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Proposal of Intellectual Productivity Model Based on Work State Transition

  • Kazune Miyagi
  • Kotaro Oishi
  • Kosuke Uchiyama
  • Hirotake Ishii
  • Hiroshi Shimoda
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8019)

Abstract

Aiming to reveal the mechanism of intellectual productivity variation of office workers, the authors analyzed the behavior of subjective experiment assuming office work, and proposed an intellectual productivity model. The model is a three state transit model assuming “working state”, “short-term rest state” and “long-term rest state”. A subject experiment was conducted where illuminance on the desk and work motivation were controlled to vary their productivity. The result was analyzed with this model and it is confirmed that the model can explain the productivity variation.

Keywords

intellectual productivity human modeling working state illuminance 

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References

  1. 1.
    Lomonaco, G., Miller, D.: Environmental Satisfaction, Personal Control and the Positive Correlation to Increased Productivity. Johnson Controls, Inc. (1997)Google Scholar
  2. 2.
    Brill, M.: Using Office Design to Increase Productivity, vol. 1. Buffalo Workplace Design and Productivity Inc. (1984)Google Scholar
  3. 3.
    Enomoto, K., Kondo, Y., Obayashi, F., Iwakawa, M., Ishii, H., Shimoda, H., Terano, M.: An Experimental Study on Improvement of Office Work Productivity by Circadian Rhythm Light, WMSCI 2008, vol. 6, pp. 121–126 (2008)Google Scholar
  4. 4.
    Bills, A.G.: Blocking: A new principle of mental fatigue. American Journal of Psychology (43), 230–245 (1931)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Kazune Miyagi
    • 1
  • Kotaro Oishi
    • 1
  • Kosuke Uchiyama
    • 1
  • Hirotake Ishii
    • 1
  • Hiroshi Shimoda
    • 1
  1. 1.Graduate School of Energy ScienceKyoto UniversityJapan

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