This PhD project explores how cross-societal factors (such as beliefs, values and social norms shared by a cultural group) influence prosocial behavior. Below you can find an overview of the first of several subprojects within this general framework.
Incentives have surprisingly inconsistent effects when it comes to encouraging people to behave prosocially. Classical economic theory, according to which a specific behavior becomes more prevalent when it is rewarded, struggles to explain why incentives sometimes backfire. More recent theories therefore posit a reputational cost offsetting the benefits of receiving an incentive — yet unexplained effects of incentives remain, for instance across incentive types and countries. We propose that social norms can offer an explanation for these inconsistencies. Ultimately, social norms determine the reputational costs or benefits resulting from a given behavior, and thus variation in the effect of incentives may reflect variation in norms. We implemented a formal model of prosocial behavior integrating social norms, which we empirically tested on the real-world prosocial behavior of blood donation. Blood donation is essential for many life-saving medical procedures, but also presents an ideal testing ground for our theory: Various incentive policies for blood donors exist across countries, enabling a comparative approach. Our preregistered analyses reveal that social norms can indeed account for the varying effects of financial and time incentives on individual-level blood donation behavior across 28 European countries. Incentives are associated with higher levels of prosociality when norms regarding the incentive are more positive. The results indicate that social norms play an important role in explaining the relationship between incentives and prosocial behavior. More generally, our approach highlights the potential of integrating theory from across the economic and behavioral sciences to generate novel insights, with tangible consequences for policy-making.
If you want to learn more about this project, you can find it on the Open Science Framework and on GitHub . The preprint can be accessed here!
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