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Characterize Innovative Space of City Based on Multivariate Data: A Case Study of Guangzhou, China

Received: 17 May 2022     Published: 19 May 2022
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Abstract

With the emergence of knowledge economy, innovation has evolved as the principal driver of economic development. In the subjects of economic geography and urban planning, the relationship between innovation and place has been a research focus. The purpose of this research is to explore the method of characterizing the spatial distribution of innovative activities in city. Four types of indexes are selected to characterize the innovative space in city: universities and scientific institutions, high-tech enterprises, incubators and patents, which come from three aspects: innovative actors, innovative carriers and innovative outputs. Using these indices, this research characterizes the pattern of the innovative space in Guangzhou. The findings show that the spatial distribution of innovative activities in Guangzhou forms two centers: Tianhe central area and Guangzhou Science City. In Tianhe central area, there are not only a large number of the actors of original innovation but also a large number of the actors of applied innovation, so its innovative mode is the mixed mode including both original innovation and applied innovation. Unlike Tianhe central area, Guangzhou Science City is a suburban high-tech park, which aims to cultivate the high-tech enterprises to promote the development of high-tech industry, so its innovative activities are mainly applied innovation.

Published in Urban and Regional Planning (Volume 7, Issue 2)
DOI 10.11648/j.urp.20220702.12
Page(s) 39-46
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Innovative Space, Spatial Distribution, Innovation, Multivariate Data, Guangzhou

References
[1] Baumol, W. (2004). The Free-Market Innovation Machine: Analyzing the Growth Miracle of Capitalism. Princeton: Princeton University Press.
[2] Schumpeter, J. (1949). The Theory of Economic Development. Cambridge: Harvard University Press.
[3] Hanusch, H., Pyka, A. (2007). Principles of neo-Schumpeterian economics. Cambridge Journal of Economics, 31 (2), 275-289.
[4] Hanusch, H., Pyka, A. (2007). Manifesto for comprehensive neo-Schumpeterian economics. History of Economic Ideas, 15 (1), 23.
[5] Hall, B., Rosenberg, N. (2010). Handbook of the Economics of Innovation. Amsterdam: Elsevier.
[6] Steil, B., Victor, D., Nelson, R. (2002). Technological innovation and economic performance. Princeton: Princeton University Press.
[7] Jenkins, G. (1992). Economic reform and institutional innovation. Development Discussion Papers, 588-596.
[8] Akcigit, U., Hanley, D., Serrano-Velarde, N. (2021). Back to basics: Basic research spillovers, innovation policy, and growth. The Review of Economic Studies, 88 (1), 1-43.
[9] Polenske, K. (2007). The Economic Geography of Innovation. Cambridge: Cambridge University Press.
[10] Penn, A., Desyllas, J., Vaughan, L. (1999). The space of innovation: interaction and communication in the work environment. Environment and planning B: Planning and design, 26 (2), 193-218.
[11] Schmitz, H., Strambach, S. (2009). The organisational decomposition of innovation and global distribution of innovative activities: insights and research agenda. International Journal of Technological Learning, Innovation and Development, 2 (4), 231-249.
[12] Moreno, R., Paci, R., Usai, S. (2005). Spatial spillovers and innovation activity in European regions. Environment and planning A, 37 (10), 1793-1812.
[13] MA, H. T., Fang, C. L., Wang, S. J. (2013). Indicators of global innovative cities and their implications for China. Urban Planning Forum. (01): 69-77.
[14] Du, D. B., Duan, D. Z. (2015). Spatial distribution, development type and evolution trend of global science and technology innovation center. Shanghai Urban Planning Review, (01): 76-81.
[15] Rammer, C., Kinne, J., Blind, K. (2020). Knowledge proximity and firm innovation: A microgeographic analysis for Berlin. Urban Studies, 57 (5), 996-1014.
[16] Duan, D. Z., Du, D. B., Liu, C. L., Grimes, S. (2016). Spatio-temporal evolution of urban innovation structure based on zip code geodatabase: An empirical study from Shanghai and Beijing. Journal of Geographical Sciences, 26 (12): 1707-1724.
[17] Zhang, Z., Li, Z. F., Xiao, Y. (2018) The Micro-Scale Spatial Features of Innovative Activities in Shanghai: A Research Based on the Patent Data. Modern Urban Research, (05): 80-85+93.
[18] Ma, S., Zeng, G. (2020). Spatial Structure, Influencing Factors and Spillover Effect of Innovation Agglomeration in Shanghai. Urban Development Studies, 27 (01): 19-25.
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  • APA Style

