Adaptive workforce exploration in complex productivity landscapes
Abstract
Specialization and task allocation enhance efficiency and innovation across diverse systems, from biological organisms to socioeconomic institutions. The evolution of task distribution and its influence on organizational productivity encapsulate the dynamics between task dependencies and adaptive strategies. We explore the organizational division of labor, inspired by the NK model of rugged landscapes, which is widely applied in evolutionary biology, and incorporate interdependencies among the attributes of technical experts within an organization. Our model considers two types of employees characterized by their task allocation strategies: specialists, who are permanently assigned to a single task, and generalists, who stochastically select a task at each time step. We investigate how the ruggedness of the productivity landscape, shaped by task interdependency, affects the organization's capacity to optimize labor division and meet market demands. Using group selection algorithms, we reveal the emergence of nonlinear adaptive dynamics, providing insights into how companies can adapt their strategies to meet market demands and foster innovation.
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BibTeX
@misc{granha2026adaptive,
title = {{Adaptive workforce exploration in complex productivity landscapes}},
author = {Mateus F. B. Granha and Igor V. G. de Oliveira and André L. M. Vilela and Chao Wang and Paulo R. A. Campos},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2608.27656},
eprint = {2608.27656},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.27656},
}
RIS
TY - UNPB
TI - Adaptive workforce exploration in complex productivity landscapes
AU - Mateus F. B. Granha
AU - Igor V. G. de Oliveira
AU - André L. M. Vilela
AU - Chao Wang
AU - Paulo R. A. Campos
PY - 2026
DA - 2026/08/27
PB - arXiv
DO - 10.48550/arxiv.2608.27656
UR - https://arxiv.org/abs/2608.27656
AB - Specialization and task allocation enhance efficiency and innovation across diverse systems, from biological organisms to socioeconomic institutions. The evolution of task distribution and its influence on organizational productivity encapsulate the dynamics between task dependencies and adaptive strategies. We explore the organizational division of labor, inspired by the NK model of rugged landscapes, which is widely applied in evolutionary biology, and incorporate interdependencies among the attributes of technical experts within an organization. Our model considers two types of employees characterized by their task allocation strategies: specialists, who are permanently assigned to a single task, and generalists, who stochastically select a task at each time step. We investigate how the ruggedness of the productivity landscape, shaped by task interdependency, affects the organization's capacity to optimize labor division and meet market demands. Using group selection algorithms, we reveal the emergence of nonlinear adaptive dynamics, providing insights into how companies can adapt their strategies to meet market demands and foster innovation.
ER -