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by Anja Lambrecht, London Business School, and Catherine Tucker, MIT Sloan School of Management

Big data is the next frontier in technology. As our economy grows more digital by the day and consumers develop ever larger online footprints, amassing enormous datasets has become easier than ever before. Powerful and inexpensive computing resources are now widely accessible, and we see companies taking advantage of complex data analysis from day one to innovate and kickstart their new ventures.

For example, many new businesses, such as online real estate tool Zillow.com, have used data to not only innovate, but also to build valuable platforms that provide better services to users. While in its early days Zillow used publicly available information on house prices to attract users, it quickly grew into a highly successful platform by incorporating user-generated content to hone its estimates and, now, provide users with a nearly real-time assessment of their property’s value.

For companies like Zillow that invest in this kind of data-driven innovation, could data be a source of sustainable competitive advantage? This question will be top of mind for European regulators this month as the French and German competition authorities prepare a report on the “data economy”, expected to be released this April.

Despite concerns to the contrary, we conclude in our recent paper that a large repository of data gives firms less of an advantage than a first glance suggests. At the heart of our analysis is the idea that for something to be a source of sustainable competitive advantage, a firm’s rivals must not be able to replicate the benefits. There is a number of reasons why this is unlikely to be the case for big data.

First, the tools for gathering and analyzing big data are commonplace and cheap; companies big and small have the ability to integrate meaningful insight from big data into their business operations.

Second, there are alternative sources for obtaining data from other firms, or even from the firm’s own customers. Data is nonrivalrous, which means if one company consumes a piece of data, this does notaffect its availability to others. As a result, information from Comcast’s TV viewing data to Bluekai’s online behavioral data is commercially available on the open market, allowing new entrants to gain insights similar to those that incumbent firms have already gathered.

There is no doubt that, when used properly, data can help firms better understand their customers and potentially elevate their businesses. However, it is clear that, by itself, data is not inherently valuable. To unlock the potential insights data holds, a company needs competent, data-savvy employees that are capable of implementing rigorous experiments or algorithms to eliminate the noise and tease out useful insights. In other words, while data may be useful, the true value lies in a business’s employees and the processes and strategies they set in place to mine this trove of information for actionable insights.

However, the clearest indications that a company with big data is not invincible to its competitors are the numerous examples of startups that began with a distinct data disadvantage but quickly grew to challenge and even outpace their more established rivals. These upstarts indicate that data is not in fact “non-substitutable”: There are many paths to success for innovative companies seeking to provide a better service to their customers. WhatsApp faced off against traditional telecommunications firms. It did so not by exploiting a data advantage over its rivals — which already had large data sets regarding the messaging habits and pricing preferences of their customers — but by introducing an easy-to-use and extremely low-cost messaging service.

Additionally, entrants in the sharing economy, such as Uber or AirBnB, outmaneuvered their more established competitors and thrived because they presented consumers with options that were more affordable, convenient and reliable.

The prevalence of such startups makes it clear that ownership of big data is not the key factor driving success in digital markets. Instead, innovative business propositions, ideas that put the customer’s wants and needs first, and smart and savvy employees are what drive success in this sphere. Rather than an anti-competitive force that limits the ambitions of new entrants, big data may in fact create more competitive industries than ever before, resulting in inventive new services and products that meet consumers’ needs in ways that were not possible even a few years ago.

Data is not a silver bullet with the power to destroy competitors and keep an unimaginative company on top. It is the quality of analysis and not the merely the quantity of data that determines success.

Anja Lambrecht, Ph.D., is an assistant professor at London Business School. Catherine Tucker, Ph.D., is the distinguished professor of management science at MIT Sloan School of Management. This piece is based on their recent paper “Can Big Data Protect a Firm from Competition?”

This writing is originally posted on the Guest Blog at BlogActive.eu and reposted here with permission from the authors. 

by Daniel O'Connor on April 2, 2015

Big data, and its effects on online markets, has been thrust into the center of the tech policy chattering class debate.  In the last few weeks, events have been held on both sides of the Atlantic focusing on the concept of big data as an entry barrier.  (The topic has also come up in speeches by FTC Commissioners [and a paper], in discussions surrounding the EU’s forthcoming Digital Single Market strategy, and is the frequent topic of recent academic writing.)  Specifically, the concept being debated is whether the accumulation of data by Internet companies hinders competition because the new entrants will not be able to compete effectively with the first mover in the marketplace.  In this post, I will address why startups and entrepreneurs should not be overly concerned.

