To better understand how R&D is conducted in today's innovation- and global-based economy and to investigate ways to improve NSF's portfolio of R&D measurements, NSF commissioned a study by the National Research Council's Committee on National Statistics (CNSTAT) in 2004. The committee published its findings in the 2005 report Measuring Research and Development Expenditures in the U.S. Economy (NRC 2005a). The essence of CNSTAT's concerns and recommendations centered on the finding that a new, more comprehensive survey was needed to "keep up with the fast-changing environment for the conduct and organization of research in the private business sector" (NRC 2005a, p 4).
In early 2009, NSF and the U.S. Census Bureau launched a new Business R&D and Innovation Survey (BRDIS). The survey covers manufacturing and service companies and includes questions on a broad range of R&D topics (listed below). The survey also begins to collect innovation data, with the ultimate objective of increasing the number and breadth of innovation-related items in the future.
For more information on the new survey, see NSF/SRS (2008b).
R&D. According to international guidelines for conducting R&D surveys, R&D, also called research and experimental development, comprises creative work "undertaken on a systematic basis to increase the stock of knowledge—including knowledge of man, culture, and society—and the use of this stock of knowledge to devise new applications" (OECD 2002).
Basic research. The objective of basic research is to gain more comprehensive knowledge or understanding of the subject under study without specific applications in mind. Although basic research may not have specific applications as its goal, it can be directed to fields of current or potential interest. This focus is often the case when performed by industry or mission-driven federal agencies.
Applied research. The objective of applied research is to gain knowledge or understanding to meet a specific, recognized need. In industry, applied research includes investigations to discover new scientific knowledge that has specific commercial objectives with respect to products, processes, or services.
Development. Development is the systematic use of the knowledge or understanding gained from research directed toward the production of useful materials, devices, systems, or methods, including the design and development of prototypes and processes.
R&D plant. This term refers to the acquisition of, construction of, major repairs to, or alterations in structures, works, equipment, facilities, or land for use in R&D activities.
Budget authority. Budget authority is the authority provided by federal law to incur financial obligations that will result in outlays. The basic forms of budget authority are appropriations, contract authority, and borrowing authority.
Obligations. Federal obligations represent the dollar amounts for orders placed, contracts and grants awarded, services received, and similar transactions during a given period, regardless of when funds were appropriated or payment was required.
Outlays. Federal outlays represent the dollar amounts for checks issued and cash payments made during a given period, regardless of when funds were appropriated or obligated.
For an annotated compilation of definitions of R&D by U.S. statistical agencies, tax statutes, accounting bodies, and other official sources, see NSF/SRS (2006).
The estimates of U.S. R&D presented in this volume are derived from surveys of organizations that have historically performed the vast majority of R&D in the United States. To evaluate U.S. R&D performance over time and in comparison with other countries, however, it is necessary to gauge how much R&D goes unmeasured. The following paragraphs describe types of unmeasured R&D performance in the United States.
To reduce cost and respondent burden, U.S. industrial R&D estimates are derived from a survey of R&D-performing companies with five or more employees. Accordingly, no estimates of R&D performance are available for companies with fewer than five employees.
The activity of individuals performing R&D on their own time and not under the auspices of a corporation, university, or other organization is similarly omitted from official U.S. R&D statistics.
Social science R&D has been excluded from U.S. industrial R&D statistics. Also, R&D in the humanities is excluded from U.S. academic R&D statistics. Other countries include both in their national statistics, making their national R&D expenditures relatively larger when compared with those of the United States. (The new U.S. Business R&D and Innovation Survey, being fielded for the first time in 2009, includes social science R&D and will better capture total federally funded R&D performed by others. Furthermore, NSF is in the process of redesigning its Higher Education R&D Survey, which will include non-S&E R&D expenditures in its reported totals.)
