1. technology and computing

18th Presidential Inauguration Speech as delivered by Her Excellency Park Geun-hye
“Opening a New Era of Hope”
My fellow countrymen!
Today, I would like to propose a new way forward on the basis of a mutually reinforcing cycle of national advancement and the
happiness of the people.
The new Administration will usher in a new era of hope premised on economic revival, happiness for the people, and cultural enrichment.
To begin with, I will work for a creative economy and economic democratization.
We are witnessing an economic paradigm shift across the world.
The convergence of science and technology with industry, the fusion of culture with industry and the blossoming of creativity made
possible by the breaking down of barriers between industries define a creative economy.
It is about creating new markets and new jobs by building on the bedrock of convergence, going beyond simply expanding existing markets.
At the very heart of a creative economy lie science, technology and the IT industry, areas that I have earmarked as key priorities.
I will raise the quality of our science and technology to world-class levels. The creativeeconomy will be brought to fruition by applying
the results of such endeavors across the board.
The new Administration’s Ministry of Future Planning and Science will be tasked with leading the emergence of a creative economy
in tandem with this new paradigm.
creative economy. We live in an age where a single individual can raise the value of an entire nation and
People are the nucleus of a even help in rescuing the economy.
New opportunities to serve the country will be opened to numerous talented Koreans thriving across the global village. And for those at
home who are equally capable, efforts will be enhanced to foster them into convergence leaders imbued with creativity and passion as
pillars of a future Korea.
THE INFORMATION AND
PRODUCTION DISRUPTION:
creative economy to truly blossom, economic democratization must be achieved.
In order for a I believe strongly that only when a fair market is firmly in place can everyone have hope and work to their fullest potential.
One of my critical economic goals is to ensure that anyone that works hard can stand on their own two feet and that small and
medium-sized enterprises can prosper alongside large companies through small business promotion policies.
Implications for Innovation Policy
By rooting out various unfair business dealings
that Peter
frustrate
micro-business
ownersHaggard
and small and medium-sized enterprises and by
Written by:
Cowhey
and Stephan
rectifying the wrong practices of the past, we will provide active support to ensure that everyone can realize their full capabilities,
regardless of where they work or what they do for a living.
“
U.S.-Korea Business Council
Innovation Working Group White Paper
The Information and Production Disruption:
Implications for Innovation Policy
Peter Cowhey and Stephan Haggard
School of International Relations and Pacific Studies
University of California, San Diego
The U.S.-Korea Business Council (USKBC) endorses President Park
Geun-hye’s efforts to boost the Korean economy through policies
and measures that support innovation and the creative economy.
At every opportunity, the USKBC has reaffirmed the U.S. business
community’s commitment to support the Park Administration’s
agenda to make the Korean economy more open, diverse, dynamic
and business friendly. This white paper from Professors Peter Cowhey
and Stephan Haggard of University of California San Diego’s School
of International Relations and Pacific Studies, which outlines best
practices and policies to support innovation, is provided by the
USKBC in this spirit.
In combination with the high-level dialogue with key government,
business, and thought leaders from both economies at the November
6, 2014, Innovation Symposium in Seoul, the USKBC hopes that
this paper will assist stakeholders by providing useful suggestions on
how to shape and prioritize the innovation agenda. We look forward
to further collaboration with the Park Administration and other
stakeholders in Korea in this area going forward. Your feedback and
continued support of the USKBC is appreciated.
Sincerely,
Tami Overby
President
U.S.-Korea Business Council
The Information and Production Disruption: Implications for Innovation Policy
The Information and Production Disruption: Implications for Innovation Policy
Peter Cowhey and Stephan Haggard1
Korea’s remarkable economic growth was initially driven by strong investment in physical and human capital and
successful technological borrowing from abroad. Over time, Korean firms mastered complex manufacturing processes
and developed cutting-edge production technologies in goods as diverse as steel, ships, cars, and integrated circuits.
More recently, larger Korean firms in the consumer electronics sector have moved from global export production bases
for software and hardware to commercially viable innovations and standards.
Yet as Korea transitioned to an advanced industrial state, the ability to continue to grow through an input-driven
model declined. Korea’s presence in the Asia-Pacific provides advantages but also challenges as it navigates a path
between rising competitors in the region and the continuing ability of the United States, Japan, and Europe to push the
technological frontier. As President Park Geun-hye’s new innovation initiative acknowledges, sustained growth will
increasingly rely on continued innovation and creativity—not only in manufacturing but in services and not only in
the largest groups but among suppliers, small and medium-sized enterprises (SMEs), and new startups as well.
This paper looks at the continuing evolution of national innovation systems since 1945 to draw lessons for public
policy. First we define innovation and the core components of national innovation systems (Part I). We then
draw some initial lessons by comparing the evolution of the American innovation system, especially for advanced
technology, to the path followed by Korea’s innovation system (Part II). In Part III we consider how an emerging
Information and Production Disruption (IPD) is once again changing established innovation systems. Specifically, two
technological disruptions pose challenges for companies and government policies. First, even as the costs of networked
information fall, the information value of commercial products is rising, even in very traditional product markets.
Second, the global system for producing goods and services is being disrupted by a new generation of production
technologies that radically lower costs, and this will affect both minimum-efficient scale and location decisions.
Together, these two forces are changing successful startup and SME strategies.
In Part IV we extend our argument by showing how market leaders in industries as diverse as agriculture and
communications and information technology, Monsanto and Qualcomm respectively, are adapting to the IPD
disruptions. We further note the implications for operations in Korea. We conclude with a discussion of nine policy
implications of these disruptions that can motivate continued dialogue between governments and leading firms on the
issues (Part V).
