IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/hal-05562955.html

Social Network Methods in Interorganizational Research

Author

Listed:
  • Peter Ebbes

    (HEC Paris - Ecole des Hautes Etudes Commerciales)

  • Stefan Wuyts

    (Penn State - Pennsylvania State University [State College, PA] - Penn State System)

Abstract

This chapter takes networks as the default lens for interorganizational research (IOR) in marketing, guiding readers from theory to practice. The chapter has four main contributions. First, we provide an overview of common pitfalls, suggested fixes, and a checklist to avoid them. Second, we offer a portable theories → constructs → metrics → data map that links key theoretical mechanisms to appropriate metrics and data requirements. We organize metrics in a macro-meso-micro scaffold, distinguishing macro-level network characteristics (e.g., degree distribution), meso-level characteristics (e.g., communities), and micro-level characteristics (e.g., network-position metrics). Third, we propose a two-by-two typology of empirical designs, unit of inference (node vs. tie) by dominant mechanism (ego-vs. structure-driven), that specifies characteristic covariates, identification needs, and statistical methods. Lastly, we offer a roadmap for future IOR research in marketing strategy. Throughout the chapter, we use a running boardinterlock example to make concrete the move from director-firm affiliations (two-mode) to firmfirm ties (one-mode), metric computation and interpretation, community detection considerations, and modeling board-interlock tie formation using Exponential Random Graph Models. Taken together, the chapter offers the reader a guide from foundations to data structures, metrics, and formation models in complex IOR settings.

Suggested Citation

  • Peter Ebbes & Stefan Wuyts, 2025. "Social Network Methods in Interorganizational Research," Working Papers hal-05562955, HAL.
  • Handle: RePEc:hal:wpaper:hal-05562955
    DOI: 10.2139/ssrn.5863162
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:wpaper:hal-05562955. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.