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Optimal scientific production over the life cycle

Author

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  • Feichtinger, G.
  • Grass, D.
  • Kort, P.M.

Abstract

The paper develops an optimization model of the career of a scientist. Recognizing that research efforts and networking get more efficient if the scientist is more knowledgeable, history dependent solutions are developed. We give a theoretical underpinning of the four different research patterns detected in Way et al. (2017, Proceedings of the National Academy of Sciences). If the scientist does not bother about his reputation at the end of his career, we show that a sufficient education level is needed for the scientist to develop a typical research pattern where productivity increases in the beginning of his career, while it declines towards retirement. If the education level is not sufficient, a fading research pattern will result where productivity declines over time. On the other hand, when the scientist appreciates to have a good reputation at the end of his career, sufficient education will result in increasing productivity over the career lifetime, preventing a midlife slump.

Suggested Citation

  • Feichtinger, G. & Grass, D. & Kort, P.M., 2019. "Optimal scientific production over the life cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    • Handle: RePEc:eee:dyncon:v:108:y:2019:i:c:s0165188918302781
    DOI: 10.1016/j.jedc.2019.103752
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    Cited by:

    1. Xu, Jing, 2022. "Competition and equilibrium effort choice," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    2. Feichtinger, Gustav & Grass, Dieter & Kort, Peter M. & Seidl, Andrea, 2021. "On the Matthew effect in research careers," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
    3. A. J. Novák & G. Feichtinger, 2022. "Accumulation and obsolescence of research knowledge," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(4), pages 1151-1166, December.
    4. Peng, Xianzhe & Xu, Huixin & Shi, Jin, 2024. "Are the bibliometric growth patterns of excellent scholars similar? From the analysis of ACM Fellows," Journal of Informetrics, Elsevier, vol. 18(3).

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