School of System science, Beijing Normal University, Beijing, China.
Department of Physics, Chalmers University of Technology, Gothenburg, Sweden.
PLoS One. 2023 Oct 23;18(10):e0287105. doi: 10.1371/journal.pone.0287105. eCollection 2023.
Many studies have shown that scaling laws widely exist in various complex systems, such as living organisms, cities, and online communities. In this research, we found that scaling laws also hold for companies. The macroscopic variables of companies, such as incomes, expenses, or total liability, all have power-law relationships with respect to the sizes of companies, which can be measured by sales, total assets, or the total number of employees. What is more, we also found the power law exponents always deviate from 1. That means large companies naturally have certain advantages, but the widely used financial indicators based on total volume or ratio may not reflect the company's status well because they are also size-dependent. To tackle this problem, this paper proposes a new set of evaluation indices based on the deviations of the macroscopic variables from the scaling law to eliminate the size-dependent effect. We found that the indicators based on deviations can give more reasonable evaluations for companies and can outperform other conventional indicators to predict the financial distress of companies.
许多研究表明,标度律广泛存在于各种复杂系统中,如生物体、城市和在线社区。在这项研究中,我们发现标度律也适用于公司。公司的宏观变量,如收入、支出或总负债,都与公司的规模呈幂律关系,可以用销售额、总资产或员工总数来衡量。更重要的是,我们还发现幂律指数总是偏离 1。这意味着大公司自然有一定的优势,但广泛使用的基于总量或比率的财务指标可能不能很好地反映公司的地位,因为它们也依赖于规模。为了解决这个问题,本文提出了一组基于宏观变量与标度律偏离的新的评价指标,以消除尺寸依赖性的影响。我们发现,基于偏差的指标可以更合理地评价公司,并能比其他传统指标更好地预测公司的财务困境。