Vincent Theroude
Research Subjects
Research Interests
Vincent Theroude has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Ilke Aydogan
IESEG School of Management, Univ. Lille, CNRS, UMR 9221 - LEM - Lille Economie Management, F-59000 Lille, France, and iRisk Research Center on Risk and Uncertainty
1 shared publication - Loïc Berger
CMCC Foundation - Euro-Mediterranean Center on Climate Change, Lecce, Italy
1 shared publication Vincent Théroude
Centro Euro- Mediterraneo sui Cambiamenti Climatici Italy
1 shared publication
Latest Publications
- Open Access
Pay all subjects or pay only some? An experiment on decision-making under risk and ambiguity
We investigate the validity of a double random incentive system where only a subset of subjects is paid for one of their choices. By focusing on individual decision-making under risk and ambiguity, we show that using either a standard random incentive system, where all subjects are paid, or a double random system, where only 10% of subjects are paid, yields similar preference elicitation results. These findings suggest that adopting a double random incentive system could significantly reduce experimental costs and logistic efforts, thereby facilitating the exploration of individual decision-making in larger-scale and higher-stakes experiments.
Open AccessPay all subjects or pay only some? An experiment on decision-making under risk and ambiguity
We investigate the validity of a double random incentive system where only a subset of subjects is paid for one of their choices. By focusing on individual decision-making under risk and ambiguity, we show that using either a standard random incentive system, where all subjects are paid, or a double random system, where only 10% of subjects are paid, yields similar preference elicitation results. These findings suggest that adopting a double random incentive system could significantly reduce experimental costs and logistic efforts, thereby facilitating the exploration of individual decision-making in larger-scale and higher-stakes experiments.