In a stylized view of the Internet economy, as a platform (such as Google, Facebook, Amazon, Pinterest or Twitter) achieves scale and gains users, it acquires more data.  This data leads to product improvement, which leads to more users and, subsequently, more data.  The process repeats.  According to proponents of the data as a barrier to entry theory, this leads to an unbreakable positive feedback loop that makes effective competition impossible.

However plausible this argument sounds, a review of the short history of the Internet economy, which has been characterized by intense competition and frequent disruption, seems to cast doubt on the soundness of the theory.  (See Andres Lerner’s discussion of the User Scale – Service Quality feedback loop.)  Besides the common examples of Facebook overtaking Myspace and Google overtaking prior search competitors (who, at the time, were predicted to be unassailable largely on account of the User Scale – Service Quality feedback loop discussed above), a casual look at online markets illustrates how competitive the market is.  Why are online markets so competitive even though some firms are believed to have an unassailable advantage in big data?

First, this view of Internet markets is extremely simplistic.  Data is just one input of many in the process of innovation and market success.  Second, unique economic characteristics of data — such as it being non-rivalrous and the diminishing marginal returns of data — mean that the accumulation of data, as opposed to other barriers to entry like intellectual property portfolios or high-fixed capital costs, in and of itself does not function as much of a barrier at all.  When you couple these characteristics with the fact that data, and the tools to use and analyze data, are readily available from numerous third party sources, the notion of an iron-clad data feedback loop falls apart.

I’ll break this down piece by piece.

1) Data is non-rivalrous and non-exclusive

Some have compared data to oil, referring to it as the essential input of the 21st century.  Although, rhetorically, this analogy has superficial appeal, it is also misleading, as Geoff Manne and Ben Sperry point out:

“But to say data is like oil is a complete misnomer. If Exxon drills and extracts oil from the ground, that oil is no longer available to BP. Data is not finite in the same way.”

In economic terms all information, including data, is non-rivalrous and non-exclusive (Matt Schruers has touched on this before).  In other words, if Twitter knows that I am a male, in a relationship and like sports, Facebook can also know those things.  Twitter knowing these things neither prevents Facebook from knowing those things nor using that knowledge to better their product to serve my tastes.  Therefore, as an input, data does not function as a barrier to entry, as say exclusive spectrum ownership or access to rare-earth minerals serve as a barriers to entry in the mobile telecommunications space (to pull two examples from the technology policy world).  In these cases, purchasing the exclusive rights to operate on a segment of a nation’s airwaves, by definition, means it is not available to other competitors.  This limits the number of firms that can provide nationwide mobile communications services.  As for rare-earth elements (REE), mobile phone manufacturers need these to build their devices.  When one firm consumes a REE in the manufacturing process, it is no longer available to other firms.

Furthermore, users tend to multihome, meaning they use many online platforms at the same time.  Whether that means using both Google and Bing, or Pinterest and Twitter, the fact that someone built a successful product does not mean that consumers will use that product exclusively.  In the online matchmaking world (which I will discuss in more detail later), consumers often use many online dating products at the same time.  What does this mean in terms of data?  Multiple companies have access to the same user data at the same time, and the use of one Internet platform does not deprive other Internet platforms from obtaining the same data from the same users.

To the extent that data, especially basic consumer behavior and preference data, is deemed essential to competitive success, the fact that no firm can control it or exclude others from using it means that it does not function as a barrier to entry in the way a finite, excludable resource could.

2) The marginal returns on data diminish rapidly

To illustrate this point theoretically, one needs not go much further than Stats 101.  If one is to conduct a survey of voting preferences for an upcoming election, one needs to construct a large enough sample size to ensure accuracy.  However, each additional survey participant does not increase the quality of the survey by the same amount as the one before her.  For example, if a pollster has 5 respondents, adding a 6th proves extremely valuable.  If the pollster already has 100,000 respondents, then adding an additional one is almost insignificant.  Therefore, a survey that has 100,000 respondents is not twice as accurate as a survey with 50,000 respondents.  In fact, in both cases, the margin of error is less than 1%.  (For the stats nerds, accuracy generally increases as a square root of the sample size, so doubling the sample size equates to roughly a 41% increase in accuracy.  Hence, the rapidly declining returns to scale.)

