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

机译:用于管理研究的指数随机图模型:高管招聘的案例研究

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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. (C) 2016 Elsevier Ltd. All rights reserved.
机译:我们在关系数据的统计分析中介绍了最新的发展,它对管理研究感兴趣的各种结构和行为效应进行了严格的区分。指数随机图模型说明了网络数据的高度相互依赖性,这对于管理研究中使用的主要推理统计分析是有问题的。我们通过一个针对大型英国公司高管招聘的应用程序来说明这种方法的价值,该应用程序将公司之间经理人的迁移建模为关系网络。我们发现行业起源对高管招聘的影响,尤其是与法律和会计活动有关的影响,提供了严格的统计支持。模型中可用的灵活性和复杂的关系变量为各种管理应用程序提供了相当可观的价值分析能力。 (C)2016 Elsevier Ltd.保留所有权利。

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