NSF has not conducted a survey on R&D performance by nonprofit organizations since 1998, although the R&D performance of nonprofits is estimated for national R&D totals. NSF and the U.S. Census Bureau collected statistics for R&D performance by state governments in the United States for 2006 and 2007, but these data have not yet been included in the national time series. Data for these performers are discussed in "Location of R&D Performance."
Measuring R&D as capital investment rather than an expense (that is, capitalizing R&D) recognizes that R&D has long-term benefits, much as do investments in physical assets. Capitalized R&D has a direct impact on GDP because business R&D becomes part of economic output instead of an expense. International activities are underway to update systems of national accounts to recognize the investment nature of R&D (UNSC 2007). A first step in the statistical systems of the United States and other OECD countries is to develop R&D satellite accounts, that is, supplementary estimates of the GDP and related measures that provide greater detail or alternative measurement concepts without changing the core accounts. Future research topics include improving the price indexes used to produce inflation-adjusted R&D investment figures and measures of the depreciation of R&D as a capital asset.
Several U.S. interagency efforts are aimed at identifying improved measures of intangibles, such as R&D, and their economic role (Aizcorbe, Moylan, and Robbins 2009; Jorgenson, Landefeld, and Nordhaus 2006). NSF's Division of Science Resources Statistics, responsible for U.S. R&D statistics, and the Bureau of Economic Analysis (BEA), responsible for the U.S. national economic accounts, are jointly developing an R&D Satellite Account (Robbins and Moylan 2007). Current plans call for incorporation of R&D capital into the National Income and Product Accounts and other core accounts in 2013.
According to BEA preliminary estimates, capitalizing R&D increased the level of current-dollar GDP by an average of 2.9% per year between 1959 and 2006. Adjusted for inflation, R&D capital would account for about 5.1% of real GDP growth between 1959 and 2006. This figure compares with a 2.2% share for all business investment in commercial and all other types of buildings. During the more recent 1995–2006 period, R&D investment accounted for about 7% of real GDP growth, with the business sector's R&D contribution amounting to 4.6% percent.
From 1995–2006, the largest estimated contributions to real GDP growth came from the pharmaceutical and medicine manufacturing industry, which accounted for more than 1% of GDP growth. The software publishing industry accounted for an additional 0.5%.
For more than 20 years, the Industrial Research Institute (IRI), a nonprofit association of more than 200 leading, R&D-performing, manufacturing and service companies, has surveyed its U.S.-based members on their intentions for the coming year with respect to R&D expenditures, focus of R&D, R&D personnel, and other items. Because IRI member companies carry out a large amount of industrial R&D in the United States, the results of these surveys help identify broad trends in corporate R&D strategies.
The most recent survey, administered during the summer of 2008, suggests that many companies continue to shift the focus of their R&D spending away from directed basic research and the support of existing business to new business projects (IRI 2009). As reflected in IRI's Sea Change Index,* IRI survey respondents also reported the following plans and expectations for 2009:
Overall, these strategic moves are consistent with companies' expectations of flat R&D budgets.
*IRI states that its Sea Change Index likely "understates the absolute value of change," but the association believes it to be a "good indicator of the direction of change." See IRI (2009) for details.
International public investment in energy research, development, demonstration, and deployment (hereafter RD&D) has grown by about 30% over the 1997–2007 period, from $8.6 billion to $11.3 billion in inflation-adjusted dollars (figure
The U.S. and Japanese governments reported by far the largest energy RD&D government funds, fluctuating around 30% of the reported IEA total for the United States and declining from 38% to 30% for Japan. France, Germany, and the United Kingdom, which are very broadly similar in overall RD&D spending, committed very different public investments to energy RD&D, with France's funding being much larger than expected relative to the other two countries. South Korea invested more than the combined total of the United Kingdom and Germany.