1
I. Defining Innovation
Economists widely acknowledge the benefits of technological innovation for growth, but the dynamics of innovation
are frequently not carefully analyzed.2
Consistent with the OECD’s approach, we define innovation as the commercialization of new knowledge.
Innovation takes several forms, and countries have excelled in different types of innovation at different times.3
This differentiation occurs, in part, because countries evolve different national innovation systems. A national
innovation system is the larger institutional and policy setting in which such activities are incentivized and
develop. Over time, national innovation systems change periodically as the environment for innovation changes and
the characteristics of the technological possibilities shift.
National innovation systems rely on five building blocks. They typically stretch beyond the boundaries of any
given firm.
1. Flexible business models. Many innovations fail because firms cannot (perhaps due to regulations) develop
new business models to capture their potential. The iPod business model, for example, turned the prevailing
wisdom of the day—that content was more important than hardware—upside down.
2. Social networks and dynamic labor markets. Innovation thrives where there are clusters of entrepreneurs,
scientists, engineers, and experts who interact unpredictably and facilitate the generation and diffusion of
ideas while still protecting intellectual property (IP).
3. Financial models to support innovation. Whether involving banks, capital markets, or venture capital (VC),
innovation requires that innovative ideas can secure funding and move from concept into production and the
market.
4. Shared assets that lower costs for innovative companies. Innovation typically draws on complementary
assets beyond the boundaries of the firm. These include universities, research facilities, and new social
infrastructure, such as broadband, that lower the costs of production and distribution. Regional technology
clusters have often played an important role in creating such shared assets, as well as social networks.
5. Appropriate government policies. They include policy with respect to foreign trade and investment.
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The Information and Production Disruption: Implications for Innovation Policy
II. Changing National Innovation Systems: The American and Korean Experiences
To simplify a complex global history, we focus on the evolution of the U.S. innovation system since 1945 as a baseline
because the U.S. has been the single strongest force in high-end innovation in this period. Changes in its system have
global ramifications. As a result, other important innovators, including Korea, explicitly or implicitly use comparisons
to the U.S. system as a benchmark for their own national progress. The innovation systems of countries like Korea or
Germany are, of course, not simple copies of the U.S. system, and this brief review makes clear ways in which the
Korean system is distinctive. Two dominant but overlapping innovation systems have existed in the U.S. since 1945.
In the first wave, during the 1950s and 1960s, vertically integrated companies anchored the system. Expertise was
internally networked in the firm’s own R&D groups, firms assiduously sorted out which assets were to be shared and
which were unique to particular business lines, and internal capital markets provided “patient capital” for new lines
of products or businesses. Firms received both direct and indirect government support through national research
institutes and particularly support for R&D and product development deemed relevant to national security.
The chaebol differ in a number of important ways from the multidivisional U.S. firm. Nonetheless, Korean experience
since its takeoff in the 1960s and 1970s has also been built around large, integrated groups that were particularly
adept at manufacturing and the incremental development of production technologies. These groups were even more
diversified than their American counterparts, operating in virtually all major product markets. The chaebol leveraged
complementarities among nominally independent firms and invested heavily in shared assets, including R&D.
Personnel movement within the group—both at the managerial and engineering levels—supported innovation.
Funding came from both the state-owned banking system and financial transactions among group companies.
Government support came in the form of industrial policies, with much less reliance on either university or
government research centers. The core of the model was successful technological borrowing from abroad coupled with
marginal innovations in production technologies.
The Second Wave
The second wave of innovation—ascendant in the U.S. since the 1980s—was dominated by a technology cluster
system built around startups and VC, usually focused in a regional cluster anchored by one or more research
universities.
In terms of business models, new firms grew rapidly by supplying key inputs to established suppliers or
complementary goods to the offerings of giants (e.g., Intel and Microsoft to IBM or Cisco as a complementary good
to Lucent). In that sense, they resembled many specialized suppliers found in the supply chain of, for example, a
global automobile maker. But, unlike 1st wave suppliers, these 2nd wave firms soon claimed increasing shares of the
value chain and often defined the leading edge of innovation for the entire market. Rapid scaling of novel, specialized
solutions was central to all the startup models. Google’s emphasis on free search (and, later on software), monetized
by ads, disrupted the Microsoft model, which had previously disrupted the vertically integrated IBM business.
3
Another feature of this 2nd wave was widespread vertical disintegration, a process that ultimately also forced changes
in 1st wave firms. Startups specialized ruthlessly, allowing them to capture value by defining standards and reaping
returns from product design and brand management. Managing complex international production networks—mostly
manufacturing in Asia—also became a core competence.
Regional clustering took on added significance. For example, Silicon Valley and Boston’s Route 128 dominated
information technology, with Seattle a close third. Biotech innovation clustered in San Francisco, Boston, and San
Diego. Communications technology migrated primarily to California, with technology for terrestrial networks focused
in the North and wireless networks in the South.
This clustering built on several components of national innovation systems outlined here. First, successful innovation
clusters required deep social and informational networking. Strong social networks, abetted by formal and informal
institutions, are essential to the circulation of knowledge and people and for building trust that makes for successful
clusters.4 Cluster leaders routinely acknowledge that people are the most important asset for ambitious innovation
industries. Clusters provide a social institutional solution for the narrowness of the human networks in highly
specialized firms. They also develop informal normative and formal legal mechanisms to protect important IP while
circulating people and ideas.
The 2nd wave system only fully matured in the context of common assets (some public, some private). Anchor
universities became critical to both underlying R&D for startups and the training and networking of human capital.
