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A Complexidade e a Estabilidade da Estrutura do Conhecimento Tecnológico na Evolução dos Micro-paradigmas

AVANCI, Vanessa de Lima; Urraca-Ruiz, Ana;

Artigo Completo:

Nas últimas décadas houve uma forte expansão da quantidade de patentes com o aumento também da quantidade de relações novas entre campos tecnológicos diferentes, ainda assim vários estudos apontam para a estabilidade da estrutura do conhecimento tecnológico. Ao emergir, os paradigmas tecnológicos criam oportunidades de pesquisa, de avanço do conhecimento tecnológico e levam a uma maior integração entre campos tecnológicos distintos. A estrutura do conhecimento tecnológico se torna mais complexa através da integração dos seus distintos componentes e cria limites às direções de pesquisa e de acumulação. Os objetivos deste trabalho são comparar a estrutura de um mapa de patentes global em períodos distintos no tempo, identificar os seus principais componentes e averiguar se a estabilidade é uma característica intrínseca a essa estrutura. A análise das redes formadas pelas patentes em 1988, 1998 e 2008 e dos agrupamentos dos campos tecnológicos mostrou que a estrutura do conhecimento tecnológico geral não se manteve estável ao longo do tempo. Os resultados também mostraram que um núcleo constituído por relações entre campos tecnológicos se tornou relativamente mais importante ao longo do tempo.

Artigo Completo:

In the last decades there has been a strong expansion of the number of patents with an increase in the number of new relations between different technological fields, yet several studies point to the stability of the technological knowledge structure. When emerging, technological paradigms create opportunities for research, advancement of technological knowledge and lead to greater integration between different technological fields. The structure of technological knowledge becomes more complex through the integration of its distinct components and creates limits to the directions of research and accumulation. The objectives of this work are to compare the structure of a global patent map at different time periods, to identify its main components and to investigate whether stability is an intrinsic characteristic of this structure. The analysis of networks formed by patents in 1988, 1998 and 2008 and of the clusters of technological fields showed that the structure of general technological knowledge has not remained stable over time. The results also showed that a core composed of relations between technological fields became relatively more important over time.

Palavras-chave: Complexidade Tecnológica, Estrutura de conhecimento, Paradigmas e Trajetórias tecnológicas, Distância Tecnológica, Patentes,

Palavras-chave: Technological Complexity, Knowledge structure, Technological Paradigms and Trajectories, Technological Distance, Patents,

