Innovation is a new idea, more effective device or process. Innovation can be viewed as the application of better solutions that meet new requirements, unarticulated needs, or existing market needs. This is accomplished through more effective products, processes, services, technologies, or ideas that are readily available to markets, governments and society. The term innovation can be defined as something original and more effective and, as a consequence, new, that "breaks into" the market or society.
While a novel device is often described as an innovation, in economics, management science, and other fields of practice and analysis, innovation is generally considered to be a process that brings together various novel ideas in a way that they have an impact on society.
- 1 Inter-disciplinary views
- 2 Diffusion of innovation=
- 3 Measures
- 4 Rate of innovation
- 5 Government policies
- 6 See also
- 7 References
Business and economics
In business and economics, innovation is the catalyst to growth. With rapid advancements in transportation and communications over the past few decades, the old world concepts of factor endowments and comparative advantage which focused on an area’s unique inputs are outmoded for today’s global economy. Economist Joseph Schumpeter, who contributed greatly to the study of innovation economics, argued that industries must incessantly revolutionize the economic structure from within, that is innovate with better or more effective processes and products, as well as market distribution, such as the connection from the craft shop to factory. He famously asserted that “creative destruction is the essential fact about capitalism”. In addition, entrepreneurs continuously look for better ways to satisfy their consumer base with improved quality, durability, service, and price which come to fruition in innovation with advanced technologies and organizational strategies.
One prime example is the explosive boom of Silicon Valley startups out of the Stanford Industrial Park. In 1957, dissatisfied employees of Shockley Semiconductor, the company of Nobel laureate and co-inventor of the transistor William Shockley, left to form an independent firm, Fairchild Semiconductor. After several years, Fairchild developed into a formidable presence in the sector. Eventually, these founders left to start their own companies based on their own, unique, latest ideas, and then leading employees started their own firms. Over the next 20 years, this snowball process launched the momentous startup company explosion of information technology firms. Essentially, Silicon Valley began as 65 new enterprises born out of Shockley’s eight former employees.
In the organizational context, innovation may be linked to positive changes in efficiency, productivity, quality, competitiveness, and market share. However, recent research findings highlight the complementary role of organizational culture in enabling organizations to translate innovative activity into tangible performance improvements. Organizations can also improve profits and performance by providing work groups opportunities and resources to innovate, in addition to employee's core job tasks. Peter Drucker wrote that "Innovation is the specific function of entrepreneurship, whether in an existing business, a public service institution, or a new venture started by a lone individual in the family kitchen. It is the means by which the entrepreneur either creates new wealth-producing resources or endows existing resources with enhanced potential for creating wealth."
According to Clayton Christensen "Disruptive Innovation" is the key to future success in business. The organisation requires a proper structure in order to retain competitive advantage. It is necessary to create and nurture an environment of innovation. Executives and managers need to break away from traditional ways of thinking and use change to their advantage. It is a time of risk but even greater opportunity. The world of work is changing with the increase in the use of technology and both companies and businesses are becoming increasingly competitive. Companies will have to downsize and re-engineer their operations to remain competitive. This will impact on employment as businesses will be forced to reduce the number of people employed while accomplishing the same amount of work if not more.
All organizations can innovate, including for example hospitals, universities, and local governments. For instance, former Mayor Martin O’Malley pushed the City of Baltimore to use CitiStat, a performance-measurement data and management system that allows city officials to maintain statistics on crime trends to condition of potholes. This system aids in better evaluation of policies and procedures with accountability and efficiency in terms of time and money. In its first year, CitiStat saved the city $13.2 million. Even mass transit systems have innovated with hybrid bus fleets to real-time tracking at bus stands. In addition, the growing use of mobile data terminals in vehicles that serves as communication hubs between vehicles and control center automatically send data on location, passenger counts, engine performance, mileage and other information. This tool helps to deliver and manage transportation systems.
Still other innovative strategies include hospitals digitizing medical information in electronic medical records. For example, the U.S. Department of Housing and Urban Development's HOPE VI initiatives turned severely distressed public housing in urban areas into revitalized, mixed-income environments; the Harlem Children’s Zone used a community-based approach to educate local area children; and the Environmental Protection Agency's brownfield grants facilitates turning over brownfields for environmental protection, green spaces, community and commercial development.
Sources of innovation
There are several sources of innovation. It can occur as a result of a focus effort by a range of different agents, by chance, or as a result of a major system failure.
