团队规模很重要:协同效应和减少绩效排名的不平等

IF 3.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Physica A: Statistical Mechanics and its Applications Pub Date : 2025-05-01 Epub Date: 2025-03-08 DOI:10.1016/j.physa.2025.130496
Sandro M. Reia , Dieter Pfoser , Paulo R.A. Campos
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引用次数: 0

摘要

当代社会经常采用基于精英原则的排名系统来评估和奖励个人的表现。然而,这些系统可能会产生意想不到的后果,影响创造力和平等。本研究提出了一个排名绩效模型的统计分析,以检查这些系统对社会动态的影响。利用模拟方法,我们探讨了模仿在决定个体成功中的作用,以及这些动态如何影响整体群体生产力和不平等。我们的研究结果揭示了增加群体规模和提高集体产出同时减少个人绩效不平等的协同效应。此外,我们研究了随机图、无标度和小世界网络上的社会动态,以了解网络拓扑结构的影响,结果表明群体内的连通性对性能和不平等都有显著影响。我们的结果还表明,高聚类与短路径长度相结合可以减少不平等。这些发现为优化排名系统提供了见解,以平衡基于绩效的认可与创新和平等的需要,并提出了增强团队协同作用的策略。
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Group size matters: Synergistic effects and reduced inequality in performance rankings
Contemporary society often employs ranking systems to evaluate and reward individual performances based on meritocratic principles. However, these systems can have unintended consequences, impacting creativity and equality. This study presents a statistical analysis of a ranking performance model to examine the implications of these systems on social dynamics. Using a simulation approach, we explore the role of imitation in determining individuals’ success and how these dynamics influence overall group productivity and inequality. Our results unveil a synergistic effect of increasing group size and enhancing collective output while reducing individual performance inequality. Additionally, we investigate the social dynamics on random graphs, scale-free, and small-world networks to understand the influence of network topology, showing that connectivity within the group significantly influences both performance and inequality. Our results also demonstrate that high clustering combined with short path lengths reduces inequalities. These findings provide insights into optimizing ranking systems to balance merit-based recognition with the need for innovation and equality, suggesting strategies to enhance group synergy.
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来源期刊
CiteScore
7.20
自引率
9.10%
发文量
852
审稿时长
6.6 months
期刊介绍: Physica A: Statistical Mechanics and its Applications Recognized by the European Physical Society Physica A publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents. Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.
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