Abstract
New frontiers of the mind are before us, and if they are pioneered with the same vision, boldness, and drive with which we have waged this war we can create a fuller and more fruitful employment and a fuller and more fruitful life.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Furthermore, see Milbergs (2005).
- 2.
See discussion on democracy in the conclusions.
- 3.
“Culture is the invisible force behind the tangibles and observables in any organization, a social energy that moves people to act. Culture is to the organization what personality is to the individual—a hidden, yet unifying theme that provides meaning, direction, and mobilization” (Killman 1985).
- 4.
- 5.
We consider the following quote useful for elucidating the meaning and role of a “knowledge nugget” as a building block of the “Mode 3” Innovation Ecosystem”: “People, culture, and technology serve as the institutional, market, and socio-economic ‘glue’ that binds, catalyzes, and accelerates interactions and manifestations between creativity and innovation as shown in Fig. 10.3, along with public-private partnerships, international Research & Development (R&D) consortia, technical/business/legal standards such as intellectual property rights as well as human nature and the ‘creative demon.’ The relationship is highly non-linear, complex and dynamic, evolving over time and driven by both external and internal stimuli and factors such as firm strategy, structure, and performance as well as top-down policies and bottom-up initiatives that act as enablers, catalysts, and accelerators for creativity and innovation that leads to competitiveness” (Carayannis and Gonzalez 2003, p. 593; see also Carayannis et al. 2003).
- 6.
Carayannis and Zedtwitz 2005.
- 7.
Networking is important for understanding the dynamics of advanced and knowledge-based societies. Networking links together different modes of knowledge production and knowledge use, and also connects (sub-nationally, nationally, trans-nationally) different sectors or systems of society. Systems theory, as presented here, is flexible enough for integrating and reconciling systems and networks, thus creating conceptual synergies.
- 8.
Carayannis and Alexander (2004).
- 9.
Carayannis and Alexander (1999a,b).
- 10.
Carayannis (2001, pp. 169–170) discusses chaos theory and fractals in connection to technological learning and knowledge and innovation system architectures: “Chaos theory is a close relative of catastrophe theory, but has shown more potential in both explaining and predicting unstable non-linearities, thanks to the concept of self-similarity or fractals [patterns within patterns] and the chaotic behavior of attractors (Mandelbrot) as well as the significance assigned to the role that initial conditions play as determinants of the future evolution of a non-linear system (Gleick 1987). There is a strong affinity with strategic incrementalism, viewed as a third-order (triple-layered), feedback-driven system that can exhibit instability in any given state as a result of the operational, tactical, and strategic technological learning … that takes place within the organization in question”.
- 11.
“A fractal is a geometric object which is rough or irregular on all scales of length, and so which appears to be “broken up” in a radical way. Some of the best examples can be divided into parts, each of which is similar to the original object. Fractals are said to possess infinite detail, and some of them have a self-similar structure that occurs at different levels of magnification. In many cases, a fractal can be generated by a repeating pattern, in a typically recursive or iterative process. The term fractal was coined in 1975 by Benoît Mandelbrot, from the Latin fractus or ‘broken.’ Before Mandelbrot coined his term, the common name for such structures (the Koch snowflake, for example) was monster curve. Fractals of many kinds were originally studied as mathematical objects. Fractal geometry is the branch of mathematics which studies the properties and behavior of fractals. It describes many situations which cannot be explained easily by classical geometry, and has often been applied in science, technology, and computer-generated art. The conceptual roots of fractals can be traced to attempts to measure the size of objects for which traditional definitions based on Euclidean geometry or calculus fail” (http://en.wikipedia.org/wiki/Fractal).
- 12.
The data in Fig. 10.4 express the R&D performance of the USA, for the period 1981–2004, in million 2000 dollars in constant prices and PPP (purchasing power parities).
- 13.
In the German language, “university-related” would qualify as “außeruniversitär” (Campbell 2003, p. 99).
- 14.
The “academic firm,” as a notion and concept, was first developed by Campbell and Güttel (2005).
References
Berridge GR, James A (2003) A Dictionary of Diplomacy (2nd ed.). New York: Palgrave Macmillan.
Bush, Vannevar (1945). Science: The Endless Frontier. Washington, D.C.: United States Government Printing Office [http://www.nsf.gov/od/lpa/nsf50/vbush1945.htm#transmittal].