According to Peter F. Drucker the general sources of innovations are different changes in industry structure, in market structure, in local and global demographics, in human perception, mood and meaning, in the amount of already available scientific knowledge, etc.
In the simplest linear model of innovation the traditionally recognized source is manufacturer innovation. This is where an agent (person or business) innovates in order to sell the innovation.
Another source of innovation, only now becoming widely recognized, is end-user innovation. This is where an agent (person or company) develops an innovation for their own (personal or in-house) use because existing products do not meet their needs. MIT economist Eric von Hippel has identified end-user innovation as, by far, the most important and critical in his classic book on the subject, The Sources of Innovation.
The robotics engineer Joseph F. Engelberger asserts that innovations require only three things:
- A recognized need,
- Competent people with relevant technology, and
- Financial support.
However, innovation processes usually involve: identifying customer needs, macro and meso trends, developing competences, and finding financial support.
The Kline chain-linked model of innovation places emphasis on potential market needs as drivers of the innovation process, and describes the complex and often iterative feedback loops between marketing, design, manufacturing, and R&D.
Innovation by businesses is achieved in many ways, with much attention now given to formal research and development (R&D) for "breakthrough innovations". R&D help spur on patents and other scientific innovations that leads to productive growth in such areas as industry, medicine, engineering, and government. Yet, innovations can be developed by less formal on-the-job modifications of practice, through exchange and combination of professional experience and by many other routes. The more radical and revolutionary innovations tend to emerge from R&D, while more incremental innovations may emerge from practice – but there are many exceptions to each of these trends.
Information technology and changing business processes and management style can produce a work climate favorable to innovation. For example, the software tool company Atlassian conducts quarterly "ShipIt Days" in which employees may work on anything related to the company's products. Google employees work on their own projects for 20% of their time (known as Innovation Time Off). Both companies cite these bottom-up processes as major sources for new products and features.
An important innovation factor includes customers buying products or using services. As a result, firms may incorporate users in focus groups (user centred approach), work closely with so called lead users (lead user approach) or users might adapt their products themselves. The lead user method focuses on idea generation based on leading users to develop breakthrough innovations. U-STIR, a project to innovate Europe’s surface transportation system, employs such workshops. Regarding this user innovation, a great deal of innovation is done by those actually implementing and using technologies and products as part of their normal activities. In most of the times user innovators have some personal record motivating them. Sometimes user-innovators may become entrepreneurs, selling their product, they may choose to trade their innovation in exchange for other innovations, or they may be adopted by their suppliers. Nowadays, they may also choose to freely reveal their innovations, using methods like open source. In such networks of innovation the users or communities of users can further develop technologies and reinvent their social meaning.
Programs of organizational innovation are typically tightly linked to organizational goals and objectives, to the business plan, and to market competitive positioning. One driver for innovation programs in corporations is to achieve growth objectives. As Davila et al. (2006) notes, "Companies cannot grow through cost reduction and reengineering alone... Innovation is the key element in providing aggressive top-line growth, and for increasing bottom-line results".
One survey across a large number of manufacturing and services organizations found, ranked in decreasing order of popularity, that systematic programs of organizational innovation are most frequently driven by: Improved quality, Creation of new markets, Extension of the product range, Reduced labor costs, Improved production processes, Reduced materials, Reduced environmental damage, Replacement of products/services, Reduced energy consumption, Conformance to regulations.
These goals vary between improvements to products, processes and services and dispel a popular myth that innovation deals mainly with new product development. Most of the goals could apply to any organisation be it a manufacturing facility, marketing firm, hospital or local government. Whether innovation goals are successfully achieved or otherwise depends greatly on the environment prevailing in the firm.
Conversely, failure can develop in programs of innovations. The causes of failure have been widely researched and can vary considerably. Some causes will be external to the organization and outside its influence of control. Others will be internal and ultimately within the control of the organization. Internal causes of failure can be divided into causes associated with the cultural infrastructure and causes associated with the innovation process itself. Common causes of failure within the innovation process in most organizations can be distilled into five types: Poor goal definition, Poor alignment of actions to goals, Poor participation in teams, Poor monitoring of results, Poor communication and access to information.