The biggest energy type is nuclear fission and
RD&D in hydrogen and fuel cell energy is of most recent vintage. It represented about 7% of the IEA 2007 total; Canada stood out with 16% of its energy RD&D funds in hydrogen and fuel cell technology. RD&D in renewable energy has slowly risen to about 12% of the total, from 8% a decade ago; the United Kingdom led in renewable energy, with an increase from 9% to 36%; Sweden's level was high at 33%, as was Germany's at 22%.
The quest for energy efficiency received a fairly steady 13% of total energy RD&D budgets, although the budget share was less in Germany, France, and the United Kingdom. All other technologies combined averaged about 20% but garnered twice that level in the United States and much less than the IEA average in Japan and France.
In some OECD countries, including the United States, figures for total government R&D support reported by government agencies differ from those reported by performers of R&D work. In keeping with international guidance and standards, most countries' national R&D expenditure totals and time series are based primarily on data reported by performers (OECD 2002). Differences may be expected between funder and performer series for many reasons, such as different bases used for reporting government obligations (fiscal year) and performance expenditures (calendar year). Nonetheless, the gap between the two U.S. R&D series has widened over the past decade or more.
During the mid-1980s, performer-reported federal
R&D in the United States exceeded federal reports of
funding by $3 to $4 billion annually (5% to 10% of the
government total). This pattern reversed itself toward
the end of the decade; in 1989, the government-reported
R&D total exceeded performer reports by $1 billion. For
FY 2007, federal agencies reported obligating $114 billion
in total R&D to all R&D performers ($44 billion to
the business sector), compared with $101 billion in federal
funding reported by the performers of R&D ($27 billion
by businesses). In other words, the business-reported total
was approximately 40% smaller than the federally reported
R&D support to industry in FY 2007 (figure
Several investigations into the possible causes for the data gap have produced insights but no conclusive explanation. According to a General Accounting Office investigation (GAO 2001):
Because the gap is the result of comparing two dissimilar types of financial data [federal obligations and performer expenditures], it does not necessarily reflect poor quality data, nor does it reflect whether performers are receiving or spending all the federal R&D funds obligated to them. Thus, even if the data collection and reporting issues were addressed, a gap would still exist.
Echoing this assessment, the National Research Council (2005a) noted that comparing federal outlays for R&D (as opposed to obligations) to performer expenditures results in a smaller discrepancy. In FY 2007, federal agencies reported total R&D outlays of $109 billion.
Comparisons of international R&D statistics are hampered by the lack of R&D-specific exchange rates. If countries do not share a common currency, some conversion must be made to compare their R&D expenditures. Two approaches are commonly used to facilitate international R&D comparisons: (1) normalize national R&D expenditures by dividing by GDP, thereby obviating the need for currency conversion altogether or (2) convert all foreign-denominated expenditures to a single currency, resulting in indicators of absolute effort. The first method is a straightforward calculation but permits only gross national comparisons of R&D intensity. The second method permits absolute-level comparisons and analyses of countries' sector- and field-specific R&D, but it entails choosing an appropriate method of currency conversion.
Because no widely accepted R&D-specific exchange rates exist, the choice is between market exchange rates (MERs) and purchasing power parities (PPPs). These rates are the only series consistently compiled and available for a large number of countries over an extended period of time.
MERs. At their best, MERs represent the relative value of currencies for goods and services that are traded across borders. That is, MERs measure a currency's relative international buying power. Nevertheless, MERs may not accurately reflect the true cost of goods or services that are not traded internationally. In addition, fluctuations in MERs as a result of currency speculation, political events (such as wars or boycotts), and official currency intervention greatly impair their statistical utility—despite the fact that such occurrences have little or nothing to do with changes in the relative prices of internationally traded goods.
PPPs. PPPs were developed because of the shortcomings of MERs (Ward 1985). PPPs take into account the cost differences across countries of buying a similar market basket of goods and services in numerous expenditure categories, including nontradables. The PPP basket is thereby assumed to be representative of total GDP across countries.