[Although the above example has been simplified for clarity, a more thorough explanation of this concept’s applicability to “big data” can be found in Andres Lerner’s paper, paragraphs 61 – 76.]

To veer back into the real world, what are the practical effects of this mathematical reality?  This is why most Internet companies test algorithmic changes on a small subset of users (see Facebook and Google).  In this case, there is little competitive advantages to scale after a certain point.  And, as industries grow, the competitive advantage a larger rival has over a smaller rival becomes even smaller.

This mathematical reality leads to the conclusion that how companies utilize and parse the data is much more important than the sheer volume of data a company has.

3) Data is readily available in the marketplace

A quick read of the FTC’s recent report on data brokers makes clear how easily data is to obtain on the open market.  Although the report calls for greater transparency and accountability, it also makes clear that these services facilitate dynamic online competition:

[C]onsumers benefit from increased and innovative product offerings fueled by increased competition from small businesses that are able to connect with consumers they may not have otherwise been able to reach.

Although the report focused on nine of the biggest data brokers, the report also makes clear that there a many more companies and products in the market providing similar services to businesses.  Therefore, a startup company can avail itself of a similar set of data driven insights of the market leaders with large user bases, as the report notes:

Among other things, the analytics products offered by some of the data brokers enable a client to more accurately target consumers for an advertising campaign, refine product and campaign messages, and gain insights and information about consumer attitudes and preferences.

4) The market for data analytics is also robust

The market for data analytics, companies making tools to help customers derive insights from data, is also incredibly robust.  In 2015, the data analytics market is predicted be worth $125 billion.  Although it is beyond the scope of this article to go into great detail on this phenomenon, it is worth noting that companies looking to utilize the data they either have or acquire can quickly, and relatively cheaply (as compared to building these tools from scratch in house), benefit from the insights of big data.  There are even free, widely-used open source technologies that allow users to analyze large datasets (i.e. Hadoop).  And, as the FTC report discusses, many data brokers provide businesses with structured and analyzed data, not just raw data sets.

5) The value of data decreases rapidly over time

The value of big data is fleeting.  Historical data can be mined for trends, which can be helpful from a product improvement standpoint, but historical data is of little value for real-time decisions, such as ad targeting, thus limiting the advantages conferred to incumbents who have caches of historical data.  As noted in a paper by Darren Tucker and Hill Wellford, 70% of unstructured data is stale after 90 days.  As a result, most data processing and analysis is done in real time (or on a near-real-time basis).

6) Barriers to entry online are very low

Focusing on data as a barrier to entry in online markets belies the fact that the Internet is a dynamic marketplace that has drastically lowered barriers to entry.  The capital costs of starting and scaling a business online are significantly lower than in the offline world.  Worldwide reach, standardized technology and communications protocols, and rapid price decreases in things like cloud platforms and storage, means that it is cheap — and getting cheaper by the day — to build an online business.   As I have discussed previously, these characteristics allow firms to scale quickly but they also allow potential competitors to scale quickly and overtake them:

On the Internet, consumers can flock to the best product or service en mass almost instantly. This means the best product or service often quickly gains impressive market share. However, the same dynamics that precipitated the rise of companies like Google and Facebook also place extreme competitive pressure on them.

In fact, the widespread availability of data (and data processing tools) lowers barrier to entry more than it entrenches current incumbents.  You don’t even have to start out with users anymore to obtain data about consumer preferences and online behavior.  Thus, on the first day of a product’s launch, a company can have already designed a product that is informed by consumer preferences and that has the programming infrastructure to respond intelligently to specific customers.

7) Ideas matter more than data

So, what insights can be derived from the preceding discussion of the economic characteristics of data?