Diffusion of innovation=
Diffusion of innovation research was first started in 1903 by seminal researcher Gabriel Tarde, who first plotted the S-shaped diffusion curve. Tarde (1903) defined the innovation-decision process as a series of steps that includes:
- First knowledge
- Forming an attitude
- A decision to adopt or reject
- Implementation and use
- Confirmation of the decision
Once innovation occurs, innovations may be spread from the innovator to other individuals and groups. This process has been proposed that the life cycle of innovations can be described using the 's-curve' or diffusion curve. The s-curve maps growth of revenue or productivity against time. In the early stage of a particular innovation, growth is relatively slow as the new product establishes itself. At some point customers begin to demand and the product growth increases more rapidly. New incremental innovations or changes to the product allow growth to continue. Towards the end of its lifecycle, growth slows and may even begin to decline. In the later stages, no amount of new investment in that product will yield a normal rate of return
The s-curve derives from an assumption that new products are likely to have "product life"—i.e., a start-up phase, a rapid increase in revenue and eventual decline. In fact the great majority of innovations never get off the bottom of the curve, and never produce normal returns.
Innovative companies will typically be working on new innovations that will eventually replace older ones. Successive s-curves will come along to replace older ones and continue to drive growth upwards. In the figure above the first curve shows a current technology. The second shows an emerging technology that currently yields lower growth but will eventually overtake current technology and lead to even greater levels of growth. The length of life will depend on many factors.
There are two different types of measures for innovation: the organizational level and the political level.
The measure of innovation at the organizational level relates to individuals, team-level assessments, and private companies from the smallest to the largest company. Measure of innovation for organizations can be conducted by surveys, workshops, consultants, or internal benchmarking. There is today no established general way to measure organizational innovation. Corporate measurements are generally structured around balanced scorecards which cover several aspects of innovation such as business measures related to finances, innovation process efficiency, employees' contribution and motivation, as well benefits for customers. Measured values will vary widely between businesses, covering for example new product revenue, spending in R&D, time to market, customer and employee perception & satisfaction, number of patents, additional sales resulting from past innovations.
For the political level, measures of innovation are more focused on a country or region competitive advantage through innovation. In this context, organizational capabilities can be evaluated through various evaluation frameworks, such as those of the European Foundation for Quality Management. The OECD Oslo Manual (1995) suggests standard guidelines on measuring technological product and process innovation. Some people consider the Oslo Manual complementary to the Frascati Manual from 1963. The new Oslo manual from 2005 takes a wider perspective to innovation, and includes marketing and organizational innovation. These standards are used for example in the European Community Innovation Surveys.
Other ways of measuring innovation have traditionally been expenditure, for example, investment in R&D (Research and Development) as percentage of GNP (Gross National Product). Whether this is a good measurement of innovation has been widely discussed and the Oslo Manual has incorporated some of the critique against earlier methods of measuring. The traditional methods of measuring still inform many policy decisions. The EU Lisbon Strategy has set as a goal that their average expenditure on R&D should be 3% of GDP.
Many scholars claim that there is a great bias towards the "science and technology mode" (S&T-mode or STI-mode), while the "learning by doing, using and interacting mode" (DUI-mode) is widely ignored. For an example, that means you can have the better high tech or software, but there are also crucial learning tasks important for innovation. But these measurements and research are rarely done.
A common industry view (unsupported by empirical evidence) is that comparative cost-effectiveness research (CER) is a form of price control which, by reducing returns to industry, limits R&D expenditure, stifles future innovation and compromises new products access to markets. Some academics claim the CER is a valuable value-based measure of innovation which accords truly significant advances in therapy (those that provide "health gain") higher prices than free market mechanisms. Such value-based pricing has been viewed as a means of indicating to industry the type of innovation that should be rewarded from the public purse. The Australian academic Thomas Alured Faunce has developed the case that national comparative cost-effectiveness assessment systems should be viewed as measuring "health innovation" as an evidence-based concept distinct from valuing innovation through the operation of competitive markets (a method which requires strong anti-trust laws to be effective) on the basis that both methods of assessing innovation in pharmaceuticals are mentioned in annex 2C.1 of the AUSFTA.
Rate of innovation
Several indexes exist that attempt to measure innovation include:
- The Innovation Index, developed by the Indiana Business Research Center, to measure innovation capacity at the county or regional level in the United States.
- The State Technology and Science Index, developed by the Milken Institute is a U.S.-wide benchmark to measure the science and technology capabilities that furnish high paying jobs based around key components.
- The Oslo Manual is focused on North America, Europe, and other rich economies.
- The Bogota Manual, similar to the above, focuses on Latin America and the Caribbean countries.
- The Creative Class developed by Richard Florida
- The Innovation Capacity Index (ICI) published by a large number of international professors working in a collaborative fashion. The top scorers of ICI 2009–2010 being: 1. Sweden 82.2; 2. Finland 77.8; and 3. United States 77.5.
