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I. Introduction
The unprecedented rise of disruptive innovations has taken the world by storm. A
disruptive product or service may emerge in any industry, with notable firms like
Uber in the taxi industry, Airbnb in the tourism accommodation industry and
MoolahSense in the financial lending space.
Key to these disruptive innovations across the different industries is the concept of
the “sharing economy” where people exchange or “share” goods and services on a
short-term basis instead of taking full ownership of the required assets to complete a
certain task at hand.1
Other than posing as a credible threat to the incumbents within the industry,
disruptive innovations are troubling to competition regulators as they are “upsetting
regulatory frameworks, introducing a wealth of new data, altering how we understand
and share assets”. 2 Thus, there is a need to rebalance and revise existing
competition policies in order to maximise the benefits of competition on economic
growth.
Given that technological innovations are necessary to sustain economic growth,
competition policies are critical in encouraging and ensuring that an optimal level of
innovation can be harnessed through healthy competition.3
1
Georgios Petropoulos, “Uber and the economic impact of sharing economy platforms” (22 February
2016) <http://bruegel.org/2016/02/uber-and-the-economic-impact-of-sharing-economy-platforms/>
(accessed 27 March 2016).
2
Leadership for a Networked World website <http://lnwprogram.org/case-point-sharing-economy-anddisruptive-innovations> (accessed 27 April 2016).
3
Jonathan Chan and Herbert Fung, “Rebalancing Competition Policy to Stimulate Innovation and
Sustain Growth” (18 November 2015)
<https://www.ccs.gov.sg/~/media/custom/ccs/files/media%20and%20publications/publications/occasi
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II. Benefits of disruptive innovations and how existing competition policies
harness these potential societal gains
Particularly in industries where there are enhanced regulations, disruptive
innovations tend to create dislocations especially in the short run. However, existing
competition policy in Singapore can reap the benefits of these disruptive innovations
as they, more often than not, encourage competition by offering goods and services
at lower prices as compared to incumbents. For example, Uber has been able to
offer their services at a lower average price as compared to traditional taxi
companies. Empirical data in the US has shown that the average price paid by
consumers riding regular taxis are higher than that of the average price paid by
consumers riding Uber in a huge majority of the cities in the US. 4 Similarly,
competition law and policy aim to enhance the welfare of consumers.5 Further, it can
harness these benefits by emphasising the prohibition of anti-competitive behaviours
by incumbents in the industry that artificially manipulate entry barriers. This in turn
encourages potential entrants with improved business models and technologies to
compete effectively and ultimately allow consumers to enjoy lower prices.
Moreover, economic theories have long advocated the need for competition in order
to incentivise businesses to eliminate business inefficiencies and engage in
innovation in order to compete more effectively.6 Thus, disruptive innovations serve
onal%20paper/ccsoccasional%20paper%20%20innovation%20research%20paper%20for%20brics%
20final.ashx> (accessed 30 April 2016).
4
Sara Silverstein, “These Animated Charts Tell You Everything About Uber Prices In 21 Cities” (17
October 2014) <http://www.businessinsider.sg/uber-vs-taxi-pricing-by-city-2014-10/#.VzCVSYR97IU>
(accessed 27 March 2016).
5
Competition Commission of Singapore website
<https://www.ccs.gov.sg/~/media/custom/ccs/files/media%20and%20publications/speeches/second%
20reading%20speech%20for%20the%20competition%20bill%20by/19oct042ndreadingspeechfinal.as
hx> (accessed 30 April 2016).
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Supra n 3.
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as a great source of competitive pressure and the reduction in costs may be passed
on to consumers who will be able to enjoy lower prices in the long run. For example,
the rise of peer-to-peer (P2P) lending platforms threatens the fabric of the traditional
lending space of the financial industry. Different types of businesses, especially the
small and medium enterprises (SMEs) are now able to raise additional capital
through these P2P platforms which they may not have been able to do so through
traditional bank loans that require a longer processing time and have tighter credit
constraints.7 In face of such competition, the banks in Singapore have upped their
ante by increasing their involvement and investments in the field of financial
technology. For example, United Overseas Bank (UOB) has announced its $10M
investment in “OurCrowd”, an equity crowdfunding site as a novel product that is
offered to UOB’s existing clientele.8 Furthermore, DBS is now partnering about 145
technology start-ups to explore new ideas in banking and finance. 9 Given these
developments, it is apparent that financial giants in Singapore are pursuing
strategies to reduce business inefficiencies in the face of stiffer competition from
disruptive innovations.
III. Challenges brought by disruptive innovations and the limits of existing
competition guidelines
7
Ankita Varma, “Getting a business loan in two hours” (17 January 2016)
<http://www.straitstimes.com/lifestyle/getting-a-business-loan-in-two-hours> (accessed 27 March
2016).
8
Terence Lee, “Singapore bank UOB will invest $10m in an equity crowdfunding site (3 March 2016)
<https://www.techinasia.com/singapore-ourcrowd-uob-crowdfunding> (accessed 27 March 2016).