Although the goods and services included in the market basket used to calculate PPP rates differ from the major components of R&D costs (fixed assets, as well as wages of scientists, engineers, and support personnel), they still result in a more suitable domestic price converter than one based on foreign trade flows. Exchange-rate movements bear little relationship to changes in the cost of domestically performed R&D. The adoption of the euro as the common currency for many European countries provides a useful example: although Germany and Portugal now share a common currency, the real costs of most goods and services are substantially less in Portugal. PPPs are, therefore, the preferred international standard for calculating cross-country R&D comparisons wherever possible and are used in all official R&D tabulations of the OECD.*
Because MERs tend to understate the domestic purchasing
power of developing countries' currencies, PPPs
can produce substantially larger R&D estimates than
MERs for these countries. For example, China's 2006
R&D expenditures (as reported to the OECD) are $38 billion
using MERs but $87 billion using PPPs. (Appendix table
Although PPPs are available for developing countries, such as India and China, they may be less useful for converting R&D expenditures in such countries than in more developed countries for a number of reasons:
*Recent research raises some questions about the use of GDP PPPs for deflating R&D expenditures. In analyzing the manufacturing R&D inputs and outputs of six industrialized OECD countries, Dougherty et al. (2007) conclude that "the use of an R&D PPP will yield comparative costs and R&D intensities that vary substantially from the current practice of using GDP PPPs, likely increasing the real R&D performance of the comparison countries relative to the United States."
Most firms that make significant investments in R&D
track their R&D expenses separately in their accounting
records and financial statements. The annual reports of
public corporations often include data on these R&D expenses.
According to information gleaned from public reports,
the 25 public corporations with the largest reported
worldwide R&D expenses spent $143 billion on R&D
in 2006. The six companies with the largest reported
R&D expenses—Toyota, Pfizer, Ford Motor Company,
Johnson & Johnson, Microsoft, and DaimlerChrysler—each spent between $7 billion and $7.5 billion. The six
automobile manufacturers on the list reported combined
spending of $39 billion on R&D (27.3% of the total for
the top 25) (table
Overall, R&D spending for the top 25 public corporations increased 5.8% in 2006. (The top 25 list was the same for 2006 as it was for 2005 except for the addition of Cisco Systems, Inc., and the deletion of Nissan Motor Company.) Sales for the group as a whole increased 6.5%; sales increased 5.2% for the automobile and pharmaceutical manufacturers, 8.9% for the ICT companies in the group, and 5.4% for the consumer product manufacturers. R&D expenses increased for the manufacturers (pharmaceuticals, 8.5%; automobiles, 0.9%; and consumer products, 11.4%). The ICT companies, representing the sector that has historically had the highest R&D intensity, reported a 6.6% increase.
U.S. universities generally do not maintain data on departmental research (i.e., research which is not separately budgeted and accounted). As such, U.S. R&D totals are understated relative to the R&D effort reported for other countries. The national totals for Europe, Canada, and Japan include the research component of general university fund (GUF) block grants provided by all levels of government to the academic sector. These funds can support departmental R&D programs that are not separately budgeted. GUF is not equivalent to basic research. The U.S. federal government does not provide research support through a GUF equivalent, preferring instead to support specific, separately budgeted R&D projects, usually to address the objectives of the federal agencies that provide the R&D funds. However, some state government funding probably does support departmental research at U.S. public universities.
The treatment of GUF is one of the major areas of difficulty in making international R&D comparisons. In many countries, governments support academic research primarily through large block grants that are used at the discretion of each higher education institution to cover administrative, teaching, and research costs. Only the R&D component of GUF is included in national R&D statistics, but problems arise in identifying the amount of the R&D component and the objective of the research. Moreover, government GUF support is in addition to support provided in the form of earmarked, directed, or project-specific grants and contracts (funds that can be assigned to specific socioeconomic categories).