- The Global Innovation Index is a global index measuring the level of innovation of a country, produced jointly by The Boston Consulting Group (BCG), the National Association of Manufacturers (NAM), and The Manufacturing Institute (MI), the NAM's nonpartisan research affiliate. NAM describes it as the "largest and most comprehensive global index of its kind".
- The INSEAD Global Innovation Index
- The INSEAD Innovation Efficacy Index
- The NYCEDC Innovation Index
The Management Innovation Index - Model for Managing Intangibility of Organizational Creativity: Management Innovation Index A peer reviewed article can be found on the Management Innovation Index in Model for Managing Intangibility of Organizational Creativity: Management Innovation Index
The International Innovation Index is one of many research studies that try to build a ranking of countries related to innovation. Other indexes are the Innovations Indikator, Innovation Union Scoreboard, Global Innovation Index, EIU Innovation Ranking, BCG International Innovation Index, Global Competitiveness Report, World Competitiveness Scoreboard, ITIF Index.
Published in 2015, the most recent and up-to-date research was conducted by Bloomberg in their Bloomberg Innovation Index. The six focused areas making up the index are research and development, manufacturing, high-tech companies, post secondary education and research personnel and patents.
The following is a ranking of the top ten countries in the 2015 Bloomberg Innovation Index:
Future of innovation
Jonathan Huebner, a physicist working at the Pentagon's Naval Air Warfare Center, argued on the basis of both U.S. patents and world technological breakthroughs, per capita, that the rate of human technological innovation peaked in 1873 and has been slowing ever since. In his article, he asked "Will the level of technology reach a maximum and then decline as in the Dark Ages?" In later comments to New Scientist magazine, Huebner clarified that while he believed that we will reach a rate of innovation in 2024 equivalent to that of the Dark Ages, he was not predicting the reoccurrence of the Dark Ages themselves.
His paper received some mainstream news coverage at the time.
The claim has been met with criticism by John Smart, founder of the Acceleration Studies Foundation, who asserted that research by technological singularity researcher Ray Kurzweil and others showed a "clear trend of acceleration, not deceleration" when it came to innovations. The foundation issued a reply to Huebner in the pages of the journal his article was published in, citing the existence of Second Life and eHarmony as proof of accelerating innovation; Huebner also replied to this. However, in 2010, Joseph A. Tainter, Deborah Strumsky, and José Lobo confirmed Huebner's findings using U.S. Patent Office data. Additional verification was provided in a 2012 paper by Robert J. Gordon.
Innovation and international development
The theme of innovation as a tool to disrupting patterns of poverty has gained momentum since the mid-2000s among major international development actors such as DFID, Gates Foundation's use of the Grand Challenge funding model, and USAID's Global Development Lab. Networks have been established to support innovation in development, such as D-Lab at MIT. Investment funds have been established to identify and catalyze innovations in developing countries, such as DFID's Global Innovation Fund, Human Development Innovation Fund, and (in partnership with USAID) the Global Development Innovation Ventures.
Given the noticeable effects on efficiency, quality of life, and productive growth, innovation is a key factor in society and economy. Consequently, policymakers have long worked to develop environments that will foster innovation and its resulting positive benefits, from funding Research and Development to supporting regulatory change, funding the development of innovation clusters, and using public purchasing and standardisation to 'pull' innovation through.
For instance, experts are advocating that the U.S. federal government launch a National Infrastructure Foundation, a nimble, collaborative strategic intervention organization that will house innovations programs from fragmented silos under one entity, inform federal officials on innovation performance metrics, strengthen industry-university partnerships, and support innovation economic development initiatives, especially to strengthen regional clusters. Because clusters are the geographic incubators of innovative products and processes, a cluster development grant program would also be targeted for implementation. By focusing on innovating in such areas as precision manufacturing, information technology, and clean energy, other areas of national concern would be tackled including government debt, carbon footprint, and oil dependence. The U.S. Economic Development Administration understand this reality in their continued Regional Innovation Clusters initiative. In addition, federal grants in R&D, a crucial driver of innovation and productive growth, should be expanded to levels similar to Japan, Finland, South Korea, and Switzerland in order to stay globally competitive. Also, such grants should be better procured to metropolitan areas, the essential engines of the American economy.
