Is There a Future for Science Parks?
Alternative Scenarios for 2030 Should Inform Policymaking
In regions around the country, clusters of universities and high-tech companies partner with local and regional governments to boost tech-based economic growth and create good jobs. The two best examples are Silicon Valley, the hotbed of computer technology in northern California, and the metropolitan Boston area connected by Route 128, which is a nexus of biotechnology research and development. For a primer on innovation clusters, see our “Regional Centers of Innovation 101.”
The federal government provides large sums of funding for basic scientific research, and boasts a variety of different programs to help companies and state and local governments prepare executives and workers for employment at young, innovative companies seeking to commercialize this research. But the federal government lacks a comprehensive approach for innovation policy. What’s needed is today is a clear-eyed blueprint for developing more innovative clusters around the country that links together federal programs, academic institutions, companies, and local and regional policymakers. In this series, Science Progress will feature bold ideas from innovation experts across the nation for how the Obama administration can develop an effective innovation policy that creates jobs, enables economic mobility, enhances science, and grows the county’s competitiveness.
Earlier this year Raleigh, North Carolina’s Research Triangle Park celebrated a very important birthday. At the largest-ever conference of the International Association of Science Parks, the industry’s global consortium, the Research Triangle Park marked 50 years of technology-led economic development alongside over 40 other parks from around the world in operation for 25 years or more. It was a grand celebration of a model for economic development pioneered by the Research Triangle Park that has been copied in every corner of the globe.
And why not? Research Triangle Park was a critical factor in transforming North Carolina from the nation’s second-poorest state in 1959 to one of its fastest growing technopoles in the country, and the third-largest biotechnology cluster in the Western hemisphere, after California and Massachusetts.
The basic science park model of using low-cost land as a lure and lens for technology companies is showing signs of aging.
Yet the basic science park model of using low-cost land as a lure and lens for technology companies is showing signs of aging. Big science park projects from Russia to Nevada are in financial trouble as public funds for speculative development dries up. And newer variants of the science park model, such as technology incubators, are starved for funds as the venture capital industry retreats to safer bets on late-stage start-up companies with identifiable exit strategies.
In the United States, federal, state and local governments are attempting to plug gaps into a deeply strained national innovation system. In Pennsylvania, strategic investment of tobacco settlement funds were channeled into life sciences clusters beginning in 2001. The SkySong expansion of Arizona State University’s campus in Scottsdale is a blueprint for how to orient university research around rapid technology transfer to industry and entrepreneurship. The Obama administration’s 2010 budget proposal calls for spending $50 million in 2010 to “create a nationwide network of public-private business incubators to encourage entrepreneurial activity in economically distressed areas,” alongside another $50 million to develop regional centers of innovation.
Today, tried-and-true technology-based economic development models face an uncertain future, yet there is a renewed sense that breakthroughs in science and technology are the key to post-recession growth over the long-term. That’s why it is so intriguing that the Research Triangle Foundation of North Carolina, which develops and manages the park under the leadership of CEO Rick Weddle, decided not to rest on its laurels and hard-won success of the past 50 years, but to instead partner with the Institute for the Future to develop a 20-year forecast of science parks and technology regions. The forecast, “Future Knowledge Systems,” is available as a free PDF download at http://www.iftf.org/iasp and as a print-on-demand booklet.
The report, drawing on over 50 experts both inside and outside the science parks and the economic development profession, paints a picture of two decades marked by upheaval in the way technology clusters grow and develop and are cultivated by public policy planners. Building on a scan of 14 key trends, the forecast highlights four areas of high uncertainty that will present strategic dilemmas for anyone seeking to spur technology-based economic growth.
The first area of high uncertainty is the future of universities as both ivory towers and economic engines. In the span of a generation, universities have supplanted industry and governments as the primary sites for basic scientific research. But the ability of educational institutions to transfer technology to the marketplace is in disarray even as the expectation of universities’ economic role grows.
What seems likely is that many universities will embrace entrepreneurialism and accelerate technology transfer while others will deliberately reject a larger role in the economy or simply be unable to do so effectively. One culprit is a focus on patent licensing as a cash cow for universities. A recent survey by the Association of University Technology Managers found that fewer than half of the 300 universities active in technology transfer make money through licensing. Research by the Kaufman Foundation argues that the focus on big payoffs from patents means that many universities neglect other paths and mechanisms for commercializing discoveries. And then there is still considerable debate among faculties and university administrators about the appropriate relationship between basic science and market-oriented research.
The second area of high uncertainty is the rise of ecological economics. Sustainable economic growth that incorporates the cost of carbon emissions will carry a price, but the basic ecoscience and economics to compute that price are in their earliest days. How much carbon and other externalities will cost over the next ten years, and where and how these costs will be measured will have huge impacts on where research and development activities locate, and how they combine physical spaces and virtual tools to increase productivity and energy efficiency.
