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Explaining the Structure of Inter-Organizational Networks using Exponential Random Graph Models

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  • Tom Broekel
  • Matté Hartog

Abstract

A key question raised in recent years is what factors determine the structure of inter-organizational networks. Most research so far has focused on different forms of proximity between organizations, namely geographical, cognitive, social, institutional and organizational proximity, which are all factors at the dyad level. However, recently, factors at the node and structural network levels have been highlighted as well. To identify the relative importance of factors at these three different levels for the structure of inter-organizational 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 factors at all different levels to matter. Out of different forms of proximity, only institutional and geographical proximity remains significant once we account for factors at the node and structural levels.

Suggested Citation

  • Tom Broekel & Matté Hartog, 2013. "Explaining the Structure of Inter-Organizational Networks using Exponential Random Graph Models," Industry and Innovation, Taylor & Francis Journals, vol. 20(3), pages 277-295, April.
  • Handle: RePEc:taf:indinn:v:20:y:2013:i:3:p:277-295
    DOI: 10.1080/13662716.2013.791126
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    File URL: http://hdl.handle.net/10.1080/13662716.2013.791126
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    Citations

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    Cited by:

    1. Horváth, Márton & Hau-Horváth, Orsolya, 2014. "A földrajzi közelség szerepe az innovációs együttműködésekben - illúzió vagy valós tényező?. Szakirodalmi áttekintés
      [The role of geographical proximity in efforts to cooperate on innovation - illu
      ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(12), pages 1419-1446.
    2. Tom Broekel & Pierre-Alexandre Balland & Martijn Burger & Frank van Oort, 2013. "Modeling Knowledge Networks in Economic Geography: A Discussion of Four Empirical Strategies," Papers in Evolutionary Economic Geography (PEEG) 1325, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Dec 2013.
    3. Ron Boschma & Pierre-Alexandre Balland & Mathijs de Vaan, 2014. "The formation of economic networks: a proximity approach," Chapters,in: Regional Development and Proximity Relations, chapter 7, pages 243-266 Edward Elgar Publishing.
    4. Tom Broekel & Wladimir Mueller, 2017. "Critical links in knowledge networks. What about proximities and gatekeeper organizations?," Papers in Evolutionary Economic Geography (PEEG) 1711, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jun 2017.

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