Many countries recognize the importance of research and development as well as innovation including Japan's Ministry of Education, Culture, Sports, Science and Technology (MEXT); Germany’s Federal Ministry of Education and Research; and the Ministry of Science and Technology in the People's Republic of China. Furthermore, Russia's innovation programme is the Medvedev modernisation programme which aims at creating a diversified economy based on high technology and innovation. Also, the Government of Western Australia has established a number of innovation incentives for government departments. Landgate was the first Western Australian government agency to establish its Innovation Program. The Cairns Region established the Tropical Innovation Awards in 2010 open to all businesses in Australia. The 2011 Awards were extended to include participants from all Tropical Zone Countries.
- Communities of innovation
- Creative competitive intelligence
- Creative problem solving
- Disruptive innovation
- Theories of technology
- Diffusion (anthropology)
- List of countries by research and development spending
- List of emerging technologies
- List of Russian inventors
- Hype cycle
- Individual capital
- Induced innovation
- Information revolution
- Innovation leadership
- Innovation system
- Global Innovation Index (Boston Consulting Group)
- Global Innovation Index (INSEAD)
- Knowledge economy
- Multiple discovery
- Open Innovation
- Open Innovations (Forum and Technology Show)
- Outcome-Driven Innovation
- Participatory design
- Pro-innovation bias
- Public domain
- Technology Life Cycle
- Technological innovation system
- Timeline of historic inventions
- Toolkits for User Innovation
- Value network
- Maranville, S (1992), Entrepreneurship in the Business Curriculum, Journal of Education for Business, Vol. 68 No. 1, pp.27-31.
- Based on Frankelius, P. (2009), Questioning two myths in innovation literature, Journal of High Technology Management Research, Vol. 20, No. 1, pp. 40–51.
- Schumpeter, J. A. (1943). Capitalism, Socialism, and Democracy (6 ed.). Routledge. pp. 81–84. ISBN 0-415-10762-8.
- Heyne, P., Boettke, P. J., and Prychitko, D. L. (2010). The Economic Way of Thinking. Prentice Hall, 12th ed. Pp. 163, 317–318.
- Gregory Gromov (2011). Silicon Valley History. http://www.netvalley.com/svhistory.html
- Salge, T.O. & Vera, A. 2012, Benefiting from Public Sector Innovation: The Moderating Role of Customer and Learning Orientation, Public Administration Review, Vol. 72, Issue 4, pp. 550-560
- West, M. A. (2002). Sparkling fountains or stagnant ponds: An integrative model of creativity and innovation implementation in work groups. Applied Psychology: An International Review,424
- http://hbr.org/2002/08/the-discipline-of-innovation/ar/1 Accessed 13 October 2013
- Christensen, Clayton & Overdorf, Michael. 2000, Meeting the Challenge of Disruptive Change
- (MIT Sloan Management Review Spring 2002-How to identify and build New Businesses)
- Anthony, Scott D.; Johnson, Mark W.; Sinfield, Joseph V.; Altman, Elizabeth J.(2008) Innovator’s Guide to growth Putting Disruptive Innovation to Work, Harvard Business School Press. ISBN 978-1-59139- 846-2.
- Salge, T.O. & Vera, A. 2009, Hospital innovativeness and organizational performance, Health Care Management Review, Vol. 34, Issue 1, pp. 54–67.
- Perez, T. and Rushing R. (2007). The CitiStat Model: How Data-Driven Government Can Increase Efficiency and Effectiveness. Center for American Progress Report. Pp. 1–18.
- Transportation Research Board. (2007). Transit Cooperative Research Program (TCRP) Synthesis 70: Mobile Data Terminals. Pp. 1–5. http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_syn_70.pdf
- Von Hippel, Eric (1988). The Sources of Innovation (PDF). Oxford University Press. Archived from the original (PDF) on 12 October 2006. Retrieved 3 December 2015.
- Engelberger, J. F. (1982). "Robotics in practice: Future capabilities". Electronic Servicing & Technology magazine.
- Kline (1985). Research, Invention, Innovation and Production: Models and Reality, Report INN-1, March 1985, Mechanical Engineering Department, Stanford University.
- Mark, M., Katz, B., Rahman, S., and Warren, D. (2008) MetroPolicy: Shaping A New Federal Partnership for a Metropolitan Nation. Brookings Institution: Metropolitan Policy Program Report. Pp. 4–103.
