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Organizational design of University laboratories: Task allocation and lab performance in Japanese bioscience laboratories

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  • Shibayama, Sotaro
  • Baba, Yasunori
  • Walsh, John P.

Abstract

A university laboratory is a fundamental unit of scientific production, but optimizing its organizational design is a formidable task for lab heads, who play potentially conflicting roles of manager, educator, and researcher. Drawing on cross-sectional data from a questionnaire survey and bibliometric data on Japanese biology professors, this study investigates task allocation inside laboratories. Results show a general pattern that lab heads play managerial roles and members (e.g., students) are engaged in labor-intensive tasks (e.g., experiment), while revealing a substantial variation among laboratories. Further examining how this variation is related to lab-level scientific productivity, this study finds that productive task allocation differs by context. In particular, results suggest that significant task overlap across status hierarchies is more productive for basic research, and that rigidly separated task allocation is more productive in applied research. However, optimal task allocation, with regard to scientific productivity, might conflict with other goals of academic organizations, particularly training of future scientists. The paper concludes with a discussion of the policy implications of these findings.

Suggested Citation

  • Shibayama, Sotaro & Baba, Yasunori & Walsh, John P., 2015. "Organizational design of University laboratories: Task allocation and lab performance in Japanese bioscience laboratories," Research Policy, Elsevier, vol. 44(3), pages 610-622.
  • Handle: RePEc:eee:respol:v:44:y:2015:i:3:p:610-622
    DOI: 10.1016/j.respol.2014.12.003
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    2. Noriyuki Morichika & Sotaro Shibayama, 2016. "Use of dissertation data in science policy research," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 221-241, July.
    3. Yaqub, Ohid & Coburn, Josie & Moore, Duncan A.Q., 2023. "Knowledge spillovers from HIV research-funding," SocArXiv gcuhn, Center for Open Science.
    4. Walsh, John P. & Lee, You-Na & Tang, Li, 2019. "Pathogenic organization in science: Division of labor and retractions," Research Policy, Elsevier, vol. 48(2), pages 444-461.
    5. Sotaro Shibayama & Yoshie Kobayashi, 2017. "Impact of Ph.D. training: a comprehensive analysis based on a Japanese national doctoral survey," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 387-415, October.
    6. Aldo Geuna & Sotaro Shibayama, 2015. "Moving Out Of Academic Research: Why Scientists Stop Doing Research?," SPRU Working Paper Series 2015-01, SPRU - Science Policy Research Unit, University of Sussex Business School.
    7. Alessandro Muscio & Sotaro Shibayama & Laura Ramaciotti, 2022. "Universities and start-up creation by Ph.D. graduates: the role of scientific and social capital of academic laboratories," The Journal of Technology Transfer, Springer, vol. 47(1), pages 147-175, February.
    8. Qinwei Cao & Peng Xie & Meng Jiao & Wanchun Duan, 2021. "The larger scientific and technological human scale, the better innovation effect? Evidence from key universities in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5623-5649, July.
    9. Corsini, Alberto & Pezzoni, Michele & Visentin, Fabiana, 2022. "What makes a productive Ph.D. student?," Research Policy, Elsevier, vol. 51(10).
    10. Haeussler, Carolin & Sauermann, Henry, 2020. "Division of labor in collaborative knowledge production: The role of team size and interdisciplinarity," Research Policy, Elsevier, vol. 49(6).
    11. Koehler, Maximilian & Sauermann, Henry, 2024. "Algorithmic management in scientific research," Research Policy, Elsevier, vol. 53(4).
    12. Walsh, John P. & Lee, You-Na, 2015. "The bureaucratization of science," Research Policy, Elsevier, vol. 44(8), pages 1584-1600.
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    16. Good, Matthew & Knockaert, Mirjam & Soppe, Birthe & Wright, Mike, 2019. "The technology transfer ecosystem in academia. An organizational design perspective," Technovation, Elsevier, vol. 82, pages 35-50.

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