Researcher well-being as a leading indicator in research-funding governance: A system dynamics exploration of top-down versus bottom-up allocation

Tomoko Sakai and Satoshi Sano
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Tomoko Sakai: National Institute of Science and Technology Policy (NISTEP) Ministry of Education, Culture, Sports

No 3cr4x_v1, SocArXiv from Center for Open Science

Abstract: Governments face a recurring dilemma in dividing public research funding between top-down, competitive, mission-oriented programmes and bottom-up, investigator-led institutional grants. This research note presents an exploratory system dynamics model that endogenizes researcher motivation, conceived following self-determination theory as a slow-moving stock of psychological capital, within the feedback structure linking funding allocation, research outputs, and societal returns. Simulation experiments across three policy scenarios reveal a consistent time-asymmetric pattern. First, accelerating the shift toward competitive funding produces an earlier but lower peak in societal returns, followed by sustained decline. Second, shifting toward bottom-up funding restores motivation but opens a transition valley in returns whose depth grows with transition speed. Third, delayed corrective reallocation exhibits hysteresis: once motivation is depleted, even aggressive reallocation requires roughly two decades before returns recover. One-at-a-time sensitivity analysis indicates that these qualitative patterns persist across the tested parameter ranges, while the level of long-run returns proves highly sensitive to the weight placed on discretionary research time, around which the baseline system undergoes a regime shift. The model implies that researcher well-being functions as a leading indicator of research-system health, preceding declines in publication-based lagging indicators. We derive three testable propositions and outline an agenda for empirical calibration, beginning with a national baseline survey of researchers being launched in Japan. For funding governance, the results imply that monitoring leading indicators and pacing allocation transitions matter as much as choosing the allocation ratio itself.

Date: 2026-09-28
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:3cr4x_v1

DOI: 10.31235/osf.io/3cr4x_v1

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