5), pp.913-928.
Ronny Kerr (2015) The top 10 sharing economy fundraisings of 2015, Available at:http://vator.tv/news/2015-12-25-the-top-10-sharing-economy-fundraisings-of-2015 (Accessed: 30th June 2016).
Rubenstein (2014) Uber, Lyft, and the end of taxi history, Available at: http://www.politico.com/states/new-york/city-hall/story/2014/10/uber-lyft-and-the-end-of-taxihistory-017042 (Accessed: 2nd July 2016).
TaskRabbit Support (2016) How do I become an Elite Tasker?, Available at: https://support.taskrabbit.com/hc/en-us/articles/204409550-How-do-I-become-an-Elite-Tasker- (Accessed: 1st July 2016).
Teal, R.F. and Berglund, M., 1987. The impacts of taxicab deregulation in the USA. Journal of transport economics and policy, pp.37-56.
The United States Department of Justice (1999) U.S. V.MICROSOFT: COURT'S FINDINGS OF FACT, Available at: https://www.justice.gov/atr/us-v-microsoft-courts-findings-fact#iiib (Accessed: 3rd July 2016).
Transport for London (2016) Apply for a taxi driver licence, Available at: https://tfl.gov.uk/info-for/taxisand-private-hire/licensing/apply-for-a-taxi-driver-licence (Accessed: 2nd July 2016).
Van Zuylen-Wood (2015) The Struggles of New York City’s Taxi King, Available at: http://www.bloomberg.com/features/2015-taxi-medallion-king/ (Accessed: 2nd July 2016).
Wallsten, S., 2015. The competitive effects of the sharing economy: howis Uber changing taxis?. Technology Policy Institute.
Zervas, G., Proserpio, D. and Byers, J., 2015. A first look at online reputation on Airbnb, where every stay is above average. Where Every Stay is Above Average (January 28, 2015).
Arun Sundararajan (2012)Why the Government Doesn’t Need to Regulate the Sharing Economy, Available at: http://www.wired.com/2012/10/from-airbnb-to-coursera-why-the-government-shouldnt-regulatethe-sharing-economy/ (Accessed: 2nd July 2016).
Cohen, M. and Sundararajan, A., 2015. Self-regulation and innovation in the peer-to-peer sharing economy.
U. Chi. L. Rev. Dialogue, 82, p.116.
Douglas, George W. "Price regulation and optimal service standards: The taxicab industry." Journal of Transport Economics and Policy (1972): 116-127.
Duncan Madsen Pirie (2008) Freedom 101, : Adam Smith Institute.
Eric Posner (2015) Why Uber Will—and Should—Be Regulated, Available at: http://www.slate.com/articles/news_and_politics/view_from_chicago/2015/01/uber_surge_pricing_federal_regulation_over_taxis_and_car_ride_services.html (Accessed: 2nd July 2016).
James D. Miller (2003) Game Theory at Work: How to Use Game Theory to Outthink and Outmaneuver Your Competition, : McGraw-Hill.
NSW Business Chamber () The Sharing Economy, Available at: http://www.nswbusinesschamber.com.au/NSWBCWebsite/media/Policy/Tourism/Sharing-Economy-Issues-Impacts-and-Regulatory-Responses-COMBINED-POLICY-9-11-15.pdf (Accessed: 2nd July 2016).
Paul Sawers (2012) Facebook, Twitter, iTunes and Google: The rise of digital monopolies, Available at: http://thenextweb.com/insider/2011/10/02/facebook-twitter-itunes-and-google-the-rise-of-digitalmonopolies/#gref (Accessed: 2nd July 2016).
Rachel Botsman (2010) The case for collaborative consumption, Available at: https://www.ted.com/talks/rachel_botsman_the_case_for_collaborative_consumption?language=en (Accessed: 3rd July 2016).
McKelvey, Richard D., McLennan, Andrew M., and Turocy, Theodore L. (2014). Gambit: Software Tools for Game Theory, Version 15.1.0. http://www.gambit-project.org.