Common assets in the private sector emerged for production (through networks of contract manufacturers),
quality testing, and knowledge creation. Some of this (e.g., in measurement technology for semiconductors) arose from
combined investments by industry and the U.S. government; other pieces depended on regional sharing
arrangements (e.g., rental time on electron microscopes from research universities).5
New systems of finance were part of the DNA of the 2nd wave. Because researchers were no longer part of internal
corporate innovation systems, funds were raised by courting venture and angel capitalists attuned to the region and
promoting incubators that lowered costs and identified prospective investors. New laws and regulations that allowed and
incentivized the creation of novel financial vehicles were essential to this model. VC and the creation of markets such as
NASDAQ rapidly generated large financial gains. In addition, huge business strategy innovations in finance emerged from
the flexible American organization of financial markets. Beginning in late 1984, Goldman Sachs let the system of IPOs
scale enormously by placing them with large institutional investors, rather than with individual retail customers.6
While the U.S. government has resorted periodically to VC-style funds for some purposes, such as those of the CIA
or e-Energy, the heart of the U.S. VC system is in the private sector. This divorce from government is critical to the
system’s success. Innovation often arises from the unexpected, not from the consensus views that likely guide the
funding path of more risk-averse government-related VC funds.
4
The Information and Production Disruption: Implications for Innovation Policy
Finally, both national and local policies undergirded these regional clusters. These policies funded basic and applied
R&D, induced the training of researchers and engineers, and enforced competition rules that kept markets open to
newcomers. There was also considerable experimentation with IP law, because firms had to strengthen IP protection
while still allowing the knowledge sharing critical to 2nd wave innovators.
Policies supporting business model innovation were also important during the 2nd wave. There were important
changes in how universities could commercially license results from federally funded research (i.e., the Bayh-Dole
Act), SEC rules about how pension funds could invest their funds (critical to funding VCs), federal competition
policy (including the breakup of AT&T) that opened up many markets for new technological entrants, and the federal
decision to use a “light hand” in technologically dynamic markets (such as refraining from government selection of
mandatory technology standards and initially taking a “green field” view of e-commerce markets to remove these
markets from traditional regulatory frameworks).7
The emergence of this 2nd wave did not altogether displace the 1st wave innovators. But most had to retool in the face
of competition from abroad—particularly Asia—and the rise of these new domestic business models. Today, many U.S.
corporate giants began as 2nd wave startups. The 30 firms that make up the Dow Jones index include long-standing
companies such as 3M, IBM, and Coca-Cola but also a number of firms that have in different ways participated in this
2nd wave model. Cisco, Intel, Microsoft, and even retail firms such as eBay, Nike, and Home Depot are examples. We
consider the challenges facing these firms in Part IV, but look first at how the Korean national innovation system evolved.
Benchmarking Korea’s Second Wave
Korean firms reaped advantages but also faced challenges in the face of this 2nd wave. In some sectors, such as autos
and shipbuilding, the 1st wave chaebol form was well-suited to continuing incremental product innovation and
moving up the value chain. In other sectors, particularly consumer electronics, Korea became skilled in incremental
and even architectural innovations and developed its own production networks in the Asian region and beyond.
In what ways did Korea’s 2nd wave align and differ from the U.S. along the dimensions outlined in this paper?
• First, with respect to business strategies, the chaebol form has persisted, with a much greater share of
total economic activity transpiring within the group than would be the case for the evolving 1st wave and
particularly 2nd wave American companies. To be sure, chaebol developed networks of dedicated suppliers,
both onshore and offshore, and this increased skills and capacity. But this has not been matched by strong
innovation in the SME sector in Korea, either from startups or from established suppliers. Strengthening the
SME sector is a central focus of President Park’s innovation strategy.
5
• A second feature of the overall business environment in Korea is the weak performance of the services sector.
Services account for about half of Korean GDP and 60% of employment, but they make little contribution to
overall productivity growth except for some Internet services. A major challenge for the Korean government and
firms is how to incentivize a more dynamic services economy, including through increased foreign investment.
• One reason why the new clustering strategy has not fully taken root is the immobility of labor. Job security
concerns, the prestige associated with chaebol employment, and group loyalty limit the flow of personnel from
large firms to smaller entrepreneurial firms. To the contrary, the chaebols have the ability to hire talent from
SMEs, limiting their growth. Within the group, the chaebols have effectively guided the movement of personnel.
• With respect to shared assets and the related phenomenon of clustering, linkages between the private sector—
both large and small—universities and government research institutes (GRIs) remain suboptimal. Universities
have not taken on board the full range of reforms and experiments that facilitate such integration, including
organizational norms that reward links with the private sector.8 Similarly, GRIs face challenges to define a role
between basic research and a more commercial approach that would deepen linkages to both larger and smaller
firms. Foreign firms will be watching the new experiment with the Institute for Basic Science in Daejeon with
interest, as well as efforts to establish Regional Technology Transfer Centres (RTTCs) and Techno Parks.
• Korea initiated experiments in government-led venture financing in the wake of the financial crisis, both directly
and through extensive incentives to startup companies. Yet its VC model still lags. Moreover, analyses of the
existing startup ecosystem in Korea shows a reliance on cues from government, for example, in overweighting
GRIs when compared to universities and a strong reliance on cues from the chaebols in the startup sector.9
• With respect to government policy, two issues are notable. First, Korea has frequently adopted best practices
from abroad. But each new government brings in a new set of ideas, including restructuring of past innovation
efforts and the creation of altogether new bodies, even ministries. This creates some uncertainty about the
durability of policy. Second, a crucial feature of the American innovation system is its surprisingly decentralized
nature. Where clusters sprung up, they frequently were the product of local actors and governments. This departs
significantly from Korea’s relatively centralized political system, which may limit local initiative.
