From network ties to network structures: Exponential Random Graph Models of interorganizational relations
Theoretical accounts of network ties between organizations emphasize the interdependence of individual intentions, opportunities, and actions embedded in local configurations of network ties. These accounts are at odds with empirical models based on assumptions of independence between network ties. As a result, the relation between models for network ties and the observed network structure of interorganizational fields is problematic. Using original fieldwork and data that we have collected on collaborative network ties within a regional community of hospital organizations we estimate newly developed specifications of Exponential Random Graph Models (ERGM) that help to narrow the gap between theories and empirical models of interorganizational networks. After controlling for the main factors known to affect partner selection decisions, full models in which local dependencies between network ties are appropriately specified outperform restricted models in which such dependencies are left unspecified and only controlled for statistically. We use computational methods to show that networks based on empirical estimates produced by models accounting for local network dependencies reproduce with accuracy salient features of the global network structure that was actually observed. We show that models based on assumptions of independence between network ties do not. The results of the study suggest that mechanisms behind the formation of network ties between organizations are local, but their specification and identification depends on an accurate characterization of network structure. We discuss the implications of this view for current research on interorganizational networks, communities, and fields. Copyright Springer Science+Business Media B.V. 2013
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 47 (2013)
Issue (Month): 3 (April)
|Contact details of provider:|| Web page: http://www.springer.com|
|Order Information:||Web: http://www.springer.com/economics/journal/11135|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Joel A. C. Baum & Robin Cowan & Nicolas Jonard, 2010.
"Network-Independent Partner Selection and the Evolution of Innovation Networks,"
INFORMS, vol. 56(11), pages 2094-2110, November.
- Baum, Joel & Cowan, Robin & Jonard, Nicolas, 2009. "Network-independent partner selection and the evolution of innovation networks," MERIT Working Papers 022, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
- Joel BAUM & Robin COWAN & Nicolas JONARD, 2009. "Network-independent partner selection and the evolution of innovation networks," Working Papers of BETA 2009-23, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
- Stuart, Toby E. & Yim, Soojin, 2010. "Board interlocks and the propensity to be targeted in private equity transactions," Journal of Financial Economics, Elsevier, vol. 97(1), pages 174-189, July.
- Piccardi, Carlo & Calatroni, Lisa & Bertoni, Fabio, 2010. "Communities in Italian corporate networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5247-5258.
- Stanley Wasserman & Philippa Pattison, 1996. "Logit models and logistic regressions for social networks: I. An introduction to Markov graphs andp," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 401-425, September.
- Hunter, David R. & Goodreau, Steven M. & Handcock, Mark S., 2008. "Goodness of Fit of Social Network Models," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 248-258, March.
- Brian Uzzi & Ryon Lancaster, 2003. "Relational Embeddedness and Learning: The Case of Bank Loan Managers and Their Clients," Management Science, INFORMS, vol. 49(4), pages 383-399, April. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:47:y:2013:i:3:p:1665-1685. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla)or (Rebekah McClure)
If references are entirely missing, you can add them using this form.