Undeniably, more data helps companies refine and evolve their products, but this is true across all sectors of the economy.  Traditional retailers, such as Tesco and Walmart, actively collect a myriad of data about consumers’ shopping preferences.  Individual stores produce heat maps to determine the most trafficked floor space, which dictates where retailers place certain products.  In the auto industry, companies like Volvo collect data on their cars through thousands of sensors that both help service current automobiles and inform later design changes.  These processes mirror that of online companies that use data to better tailor their products to consumer preferences.  Indeed, this is testament to how competitive these markets are and the need for constant product improvement to stay relevant.

However, a trove of data is not hugely important to building a better product and succeeding in the marketplace.  The quality of service offered to users is the single biggest determinant of success for new Internet products and services.  In terms of building a successful business model to compete with incumbents, it helps to build a better mousetrap.  Or, in other words, attack the same problem in a different way.

Google achieved success over other search engines by conceiving of a better way of matching users queries to relevant websites.  The fact that Yahoo and AltaVista had a lead in the race for data didn’t matter much when Google conceived of a better way to do things.  In the case of Facebook, it built a social network that users liked better (even though social networks like Myspace and Friendster had large user bases and data advantages).

Or, for a possibly more illustrative cutting-edge example, it helps to look at the evolution of the market for Internet-powered dating services.  If ever there were a market where data would serve as a barrier to entry, online dating would be a perfect example.  Given the complex,  varied, and poorly understood nature of human affection, possessing a large user base (and their detailed personal information and preferences) and troves of data about human attraction and relationship compatibility should give early movers in the online dating space an unassailable advantage.  Yet, Tinder — an online dating app that launched less than 3 years ago — is adding a million users a week and is already valued at over $1 billion.  Given the nature of this market, and the theoretically large data advantage rivals such as Match.com, eHarmony and OkCupid enjoyed, the iron-clad feedback loop theory of data should have meant that Tinder shouldn’t even have tried to compete, let alone achieved significant success.  But, the founders of Tinder — like Internet entrepreneurs that went before them — thought they had a better idea.  In the case of Tinder, this was the “double opt in”.  In other words, the fact that Tinder didn’t have a matchmaking algorithm (and loads of matchmaking data) didn’t matter.  As one GQ author puts it:

The key to Tinder—the “double opt-in”—is an idea born of real-world experience (this is what you want in a bar—to know that the person you want to hit on wants you to hit on him or her) as opposed to sophisticated computer metrics.

The process Tinder’s founders created through the mobile application — the double opt-in where users declare secretly who they are attracted to and are only matched after both say yes — immediately posed a challenge to the established dating websites and their algorithms.  Now, Tinder has million of users and, according to its own stats, facilitates 21 million matches a day, which gives it a mountain of data through which it can refine its product and tailor its user experience.  (Given that many of Tinder’s users use multiple online dating services, this also illustrates the multihoming concept discussed previously.)  But that data isn’t going to protect the company from the next entrepreneur that thinks she has a better approach from starting a mobile dating app.  In fact, a number of Tinder competitors have emerged, with different ideas on how to best facilitate matchmaking.  For example, Hinge, which combines Tinder’s location-driven approach with your friend information from Facebook and your past preferences, is trying to solve what its founder saw as a problem with Tinder for many users: the randomness factor of Tinder that makes the app uncomfortable for some users.  According to a Hinge spokesman, “If Tinder feels like meeting a stranger at a bar, Hinge feels like getting warmly introduced at a cocktail party.”

Hinge is also a great example of the role of data in online competition.  Although Hinge uses data it gains from its users to improve its matching algorithm, the fact that other dating platforms already had a lot of data did not prevent it from entering the market.  A Hinge factsheet explains its process:

Think of setting up your pickiest friend. First, you’d think of all the people you know who he/she might like to meet. Then you would prioritize those recommendations based on what you know about your friend…. Finally, over time you would start to learn his/her tastes and refine your recommendations. That’s exactly how Hinge’s algorithm works.

In this case, data about individual users improves the apps performance, but not having detailed information on users did not prevent market entry.

Since its launch, Hinge has grown rapidly (even as Tinder is still rapidly expanding) and recently secured significant venture funding.  And, according to recent statements by its CEO, it is growing its user base by 20% a month.

[]

The evolution of the online dating platform mirrors the evolution of other sectors of online competition. (In the above video, Hinge’s CEO likens his approach to competing with Tinder to how Facebook took on MySpace).  Data is a useful input, but a slightly different idea or algorithm can easily lead to the dethroning of the current market leaders, which parallels the success stories of Google and Facebook.

