Innovation economics is a growing economic theory that emphasizes entrepreneurship and innovation. Innovation economics is based on two fundamental tenets: that the central goal of economic policy should be to spur higher productivity through greater innovation, and that markets relying on input resources and price signals alone will not always be as effective in spurring higher productivity, and thereby economic growth.
Joseph Schumpeter introduced innovation economics in his 1942 book Capitalism, Socialism and Democracy. In contrast to his contemporary John Maynard Keynes, Schumpeter contended that evolving institutions, entrepreneurs, and technological change were at the heart of economic growth, not independent forces that are largely unaffected by policy. He argued that creative destruction is crucial to capitalism.[clarification needed]
But it is only within the last 15 years that a theory and narrative of economic growth focused on innovation that was grounded in Schumpeter’s ideas has emerged. Innovation economics attempted to answer the fundamental problem in the puzzle of total factor productivity growth. Continual growth of output could no longer be explained only in increase of inputs used in the production process as understood in industrialization. Hence, innovation economics focused on a theory of economic creativity that would impact the theory of the firm and organization decision-making. Hovering between heterodox economics that emphasized the fragility of conventional assumptions and orthodox economics that ignored the fragility of such assumptions, innovation economics aims for joint didactics between the two. As such, it enlarges the Schumpeterian analyses of new technological system by incorporating new ideas of information and communication technology in the global economy.
Indeed, a new theory and narrative of economic growth focused on innovation has emerged in the last decade. Innovation economics emerges on the wage of other schools of thoughts in economics, including new institutional economics, new growth theory, endogenous growth theory, evolutionary economics, neo-Schumpeterian economics—provides an economic framework that explains and helps support growth in today’s knowledge economy.
Leading theorists of innovation economics include both formal economists, as well as management theorists, technology policy experts, and others. These include Paul Romer, Elhanan Helpman, W. Brian Arthur, Robert Axtell, Richard R. Nelson, Richard Lipsey, Michael Porter, Christopher Freeman, Igor Yegorov.
Innovation economists believe that what primarily drives economic growth in today’s knowledge-based economy is not capital accumulation, as claimed by neoclassicalism asserts, but innovative capacity spurred by appropriable knowledge and technological externalities. Economics growth in innovation economics is the end-product of knowledge (tacit vs. codified); regimes and policies allowing for entrepreneurship and innovation (i.e., R&D expenditures, permits, licenses); technological spillovers and externalities between collaborative firms; and systems of innovation that create innovative environments (i.e., clusters, agglomerations, metropolitan areas).
In 1970, economist Milton Friedman said in the New York Times that a business’s sole purpose is to generate profits for their shareholders and companies that pursued other missions would be less competitive, resulting in fewer benefits to owners, employees, and society. Yet data over the past several decades shows that while profits matter, good firms supply far more, particularly in bringing innovation to the market. This fosters economic growth, employment gains, and other society-wide benefits. Business school professor David Ahlstrom asserts: “the main goal of business is to develop new and innovative goods and services that generate economic growth while delivering benefits to society.”
In contrast to neoclassical economics, innovation economics offer differing perspectives on main focus, reasons for economic growth, and the assumptions of context between economic actors:
|Neoclassical||Market price signals in using scarce resources||Productive factor accumulation (capital, labor)||Individuals and firms behaving in vacuum|
|Innovation||Innovative capacity to create more effective processes, products, business models||Knowledge/technology (R&D, patents)||Institutions of research, government, society|
Despite the differences in economic thought, both perspectives are based on the same core premise: the foundation of all economic growth is the optimization of the utilization of factors and the measure of success is how well the factor utilization is optimized. Whatever the factors, it nonetheless leads to the same situation of special endowments, varying relative prices, and production processes. So while, the two differ in theoretical concepts, innovation economics can find fertile ground in mainstream economics, rather than remain in diametric contention.
