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Identifying Geographic Clusters: A Network Analytic Approach

Author

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  • Catini, Roberto
  • Karamshuk, Dmytro
  • Penner, Orion
  • Riccaboni, Massimo
Abstract
In recent years there has been a growing interest in the role of networks and clusters in the global economy. Despite being a popular research topic in economics, sociology and urban studies, geographical clustering of human activity has often studied been by means of predetermined geographical units such as administrative divisions and metropolitan areas. This approach is intrinsically time invariant and it does not allow one to differentiate between different activities. Our goal in this paper is to present a new methodology for identifying clusters, that can be applied to different empirical settings. We use a graph approach based on k-shell decomposition to analyze world biomedical research clusters based on PubMed scientific publications. We identify research institutions and locate their activities in geographical clusters. Leading areas of scientific production and their top performing research institutions are consistently identified at different geographic scales.

Suggested Citation

  • Catini, Roberto & Karamshuk, Dmytro & Penner, Orion & Riccaboni, Massimo, 2015. "Identifying Geographic Clusters: A Network Analytic Approach," MPRA Paper 64454, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:64454
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    References listed on IDEAS

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    Cited by:

    1. O’Clery, Neave & Kinsella, Stephen, 2022. "Modular structure in labour networks reveals skill basins," Research Policy, Elsevier, vol. 51(5).
    2. René Belderbos & Marcelina Grabowska & Stijn Kelchtermans & Bart Leten & Jojo Jacob & Massimo Riccaboni, 2021. "Whither geographic proximity? Bypassing local R&D units in foreign university collaboration," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 52(7), pages 1302-1330, September.
    3. John Gibson, 2021. "The micro‐geography of academic research: How distinctive is economics?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(4), pages 467-484, September.
    4. Martina Cioni & Giovanni Federico & Michelangelo Vasta, 2022. "Persistence studies: a new kind of economic history?," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 42(3), pages 227-248, December.
    5. Verginer, Luca & Riccaboni, Massimo, 2021. "Talent goes to global cities: The world network of scientists’ mobility," Research Policy, Elsevier, vol. 50(1).
    6. Marion Maisonobe & Bastien Bernela, 2019. "Exploring the Scope of a Cross-regional Knowledge Network. The Case of a Green Chemistry Research Federation in France," Working Papers hal-02053595, HAL.
    7. Christoph Stich & Emmanouil Tranos & Max Nathan, 2023. "Modeling clusters from the ground up: A web data approach," Environment and Planning B, , vol. 50(1), pages 244-267, January.
    8. Luca Verginer & Massimo Riccaboni, 2018. "Brain-Circulation Network: The Global Mobility of the Life Scientists," Working Papers 10/2018, IMT School for Advanced Studies Lucca, revised Oct 2018.
    9. György Csomós & Zsófia Viktória Vida & Balázs Lengyel, 2020. "Exploring the changing geographical pattern of international scientific collaborations through the prism of cities," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-20, November.
    10. Marion Maisonobe & Bastien Bernela, 2019. "Exploring the borders of a transregional knowledge network. The case of a French research federation in green chemistry," Post-Print hal-02053595, HAL.
    11. Neave O'Clery & Samuel Heroy & Francois Hulot & Mariano Beguerisse-D'iaz, 2019. "Unravelling the forces underlying urban industrial agglomeration," Papers 1903.09279, arXiv.org, revised Jun 2019.
    12. Chengliang Liu & Tao Wang & Qingbin Guo, 2018. "Factors Aggregating Ability and the Regional Differences among China’s Urban Agglomerations," Sustainability, MDPI, vol. 10(11), pages 1-20, November.

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    More about this item

    Keywords

    innovation clusters; network analysis; bio-pharmaceutical industry;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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