If the online dating market shows us anything, data can help you improve your product or better monetize traffic, but it does little to protect you from competition — especially when a company has better idea.

This writing is originally posted on Project Disco Blog and reposted here with permission from the author.

Daniel O’Connor (Vice President of Public Policy at the Computer & Communications Industry Association (CCIA))*

Not surprisingly, as the Internet matures, and online platforms play an increasingly important role in the world’s economy, the question of how to regulate these relatively new online platforms has received significant attention.  As regulators and competition policy experts turn their attention to online platforms, it is important for them to take into consideration how these platforms function, the considerations they must take into account, and how they differ from the traditional companies and markets from Econ 101. (See CCIA and CPI’s ebook for a more in depth analysis of online platforms and regulatory policy)  

Unlike traditional markets, where companies buy and sell products or services, platforms often function as matchmakers that connect different groups of producers and consumers.  Although this phenomenon is not unique to the online world, as shopping malls, stock exchanges and newspapers also function as platforms, platforms are particularly common on the Internet.  Their business viability often comes from solving traditional frictions in the economy, thus making it easier for third parties to engage in mutually beneficial interactions.  In facilitating these interactions, the platform operators have to balance interests of all platform users in order for their platforms to grow.  This can create political friction, as the different constituencies on a platform often have conflicting interests in how the costs and benefits of the platform are distributed.  Parker, Van Alstyne, and Choudary sum up this dynamic in their book, Platform Revolution:

“Multi-sided platforms involve interests that don’t always align. This makes it difficult for platform managers to ensure that various participants create value for one another, and make it likely that conflicts will emerge that governance rules must resolve....This is a juggling act that even giants and geniuses get wrong.”

Instead of being traditional markets subject to a standard supply and demand function, these platforms bring together different groups of interdependent users.   For example, Uber is not a company with a one-way relationship with riders or drivers, instead it provides the platform that connects suppliers of trips to potential customers and provides tools that allow for transparent pricing, easy payments, and clear ratings.  Instead of higher prices indicating increased market power for Uber, they instead indicate a mismatch of supply and demand and the need to entice more drivers onto the platform at a given moment in a particular location.   And, as illustrated by the Uber example, the different constituencies served by the platform have different interests.  Riders want cheaper rides and strict monitoring of the drivers to limit the chances they get into a car with a bad or unsafe driver.  Drivers, want higher prices for rides, and often chafe at the strict rules and performance targets that Uber requires for them to continue offering rides on the platform.  Unsurprisingly, riders and drivers have both legally and politically challenged Uber for how the costs and benefits of the Uber platform are distributed: with riders suing the company over its surge pricing and drivers complaining that the performance rules are too stringent.   Like other gripes about online platforms, these complaints tend to focus on the effects one constituency, not on all users of the platform.  If riders get their way, the price of Uber rides will fall, benefiting them, but harming drivers, some of whom are already complaining about the prices being too low.  If Uber rules skewed more towards drivers, then riders would be harmed by higher prices and lower quality drivers on the platform.

Regulators need to be wary as well.  The political economy of platforms means that the temptation exists for constituencies on the platform to politically organize and shift costs to other groups of the platform’s users, helping one group but doing more total harm than good.  This is not a theoretical concern, as it is exactly what happened with Australia’s intervention in the credit card interchange fees (aka operators of a payment platform) responding to the complaints of merchants. 

It is the job of a platform operator to balance these interests to keep all users of the platform happy.  If prices are too low, or rules on drivers too onerous, drivers can easily flee to a competing platform like Lyft.  If prices are too high, or drivers of too low quality, users can do the same.  Platform operators have to carefully balance interests of all users of the platform.  An open source mobile platform, such as Android, has to balance the interests of smartphone users, application developers, and mobile device manufacturers.  Ebay has to the balance the interest of buyers and sellers.  Facebook has to balance the interests of users with multiple types of preferences and privacy, security and decorum with that of the advertisers that are thinking of associating their brands with the platform.

