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Explaining the structure of inter-organizational networks using exponential random graph models: does proximity matter?


  • Tom Broekel


  • Matte Hartog



A key question raised in recent years is which factors determine the structure of inter-organizational networks. While the focus has primarily been on different forms of proximity between organizations, which are determinants at the dyad level, recently determinants at the node and structural level have been highlighted as well. To identify the relative importance of determinants at these three different levels for the structure of networks that are observable at only one point in time, we propose the use of exponential random graph models. Their usefulness is exemplified by an analysis of the structure of the knowledge network in the Dutch aviation industry in 2008 for which we find determinants at all different levels to matter. Out of different forms of proximity, we find that once we control for determinants at the node and structural network level, only social proximity remains significant.

Suggested Citation

  • Tom Broekel & Matte Hartog, 2011. "Explaining the structure of inter-organizational networks using exponential random graph models: does proximity matter?," Papers in Evolutionary Economic Geography (PEEG) 1107, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Apr 2011.
  • Handle: RePEc:egu:wpaper:1107

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    References listed on IDEAS

    1. Corinne Autant-Bernard & Pascal Billand & David Frachisse & Nadine Massard, 2007. "Social distance versus spatial distance in R&D cooperation: Empirical evidence from European collaboration choices in micro and nanotechnologies," Papers in Regional Science, Wiley Blackwell, vol. 86(3), pages 495-519, August.
    2. Jarno Hoekman & Koen Frenken & Frank Oort, 2009. "The geography of collaborative knowledge production in Europe," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 43(3), pages 721-738, September.
    3. Anne Ter Wal & Ron Boschma, 2009. "Applying social network analysis in economic geography: framing some key analytic issues," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 43(3), pages 739-756, September.
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    Cited by:

    1. Cilem Selin Hazir & Corinne Autant-Bernard, 2012. "Using Affiliation Networks to Study the Determinants of Multilateral Research Cooperation Some empirical evidence from EU Framework Programs in biotechnology," Working Papers 1212, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    2. 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.

    More about this item


    exponential random graph models; inter-organizational network structure; network analysis; proximity; aviation industry; economic geography;

    JEL classification:

    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L62 - Industrial Organization - - Industry Studies: Manufacturing - - - Automobiles; Other Transportation Equipment; Related Parts and Equipment

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