6
The Information and Production Disruption: Implications for Innovation Policy
III. Sources of Disruption: A New Innovation System?
Disruptive technological forces are at work once more that could change how countries and companies organize to
innovate. Technological disruption has two broad effects. The first order consequences are obviously changes in the
pattern of winners and losers in marketplaces. The second order consequences of disruption are the emergence of
complementary risks that must be managed. Frequently, this leads to innovation in both private market institutions,
such as the emergence of large scale insurance syndicates to deal with the risks of rising global shipping commerce, and
government policies, such as the creation of maritime safety regulation.
If we are correct, the 2nd wave innovation system in the U.S. is now facing a disruption that should have global
implications. Cowhey and Aronson10 argue that IPD encompasses two intertwined drivers:
1. The information value of commercial products is rising, even in very traditional product markets;
2. The global system for producing goods and services is being disrupted by a new generation of production
technologies.
Networked information technology is nearly ubiquitous and incredibly inexpensive even compared with 2000.11 The
result is that ideas (enshrined in IP), networked information (software), the collection and analysis of big data, and
services are growing rapidly as a share of value-added in many products, including manufactured products. This is true
even in traditional products ranging from farm field plowing to the making of household keys and highly customized—yet
mass distributed—clothing and footwear. Indeed, the line between manufacturing and services is increasingly blurred.12
These factors not only constitute a much larger share of value-added in any given product but information derived
from products can itself become a center for anticipated revenue streams. For example, the big data collected as part of
the primary product being delivered to the consumer can be reused flexibly to create additional products or sold and
then recombined with other data by third parties.
Perhaps, most importantly, the continuous networked interaction of the product supplier and users allows for a
continuous reinvention of the product/business model, thus amplifying and accelerating the concept of “user
co-invention” of technology product innovation that is one of the hidden catalysts of continuous innovation.13
The second disruption is that production technologies (additive manufacturing or 3D printing, new materials, and
robotics) are changing rapidly, affecting both the speed and cost of product development and scale economies.
Additive manufacturing has radically lowered the cost of generating prototypes, if not production, creating possibilities
for highly decentralized, small-scale innovation centers and clusters. This should greatly brighten the future for
companies built on sophisticated batch manufacturing of specialized products. New financial models for funding
innovation are also enabled by information technology, such as crowdsourcing, and are being married to platforms
that allow potential users to provide inputs to marketing and design refined through interactive feedback from the web,
thus changing the economics of these functions markedly.14
7
Even for products typically considered capital intensive, we see these forces at work. Tesla used new computer-assisted
design systems and the latest generation of robots for its design and production process and significantly reduced the
time from model conception to commercial production, improving on previous industry best practices by one-third.
Smart materials are emerging that will embed networked sensors (sometimes called network-centric production
materials), thereby improving the accuracy of quality control systems. This will reduce costs, enhance product
reputations, and even allow manufacturers to sell “near-miss” components for uses that demand less precision.
We can anticipate four major consequences of these disruptions:
1. These technologies substantially lower the cost of many forms of technology innovation, thereby making entry
even easier and probably leading to more interesting hybrid innovations. For example, conventional estimates
are that ICT costs of startups for hardware and software plus personnel have dropped by 70% to 80% since
2000. Greater reliance on ideas embedded in information technologies also permit new management
strategies.15 Even laboratory experimental investigations are yielding to the same economics as contract
manufacturing systems. Emerald Therapeutics, for instance, has networked sophisticated laboratory testing
equipment and integrated them with its own software operating system. This allows the company to offer
sophisticated lab testing for new bio-pharma firms at low cost with rapid turnaround, permitting them to
design and monitor experiments via a web interface and lowering the amount of high-end equipment and
laboratory personnel needed for a bio-pharma startup.16
2. The intermingling of traditional goods with information-enabled services and new production technologies
will disrupt even the most traditional markets.17 Consider Dropcam, a company that sells systems of cameras
that initially were dedicated to security systems (broadly defined) and have become ubiquitous consumer
devices for observing home life and offices. The founders began with a software application that they hacked
into the standardized software embedded in the chips of digital cameras purchased off the shelf. They then
used the cameras in an observation system backed with cloud storage capacity. As the company grew, it
decided to lower costs to accelerate a mass market by building its own cameras. 3D prototyping made the
initial design an order of magnitude less expensive than would have been possible a few years earlier. When
Dropcam went to mass production, where replicable quality and scale economies matter, it outsourced
manufacturing in China. But driven by interactive experience with users, the hardware simply facilitated
the software systems solution where the bulk of the value resides.18 Perhaps the ultimate testament to this
successful integration of software, big data, and cloud computing was its 2014 purchase by Google.
3. The disruptions will enable new types of regional startup clusters to thrive covering a more diverse range of
industries and locations. Take New York City. For all its public relations in the 1990s, Silicon Alley in New York
was not a substantial player in the information industry despite New York City’s huge strength in creating
content. Today, New York City has finally emerged as one of the major application content innovators because
the Cloud eliminates the need to maintain an indigenous information technology platform, involving many
8
The Information and Production Disruption: Implications for Innovation Policy
machines, thus large rental spaces, and many high salaried ICT engineers, in Manhattan. While this example
focuses on information services and content, the same dynamics apply to traditional physical goods and
services. (See the later discussion of Monsanto.)19
4. While local clusters encompassing a far wider range of market specializations than in the 2nd wave will emerge,
the IPD’s productive potential is inherently global. The nature of interactive user experience and big data
analysis will require drawing on global experience and feedback. At the same time, the information disruption
makes it easier for even smaller firms to productively network clusters of specialized local talent on a global
basis. This should stimulate the growth of specialized batch products with higher value-added content,
including mixtures of goods and services, for global markets. Importantly, the production revolution will
further blur the distinctions between goods and services: Is an information design from the U.S. downloaded
into a 3D printer in Brazil a good or a service?