- The sociologist Silvia Leal Martín created the Innova3DX method to promote innovation in companies and professionals. See Forbes India New trends in Innovation Management: .http://forbesindia.com/article/ie/new-trends-in-innovation-management/33905/1#ixzz2iiuuDxVq
- "U-STIR". U-stir.eu. Retrieved 7 September 2011.
- Tuomi, I. (2002). Networks of Innovation. Oxford University Press. Networks of Innovation
- Siltala, R. (2010). Innovativity and cooperative learning in business life and teaching. University of Turku.
- Davila, T., Epstein, M. J., and Shelton, R. (2006). "Making Innovation Work: How to Manage It, Measure It, and Profit from It. " Upper Saddle River: Wharton School Publishing.
- Khan, A. M (1989). Innovative and Noninnovative Small Firms: Types and Characteristics. Management Science, Vol. 35, no. 5. Pp. 597–606.
- O'Sullivan, David (2002). "Framework for Managing Development in the Networked Organisations". Journal of Computers in Industry 47 (1): 77–88.
- Tarde, G. (1903). The laws of imitation (E. Clews Parsons, Trans.). New York: H. Holt & Co.
- Rogers, E. M. (1962). Diffusion of Innovation. New York, NY: Free Press.
- Davila, Tony; Marc J. Epstein and Robert Shelton (2006). Making Innovation Work: How to Manage It, Measure It, and Profit from It. Upper Saddle River: Wharton School Publishing
- OECD The Measurement of Scientific and Technological Activities. Proposed Guidelines for Collecting and Interpreting Technological Innovation Data. Oslo Manual. 2nd edition, DSTI, OECD / European Commission Eurostat, Paris 31 December 1995.
- "Industrial innovation – Enterprise and Industry". Ec.europa.eu. Retrieved 7 September 2011.
- Chalkidou K, Tunis S, Lopert R, Rochaix L, Sawicki PT, Nasser M, Xerri B. Comparative Effectiveness research and Evidence-Based Health Policy: Experience from Four Countries. The Milbank Quarterly 2009; 87(2): 339–367 at 362–363.
- Roughead E, Lopert R and Sansom L. Prices for innovative pharmaceutical products that provide health gain: a comparison between Australia and the United States Value in Health 2007;10:514–20
- Hughes B. Payers Growing Influence on R&D Decision Making. Nature Reviews Drugs Discovery 2008; 7: 876–78.
- Faunce T, Bai J and Nguyen D. Impact of the Australia-US Free Trade Agreement on Australian medicines regulation and prices. Journal of Generic Medicines 2010; 7(1): 18-29
- Faunce TA. Global intellectual property protection of “innovative” pharmaceuticals: Challenges for bioethics and health law in B Bennett and G Tomossy (eds) Globalization and Health Springer 2006 http://law.anu.edu.au/StaffUploads/236-Ch%20Globalisation%20and%20Health%20Fau.pdf . Retrieved 18 June 2009.
- Faunce TA. Reference pricing for pharmaceuticals: is the Australia-United States Free Trade Agreement affecting Australia's Pharmaceutical Benefits Scheme? Medical Journal of Australia. 20 August 2007;187(4):240–2.
- "Tools". Statsamerica.org. Retrieved 7 September 2011.
- Huebner, J. (2005). "A possible declining trend for worldwide innovation". Technological Forecasting and Social Change. 72 (8): 980–986. doi:10.1016/j.techfore.2005.01.003.
- Adler, Robert (2 July 2005). "Entering a dark age of innovation". New Scientist. Retrieved 30 May 2013.
- Hayden, Thomas (7 July 2005). "Science: Wanna be an inventor? Don't bother". U.S. News & World Report. Retrieved 10 June 2013.
- Smart, J. (2005). "Discussion of Huebner article". Technological Forecasting and Social Change. 72 (8): 988–995. doi:10.1016/j.techfore.2005.07.001.
- Huebner, Jonathan. "Response by the Authors". Technological Forecasting and Social Change. 72 (8): 995–1000. doi:10.1016/j.techfore.2005.05.008.
- Strumsky, D.; Lobo, J.; Tainter, J. A. (2010). "Complexity and the productivity of innovation". Systems Research and Behavioral Science. 27 (5): 496. doi:10.1002/sres.1057.
- Gordon, Robert J. (2012). "Is U.S. Economic Growth Over? Faltering Innovation Confronts the Six Headwinds". National Bureau of Economic Research. doi:10.3386/w18315.
- "Science and Technology". MEXT. Retrieved 7 September 2011.
- "BMBF " Ministry". Bmbf.de. Retrieved 7 September 2011.