DOI: 10.5151/enei2017-70

Referências bibliográficas
  • [1] Aharonson, B. S., Schilling, M. A. (2016). Mapping the technological landscape: Measuring technology distance, technological footprints, and technology evolution. Research Policy, 45(1), 81-96.
  • [2] Benson, C. L., & Magee, C. L. (2013). A hybrid keyword and patent class methodology for selecting relevant sets of patents for a technological field. Scientometrics, 96, 69–8
  • [3] Benson, C. L., & Magee, C. L. (2015). Technology structural implications from the extension of a patent search method. Scientometrics, 102, 1965–1985.
  • [4] Boschma, R., Balland, P.-A., & Kogler, D. F. (2015). Relatedness and technological change in cities: The rise and fall of technological knowledge in US metropolitan areas from 1981 to 2010. Industrial and Corporate Change, 24, 223–250.
  • [5] Breschi, S., Lissoni, F., Malerba, F. (2003). Knowledge-relatedness in firm technological diversification. Research Policy, 32(1), 69-87.
  • [6] Dosi, G. (1984). Technical change and industrial transformation: the theory and an application to the semiconductor industry. Springer.
  • [7] Fleming, L. (2001). Recombinant uncertainty in technological search. Management Science, 47(1), 117–132.
  • [8] Fontana, R., Nuvolari, A., & Verspagen, B. (2009). Mapping technological trajectories as patent citation networks. An application to data communication standards. Economics of Innovation and New Technology, 18(4), 311-336.
  • [9] Granstrand, O., Sjölander, S. (1990). The acquisition of technology and small firms by large firms. Journal of Economic Behavior & Organization, 13(3), 367-386.
  • [10] Granstrand, O., P. Patel and K. Pavitt (1997), "Multi-Technology Corporations: Why They Have 'Distributed' Rather than 'Distinctive Core' Competencies", California Management Review, 39, 8-25.
  • [11] Hidalgo, C.A., Klinger, B., Barabasi, A.-L. & Hausmann, R. (2007). The Product Space Conditions the Development of Nations. Science 317 (5837), 482-487.
  • [12] Hinze, S., Reiß, T., Schmoch, U. (1997). Statistical analysis on the distance between fields of technology. Fraunhofer-Inst. Systems and Innovation Research.
  • [13] Joo, S., & Kim, Y. (2010). Measuring relatedness between technological fields. Scientometrics, 83, 435–454.
  • [14] Kajikawa, Y., Yoshikawa, J., Takeda, Y., & Matsushima, K. (2008). Tracking emerging technologies in energy research: Toward a roadmap for sustainable energy. Technological Forecasting & Social Change, 75, 771–782.
  • [15] Kay, L., Newman, N., Youtie, J., Porter, A. L., Rafols, I. (2014). Patent overlay mapping: Visualizing technological distance. Journal of the Association for Information Science and Technology, 65(12), 2432-2443.
  • [16] Levinthal, D.A. & March, J.G. (1993). The Myopia of Learning. Strategic Management Journal, 14 (S2), 95-112. doi: 10.1002/smj.4250141009
  • [17] Leydesdorff, L., Kushnir, D., Rafols, I. (2014). Interactive overlay maps for US patent (USPTO) data based on International Patent Classification (IPC). Scientometrics, v. 98, n. 3, p. 1583-1599.
  • [18] Malerba, F., Orsenigo, L. (1996). Schumpeterian patterns of innovation are technology-specific.Research policy, 25(3), 451-478.
  • [19] Mina, A., Ramlogan, R., Tampubolon, G., Metcalfe, J. S. (2007). Mapping evolutionary trajectories: Applications to the growth and transformation of medical knowledge. Research Policy 36, 789–806.
  • [20] Nakamura, H., Suzuki, S., Sakata, I., & Kajikawa, Y. (2015). Knowledge combination modeling: The measurement of knowledge similarity between different technological domains. Technological Forecasting and Social Change, 94, 187–201.
  • [21] Nooteboom, B. (2000). Learning and Innovation in Organizations and Economies. Oxford: Oxford University Press.
  • [22] Ogawa, T., & Kajikawa, Y. (2015). Assessing the industrial opportunity of academic research with patent relatedness: A case study on polymer electrolyte fuel cells. Technological Forecasting & Social. Change, 90, 469–475.
  • [23] Patel, P., K. Pavitt (1997), "The Technological Competencies of the World's Largest Firms: Complex and Path-Dependent, but not much Variety", Research Policy, 26, 141-156.
  • [24] Rigby, D. L. (2015). Technological relatedness and knowledge space: Entry and exit of US cities from patent classes. Regional Studies, 49, 1922–1937.
  • [25] Sahal, D. (1985). Technological guideposts and innovation avenues. Research policy, 14(2), 61-82.
  • [26] Schoen, A., Villard, L., Laurens, P., Cointet, J. P., Heimeriks, G., Alkemade, F. (2012). The network structure of technological developments; technological distance as a walk on the technology map. In Science & Technology Indicators (STI) Conference.
  • [27] Teece, D. J., Rumelt, R., Dosi, G., & Winter, S. (1994). Understanding corporate coherence: Theory and evidence. Journal of Economic Behavior & Organization, 23, 1–30.
  • [28] Veefkind, V., Hurtado-Albir, J., Angelucci, S., Karachalios, K., & Thumm, N. (2012). A new EPO classification scheme for climate change mitigation technologies. World Patent Information, 34(2), 106-111.
  • [29] Verspagen, B. (2007). Mapping technological trajectories as patent citation networks: A study on the history of fuel cell research. Advances in Complex Systems, 10(01), 93-115.
Como citar:

AVANCI, Vanessa de Lima; Urraca-Ruiz, Ana; "A Complexidade e a Estabilidade da Estrutura do Conhecimento Tecnológico na Evolução dos Micro-paradigmas", p. 1306-1320 . In: . São Paulo: Blucher, 2017.
ISSN 2357-7592, DOI 10.5151/enei2017-70

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