We see these changes affecting policies for national innovation systems in ways that are significant for both Korea and
the U.S. Part V draws out these lessons. We turn now to two mini-case studies to show that the IPD changes more than
startups. It also changes the landscape for established industry leaders in traditional and high technology markets.
IV. Case Studies in Innovation by Major Global Companies
This section uses two mini-case studies to illustrate the opportunities and changes ahead for large market leaders due
to disruption, linking them to trends in other industries as well. The case of Monsanto shows how the IPD is
transforming even the agriculture market, with implications for the management and control of data. The case of
Qualcomm shows how a winner in the 2nd wave is experimenting with adaptation to the next generation of
innovation, including through investment in Korea. The Qualcomm experiment illustrates the difference between an
ecosystem, rather than a conglomerate strategy, and demonstrates the evolving logic of global “platform economics.”
As we explore these cases, we are not predicting commercial success for any particular experiment. Rather, we are
showing how the IPD’s disruptive forces drive even the strategies of successful incumbents and generate consequences
for government policy.
Monsanto: Market Disruption and Governance Innovations
Cowhey and Aronson first pointed out that mobile broadband would transform processes outside the traditional
domain of information intensive-business models.20 To illustrate how technological disruption has opened a new space
for innovation in the world’s oldest market, agriculture, consider the case of Monsanto.
9
Monsanto, a prime example of a 1st wave technology agricultural innovator, subsequently bought Precision
Planting, which combined data analytics (a service called FieldScripts) and an innovative piece of hardware (a planter
that trailed behind tractors) to guide optimal planting (the spacing and depth of seeds in fields). The Monsanto system
raised yields by 5% in two years and could ultimately raise corn productivity by 25%, gains that would not otherwise be
possible. Monsanto also paid $930 million for The Climate Corporation, a big data company focused on
agriculture and climate. Monsanto anticipated that the new firms would help its forward planning for new products
and open up a complementary market potential of $20 billion for agricultural data services. Using remote sensing and
big data models, Climate Corp insures crops that fall below expected yields due to weather outside predicted
parameters for the crop’s success.
The Monsanto story illustrates how mobile broadband-enabled services can add new capabilities to a traditional
market segment and significantly change the business model. It also demonstrates how hardware (the Precision
Planting equipment) and services (FieldScripts and Climate Corp insurance) intersect in new integrated models.
Significantly, other specialized suppliers are emerging in the space by utilizing local knowledge. Local expertise is
leading to cities like Des Moines becoming clusters for new applications for information-intensive agriculture.21 This
movement to new types of regional knowledge hubs is exactly what we would expect in many disrupted industries.
Personalized individual or business data from farmers are critical for the success of these models, thus raising issues
traditionally treated under the rubric of privacy rights; mechanisms were needed for negotiating the terms on which
data could be used by information service firms or their third-party clients. Concerns arose about whether Monsanto
could resell farmer’s private expertise (in the form of information) to others, or use the data from its services to
farmers to backward integrate into farming by purchasing lower-yield farms or even speculate on futures in
commodity markets in ways that could hurt farmers.
Predictably, new types of startups emerged that claimed competitive advantages in helping manage risks from big data.
The new entrants take the form of companies like the Grower Information Services Co-operative that negotiate on
behalf of farmers with big data services and the rise of specialized service suppliers like Geosys (owned by the large
Land O’Lakes farmer cooperative) that emphasize the alignment of their interests with those of farmers. Both startups
represented ways to reduce risks for farmers from a new shared production asset (information services) that posed
novel governance issues. And both are easier to create because of the disruptive changes in information technology.
Governance does not have to be articulated or implemented by government agencies or private agreements alone.
It can also take place through the non-profit sector. In this case, the American Farm Bureau (AFB), the leading
private farm organization, is writing a code of conduct stating that farmers own their own data and firms may not
use data (or supply the data to third parties) except for agreed-upon purposes. Moreover, the AFB wants farmers to
be compensated for the use of their data. Finally, the AFB is concerned about revealing information about farmers’
practices (e.g., about the use of pesticides) that may usually fit under the traditional privacy rubric. Companies like
Monsanto have agreed in principle to this approach, although their contracts do not yet incorporate these terms.22
10
The Information and Production Disruption: Implications for Innovation Policy
This case illustrates a number of features emerging from the IPD: the application of new, highly networked
information to traditional sectors; close marriage of supply of goods (e.g., tractors and specialized planters) and
services (e.g., data analytics); new risks, including with respect to privacy and the use of big data, and corresponding
new entities, both public and private, to govern those risks.
Qualcomm: What Do Big Technology Firms Do?
The leading technology giants will face many challenges in the IPD. Their opportunity is continuing to add value
within their core technological competence while marrying their traditional strengths to new pools of unconventional
demand. The stories of Qualcomm and wireless health fit this model. The Qualcomm story also shows how
international innovation efforts may work in the IPD.
One strategy for building on traditional core strengths is for specialized firms to play a direct role in stimulating early
rounds of novel innovation entrants that are complementary to their business strategies. Here are two interesting tools.
First, Qualcomm can become more like an angel investor—making smaller investments to accelerate
undertakings that are too novel for conventional VC funding. Second, it can experiment with the use of prizes to
stimulate initial inventions. For example, Qualcomm is offering an “X Prize” for a wireless medical diagnostic device
(patterned on the “medical tricorder” from Star Trek lore). Its purpose is to feed an ecosystem of new innovation
groups that can become new sources of market demand for Qualcomm chip technologies.
Importantly, Qualcomm’s efforts, while ambitious, are only a small fraction of the emerging technological
convergence of networked information and medical devices. If Qualcomm, or a small number of firms, defined the
effective funding market for these fledgling efforts, it would run into an adverse selection problem. Its biases
(conscious or not) would shape the types of entrants and technologies, instead of allowing Qualcomm to sample a
diverse range of experiments.
