Intermittent Reinforcement and the Persistence of Behavior: Experimental Evidence

Whereas economists have made extensive studies of the impact of levels of incentives on behavior, they have paid little attention to the effects of regularity and frequency of incentives. We contrasted three ways of rewarding participants in a real-effort experiment in which individuals had to decide when to exit the situation : a continuous reinforcement schedule (all periods paid) ; a fixed intermittent reinforcement schedule (one out of three periods paid) ; and a random intermittent reinforcement schedule (one out of three periods paid on a random basis). In all treatments, monetary rewards were withdrawn after the same unknown number of periods. Overall, intermittent reinforcement leads to more persistence and higher total effort, while participants in the continuous condition exit as soon as payment stops or decrease effort dramatically. Randomness increases the dispersion of effort, inducing both early exiting and persistence in behavior ; overall, it reduces agents' payoffs. Our interpretation is that, in the presence of regime shifts, both the frequency and the randomness of the reinforcement schedules influence adjustments that participants make across time to their reference points in earnings expectations. This could explain why agents persist in activities although they lose money, such as excess trading in stock markets.Intermittent reinforcement ; ambiguity ; randomness ; incentives ; experiment

Intermittent Reinforcement and the Persistence of Behavior: Experimental Evidence

Whereas economists have made extensive studies of the impact of levels of incentives on behavior, they have paid little attention to the effects of regularity and frequency of incentives. We contrasted three ways of rewarding participants in a real-effort experiment in which individuals had to decide when to exit the situation: a continuous reinforcement schedule (all periods paid); a fixed intermittent reinforcement schedule (one out of three periods paid); and a random intermittent reinforcement schedule (one out of three periods paid on a random basis). In all treatments, monetary rewards were withdrawn after the same unknown number of periods. Overall, intermittent reinforcement leads to more persistence and higher total effort, while participants in the continuous condition exit as soon as payment stops or decrease effort dramatically. Randomness increases the dispersion of effort, inducing both early exiting and persistence in behavior; overall, it reduces agents’ payoffs. Our interpretation is that, in the presence of regime shifts, both the frequency and the randomness of the reinforcement schedules influence adjustments that participants make across time to their reference points in earnings expectations. This could explain why agents persist in activities although they lose money, such as excess trading in stock markets.randomness, ambiguity, intermittent reinforcement, incentives, experiment

Ambiguous incentives and the persistence of effort: Experimental evidence

International audienceWhen the assignment of incentives is uncertain, we study how the regularity and frequency of rewards and risk attitudes influence participation and effort. We contrast three incentive schemes in a real-effort experiment in which individuals decide when to quit : a continuous incentive scheme and two intermittent ones, fixed and random. In all treatments, we introduce a regime shift by withdrawing monetary rewards after the same unknown number of periods. In such an ambiguous environment, we show that less able and more risk averse players are less persistent in effort. Intermittent incentives lead to a greater persistence of effort, while continuous incentives entail exit as soon as payment stops. Randomness increases both earlier and later exiting. This selection effect in terms of ability and risk attitudes combined with the impact of intermittent rewards on persistence lead to an increase in mean performance after the regime shift when incentives are intermittent

The Effects of Financial Incentives in Experiments: A Review and Capital-Labor-Production Framework

We review 74 experiments with no, low, or high performance-based financial incentives. The modal result has no effect on mean performance (though variance is usually reduced by higher payment). Higher incentive does improve performance often, typically judgment tasks that are responsive to better effort. Incentives also reduce “presentation” effects (e.g., generosity and risk-seeking). Incentive effects are comparable to effects of other variables, particularly “cognitive capital” and task “production” demands, and interact with those variables, so a narrow-minded focus on incentives alone is misguided. We also note that no replicated study has made rationality violations disappear purely by raising incentives

The Effects of Financial Incentives in Experiments: A Review and Capital-Labor-Production Framework

We review 74 experiments with no, low, or high performance-based financial incentives. The modal result is no effect on mean performance (though variance is usually reduced by higher payment). Higher incentive does improve performance often, typically judgment tasks that are responsive to better effort. Incentives also reduce "presentation" effects (e.g., generosity and risk-seeking). Incentive effects are comparable to effects of other variables, particularly "cognitive capital" and task "production" demands, and interact with those variables, so a narrow-minded focus on incentives alone is misguided. We also note that no replicated study has made rationality violations disappear purely by raising incentives

Sense-making strategies in explorative intelligence analysis of network evolutions

Visualising how social networks evolve is important in intelligence analysis in order to detect and monitor issues, such as emerging crime patterns or rapidly growing groups of offenders. It remains an open research question how this type of information should be presented for visual exploration. To get a sense of how users work with different types of visualisations, we evaluate a matrix and a node-link diagram in a controlled thinking aloud study. We describe the sense-making strategies that users adopted during explorative and realistic tasks. Thereby, we focus on the user behaviour in switching between the two visualisations and propose a set of nine strategies. Based on a qualitative and quantitative content analysis we show which visualisation supports which strategy better. We find that the two visualisations clearly support intelligence tasks and that for some tasks the combined use is more advantageous than the use of an individual visualisation