A computational study of promotion dynamics and organizational efficiency

Yuan Cheng, Meng Chang and Yanbo Xue

Physica A: Statistical Mechanics and its Applications, 2020, vol. 560, issue C

Abstract: We propose a new computational model for observing organizational efficiency and promotion dynamics. Different from the previous research, we study the influence of correlation degree between various levels of positions and uncertainty in the promotion process on organizational efficiency. We set up the model in three perspectives: overall, level-by-level and individual career path inside the organization. We also introduce two promotion evaluation mechanisms: myopic and look-ahead. Simulation results show that organizational efficiency increases as the correlation degree increases, and decreases as the uncertainty in the evaluation system for promotion increases. It is found that if the uncertainty is small and the correlation degree is high, employees at higher levels will have higher efficiency and, if the correlation degree is low and the uncertainty is large, employees at the lowest level perform the best while mid-level employees perform the worst. This work can provide new insights for understanding the long-tested Peter Principle.

Keywords: Agent-based model; Complex system; Promotion dynamics; Organizational efficiency; Peter Principle (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:560:y:2020:i:c:s0378437120306233

DOI: 10.1016/j.physa.2020.125194

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