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The underlying geometry of organizational dynamics: similarity-based social space and labor flow network communities
Computational and Mathematical Organization Theory ( IF 1.8 ) Pub Date : 2017-11-13 , DOI: 10.1007/s10588-017-9260-6
Hernan Mondani

In this article, we use Swedish longitudinal register data to study the effect that similarity in organizational properties has on the interaction between organizations. We map out the social space of large organizations in the Stockholm Region and the interplay between social distance and the network communities of employee movements between organizations. We firstly use homogeneity analysis to describe the dynamics of organizations in terms of the time evolution of their similarity. Our results show that most categorical variables are quite stable over time. Organizations linked through employee movement edges have a lower average distance in social space than non-linked organizations. Secondly, we look at network community dynamics in social space. Employee flows between organizations in different communities exhibit a so-called gravity law from spatial statistics, decaying more slowly than observed geographical networks, meaning that employees reach out regions of social space further than of physical space. Finally, the rate of change of distance in homogeneity space exhibits a statistical distribution similar to the ones found in various other growth processes in natural and man-made systems.

中文翻译:

组织动力的基本几何:基于相似性的社会空间和劳动力流动网络社区

在本文中,我们使用瑞典纵向注册数据来研究组织属性相似性对组织之间交互的影响。我们绘制了斯德哥尔摩地区大型组织的社交空间,以及社交距离与组织之间员工流动的网络社区之间的相互作用。我们首先使用同质性分析从组织相似性的时间演变来描述组织的动态。我们的结果表明,大多数分类变量随时间推移都相当稳定。通过员工活动边缘链接的组织在社交空间中的平均距离比未链接的组织要低。其次,我们研究社交空间中的网络社区动态。来自不同社区的组织之间的员工流动表现出一种从空间统计数据得出的引力定律,其衰减比观察到的地理网络慢得多,这意味着员工接触的社会空间范围要大于物理空间范围。最后,同质空间中距离的变化率表现出与自然和人造系统中各种其他生长过程相似的统计分布。
更新日期:2017-11-13
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