How a platform balances interests between different groups of platform users is not easy, and is usually the key determinant of whether a platform succeeds or fails.  Facebook thrived because it learned lessons in social network management from Friendster and MySpace, which failed to balance interests in a way that pleased enough of their users and attract mainstream advertisers.  Although some users might want more freedom to post provocative content or remain anonymous, Facebook chose to have strict rules governing the nature and content of participation in its social network partly because it saw how MySpace’s anonymity and lack of moderation of content drove many users away and turned off the bulk of corporate advertisers.

Furthermore, the supply and demand functions of platform users are interlinked, which confound traditional economic assumptions, as David Evans and Richard Schmalensee have noted:

“The old formulas—including the ones we have taught generations of undergraduates in Econ 1—do not give the right answers for multi-sided platforms.  The math is simply wrong. Traditional economics holds, for example, that it’s never profitable to sell products at less than cost.  The new multi-sided economics shows that even paying some customers rather than charging them anything can be profitable in theory.”

Different groups of users on a platform have different preferences and intensities of preferences.  Traditional economics teaches that pricing below marginal cost is not possible for an extended period of time, and traditional antitrust enforcement has viewed such activity as potentially an indication of predatory pricing designed to drive competitors from the market.  However, with platforms, it often makes sense to subsidize one side of the market (usually the side with the most elastic demand curve) in order to produce the greatest overall utility.  Search engines offer free searching to users, and make money by charging advertisers.  Newspapers often make content available to readers very cheaply (and sometimes for free) in order to increase the appeal of the platform to advertisers.  Online platforms that connect buyers and sellers, such as Ebay or Etsy, usually allow shoppers to peruse their websites for free and make money on commissions from the seller when a product or service is sold on their platform. 

Although the price structures and rules implemented by online platforms should not be exempt from regulatory oversight, it is important for regulators to take a wide view of the all constituencies of platform users and weigh the costs and benefits of rules and price structures across the entirety of the platform.  Regulators should not lose sight of the likely ripple effects on other users of the platform, if they contemplate actions aimed at addressing the complaints of one constituency.  Given that operating a platform usually requires a precise and tricky balancing act to keep all users happy enough, even slight changes to that equation can throw off the platform’s equilibrium.  Indeed, platform markets are complex and should be approached with care. 

* Daniel O’Connor is the Vice President of Public Policy at the Computer & Communications Industry Association (CCIA), where he works with government and industry leaders on competition, intellectual property, international trade and global Internet policy. He leads CCIA’s efforts on antitrust policy and covers business and technological developments in high-tech markets. O’Connor has published many articles discussing the single digital market, Android competition and platform regulation. 

Dae-Sik Hong (Professor, Sogang University)

The purpose of competition law is to deter enterprises’ conducts which restrict competition. The focus of analysis is fundamentally based on the characteristics and the effects of restricting competition by any conducts of enterprises. The enforcer of competition law has, with the experts’ help and enforcement experience, developed the normative analytic framework that can be applied to any market for this type of analysis. The basic structure of analytic framework is to define a related market for a measurement to figure out whether competition is restricted, find out the competition relationship of that market, and distinguish which company has market power or market-dominant power and what kind of impact the conducts of the said company have on competition. The effect of the actions of a company on competition can be inferred from the effects felt by the parties dealing business with the company or its competitor. Therefore competition analysis is normally divided into restriction of conduct on a level of factual analysis and restriction of competition on a level of empirical analysis. Ever since the Posco Ruling in 2007,[1] the Supreme Court is conceptually distinguishing between concrete disadvantages suffered by the specific enterprise or the trading partner and a circumstance acknowledgeable as an actual result of restricted competition. If the former concrete disadvantages are due the problem of factual analysis on restriction of conduct, the latter case belongs to the problem of empirical analysis of competition restriction.

             For competition effect analysis, which is the central step in applying the normative framework for analysis, we need the theoretical model of ‘theory of competitive harm’ to explain the effects of a concerned case economic phenomenon on competition, efficiency and consumer welfare. Although application of competition law is a normative analysis, for establishing the theory of competitive harm it requires assistance from related study of economics or management. In the area of the traditional norm, it is not familiar to predict and analyze the effect of a certain conduct on the market that goes beyond the interests of the parties. This is the reason why the healthy interaction and cooperation is important between law, economics and management in competition law.