A second strategy is to create the infrastructure to support the innovation environment for more specialized firms with midsized product markets. For Qualcomm Life, the infrastructure consists of a package of a middle ware that makes it easier to
convert applications built for the diverse wireless operating platforms (e.g., Apple, Android, and Windows) to the necessary
ICT infrastructure to support them. It also includes a wireless “hub” that can exchange data gathered by, and requested by, the
mobile application and a cloud storage system for the data that is fully compliant with health privacy rules.
The Qualcomm package allows the wireless health application provider to avoid all the costs of creating a back end for their
device and/or software application. Equally important, Qualcomm maintains a catalogue and road map system for its users
that enables a company to look up the intended road map for each operating system in the standards setting community (so
it knows what has to be designed next without costly participation in the standards process) and a catalogue of solutions for
wireless applications in new global markets (because radio spectrum and other design details vary by country).23
11
There are two features of these experiments worth considering further. First, they permit Qualcomm to expand
on its core strengths (such as radio technology and power efficient computing capacity on mobile devices)
without diversifying into a wholly new range of technologies with rapidly changing business models. This is
different from the traditional conglomerate approach. Second, they represent the economic logic of “two-sided
platforms.” A key feature of markets with heavy information technology characteristics, as is wireless health, is
that the true value of any single product has to be seen in the context of the entire solution set.24 For example,
the value of a personal computer varies depending on the value of printers.
It should be noted that Qualcomm is taking its strategy global. Qualcomm Ventures was also established in Korea in
October 2010, following a $4 million investment into Pulsus Technologies. Since then, Qualcomm Ventures has
quickly established itself as a significant VC in Korea. Despite the fact that Qualcomm is not a financial sector enterprise, it expanded its total portfolio to five companies in less than two years. QC Ventures’ current portfolio includes
companies in consumer apps, components, network infrastructure, and gaming. Qualcomm has also used the prize
mechanism to incentivize innovation in Korea.25
In 2010, Qualcomm also established Qualcomm Research Korea and started venture investment to provide a
similar platform that brings Qualcomm and the Korean government, the research community, opinion leaders,
the media, and the public together. Qualcomm Research Korea has now grown to more than 20 locally hired
researchers, most with Ph.Ds. from Korean universities and many with industry experience. The goal is to develop new technologies that drive the next generation of smartphones by focusing on two areas of innovation:
(1) using the phone’s microphone to enable human-like hearing functions; and (2) using the phone’s camera to
enable human-like vision functionalities. Both projects rely on a growth model different from the traditional
conglomerate strategy and nicely illustrate the dynamics of platform economics.
12
The Information and Production Disruption: Implications for Innovation Policy
V. Issues for Government Policy
The IPD disruptions in the innovation system have implications for both small and large firms. This section
recapitulates the big market impacts on innovation that both the U.S. and Korea should consider. It then draws
implications for policy regarding each impact. As we draw out nine policy implications, we note how they often shed
fresh light on, or reinforce, the 2011 APEC Leaders statement on APEC Innovation Principles.26
1. These technologies substantially lower the cost of many forms of technology innovation, thereby making entry
even easier and probably leading to more interesting hybrid innovations that will combine more diverse ranges of
expertise.
2. The intermingling of traditional goods with information-enabled services and new production technologies will
disrupt even the most traditional markets.
3. The disruptions will enable new types of regional startup clusters to thrive, covering a more diverse range of
industries and locations.
4. While local clusters encompassing a far wider range of market specializations than in the 2nd wave will emerge,
the IPD’s productive potential is inherently global.
As the costs of innovation decline due to IPD, we will see enormous experimentation by both small and large firms
with novel combinations of expertise. This is exactly what is happening in whole new industries, such as wireless
health devices and services and in very traditional industries now embracing the information revolution. At the same
time, interactive user-supplier exchanges and learning from the resulting generation of big data are central to the IPD.
Policy must be careful not to restrict business model innovations built around these features. Some of the appropriate
policy guidelines are the same as those refined over the past three decades, such as the critical importance of regulatory
transparency to both improve the quality of decisions through feedback and learning and to reduce business risks.
Now we turn to special considerations arising from the IPD.
First policy implication: Policies to protect privacy and enhance cybersecurity are imperative but have to be
mindful of the costs of restricting global information flows. To the maximum extent possible, national policy should
encourage market incentives and market-based institutional innovations to cope with these information, data, privacy,
and security issues. Efforts to enhance the security of private data can interfere with interactive learning with users that
is vital to continuous innovation. Korea’s evolving guidelines about cloud computing and cross-border flows of data
have been the subject of concerned discussion with the U.S. for these reasons.
Second policy implication: Central command and control guidance, such as mandatory national technical
standards, can restrict innovation. The international trade guidelines calling for industry-led and voluntary standards
decisions exactly fit the IPD logic.27 In contrast, when some level of authoritative government decisions are vital, such
13
as for sensitive safety certification systems (e.g., biomedical safety), the process should be more flexible in order to
take advantage of new and surprising possibilities. In this regard, the European Union has significant lessons for best
practices for both the U.S. and Korea.
Third policy implication: The APEC Innovation Principles calls on APEC members to “develop and maintain an
open economy that allows the flow of capital, people, ideas, goods, and services across borders in ways that ensure
competition, enhance productivity, and foster growth.” It also calls on countries to remove restrictions on foreign direct
investment (FDI). This remains a challenge for both Korea and the U.S. Despite the substantial liberalization of FDI
following the Asian financial crisis, the role of FDI in the Korean economy remains smaller than in many
comparator economies. For the U.S., a particular challenge is balancing legitimate national security scrutiny and the
need for investment in global information networks.