9
Wong Wei Han, “Financial giants take on fintech players” (10 October 2015)
<http://www.straitstimes.com/business/banking/financial-giants-take-on-fintech-players> (accessed 27
March 2016).
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Given the novelty of business models and the speed at which disruptive innovations
capture a significant share of the market, the competition policy in Singapore may
face significant constraints in keeping up with these rapid evolutions. Thus, there is a
possibility that the existing guidelines do not encompass the full range of situations
where these disruptive innovators may engage in commercial behaviours that may,
intentionally or unintentionally, distort competition.
Take for example the dynamic pricing model of Uber. This model adjusts fares in
accordance to the demand and supply of the market. In periods of high demand,
rides are priced at a higher range to incentivise drivers to supply their services.
Given that pricing is done on a real-time basis, it is an almost perfect example of
allowing Adam Smith’s invisible hand to do the work of clearing markets. However,
this very nature of dynamic pricing actually encourages drivers to engage in tacit
collusion to maximise their income.10 In times of surge pricing, drivers may directly or
indirectly collude and delay their services in anticipation of even higher prices and
thus higher income. This scenario would serve as a theoretic case where collusion is
achieved despite the absence of communication between drivers. Recent reports of
instances where surge pricing had occurred, for instance when the Mass Rapid
Transport (MRT) system in Singapore experienced a breakdown, have shown that
consumers indeed pay hefty price tags that could go up to SGD169 during such
times of intense demand.11 Existing competition guidelines do not fully encompass
such situations and this problem is further exacerbated by the novelty of the situation
10
Jill Priluck, “When Bots Collude” (25 April 2015)
<http://www.newyorker.com/business/currency/when-bots-collude> (accessed 27 March 2016).
11
Linette Heng, “Business manager's $169 27-minute long Uber taxi ride: When surge pricing hits”
(11 November 2015) <http://www.straitstimes.com/singapore/business-managers-169-27-minutelong-uber-taxi-ride-when-surge-pricing-hits> (accessed 27 March 2016).
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where there is minimal research to show that tacit collusion does even exist.12 Even
if it is proven to exist, it may be difficult to pinpoint the exact time periods of
heightened tacit collusions.13 Given how networks externalities amplify the effects of
these situations, this may be a potentially significant distortion of competition within
the market.14
Disruptive businesses may abuse their first mover advantage by adopting strategies
such as predatory pricing and loyalty discounts to crowd out existing incumbents and
potential entrants. The conventional business strategy of gaining the first-mover
advantage in any industry has been widely researched and raved about. Examples
such as Uber and Grab have been aggressively pursuing such first-mover
advantages within the third party taxi booking smartphone application industry. A
common feature among these taxi booking applications is the idea of Loyalty
Programmes 15 in order to retain their drivers. Upon attaining certain targets in
relation to ridership frequency, drivers receive a myriad of perks and benefits which
includes insurance coverage, financial incentives and enjoy special discounts when
purchasing from partner brands. While these strategies may seem deceptively
harmless at the surface level, they can actually give rise to competition concerns as
they have the effect of restricting competition by discouraging drivers from working
for competitor taxi booking application 16 . Given that the industry exhibits strong
12
Ariel Ezrachi and Maurice E. Stucke, “Artificial Intelligence & Collusion: When Computers Inhibit
Competition” Oxford Legal Studies Research Paper No. 18/2015; University of Tennessee Legal
Studies Research Paper No. 267.
13
Ibid.
14
Ibid.
15
Jean Khoo, “Taxi-Booking Apps Are Racing To Launch Loyalty Programmes in Malaysia. Here's
Why.” (24 June 2015) <https://vulcanpost.com/286961/uber-myteksi-loyalty-programme/> (accessed
27 March 2016).
16
Organisation for Economic Co-operation and Development, “The impact of disruptive innovations
on competition law enforcement” (16 October 2015)
<http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=DAF/COMP/GF/WD(2015)2
4&docLanguage=En> (accessed 30 March 2016).
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network externalities, consumers may be discouraged from using alternative taxi
booking applications particularly if the chance of successfully booking a suitable ride
is lower on alternative platforms.17 In the worst case scenario, a “downward spiral”
may occur which deters potential entrants and even force the incumbents out of
business18. This may ultimately give rise to a single firm with dominant market share
which could potentially abuse its monopoly power. Such a scenario is highly
probable given that network externalities amplify the effects of these strategies.
In the midst of creating new market spaces, disruptive innovations may
unintentionally create market structures with high switching costs, resulting in high
barriers to entry which stifles future competitive pressures within new markets. As
directed by various market research, the next big change for businesses will be the
rise of Big Data. Unsurprisingly, we observe that many successful disruptive
innovations have one thing in common: the heavy reliance of data as the key input
for value creation. Simply put, firms which have a multitude of data are able to exploit
them to reap profits through insights gleaned through data analytics. The introduction
of Robo-advisors within the financial services industry sufficiently illustrates this point.