             In Korea, where the history of competition law is not long, it is difficult to find scholars who are well-versed in both law and economics. I myself have studied only law since college, with the only official economic studies being the four classes during undergraduate and 1 class during graduate. If I had to add more to this, I would mention that I studied economics to prepare for tests when economics was a required subject in the preliminary national bar examination. It is always questionable as a law scholar whether my limited economics background is enough to have a smooth interaction and cooperation with economists. However, as someone who is participating in a transitional period in progress of national competition law it is my resolve to create a bridge for those to come.

             Even with the help of related study, application of competition law is undoubtedly a work of normative judgment. Especially economic analysis, which provides the source of the theory of competitive harm in complicated and hard cases, is normal for it to not conclude in one direction and requires large amount of costs, so in a normative world a series of proxy variable and shortcuts in process of legal reasoning was developed as a tool in order to reduce the burden of such analysis, and majority of these has a form of rebuttable legal principles of presumption. For example, in the case of price fixing, the Supreme Court rules that, as long as there is no special circumstance, anti-competitiveness is recognized by comprehensively considering specific consideration factors for determining anti-competitiveness even if there isn’t an exact market share estimation based on legitimate market definition since it can be easily shown whether an agreement has an effect that restricts competition based on the contents of the agreement as such.[2] This can be considered as a case of progressive legal principles of presumption which reasonably sets up the relation of the definition of the relevant market and anti-competitiveness determination in the Korean competition law system in which the definition of the relevant market is statutorily required for judgment on the anti-competitiveness.

             As long as the market is developed and is function to some extent, competition law is a law of the market that can be applied in any market. As industry and technology advances, the market’s extension grows larger and therefore competition law’s area of application grows as well. In ICT (Information and Communications Technologies) industry’s developing market, which is rising as our new opportunity in the changed industry environment of the 21st century, the discussion on the possibility and the way of the application of competition law is a hot topic. Although there are many debates, one of the most influential view is that it is not appropriate to apply the traditional framework of analysis, which was designed for structure and method of production of goods and provision of services, business model and competition mode in the traditional industries, to the area of ICT industry as it is. The author agrees with this view. However, the problem is that as scholar of competition law I cannot stop at just expressing support for this view. Saying that the method of application of competition law should be different is one thing, and saying that application of competition law should be refrained is another.

             In the field of ICT industry, there is a need for approach that is new or at least in all decision steps common in traditional analytic framework, leading to definition of the relevant market, market power or market dominance identification, barrier of entry or expansion, anti-competitive effects and efficiency. In this field, it is basically difficult to simplify market participants’ relationship in appropriately defined markets as horizontal or vertical relationship with a certain company at its center, and to assess the competition impact based on the outcome such as price. This is because methods of producing goods or providing services are linked with networks among many companies often described as C-P-N-D (Content-Platform-Network-Device) through diverse modularity, and because business models and competition modes are diverse. These situations affect the way of intervention as well as the standard whether competition law is applied. In ICT industry field, it is difficult to predict competition situation which would have been prevailed but for the conduct in question. If intervention is made in a way to remove a certain company’s business model’s central element in situations of competing for the ecosystem initiative beyond the relevant market, there is no guarantee that the effects of such intervention on competitive landscape would happen fairly between companies.

             The author fundamentally has faith that competition law can find the solution with which it reasonably addresses the challenges of ICT industry. The traditional framework of analysis adopted by the competition law has been developed with premises of one-sided market as traditional industrial configuration and homogeneous product market. Even so, there are precedents in which competition law has successfully responded to new business models like as differentiated products or product integration situation, franchise and two-sided markets by adjusting or extending the framework. However, in a situation in which complications of analysis and the risks of false negatives increase, the pressure on enforcers and professionals, who are involved in application of competition law, to improve intellectual research and cognitive ability increases as well. More than anything there is a need to abandon the prejudice that ‘market’s competition should be this way’ based on competition image that is  grown used to in traditional industry’s competition environment, and make an effort to observe the situation faithful to the questions like ‘if there was no such conduct in question, how would competition look like?’ The ICT industry is creating a dynamic market with technology and business innovation we have not foreseen or predicted. Conducts that may seem questionable in a traditional mindset might be in fact the central element in such market creation. If that element is interfered and eliminated in the name of competition law, our reality might be akin to that of Marty McFly [Protagonist of the ‘Back to the Future’ (1985) movie], who was confused after travelling to the past to prevent events that were supposed to happen and finding his own present time in mishmash.