Fourth policy implication: The APEC Innovation Principles highlight the importance of international research
flows. (“Encourage cooperation and interaction among researchers and laboratories, including through joint research
and development, in order to accelerate innovation.”) This is a particular challenge for Korea. As the 2014 OECD
assessment of Korea stated: “Very little R&D carried out in Korea is financed from abroad, linkages with foreign firms
and institutions are relatively weak, and few foreign researchers and students come to Korea to work or study, a sign
that Korea may not draw sufficiently on the growing global stock of knowledge.” Once again, for the U.S., which has
long been the hub of global research flows, the challenge is how to deal with restrictions on research flows due to
national security policies and immigration concerns.
Fifth policy implication: Because the line between goods and services will further erode, national innovation
strategies have to craft policies to foster services as well as manufacturing innovation. For the U.S., the big challenge
is resetting policy to embrace the potential of the production revolution; services are already thriving, but more
could be done to support innovative manufacturing opportunities. In Korea, the problem is the opposite. Korea has
a long tradition of rapid adoption of cutting-edge production technologies, but its political economy works against a
thorough embrace of the pervasive merger of goods and services production.
Sixth policy implication: Globally, even more must be done to erase distinctions between the treatment of goods
and services under trade rules. The KORUS FTA greatly expanded bilateral liberalization of services trade, but there is
still much to be done with global trade rules to align trade with the IPD.
Seventh policy implication: Successful innovation systems all rest on supportive government policy but policy that
is not heavy-handed and does not encourage disruptive technologies. Strong government support for basic research
and university training is crucial to a number of dynamic industries, such as biotech and medical devices. But political
leaders and large firms can unintentionally blunt the new wave of innovation when trying to guide innovation. This
is a bigger challenge for Korea than the U.S., because its innovation system tends to overweigh the role of government
plans and the strategies of the chaebols. Provincial and local governments are also far less influential in innovation
policies than in the U.S. or even China. A risk exists that the growing opportunities for new types of innovation clusters
14
The Information and Production Disruption: Implications for Innovation Policy
regionally will not be seized in Korea. Government VC efforts may have also pre-empted the emergence of a stronger
private VC ecosystem, including from foreign investors, a crucial factor for many emerging industries in the IPD. This
is especially true when financial innovation, such as crowdsourcing, is part of the IPD. Attention must
continually focus on creating the space for unanticipated challengers by appropriate government support for
innovation but not government micromanagement.
Eighth policy implication: National efforts to enhance precompetitive technological strengths in key fields is a
productive policy investment as long as it does not try to pick specific winning technologies or exclude full
participation by all members of the global economic system. Identifying a field that will be germane to many areas of
innovation, such as better battery technology or new production technologies, and creating a steady set of supports
for this ecosystem can seed commercial innovations. Steady meaningful support for precompetitive technological
competences is an area where Korea has arguably done a better job than the U.S. recently has.
Ninth policy implication: Finally, we can do no better than cite the APEC principles when it comes to the crucial
role that IP protection has played in innovation. “Effective protection and enforcement of IP rights is essential to
creating a climate in which innovators, including small and medium-sized businesses, are encouraged to invest in the
research, development, and commercialization. This includes rejecting any measures that make the location of the
development or ownership of IP a condition for eligibility for government procurement preferences, without
prejudice to economies’ positions in the WTO.” These observations extend beyond the law itself to ensuring adequate
enforcement, including through appropriate standing in local courts and regulatory processes. It is also important to
“ensure that the terms and conditions of transfer of technology, production processes, and other proprietary
information are left to the agreement between individual enterprises.”
The U.S. and Korea are both major innovators, although their specific centers of strength vary and their national
innovation systems vary in their structures. But both will face the disruptive forces of IPD. We believe that the
decentralized U.S. innovation system has some early advantages in adapting to these disruptions, but both countries
can, and must, encourage changes in governance enacted by both civil society (e.g., firms and NGOs) and governments
through funding and regulation. We hope that the policy implications in this closing section are helpful to the
discussions of the U.S.-Korea Business Council.
15
Endnotes
1.
The authors thank Cowhey’s co-authors on other work on innovation, Jonathan Aronson and Danny
Breznitz. This paper draws on this co-authored work.
2.
Robert D. Atkinson and Stephen J. Exell, Innovation Economics (New Haven: Yale University Press, 2012).
3.
We can cluster innovation into three fundamental types: incremental product and process innovations (e.g.,
the evolution of automobile transmissions or the German machine tool industry); architectural innovation
that combines mostly established technical capabilities in important new ways (e.g., the iPad); and novel
product innovation (e.g., fundamental new technologies, such as lasers or monoclonal antibodies). Korea
has impressively progressed on incremental and architectural innovations. The special strength of the United
States continues to be novel product innovation. Dan Breznitz and Peter Cowhey, “America’s Two Systems of
Innovation: Innovation for Production in Fostering U.S. Growth,” Innovations, 7, 3 (Summer 2012): 127-154.
4.
The classic analysis of why the Silicon Valley cluster dominated all others stresses the stronger social
network emerging among the flatter startup structures of California firms. See AnnaLee Saxenian,
Regional Advantage: Culture and Competition in Silicon Valley and Route 128 (Cambridge: Harvard
University Press, 1994). On clusters and anchor research universities, see Martin Kenney and David C.
Mowery, Public Universities and Regional Growth: Insights from the University of California (Palo Alto:
Stanford University Press, 2014).
5.
On measurement technology, see Atkinson and Exell, Innovation Economics, p. 147.
6.
U.S. IPOs were $1.3 billion in 1980 but reached $150 billion in 2013. Both figures quoted in 2013 dollars
in Leslie Picker, “Meet the Father of the Modern IPO,” Bloomberg Businessweek, May 15, 2014.
