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Why Scientists Chase Big Problems: Individual Strategy and Social Optimality

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arxiv 1605.05822 v2 pith:QHTDN54H submitted 2016-05-19 physics.soc-ph

classification physics.soc-ph
keywords scientistscollectiveproblemsciencediscoveryopenpartialproblems
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Scientists pursue collective knowledge, but they also seek personal recognition from their peers. When scientists decide whether or not to work on a big new problem, they weigh the potential rewards of a major discovery against the costs of setting aside other projects. These self-interested choices can potentially spread researchers across problems in an efficient manner, but efficiency is not guaranteed. We use simple economic models to understand such decisions and their collective consequences. Academic science differs from industrial R&D in that academics often share partial solutions to gain reputation. This convention of Open Science is thought to accelerate collective discovery, but we find that it need not do so. The ability to share partial results influences which scientists work on a particular problem; consequently, Open Science can slow down the solution of a problem if it deters entry by important actors.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. How competition propels scientific risk-taking

    physics.soc-ph 2025-09 accept novelty 6.0 of 10

    A game-theoretic model of multi-prize contests shows that competition for scarce scientific rewards drives researchers toward riskier, higher-return projects.

  2. The unintended consequences of large language models as a labor-augmenting technology in science

    physics.soc-ph 2026-07 conditional novelty 5.0 of 10

    LLM speed-ups in discovery or production raise the opportunity cost of researcher time, making scientists more selective in some phases, less thorough in most, and only deeper when follow-up work itself is accelerated.

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