Braun, C. F. von (1997). The Innovation War. Upper Saddle River, NJ: Prentice Hall.
Campbell, David F. J. (2001). Politische Steuerung über öffentliche Förderung universitärer Forschung? Systemtheoretische Überlegungen zu Forschungs- und Technologiepolitik. Österreichische Zeitschrift für Politikwissenschaft 30 (4), 425–438.
Campbell, David F. J., Wolfgang H. Güttel (2005). Knowledge Production of Firms: Research Networks and the “Scientification” of Business R&D. International Journal of Technology Management 31 (1/2), 152–175.
Carayannis, Elias G. (2001). The Strategic Management of Technological Learning, CRC Press.
Carayannis, Elias G. (2004). Measuring Intangibles: Managing Intangibles for Tangible Outcomes in Research and Innovation. International Journal of Nuclear Knowledge Management, v. 1, no. 1, January.
Carayannis, Elias G., Jeffrey Alexander (1999a). Winning by Co-opeting in Strategic Government-University-Industry (GUI) Partnerships: The Power of Complex, Dynamic Knowledge Networks. Journal of Technology Transfer 24 (2/3, August), 197–210.
Carayannis, Elias G., Jeffrey Alexander (1999b). Technology-Driven Strategic Alliances: Tools for Learning and Knowledge Exchange in a Positive-Sum World, 1-32 until 1-41, in: Richard C. Dorf (ed.): The Technology Management Handbook. Boca Raton, Florida: CRC Press.
Carayannis, Elias G., Edgar Gonzalez (2003). Creativity and Innovation = Competitiveness? When, How, and Why, Vol. 1, Chap. 8, pp. 587–606, in: Larisa V. Shavinina (ed.): The International Handbook on Innovation. Amsterdam: Pergamon.
Carayannis, Elias G., Edgar Gonzalez, John Wetter (2003). The Nature and Dynamics of Discontinuous and Disruptive Innovations From a Learning and Knowledge Management Perspective, Vol. 1, Chap. 4, pp. 115–138, in: Larisa V. Shavinina (ed.): The International Handbook on Innovation. Amsterdam: Pergamon.
Carayannis, Elias G., Jeffrey Alexander (2004). Strategy, Structure and Performance Issues of Pre-competitive R&D Consortia: Insights and Lessons Learned. IEEE Transactions of Engineering Management 52 (2).
Carayannis, Elias G., Maximilian von Zedtwitz (2005). Architecting GloCal (Global – Local), Real-Virtual Incubator Networks (G-RVINs) as Catalysts and Accelerators of Entrepreneurship in Transitioning and Developing Economies. Technovation 25, 95–110.
Carayannis, Elias G., Jeffrey M. Alexander (2006). Global and Local Knowledge. Glocal Transatlantic Public-Private Partnerships for Research and Technological Development. Houndmills: Palgrave MacMillan.
Carayannis, Elias G., David F. J. Campbell (2006a). „Mode 3“: Meaning and Implications from a Knowledge Systems Perspective, 1-25, in: Elias G. Carayannis, David F. J. Campbell (eds.): Knowledge Creation, Diffusion, and Use in Innovation Networks and Knowledge Clusters. A Comparative Systems Approach across the United States, Europe and Asia. Westport, Connecticut: Praeger.
Carayannis, Elias G., David F. J. Campbell (2006b). Conclusion: Key Insights and Lessons Learned for Policy and Practice, 331-341, in: Elias G. Carayannis, David F. J. Campbell (eds.): Knowledge Creation, Diffusion, and Use in Innovation Networks and Knowledge Clusters. A Comparative Systems Approach across the United States, Europe and Asia. Westport, Connecticut: Praeger.
Carayannis, Elias G., David F. J. Campbell (2006c). Introduction and Chapter Summaries, ix-xxvi, in: Elias G. Carayannis, David F. J. Campbell (eds.): Knowledge Creation, Diffusion, and Use in Innovation Networks and Knowledge Clusters. A Comparative Systems Approach across the United States, Europe and Asia. Westport, Connecticut: Praeger.
Carayannis, Elias G., John E. Spillan, Christopher Ziemnowicz (2007). Introduction: Why Joseph Schumpeter’s Creative Destruction? Everything has Changed, 1-5, in: Elias G. Carayannis, Christopher Ziemnowicz (eds.): Rediscovering Schumpeter. Creative Destruction Evolving into “Mode 3”. Houndmills: Palgrave MacMillan.