These costs are at present unknowable. Clean energy legislation now moving through Congress will impose costs on carbon but also spur new investment in clean energy—investments that will flow in uncertain directions depending on the science. While increased costs of construction, facilities operations, and transportation will all impact science parks and technology incubators, federal investments in energy research hubs will also create new demand for space. With eight clean-energy research centers proposed by the Obama administration, the Department of Energy’s ambitious plan could plant the seeds for new clusters of technology-based economic development.
The third area of high uncertainty will be the expansion and evolution of new science networks and new institutions driven by the web and globalization. We are on the cusp of a new information revolution in the scientific world—professional societies, journals, and other institutions that set the basic rules of who can call themselves a scientist, and how they should conduct research and share results, and how they are rewarded, are under tremendous strain. Something will replace these institutions, but how these new networks of science will connect to existing technology clusters is unclear.
The final area of high uncertainty is the life sciences sector and the question of whether it will ever make any money. Industry observers, most notably Gary Pisano of Harvard Business School, note that over the past thirty years the biotechnology industry has yielded $300 billion in revenue, but consumed just as much investment capital. In essence, while biotech firms created numerous new technologies, what they have not created are profits for their investors. Unless life sciences can move beyond this profitless growth stage and serious structural challenges to discovery and innovation can be fixed, the much-anticipated 21st century bio-industrial complex might never blossom into the economic linchpin many hope for.
Scenarios of the future
While trends are valuable for understanding directions of change, the future is messy and will be shaped by trends acting in combination. To understand what the big picture for science parks might look like, the Institute for the Future developed three scenarios in the “Future Knowledge Systems” report that illustrate how these uncertainties might lead to different outcomes.
Scenario 1: Science and Technology Parks 3.0
In 2030, we will still recognize science parks, but rather than simply managing collections of shiny office buildings they will be actively working to cultivate knowledge ecosystems—collections of people, companies, networks, and know-how—by providing gathering spaces for people to collaborate. Their boldest move a decade from now will have been their push into green technologies, going beyond merely carbon-neutral toward carbon-negative. Science parks, in short, will transform themselves into “living labs” for ecological and economic sustainability.
Scenario 2: Rise of Research Clouds
Like the Oort cloud of comets that surrounds the solar system—massive yet invisible, and occasionally firing off a life-laden payload towards the Sun—networks of small collaborative lab spaces will exist around universities, big corporations, and legacy science parks. Tied together by social software, these collaborative labs will become a place where big companies and small startups can co-locate in close proximity despite very different space needs and ability to pay—something the real estate model of science parks could never figure out.
Scenario 3: Dematerialized Innovation
In this scenario, a failure to plan for contingencies such as high energy prices, declining productivity in R&D, or an extended recession will require companies to take a scalpel to R&D once again, dramatically cutting their need for traditional science park space, and pushing what’s left into highly virtual collaboration platforms. Today’s platforms for crowd-sourcing innovation such as Innocentive will become the model for dematerializing the corporate lab. No more science parks get built.
The purpose of these scenarios is not to be a pointed forecast. No one can predict the future. But they can be used as a kind of litmus test or yardstick for economic development strategy and policymaking. What are our goals? What decisions today might create the conditions that push us towards one scenario or another?
In that light, there are several policy implications for the United States, states and regions, and local communities. At the federal level, we need to look at how funding can be directed at the physical infrastructure that supports not just basic research, but also technology transfer. The economic stimulus package, for example, enacted earlier this year contained significant funding for biomedical research facilities—yet existing research centers already have a considerable backlog of discoveries with commercial potential that is not being fully explored.
Accelerators, incubators, and other mechanisms for moving discoveries out of the lab should be supported. Economic developers often misunderstand the relationship between scientists and entrepreneurs. In a few rare cases, one remarkable individual excels both in lab science and business. More often than not, however, researchers prefer to move on to the next intellectual challenge rather than invest the time needed to develop a lab discovery to the proof-of-concept phase and then to a marketable product. Accelerators—organizations that bring together researchers, entrepreneurs, and investors—are increasingly popular in the life sciences, where technology transfer requires much longer periods of time and much larger capital investments.
At the state level, policy needs to shift from solely focusing on universities and individual development projects and develop grand visions at the regional level that can guide and coordinate actions over many years. The success of North Carolina over the past 50 years stemmed from not only its ability to create such a grand vision, but also from the consensus to sustain that vision across multiple generations. It took decades for the Research Triangle to fully reverse the “brain drain” that threatened the state’s future. The trans-generational handoff of stewardship over this grand vision is a tricky but essential act of political leadership.
Finally, at the local level, communities need to spread investments across projects that complement each other and leverage existing industrial and knowledge assets. Instead of copying Silicon Valley, think of ways that imported technologies can be used to re-invent local industries in manufacturing, services, or agriculture.
Anthony Townsend is Research Director in the Technology Horizons Program at the Institute for the Future, a Silicon Valley-based think tank established in 1968. His research and analysis on science, innovation and place can be found at http://www.iftf.org/innovation.
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