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The mechanisms of labor division from the perspective of individual optimization

Author

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  • Zhu, Lirong
  • Chen, Jiawei
  • Di, Zengru
  • Chen, Liujun
  • Liu, Yan
  • Stanley, H. Eugene

Abstract

Although the tools of complexity research have been applied to the phenomenon of labor division, its underlying mechanisms are still unclear. Researchers have used evolutionary models to study labor division in terms of global optimization, but focusing on individual optimization is a more realistic, real-world approach. We do this by first developing a multi-agent model that takes into account information-sharing and learning-by-doing and by using simulations to demonstrate the emergence of labor division. We then use a master equation method and find that the computational results are consistent with the results of the simulation. Finally we find that the core underlying mechanisms that cause labor division are learning-by-doing, information cost, and random fluctuation.

Suggested Citation

  • Zhu, Lirong & Chen, Jiawei & Di, Zengru & Chen, Liujun & Liu, Yan & Stanley, H. Eugene, 2017. "The mechanisms of labor division from the perspective of individual optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 488(C), pages 112-120.
    • Handle: RePEc:eee:phsmap:v:488:y:2017:i:c:p:112-120
    DOI: 10.1016/j.physa.2017.06.024
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    References listed on IDEAS

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    Cited by:

    1. de Oliveira, Viviane M. & Campos, Paulo R.A., 2019. "The emergence of division of labor in a structured response threshold model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 153-162.
    2. Qin, Shipeng & Zhang, Gang & Tian, Haiyan & Hu, Wenjun & Zhang, Xiaoming, 2020. "Dynamics of asymmetric division of labor game with environmental feedback," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 543(C).

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