Geoffrey A. Manne (Executive Director of the International Center for Law and Economics)*

Android is one of the world’s most successful open platforms. It has undeniably engendered a remarkable level of economic growth and creativity in the mobile economy — particularly in South Korea. From providing consumers with greater choice and lower prices to facilitating unprecedented innovation by app developers and device makers, Android’s operating system is at the center of the mobile revolution^[1] — and it is no exaggeration to say that Android has placed South Korea squarely at the forefront of the global mobile economy.

So why is Android the focus of renewed antitrust attention and complaints that Google’s business practices around the mobile OS are harming competition in Korea?

In 2011, in response to similar complaints from two Korean search giants, Naver and Daum, the Korea Fair Trade Commission (KFTC) engaged in a thorough investigation into Google’s Android-related business practices. The investigation ended in 2013 with the KFTC rejecting all of the allegations against the company.

But in light of the European Commission’s recent Statement of Objections alleging harms to competition in Europe, there have been calls in major media publications for the KFTC to carry out exactly the same investigation again, even though competitive conditions haven’t changed since the last investigation.

The KFTC should once again reject these calls for regulation that benefits competitors rather than consumers, and remain one of the vast majority of world antitrust regulators^[2] that have found no basis to bring a challenge against Google.

The European Commission’s complaints against the company are fundamentally based on the theory that Google’s aim is to “preserve and strengthen its dominance in general internet search.” But it can hardly be said that bundling Google Search with Android serves to “preserve” Google’s dominant search position in Korea. For one thing, despite some recent gains, Google’s search market share^[3] has long been negligible compared to its primary domestic competitors, and Android has done little to dent their dominance. And if the practice is meant to lift Google up from its relatively weak position in search, it has been decidedly unsuccessful thus far.

Google simply doesn’t have the ability (nor the inclination) to harm consumers or competition in Korea in the manner alleged by the European Commission.

In Korea, Google, with its branded Android operating system, remains a significant but — importantly — non-dominant player. While some Android devices install Google services, many others do not.^[4] Nor do Google’s practices lock device manufacturers into Android at all, as Samsung’s burgeoning Tizen operating system ecosystem demonstrates.

The KFTC looked at these facts in 2013 and concluded that Google had not engaged in behavior to harm competition. If anything, the economic conditions supporting that conclusion have only gotten stronger since.

Today manufacturers are deploying Android to power phone and tablets but also watches and TVs. Developers are building an ever-widening array of apps and software for this ecosystem, bolstered by the cross-device interoperability that Android affords. In fact, among the apps being sold in Google’s (global) Android app store, South Korea boasts the fifth highest number of developers.^[5]

Meanwhile, the average South Korean smartphone user downloads 40 apps,^[6] more than in any other country — nearly all of them free. Whatever else may be said about the bundling of Google Play with Android, it can’t be seriously argued that it has harmed the ability of South Koreans to access the apps of their choice, including apps made by Google’s Korean search competitors, several of which are among the app store’s top downloads.^[7] 

One has only to look at Korea’s vibrant^[8] and informed^[9] mobile marketplace to see there is no evidence to suggest that Google has harmed app developers’ incentives to innovate, either. Korean mobile app companies are thriving. Color-Note, a Korean mobile media business, has exhibited remarkable growth. And KakaoTalk,^[10] a Korean messaging platform, not only minted a billionaire, but was one of the companies at the forefront of integrating messaging platforms with a wide range of other apps — a technological development now being wielded by Facebook’s Messenger app to challenge the supremacy of app stores^[11] like Google’s.

Consumers in South Korea are among the most savvy tech adopters in the world. The country’s embrace of the Android platform has served to encourage immense innovation, and developers, device manufacturers, consumers and competitors have all benefitted as a result. 

Korea should not blindly follow Europe when it comes to internet regulation. The KFTC has already conducted an investigation into Google’s practices in the country and found no evidence of harm to competition. Korea has a thriving digital ecosystem and is a global leader precisely because regulators have focused on supporting Korean innovation. They should continue on that path to continued economic success.