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Working too much for too little: stochastic rewards cause work addiction

Brice Corgnet (), Simon Gaechter and Roberto Hernan Gonzalez ()
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Simon Gaechter: UON - University of Nottingham, UK

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Abstract: People are generally assumed to shy away from activities generating stochastic rewards, thus requiring extra compensation for handling any additional risk. In contrast with this view, neurosci-ence research with animals has shown that stochastic rewards may act as a powerful motivator. Applying these ideas to the study of work addiction in humans, and using a new experimental paradigm, we demonstrate how stochastic rewards may lead people to continue working on a repetitive and effortful task even after monetary compensation becomes saliently negligible. In line with our hypotheses, we show that persistence on the work task is especially pronounced when the entropy of stochastic rewards is high, which is also when the work task generates more stress to participants. We discuss the economic and managerial implications of our findings.

Keywords: Incentives; Work Addiction; Occupational Health; Experiments (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-exp
Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-02483337
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Working Paper: Working Too Much for Too Little: Stochastic Rewards Cause Work Addiction (2020) Downloads
Working Paper: Working too much for too little: stochastic rewards cause work addiction (2020) Downloads
Working Paper: Working Too Much for Too Little: Stochastic Rewards Cause Work Addiction (2020) Downloads
Working Paper: Working Too Much for Too Little: Stochastic Rewards Cause Work Addiction (2020) Downloads
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