    Gang Li. (2022). Characterize Innovative Space of City Based on Multivariate Data: A Case Study of Guangzhou, China. Urban and Regional Planning, 7(2), 39-46. https://doi.org/10.11648/j.urp.20220702.12

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    ACS Style

    Gang Li. Characterize Innovative Space of City Based on Multivariate Data: A Case Study of Guangzhou, China. Urban Reg. Plan. 2022, 7(2), 39-46. doi: 10.11648/j.urp.20220702.12

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    AMA Style

    Gang Li. Characterize Innovative Space of City Based on Multivariate Data: A Case Study of Guangzhou, China. Urban Reg Plan. 2022;7(2):39-46. doi: 10.11648/j.urp.20220702.12

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  • @article{10.11648/j.urp.20220702.12,
      author = {Gang Li},
      title = {Characterize Innovative Space of City Based on Multivariate Data: A Case Study of Guangzhou, China},
      journal = {Urban and Regional Planning},
      volume = {7},
      number = {2},
      pages = {39-46},
      doi = {10.11648/j.urp.20220702.12},
      url = {https://doi.org/10.11648/j.urp.20220702.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.urp.20220702.12},
      abstract = {With the emergence of knowledge economy, innovation has evolved as the principal driver of economic development. In the subjects of economic geography and urban planning, the relationship between innovation and place has been a research focus. The purpose of this research is to explore the method of characterizing the spatial distribution of innovative activities in city. Four types of indexes are selected to characterize the innovative space in city: universities and scientific institutions, high-tech enterprises, incubators and patents, which come from three aspects: innovative actors, innovative carriers and innovative outputs. Using these indices, this research characterizes the pattern of the innovative space in Guangzhou. The findings show that the spatial distribution of innovative activities in Guangzhou forms two centers: Tianhe central area and Guangzhou Science City. In Tianhe central area, there are not only a large number of the actors of original innovation but also a large number of the actors of applied innovation, so its innovative mode is the mixed mode including both original innovation and applied innovation. Unlike Tianhe central area, Guangzhou Science City is a suburban high-tech park, which aims to cultivate the high-tech enterprises to promote the development of high-tech industry, so its innovative activities are mainly applied innovation.},
     year = {2022}
    }
    

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  • TY  - JOUR
    T1  - Characterize Innovative Space of City Based on Multivariate Data: A Case Study of Guangzhou, China
    AU  - Gang Li
    Y1  - 2022/05/19
    PY  - 2022
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    DO  - 10.11648/j.urp.20220702.12
    T2  - Urban and Regional Planning
    JF  - Urban and Regional Planning
    JO  - Urban and Regional Planning
    SP  - 39
    EP  - 46
    PB  - Science Publishing Group
    SN  - 2575-1697
    UR  - https://doi.org/10.11648/j.urp.20220702.12
    AB  - With the emergence of knowledge economy, innovation has evolved as the principal driver of economic development. In the subjects of economic geography and urban planning, the relationship between innovation and place has been a research focus. The purpose of this research is to explore the method of characterizing the spatial distribution of innovative activities in city. Four types of indexes are selected to characterize the innovative space in city: universities and scientific institutions, high-tech enterprises, incubators and patents, which come from three aspects: innovative actors, innovative carriers and innovative outputs. Using these indices, this research characterizes the pattern of the innovative space in Guangzhou. The findings show that the spatial distribution of innovative activities in Guangzhou forms two centers: Tianhe central area and Guangzhou Science City. In Tianhe central area, there are not only a large number of the actors of original innovation but also a large number of the actors of applied innovation, so its innovative mode is the mixed mode including both original innovation and applied innovation. Unlike Tianhe central area, Guangzhou Science City is a suburban high-tech park, which aims to cultivate the high-tech enterprises to promote the development of high-tech industry, so its innovative activities are mainly applied innovation.
    VL  - 7
    IS  - 2
    ER  - 

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Author Information
  • School of Architecture, South China University of Technology (SCUT), Guangzhou, China

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