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Evaluating proposals in innovation contests: Exploring negative scoring spillovers in the absence of a strict evaluation sequence

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  • Elhorst, Paul
  • Faems, Dries

Abstract

Prior research demonstrated that, when a strict evaluation sequence is present in innovation contests, the score of the previously evaluated proposal negatively influences the scoring of a subsequent proposal. In this paper, we expand our understanding of such negative scoring spillovers by analysing a setting where not only the previously evaluated proposal, but all other proposals within the same meeting can potentially contribute to negative scoring spillovers. We rely on a sample of 561 proposals in 53 publicly funded innovation contests, launched within the scope of four regional innovation programs in the Netherlands. We also introduce an alternative methodological approach with peer effects to adequately model and test the existence of negative scoring spillovers in contests where a strict evaluation sequence is absent. We provide evidence that, in such contests, proposals can mutually influence each other and that the magnitude of these spillovers depends on the design of the innovation contest. We also discuss the implications of these findings for the specific literature on innovation contests and the broader literature on evaluation spillovers in decision-making processes.

Suggested Citation

  • Elhorst, Paul & Faems, Dries, 2021. "Evaluating proposals in innovation contests: Exploring negative scoring spillovers in the absence of a strict evaluation sequence," Research Policy, Elsevier, vol. 50(4).
  • Handle: RePEc:eee:respol:v:50:y:2021:i:4:s0048733321000020
    DOI: 10.1016/j.respol.2021.104198
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    Cited by:

    1. Kok, Holmer & Faems, Dries & de Faria, Pedro, 2022. "Pork Barrel or Barrel of Gold? Examining the performance implications of earmarking in public R&D grants," Research Policy, Elsevier, vol. 51(7).

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    More about this item

    Keywords

    Innovation; Funding; Peer effects; Evaluation spillovers;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D7 - Microeconomics - - Analysis of Collective Decision-Making
    • H25 - Public Economics - - Taxation, Subsidies, and Revenue - - - Business Taxes and Subsidies
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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