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

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

Arrieta-Paredes, Mary-Paz and Cronin, Bruce (2016) Exponential random graph models for management research: a case study of executive recruitment. European Management Journal, 35 (3). pp. 373-382. ISSN 0263-2373 (doi:10.1016/j.emj.2016.08.002)

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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 (ERGMs) account for the highly interdependent nature of network data that is 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.

Item Type: Article
Additional Information: © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: Executive recruitment, industry origin, managerial performance, shareholder value, social network analysis, exponential random graph models.
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
H Social Sciences > HG Finance
H Social Sciences > HM Sociology
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Centre for Business Network Analysis
Faculty of Business > Department of International Business & Economics
Last Modified: 28 Sep 2017 09:55
Selected for GREAT 2016: None
Selected for GREAT 2017: GREAT b
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/15698

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