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Exponential random graph models for management research: A case study of executive recruitment

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  • Arrieta-Paredes, Mary-Paz
  • Cronin, Bruce

Abstract

We introduce a recent development in the statistical analysis of relational data that offers rigorous discrimination of a variety of structural and behavioural effects of interest to management research. Exponential random graph models account for the highly interdependent nature of network data that are problematic for the predominant inferential statistical analysis used in management research. We illustrate the value of the approach with an application focused on executive recruitment by large UK firms, modelling migrations of managers among firms as a network of relationships. We find rigorous statistical support for the influences of industry origin in executive recruitment, particularly in relation to legal and accounting activities. The flexibility and sophisticated relational variables available in the models offer considerable analytical power of value to a wide range of management applications.

Suggested Citation

  • Arrieta-Paredes, Mary-Paz & Cronin, Bruce, 2017. "Exponential random graph models for management research: A case study of executive recruitment," European Management Journal, Elsevier, vol. 35(3), pages 373-382.
  • Handle: RePEc:eee:eurman:v:35:y:2017:i:3:p:373-382
    DOI: 10.1016/j.emj.2016.08.002
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    More about this item

    Keywords

    Executive recruitment; Industry origin; Managerial performance; Shareholder value; Social network analysis; Exponential random graph models;
    All these keywords.

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance

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