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Determinants of cross-regional R and D collaboration networks: an application of exponential random graph models

Author

Listed:
  • Tom Broekel

    (Institue of Economic and Cultural Geography, Leibnitz-University of Hannover)

  • Matte Hartog

    (Section of Economic Geography, Faculty of Geosciences, Utrecht University)

Abstract

This study investigates the usefulness of exponential random graph models (ERGM) to analyze the determinants of cross-regional R and D collaboration networks. Using spatial interaction models, most research on R and D collaboration between regions is constrained to focus on determinants at the node level (e.g. R and D activity of a region) and dyad level (e.g. geographical distance between regions). ERGMs represent a new set of network analysis techniques that have been developed in recent years in mathematical sociology. In contrast to spatial interaction models, ERGMs additionally allow considering determinants at the structural network level while still only requiring cross-sectional network data. The usefulness of ERGMs is illustrated by an empirical study on the structure of the cross-regional R and D collaboration network of the German chemical industry. The empirical results confirm the importance of determinants at all three levels. It is shown that in addition to determinants at the node and dyad level, the structural network level determinant “triadic closure†helps in explaining the structure of the network. That is, regions that are indirectly linked to each other are more likely to be directly linked as well.

Suggested Citation

  • Tom Broekel & Matte Hartog, 2013. "Determinants of cross-regional R and D collaboration networks: an application of exponential random graph models," Working Papers on Innovation and Space 2013-04, Philipps University Marburg, Department of Geography.
  • Handle: RePEc:pum:wpaper:2013-04
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    References listed on IDEAS

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    Cited by:

    1. Peng, Tai-Quan, 2015. "Assortative mixing, preferential attachment, and triadic closure: A longitudinal study of tie-generative mechanisms in journal citation networks," Journal of Informetrics, Elsevier, vol. 9(2), pages 250-262.
    2. Iris Wanzenböck, 2016. "Measuring network proximity of regions in R&D networks," Innovation Studies Utrecht (ISU) working paper series 16-03, Utrecht University, Department of Innovation Studies, revised Nov 2016.

    More about this item

    Keywords

    cross-regional R and D collaboration; exponential random graph models; network;

    JEL classification:

    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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