7.
Peter F. Cowhey and Jonathan Aronson, in Transforming Global Information and Communications Markets
(Cambridge: MIT Press, 2009), explain how the structure of the U.S. political system (especially the
important role of federalism) and the impact of its continental sized, diverse internal market shaped an
approach to competition policy over the past 125 years that favored these outcomes. In short, there is a
political economic explanation of how competition policy has influenced the U.S. approach to innovation.
8.
During the 2nd wave in the U.S., these were led by Technology Transfer Offices but have since
expanded to a variety of other models, including approaches to vest some rights with inventors, while
maintaining some degree of university ownership (so-called free agency models).
9.
Josh Lerner, The Architecture of Innovation (Cambridge: MIT Press, 2012) calculates that U.S. VC
investments were twice that of all other nations combined as of 2010, and South Korea ranked 10th
in size of VC investments, trailing Brazil and India. He also calculated that U.S. investments in VC
measured as a stock were equal to 20% of its GDP, while they were worth 4% in Korea (Korea ranked
14th on this calculation). Private equity funding in Korea is equivalent to 0.14% of GDP annually, about
equal to that of Brazil, but small compared with the U.S. ratio of 0.67% of GDP. See Private Equity
Korea at http://www.privateequitykorea.com/pef-market-size-in-korea/. http://mjpvl.org/the-south-koreangovernment-and-venture-capital-the-costs-of-planned-growth/.
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The Information and Production Disruption: Implications for Innovation Policy
10. Peter F. Cowhey and Jonathan D. Aronson, The Information and Production Disruption: Global Policy
Implications (working title, in progress).
11. The cost of 1 million transistors (a standard measure of computing power) was $527 in 1990, $1 in
2002, and $.05 in 2012. The cost of storage of a gigabyte of data went from $569 in 1992 to $1 in 2002
to $.02 in 2012, and the bandwidth cost of transmitting 1000 Mbps went from $1,245 in 1999 to $100
in 2009 to $16 in 2013. Mary Meeker, Internet Trends in 2014, Kleiner, Perkins, Caufield, Byers at http://
www.kpcb.com/internet-trends.
12. See Cowhey and Aronson, Transforming Global Information and Communication Markets.
13. Eric von Hippel, Democratizing Innovation (Cambridge: MIT Press, 2005).
14. Steve Blank and Bob Dorf, The Startup Owner’s Manual (K&S Ranch Press, 2012).
15. Andrew McAfee and Erik Brynjolfsson, “Big Data: The Management Revolution” Harvard Business Review
(October 2013); V. Mayer-Schonberger and K. Cukier, Big Data (New York: Oxford University Press, 2013).
16. Bloomberg Businessweek, “This Lab for Hire,” July 7-13, 2014 at http://emeraldtherapeutics.org/.
17. In the U.S. “minuteKEY” successfully created a new business model for making copies of household
and car keys using information technology.
18. The company generates more user uploaded data on a daily basis than YouTube. It now uses data
analytics to refine visual recognition to send specific automatic alerts on particular activities to users.
Daniela Hernandez, “Software Is Still King. Hardware Is Just Along for the Ride,” Wired, July 8, 2013,
at http://www.wired.com/business/2013/07/software-is-still-king-hardware-is-just-coming-along-for-theride/?cid=co9596544.
19. On the geographic bias of VCs because of how they monitor investments, see Lerner, 2012, p. 68.
Crowdsourced funding, while still only capable of providing funding of a few million dollars at best, is
less geographically biased in its funding selections than traditional VC funding in the U.S.
20. Cowhey and Aronson, Transforming Global Information and Communications Markets.
21. See John Eligon, “Tech Start-Ups Find a Home on the Prairie”, The New York Times, November 22, 2012.
22. See American Farm Bureau, “Data Privacy,” March 2014 at http://www.fb.org/index.php?action=issues.
bigdata. On Monsanto strategy, see http://seekingalpha.com/article/1729352-monsanto-now-the-bigdata-buzz-hit-the-agriculture-industry (accessed October 4, 2013); Daniel Shea, “What are they doing at
Monsanto?” Bloomberg Businessweek, June 2014, p. 52; Schumpeter, “Digital disruption on the farm”
The Economist, May 24, 2014, p. 64.
17
23. General Electric’s strategy for the “Internet of Things” is similar. GE works with partners on defining
process solutions that improve the reliability of complex systems (such as aircraft or ships). The goal
is to use ICT and sensors to reduce maintenance costs and downtime on critical equipment, while
fulfilling all the required technical standards (such as ISO quality standards).
24. David Evans, A. Hagiu, and R. Schmalensee. Invisible Engines: How Software Platforms Drive
Innovation and Transform Industries (Massachusetts: MIT Press, 2006).
25. Ventures’ QPrize has been instrumental in establishing the Qualcomm brand in the Korea VC
community. The first QPrize was held in 2010, and 43 companies applied. The second QPrize held in
2013 skyrocketed to139 applications. In the medium term, Qualcomm Ventures is looking to expand
these efforts into the so-called 1000x challenge—the prospect that data flows will increase even faster
than Moore’s Law—and adding later-stage companies to the portfolio to mitigate risk.
26. The full title of the statement is: The 2011 APEC Leader’s Statement on Promoting Effective,
Non-Discriminatory and Market-Driven Innovation Policies.
27.
The APEC principles call on governments to “maintain regulatory systems that are transparent and
non-discriminatory, provide due process, and include opportunities for early and meaningful stakeholder
engagement.” Keeping the standards-setting process both timely and responsive to the full range of
stakeholder interests is a difficult task. It has to encompass feedback from global experience and best
practices, and foreign participation is vital to achieve this feedback.
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