In the United States, the federal government is much more directly involved in choosing which academic research projects are supported than are national governments in Europe and elsewhere—although this is not necessarily the case with state governments. In several European G-7 countries (France, Germany, Italy, and the United Kingdom), GUF accounts for 50% or more of total government R&D funding to universities. In Canada, GUF accounts for about 38% of government academic R&D support. These data reflect not only the relative international funding priorities but also the funding mechanisms and philosophies regarded as the best methods for financing academic research.
Direct investment is defined as ownership or control of 10% or more of the voting securities of a business (affiliate) in another country. As with other overseas activity, the geographic distribution of affiliates' R&D varies by investing country and industry (OECD 2007). FDI in R&D is driven by factors ranging from costs and long-term market and technological opportunities to infrastructure and policy considerations, such as availability of appropriately trained human resources and intellectual property protection (Niosi 1999; Thursby and Thursby 2006; von Zedtwitz and Gassmann 2002).
Statistics on R&D by affiliates of foreign companies located in the United States, and by foreign affiliates of U.S. MNCs and their parent companies, can be obtained from BEA's Survey of Foreign Direct Investment in the United States (FDIUS) and BEA's Survey of U.S. Direct Investment Abroad (USDIA). BEA data used in this section cover nonbank companies.* Affiliate data cover majority-owned affiliates, that is, those in which the ownership stake of parent companies totals more than 50%. Annual changes in FDI R&D reflect a combination of mergers and acquisitions; newly built factories, service centers, or laboratories; and activities in existing facilities. Available data do not, however, allow for distinguishing among these alternative investments.â€
*Nonbank data exclude activities by companies classified in depository credit intermediation, which comprises commercial banks, savings institutions, credit unions, bank holding companies, and financial holding companies.
â€ For detailed methodology, see http://www.bea.gov/international/usdia2004f.html (USDIA) and http://www.bea.gov/scb/pdf/internat/fdinvest/meth/FDIUS2002Benchmark.pdf (FDIUS).
An ongoing data development project aims to integrate the statistical information from BEA's international investment surveys with the NSF/Census Survey of Industrial Research and Development. Combining technological and investment data from these complementary sources will facilitate a better assessment of globalization trends in R&D and technological innovation. The initial methodological study demonstrated the feasibility and utility of such a linkage.
A combined preliminary data set provided information for the first time on R&D expenditures by U.S. and foreign MNCs by character of work (basic research, applied research, and development). The study has also produced tangible benefits for the participating agencies, including improvements in survey sampling and the quality of reported data. These promising initial results have prompted the three participating agencies to continue work in this area. For more information, see NSF/SRS (2007b) and Census Bureau et al. (2005).
Interest in R&D and innovation-related metrics by governments, academic researchers, and businesses has a long history (Earl and Gault 2006) but has intensified in recent years in the United States (DOC 2008; Mandel 2008; McKinsey & Company 2008; Moris, Jankowski, and Perolle 2008; NRC 2005a; NSF/TCB 2008) and elsewhere (Gault and von Hippel 2009; OECD 2008c). Recent developments in innovation-related metrics are driven by a number of factors, including:
Innovation is defined as the introduction of new or significantly improved products (goods or services), processes, organizational methods, and marketing methods in internal business practices or the marketplace (OECD/Eurostat 2005, p 146). R&D is only one of many possible knowledge inputs driving innovation. For example, innovation may result from the integration of existing technology or from a new business model. Enhanced international guidance and ongoing methodological studies to better capture statistics on nontechnological innovation, innovation linkages, and service-sector activities are driving development of metrics across OECD countries.
Part of the challenge in developing new metrics resides in the broad scope of innovation activities covering inputs, processes, cross-sector linkages, immediate outputs (for example, products or patents), long-term socioeconomic impacts, and infrastructure or system-wide variables (such as policy incentives or technology standards). Accordingly, data development spans multiple strategies, including surveys and data linking and integration, as well as non-survey-based methods, such as case studies, administrative databases, and Web-based information—pursued in parallel or in combination (NSF/SRS 2007a; NSF/TCB 2008). The following describes selected activities in the development of these indicators.
