Webb Frank, Stimpson Daniel, Purcell Miesha, López Eduardo
Department of Computational and Data Sciences, George Mason University, Fairfax, VA 22030, USA.
United States Army Acquisition Support Center (USAASC), 9900 Belvoir Road, Fort Belvoir, VA 22060, USA.
Entropy (Basel). 2023 May 11;25(5):784. doi: 10.3390/e25050784.
The movement of employees within an organization is a research area of great relevance in a variety of fields such as economics, management science, and operations research, among others. In econophysics, however, only a few initial incursions have been made into this problem. In this paper, based on an approach inspired by the concept of labor flow networks which capture the movement of workers among firms of entire national economies, we construct empirically calibrated high-resolution networks of internal labor markets with nodes and links defined on the basis of different descriptions of job positions, such as operating units or occupational codes. The model is constructed and tested for a dataset from a large U.S. government organization. Using two versions of Markov processes, one without and another with limited memory, we show that our network descriptions of internal labor markets have strong predictive power. Among the most relevant findings, we observe that the created by our method based on operational units possess a power law feature consistent with the distribution of firm sizes in an economy. This signals the surprising and important result that this regularity is pervasive across the landscape of economic entities. We expect our work to provide a novel approach to study careers and help connect the different disciplines that currently study them.
员工在组织内部的流动是经济学、管理科学和运筹学等诸多领域中一个极具相关性的研究领域。然而，在经济物理学中，对这个问题的研究才刚刚起步。在本文中，基于受劳动力流动网络概念启发的一种方法，该概念捕捉了整个国民经济中企业间工人的流动情况，我们构建了经过实证校准的内部劳动力市场高分辨率网络，其节点和链接是根据工作岗位的不同描述（如运营单位或职业代码）来定义的。该模型是针对一个大型美国政府组织的数据集构建并进行测试的。使用两种版本的马尔可夫过程，一种无记忆，另一种有有限记忆，我们表明我们对内部劳动力市场的网络描述具有很强的预测能力。在最相关的发现中，我们观察到基于运营单位的方法所创建的[此处原文缺失具体内容]具有与经济中企业规模分布一致的幂律特征。这表明了一个令人惊讶且重要的结果，即这种规律性在经济实体领域中普遍存在。我们期望我们的工作能为研究职业提供一种新方法，并有助于将目前研究职业的不同学科联系起来。
