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Are threshold-based financial incentive schemes more effective than proportional ones for driving behavior change?

Author

Listed:
  • Yves Arrighi
  • Fahariat Boukari
  • David Crainich
  • Léontine Goldzahl
  • Vincent Lenglin

    (ANTHROPO LAB - Laboratoire d'Anthropologie Expérimentale - ETHICS EA 7446 - Experience ; Technology & Human Interactions ; Care & Society : - ICL - Institut Catholique de Lille - UCL - Université catholique de Lille, ETHICS EA 7446 - Experience ; Technology & Human Interactions ; Care & Society : - ICL - Institut Catholique de Lille - UCL - Université catholique de Lille, UCL - Université catholique de Lille)

Abstract

While financial incentives are increasingly used in field experiments to change health behavior, little is known about which design would lead to the highest efficacy. This study investigates the relative efficacy of two financial incentive schemes, threshold-based and proportional, to encourage effort. The threshold-based scheme rewards participants only upon achieving a specific target, while the proportional scheme offers incremental rewards that increase with higher achievement. Our theoretical model predicts that subjects exert more efforts under the threshold-based scheme than under the proportional scheme. We test this prediction in a pre-registered lab experiment using a real-effort task. The results indicate no significant difference in overall performance between the two schemes. However, the threshold-based scheme demonstrates greater cost-effectiveness by incentivizing participants at a lower total expense. In non-preregistered analyses, we explore potentially different dynamics that could have led to that result.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Yves Arrighi & Fahariat Boukari & David Crainich & Léontine Goldzahl & Vincent Lenglin, 2025. "Are threshold-based financial incentive schemes more effective than proportional ones for driving behavior change?," Post-Print hal-05423616, HAL.
    • Handle: RePEc:hal:journl:hal-05423616
    DOI: 10.1007/s11238-025-10085-5
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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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