Empirical evidence worldwide points to a positive link between technological innovation and economic performance. The drive of biotech firms in Germany was due to the R&D subsidies to joint projects, network partners, and close cognitive distance of collaborative partners within a cluster. These factors increased patent performance in the biotech industry. Additionally, innovation capacity explains much of the GDP growth in India and China between 1981–2004 but especially in the 1990s. Their development of a National Innovation System through heavy investment of R&D expenditures and personnel, patents, and high-tech/service exports strengthened their innovation capacity. By linking the science sector with the business sector, establishing incentives for innovative activities, and balancing the import of technology and indigenous R&D effort, both countries experienced rapid economic growth in recent decades. Also, the Council of Foreign Relations asserted that since the end of the 1970s, the U.S. has gained a disproportionate share of the world’s wealth through their aggressive pursuit of technological change, demonstrating that technological innovation is a central catalyst of steady economic performance. Concisely, evidence shows that innovation contributes to steady economic growth and rise in per capita income.
However, some empirical studies investigating the innovation-performance-link lead to rather mixed results and indicate that the relationship be more subtle and complex than commonly assumed. In particular, the relationship between innovativeness and performance seems to differ in intensity and significance across empirical contexts, environmental circumstances, and conceptual dimensions.
All of the above has taken place in an era of data constraint, as identified by Zvi Griliches twenty years ago. Because the primary domain of innovation is commerce the key data resides there; continually out of campus reach in reports hidden within factories, corporate offices and technical centers. This recusal still stymies progress today. Recent attempts at data transference have led, not least, to the ‘positive link’ (above) being upgraded to exact algebra between R&D productivity and GDP allowing prediction from one to the other. This is pending further disclosure from commercial sources but several pertinent documents are already available.
While innovation is important, it is not a happenstance occurrence as a natural harbor or natural resources are, but a deliberate, concerted effort of markets, institutions, policymakers, and effect use of geographic space. In global economic restructuring, location has a become key element in establishing competitive advantage as regions focus on their unique assets to spur innovation (i.e., information technology in Silicon Valley, CA; digital media in Seoul, South Korea). Even more, thriving metropolitan economies that carry multiple clusters (i.e., Tokyo, Chicago, London) essentially fuel national economies through their pools of human capital, innovation, quality places, and infrastructure. Cities become “innovative spaces” and “cradles of creativity” as drivers of innovation. They become essential to the system of innovation through the supply side: ready, available, abundant capital and labor; good infrastructure for productive activities, and diversified production structures that spawn synergies and hence innovation. In addition they grow due to the demand side: diverse population of varying occupations, ideas, skills; high and differentiated level of consumer demand; and constant recreation of urban order especially infrastructure of streets, water systems, energy, and transportation.
- semiconductors and information technology in Silicon Valley in California
- high-technology and life sciences in Research Triangle Park in North Carolina
- energy companies in Energy Corridor in Houston, Texas
- financial products and services in New York City
- biotechnology in Genome Valley in Hyderabad, India and Boston, Massachusetts
- nanotechnology in Tech Valley, New York (College of Nanoscale Science and Engineering)
- precision engineering in South Yorkshire, United Kingdom
- petrochemical complexes in Rio de Janeiro, Brazil
- train locomotive and rolling stock manufacturing in Beijing, China
- automotive engineering in Baden-Württemberg, Germany
- digital media technologies in Digital Media City in Seoul, South Korea
- Business cluster
- Economic development
- Keynesian economics
- Knowledge economy
- Innovation saturation
- International Innovation Index
- Metropolitan economy
- Neoclassical economics
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- Innovation Economics: The Economic Doctrine for the 21st Century
- Books and Journal Articles on Innovation Economics
- Innovation Economics: The Integration and Capitalization of Knowledge
- Innovation Economics Roundtable
- Business Week Podcast - Innovation Economics
- Business Models Innovation
- Innovation Economics in practice for city/regional growth and economic development