Intangible Investment and GDP
Treating spending on intangibles, such as software and R&D, as investment in the national income and product accounts (NIPA) (which include GDP and other U.S. economic accounts) recognizes intangible capital, along with other forms of investment inputs, in the production of economic output (Corrado, Hulten, and Sichel 2006; UNSC 2007). International statistical manuals are being updated or developed to provide guidance for comparable measures in this area, including an updated manual for the United Nations System of National Accounts (SNA) and a new OECD handbook covering intangibles and national accounts (Aspden 2008). Software has been considered an investment in U.S. NIPA since 1999, and BEA and NSF continue to work on an R&D satellite account, as described earlier in this chapter. BEA plans to incorporate both R&D and spending on artistic and literary originals as intangible investment in the core economic accounts in 2013 and is considering an expanded satellite account that would contain experimental statistics for other intangibles (Aizcorbe, Moylan, and Robbins 2009).
Science of Science and Innovation Policy
Program, Research Data Infrastructure, and
Advanced Computing Tools
The NSF Science of Science and Innovation Policy (SciSIP) program supports research designed to advance the scientific basis of science and innovation policy. Research funded by the program is aimed at developing, improving, and expanding models, analytical tools, data, and metrics. An area of interest is the development of data infrastructure to support empirical research on innovations within organizations (NSF/TCB 2008). Other efforts focus on cyber-infrastructure research; advanced computing and Web-based tools to protect, archive, link, mine, and analyze data (Lane, Heus, and Mulcahy 2008); and advanced visualization and analytical tools for document-based information, such as patents and bibliographic entries (Börner, Chen, and Boyack 2003).
Entrepreneurship and Business Dynamics
Two National Research Council (NRC) reports cite the need to leverage business data collected by statistical agencies for research and policymaking purposes by more effectively integrating data sets (NRC 2006, 2007b). Data sets for the study of business dynamics include the Census Bureau's Business Dynamics Statistics (BDS) (Census Bureau 2009) and Longitudinal Employer-Household Dynamics (LEHD) program (Abowd, Haltiwanger, and Lane 2004), along with the Business Employment Dynamics published by the Bureau of Labor Statistics (BLS 2009). Research topics of interest include technology adoption, innovation, outsourcing, globalization, market entry and exit by companies, and new or small technology-based firms. Indeed, entrepreneurship has been extensively researched as a vehicle for transferring and exploiting new knowledge from public or private sources (Audretsch 2009). In the United States, the Kauffman Foundation funds research in entrepreneurship and innovation (Kauffman 2008) and sponsors a social longitudinal survey on young firms (Kauffman 2009).
OECD Innovation Microdata Project and EU
Community Innovation Surveys
The OECD innovation microdata project aims at exploiting microdata from the EU Community Innovation Surveys (CIS) for economic analysis. In recent years, research teams from different OECD countries have collaborated in applying similar methodologies to their national CIS. Expected products include analytical studies and new innovation indicators covering, for example, international technology transfer, nontechnological innovation, and intellectual property rights (OECD 2009a).
The project is part of a larger OECD Innovation Strategy initiative established in 2007; the objective is to explore strategies to harness the potential of innovation based on a better understanding of innovation. Research is focusing on markets and governance, human capital, global dimensions, and the changing nature of innovation, along with measurement, reporting, and assessment of innovation (OECD 2009b)
Technology Innovation Act of 1980 (Stevenson-Wydler Act) (Public Law 96-480)—established technology transfer as a federal government mission by directing federal labs to facilitate the transfer of federally-owned and originated technology to nonfederal parties.
University and Small Business Patent Procedures Act of 1980 (Bayh-Dole Act) (Public Law 96-517)—permitted small businesses, universities, and nonprofits to obtain titles to inventions developed with federal funds. Also permitted government-owned and government-operated laboratories to grant exclusive patent rights to commercial organizations.
