In this paper we present two simple mathematical models to describe human behavior in reaction to deadlines. When a real commitment (e.g. money) is involved, as in the case of a payment deadline, the expected reaction is to postpone it as close as possible to the deadline to minimize the risk of loosing the value. For low risk commitments this tendency is still present but expected to be looser. In order to test these predictions in a quantitative way, we performed data analysis for the total number of registrations and fee payments vs. time for the recent scientific conference "Statphys 23", comparing it with the data of another conference in order to recover universal features. Two related models respectively for registrations (weak engagement) and fee payment (strong engagement) are then introduced which are able to explain in a simple way both behaviors, and which show an excellent agreement with real data.
Alfi, V., Gabrielli, A., Pietronero, L. (2009). How people react to a deadline: Time distribution of conference registrations and fee payments. CENTRAL EUROPEAN JOURNAL OF PHYSICS, 7(3), 483-489 [10.2478/s11534-009-0059-z].
How people react to a deadline: Time distribution of conference registrations and fee payments
Gabrielli A.;
2009-01-01
Abstract
In this paper we present two simple mathematical models to describe human behavior in reaction to deadlines. When a real commitment (e.g. money) is involved, as in the case of a payment deadline, the expected reaction is to postpone it as close as possible to the deadline to minimize the risk of loosing the value. For low risk commitments this tendency is still present but expected to be looser. In order to test these predictions in a quantitative way, we performed data analysis for the total number of registrations and fee payments vs. time for the recent scientific conference "Statphys 23", comparing it with the data of another conference in order to recover universal features. Two related models respectively for registrations (weak engagement) and fee payment (strong engagement) are then introduced which are able to explain in a simple way both behaviors, and which show an excellent agreement with real data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.