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Predicting Research Productivity in STEM Faculty: The Role of Self-determined Motivation

Author

Listed:
  • Robert H. Stupnisky

    (University of North Dakota)

  • Vincent Larivière

    (University of Montreal)

  • Nathan C. Hall

    (McGill University)

  • Oluwamakinde Omojiba

    (University of North Dakota)

Abstract

How are university faculty members in STEM disciplines motivated to conduct research, and how does motivation predict their success? The current study assessed how multiple types of self-determined motivation predict research productivity in a sample of 651 faculty from 10 US institutions. Using structural equation modeling, the basic psychological needs of autonomy and competence predicted autonomous motivation (enjoyment, value) that, in turn, was the strongest predictor of self-reported research productivity. Using negative binomial regression, autonomous motivation was the strongest predictor of faculty publications and citations, with a one-standard deviation increase in autonomous motivation (approximately a half response option on a 1–5 Likert scale) corresponding to an 11.63% increase in publications and a 22.57% increase in citations over a three-year period. Occupational and social-environmental background variables (e.g., research percentage on contract, career age, balance, collegiality), as well as controlled motivation (guilt, rewards), had comparatively limited predictive effects. These results are of relevance to higher education institutions aiming to support scholarly productivity in STEM faculty in identifying specific beneficial and detrimental aspects of faculty motivation that contribute to measurable gains in research activity.

Suggested Citation

  • Robert H. Stupnisky & Vincent Larivière & Nathan C. Hall & Oluwamakinde Omojiba, 2023. "Predicting Research Productivity in STEM Faculty: The Role of Self-determined Motivation," Research in Higher Education, Springer;Association for Institutional Research, vol. 64(4), pages 598-621, June.
    • Handle: RePEc:spr:reihed:v:64:y:2023:i:4:d:10.1007_s11162-022-09718-3
    DOI: 10.1007/s11162-022-09718-3
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    References listed on IDEAS

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    1. Vincent Larivière & Éric Archambault & Yves Gingras & Étienne Vignola‐Gagné, 2006. "The place of serials in referencing practices: Comparing natural sciences and engineering with social sciences and humanities," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(8), pages 997-1004, June.
    2. Vincent Larivière & Chaoqun Ni & Yves Gingras & Blaise Cronin & Cassidy R. Sugimoto, 2013. "Bibliometrics: Global gender disparities in science," Nature, Nature, vol. 504(7479), pages 211-213, December.
    3. Philippe Mongeon & Adèle Paul-Hus, 2016. "The journal coverage of Web of Science and Scopus: a comparative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 213-228, January.
    4. Janet H. Lawrence & Sergio Celis & Molly Ott, 2014. "Is the Tenure Process Fair? What Faculty Think," The Journal of Higher Education, Taylor & Francis Journals, vol. 85(2), pages 155-192, March.
    5. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
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