Small Business Innovation Development Act of 1982 (Public Law 97-219)—established the Small Business Innovation Research (SBIR) program, which required federal agencies to set aside funds for small businesses to engage in R&D connected to agency missions.
National Cooperative Research Act of 1984 (Public Law 98-462)—encouraged U.S. firms to collaborate in generic precompetitive research by establishing a rule of reason for evaluating the antitrust implications of research joint ventures.
Patent and Trademark Clarification Act of 1984 (Public Law 98-620)—provided further amendments to the Stevenson-Wydler Act and the Bayh-Dole Act regarding the use of patents and licenses to implement technology transfer.
Federal Technology Transfer Act of 1986 (Public Law 99-502)—enabled federal laboratories to enter cooperative research and development agreements (CRADAs) with outside parties and to negotiate licenses for patented inventions made at the laboratory.
Omnibus Trade and Competitiveness Act of 1988 (Public Law 100-418)—in addition to measures on trade and intellectual property protection, the act directed attention to public-private cooperation on R&D, technology transfer, and commercialization. It also established NIST's Manufacturing Extension Partnership (MEP) program.
National Competitiveness Technology Transfer Act of 1989 (Public Law 101-189)—amended the Federal Technology Transfer Act to expand the use of CRADAs to include government-owned, contractor-operated federal laboratories and to increase nondisclosure provisions.
National Cooperative Research and Production Act of 1993 (Public Law 103-42)—relaxed restrictions on cooperative production activities, which enable research joint venture participants to work together in the application of technologies they jointly acquire.
National Technology Transfer and Advancement Act of 1995 (Public Law 104-113)—amended the Stevenson-Wydler Act to make CRADAs more attractive to federal laboratories, scientists, and private industry.
Technology Transfer Commercialization Act of 2000 (Public Law 106-404)—broadened CRADA licensing authority to make such agreements more attractive to private industry and increase the transfer of federal technology. Established procedures for performance reporting and monitoring by federal agencies on technology transfer activities.
America COMPETES Act of 2007 (America Creating Opportunities to Meaningfully Promote Excellence in Technology, Education, and Sciences [COMPETES] Act) (Public Law 110-69)—increased investment in R&D; strengthened educational opportunities in science, technology, engineering, and mathematics from elementary through graduate school; and further developed the nation's innovation infrastructure. Among other measures, the act established NIST's Technology Innovation Program (TIP) and called for a President's Council on Innovation and Competitiveness.
Federal technology transfer can take a variety of forms (FLC 2006), including the following:
Most federal labs engage in all of these forms of technology transfer to some extent. The emphases and relative levels of each vary widely across the federal agencies, depending on the parent agency's mission, the lab's main areas of scientific and technological interest, typical clients, prevailing scientific/technical culture, and any special transfer authorities the agency may have been granted. For some agencies and their labs, the principal technology transfer thrust is patents, patent licenses, and material transfer agreements. Others emphasize traditional public dissemination of new scientific or technical knowledge and cooperative R&D relationships with outside organizations—with patenting and licensing activity taking place only when it is determined that private-sector investment in a new technology is needed to achieve development and commercialization goals.
Several metrics illustrate activities and agency priorities among three main classes of mechanisms. The invention disclosure and patenting category involves counts of invention disclosures filed (typically, an inventing scientist or engineer filing a written notice of the invention with the lab's technology transfer office), patent applications filed with the U.S. Patent and Trademark Office (or abroad), and patent awards received. The licensing category covers federal lab licensing of federal intellectual property, such as patents or copyrights, to outside parties to enable further development and commercialization, usually through the technology transfer office. For example, in recent years, DOE's government-owned, contractor-operated laboratories have increasingly used their special authority to transfer software technology through relatively quickly executed copyright license mechanisms. The third main category is collaborative relationships for R&D, including CRADAs.