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Knowledge as a Driver of Technological Change and Regional Growth

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Knowledge Flows, Technological Change and Regional Growth in the European Union

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Abstract

In order to pursue a comprehensive analytical approach to study technological change and its role in regional growth in the EU, this chapter draws on an overview of the economic theory of knowledge, endogenous growth theories, and “new economic geography” to prepare a theoretical framework for the models estimated in Chaps. 3, 4, 5 and 6.

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Notes

  1. 1.

    “Technological breakthrough” refers to the use of a substantially different technology than existing products without considerably increasing the benefits to consumers, whereas “radical innovation” is a product that is high on both the technology and market dimension; it involves a substantially different technology while offering a substantial increase in customer benefits. See also: http://www.carlsonschool.umn.edu/Assets/71621.pdf

  2. 2.

    Technological knowledge should not be confused with technical knowledge. The term “technology” means the practice and results of engineering as well as scientific research on engineering, whereas “technical” applies to engineering practice (Ropohl 1997, pp. 65–72).

  3. 3.

    It is important to note that this does not mean that high-tech industries, e.g. the pharmaceutical industry, are less driven by market or managerial knowledge than low-tech industries, e.g. the pulp and paper industry. It means rather that the paper producer may be more efficient due to rationalisation and process innovation than due to product innovations.

  4. 4.

    According to Vernon Ruttan (2006, pp. 252–172) institutions are the rules of a society or of organizations that facilitate coordination among people by helping them form expectations, which each person can reasonably hold in dealing with others. Institutions, like technology, must change if development is to occur. Ruttan also considers cultural endowment, religion, and ideology as important factors of institutional innovation.

  5. 5.

    Technology includes “hard” technologies (such as computer-controlled machine tools) and “soft” technologies (e.g. improved manufacturing, quality, or training methods).

  6. 6.

    “Knowledge spillovers” refer to the unintentional flows of knowledge to others beyond the intended boundary. If knowledge is exchanged with the intended people or organizations, it is a “knowledge transfer”; any knowledge that is exchanged outside the intended boundary is a spillover (Verspagen, 2008).

  7. 7.

    Florida examines the relationship between measures of diversity and tolerance and high-technology success in the 50 most populated metropolitan areas in the United States. He shows the relationship between high concentrations of creative people or “bohemians” and high technology success. One of the measures of diversity and tolerance is the gay population’s rate in a metropolitan area (2001).

  8. 8.

    The main goal of the ERA is to strengthen networking between research partners and across research disciplines, as well as to link geographically-distant centers of excellence and to disseminate knowledge across Europe. Data on research networks financed by the EU within different FP are publicly available through the CORDIS.

  9. 9.

    Following the aggregations of services based on NACE Rev 1.1, the KIS include: 61 – Water transport; 62 – Air transport; 64 – Post and telecommunications; 65–67 – Financial intermediation; 70–74 – Real estate, renting, and business activities; 80 – Education; 85 – Health and social work; 92 – Recreational, cultural, and sporting activities. Data from October 2011, Eurostat.

  10. 10.

    Knowledge-intensive high-tech services: Post and Telecommunications (64); Computer and related activities (72); Research and development (73), Eurostat, Statistics in Focus, Science and Technology, 4/2005, R&D Statistics, Luxembourg, 2005.

  11. 11.

    Many companies have set up their own R&D centers in India or China in order to reduce complexity and cost of their production processes in such sectors as IT and electronics. As a result, both of these countries became almost overnight global hubs for these industries; http://www.design-reuse.com/news/8711/outsourcing-india-shifts-d.html; http://www.chnsourcing.com/top50/2008/.

  12. 12.

    The OECD has classified the manufacturing sectors according to their R&D intensity. High-technology industries include: Aircraft and spacecraft; Office machinery and computers; Electronic and communication equipment; Pharmaceuticals, medicinal chemicals, and botanical products; Medical, precision and optical instruments, and watches and clocks. Medium-high technology includes: Electrical machinery and apparatuses; Motor vehicles, trailers, and semi-trailers, railway and tramway locomotives and rolling stock; Chemicals and chemical products; Machinery and equipment.

  13. 13.

    Traditionally, technology transfer included the transfer of hardware objects. However, due to the rapid development of ICT infrastructure, transfer often involves information (e.g. a computer software program or a new idea). The Work Regulations of the United Nations define technology transfer as a systematic transfer of knowledge for the manufacture of a product or provision of service (Yu 1991). Knowledge transfer is the fundamental element of technology transfer; without knowledge transfer, technology transfer does not take place. It includes the transfer of tangible and intellectual property, expertise, learning, and skills between academia and the non-academic community.

  14. 14.

    Varga (1989) identifies several ways of university-business knowledge transfers: formal co-operations and agreements on R&D, industry financed university research centers, faculty consulting in industry, scholarly journal publications and industrial associates programs. Other forms of knowledge transfers are industrial incubators and industrial parks, aimed mainly at providing facilities to start-up firms, as well as university spin-offs.

  15. 15.

    Zand and van Beers (2008) emphasize that radical innovation performance is positively influenced by collaboration schemes with all partners except for competitors. The threat of leakage of sensitive information towards competitors can explain why R&D co-operation with competitors affects radical innovation performance negatively.

  16. 16.

    Even though Porter’s (1998, 2008) cluster approach has been vastly popularized at the regional and local level in the US, there are still problems with the definition of clusters. One of the simplest ways to define cluster is suggested by Doeringer and Terkla, according to whom industry clusters are “the geographical concentrations of industries that gain performance advantages through co-location” (1995, p. 225). Other authors, Barkley and Henry, define cluster as “a loose, geographically bounded collection of similar and/or related firms that together create competitive advantages for Memberfirms and the regional economy” (2002). Gibbs and Bernat (1997) further add to these definitions by identifying shared input needs and inter-relationships with suppliers and buyers. On the other hand, Swann and Prevezer put it very simply – they say that “geographical cluster is a collection of related companies located in a small geographical area. (…) Companies group together to take advantage of strong demand in the location, a large supply of scientific manpower and the network of complementary strengths in neighboring firms” (1998, p. 3).

  17. 17.

    Other factors that influence all firms and institutions in a cluster include legislation, regional cultures, social institutions and conventions, as well as regional assets. For example, a regional culture, like the one in the Italian industrial districts or in Silicon Valley, influences all firms to the same extent, whether they are part of a cluster or not.

  18. 18.

    While cluster boundaries often fit political boundaries, they may also cross state and even national borders, especially in smaller States and nations and in cities located near borders (Porter 2008, pp. 204–205). Maskell (2001) defined the boundaries of the cluster as the “fit between the economic activities carried out by the related firms of the cluster on the one hand and the particular institutional endowment developed over time to assist these activities on the other.”

  19. 19.

    Attempts to introduce it by presenting models with a separate technology-producing sector were made by Uzawa (1965), Phelps (1966), Shell (1967), and others. However, by the early 1970s, growth theory went out of fashion together with the idea of endogenous technological progress. As a consequence, these models had little, if any, impact on the empirical work that accompanied theoretical discussions of the 1960s.

  20. 20.

    This is the way Abramovitz (1994) explained the failure of most industrialized countries to catch up with the US prior to World War II. Mainly, according to Abramovitz, a country that differs much from the technological leader in factor supply may sometimes find it difficult to absorb the leader country’s technology.

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    Małgorzata Runiewicz-Wardyn

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Runiewicz-Wardyn, M. (2013). Knowledge as a Driver of Technological Change and Regional Growth. In: Knowledge Flows, Technological Change and Regional Growth in the European Union. Contributions to Economics. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00342-9_1

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