Robo-advisors are in essence computer algorithms that process a huge load of
financial data including credit ratings, risk metrics, historical returns and portfolio
analysis before providing customised financial advice for individual clients 19. Firms
such as Smartly and Infinity Partners have announced plans to start providing roboadvisory services to the South East Asian market and in particular, Singapore20. The
17
Ibid.
Ibid.
19
John Sedgwick “Robo advisers booting up in Asia” (15 February 2015)
<http://www.ft.com/cms/s/0/8140cdd6-b521-11e4-836200144feab7de.html?ft_site=falcon&desktop=true#axzz48LJKTip2> (accessed 27 March 2016).
20
Fintechnews Singapore, “Smartly.sg Announces Robo-Advisor for Singapore Targeted at
Southeast Asian Millennials” (17 February 2016) <http://fintechnews.sg/1483/roboadvisor/smartly-sgannounces-robo-advisor-targeted-southeast-asian-millennials/> (accessed 27 March 2016).
18
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value of such services is heavily derived from the data it processes, especially usergenerated data such as an individual’s unique investment habits and risk appetite.
An analysis of existing competition policy in Singapore would reveal that there is
minimal coverage on the issue of data portability for the new market space of roboadvisory. Hence, there is a clear risk that firms such as Smartly and Infinity Partners
have the ability whether intentionally or not, to create high switching costs for their
clients, which in turn prevents these clients from switching to similar services
provided by competitors. This issue is even more significant since there is
inadequate framework to determine who owns the rights to the user-generated data.
Such a situation definitely favours these firms but potentially distorts competition
through high barriers to entry for new entrants seeking to grab a share of the growing
robo-advisory market.
IV. Recommendations and suggestions for the future of competition policy
The challenges, as elaborated above, only present a fraction of the possible
competition concerns that may arise as a result of disruptive innovations. In
anticipation of these challenges, it is imperative for policy makers to revise the
existing competition guidelines in order to catch up with rapid technological
advancements and changes.
First, competition guidelines may be rebalanced to allow for greater collective
bargaining by redistributing bargaining powers of relevant parties within the industry,
thereby creating a democratising effect in emerging market places. 21 Drawing
parallels to the successful business model of Airbnb, regulations should encompass
21
Supra n 1.
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the need to allow suppliers within these emerging industries to set their own prices
rather than have prices dictated by a single or a few firms.22 For example, Airbnb
allows homeowners to determine their own rental prices and have little control or
influence over homeowners’ decisions in setting these rates. However, in the case of
third party taxi booking applications, these firms usually have a high degree of price
setting power, resulting in drivers having little or even no say in determining the price
levels. With the power to set prices concentrated among these third party taxi
booking applications, these firms tend to have the ability to adopt strategies to erect
high barriers to entry within the respective markets which may ultimately distort the
competition landscape.
Additionally, existing guidelines could be revised to allow for greater data portability
and to better define the respective rights of the different parties involved, especially
user-generated data.
Lessons can be drawn from precedence with similar underlying concepts. For
instance, in the telecommunications industry, the Info-communications Development
Authority of Singapore introduced policies for Full Mobile Number Portability for
consumers to retain their existing mobile numbers even when they switch from one
mobile operator to another. 23 The portability of data allows consumers to switch their
mobile operators with lower costs. Hence, consumers are less deterred from making
the switch to mobile operators that better suit their needs, thereby levelling the
playing field within the industry. Ultimately, the lower switching costs could
encourage greater competition which would spur mobile operators to improve on
22
Airbnb website <https://www.airbnb.com.sg/help/article/474/how-do-i-set-my-base-price> (accessed
27 Match 2016).
23
Info-communications Development Authority of Singapore website
<https://www.ida.gov.sg/Policies-and-Regulations/Regulations/Store/Consumer-Guide-To-Full-MobileNumber-Portability> (accessed 27 March 2016).
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existing mobile plans and allow consumers to enjoy a wider range of product
offerings. The benefits may spill over to the product offerings in other areas such as
cable television. A similar approach can hence be adopted for user-generated data
among disruptive business models. The intricacies of data rights and portability have
to be critically analysed with the overall aim of giving consumers greater control of
the data generated through their prolonged historical use of the various platforms.
For example, investors adopting the services of Robo-advisors should have the right
to export certain aspects of their investment and portfolio history to competitor
platforms. Such arrangements could potentially lower the risk of a single dominant
firm abusing its power by erecting extremely high barriers to entry and encourage the
different platforms to engage in further innovation in order to maximise their profits
as well as the value that they can provide to consumers.
V. Conclusion
As discussed, disruptive innovation can be both a friend and a foe to competition
policy in Singapore. However, implementing a complete ban or strict regulations to
these disruptive innovations is not the way forward. It is of utmost importance for
policy makers to respond and adjust to these newly emerging technologies to
determine whether or not the industry should revert back to its pre-existing status
quo or undergo incremental or even radical development, keeping in mind the
ultimate objective of maximising societal welfare and sustaining long-term economic
growth.
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