Carayannis, Elias G., Firm evolution dynamics: toward sustainable entrepreneurship and robust competitiveness in the knowledge economy and society, Int. J. Innovation and Regional Development, (1)3: 235–254, 2009.
Carayannis, Elias G. and David F.J. Campbell, ‘Mode 3’ and ‘Quadruple Helix’: toward a 21st century fractal innovation ecosystem, International Journal of Technology Management, 46(3/4): 201–234, 2009.
Carayannis, Elias G., Knowledge-Driven Creative Destruction, or Leveraging Knowledge for Competitive Advantage: Strategic Knowledge Arbitrage and Serendipity as Real Options Drivers Triggered by Co-Opetition, Co-Evolution and Co-Specialization, Industry and Higher Education, 22(6): 343–353, December 2008.
Cesaroni, Fabrizio, Alfonso Gambardella, Walter Garcia-Fontes, Myriam Mariani (2004). The Chemical Sectoral System: Firms, Markets, Institutions and the Processes of Knowledge Creation and Diffusion, 121-154, in: Malerba, Franco (ed.): Sectoral Systems of Innovation. Concepts, Issues and Analyses of Six Major Sectors in Europe. Cambridge: Cambridge University Press.
Etzkowitz, Henry, Loet Leydesdorff (2000). The dynamics of innovation: from National Systems and “Mode 2” to a Triple Helix of university-industry-government relations. Research Policy 29, 109–123.
Etzkowitz, Henry (2003). Research groups as “quasi-firms”: The invention of the Entrepreneurial University. Research Policy 32, 109–121.
Florida, Richard (2004). The Rise of the Creative Class: And How It’s Transforming Work, Leisure, Community, and Everyday Life. Cambridge, MA: Basic Books.
Gerybadze, Alexander, Guido Reger (1999). Globalization of R&D: Recent Changes in the Management of Innovation in Transnational Corporations. Research Policy 28, 251–274.
Gibbons, Michael, Camille Limoges, Helga Nowotny, Simon Schwartzman, Peter Scott, Martin Trow (1994). The New Production of Knowledge. The Dynamics of Science and Research in Contemporary Societies. London: Sage.
Gleick, James (1987). Chaos: Making a New Science. New York: Viking Press.
Hooghe, Liesbet, Gary Marks (2001). Multi-Level Governance and European Integration. Lanham: Rowman & Littlefield Publishers.
Killman, R. (1985). Gaining Control of the Corporate Culture. New York: McGraw-Hill.
Kuhlmann, Stefan (2001). Future Governance of Innovation Policy in Europe – Three Scenarios. Research Policy 30, 953–976.
Milbergs, Egils (2005). Innovation Ecosystems and Prosperity. Center for Accelerating Innovation [http://www.innovationecosystems.com].
OECD (1994). Frascati Manual. The Measurement of Scientific and Technological Activities. Proposed Standard Practice for Surveys of Research and Experimental Development. Paris: OECD.
OECD (2006). Research and Development Statistics. (On-Line Database). Paris: OECD.
Rana S (2007) Economic diplomacy negotiations http://berkouk-mhand.yolasite.com/resources/Negotiations_for_Economic_Diplomacy.pdf.
Schumpeter, Joseph A. (1942). Capitalism, Socialism and Democracy. New York: Harper & Brothers.
Shapira, Philip, Stefan Kuhlmann (eds.) (2003). Learning from Science and Technology Policy Evaluation. Experiences from the United States and Europe. Cheltenham: Edward Elgar.
Tassey, Gregory (2001). R&D Policy Models and Data Needs, 37-71, in: Maryann P. Feldman, Albert N. Link (eds.). Innovation Policy in the Knowledge-Based Economy. Boston: Kluwer Academic Publishers.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Del Giudice, M., Carayannis, E.G., Peruta, M.R.D. (2012). Cross-Cultural Knowledge Management and Open Innovation Diplomacy: Definition of Terms. In: Cross-Cultural Knowledge Management. Innovation, Technology, and Knowledge Management, vol 11. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-2089-7_10
Download citation
DOI: https://doi.org/10.1007/978-1-4614-2089-7_10
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-2088-0
Online ISBN: 978-1-4614-2089-7
eBook Packages: Business and EconomicsBusiness and Management (R0)