The laboratory

The BEL is a multidisciplinary and state of the art research facility for studying individual and group decision-making in a controlled experimental setting. It is a laboratory consisting of 19 PCs, separated by privacy blinds, which are interconnected in order to allow real-time interactions between lab participants, either individually or as groups. The BEL contains a projector and screen for the delivery of experimental instructions, and space for experiments involving communication between participants, teamwork, or group interviews.


Experimental control

Nearly all of the experiments conducted in the BEL are administered via computer. The BEL can be used to perform networked experiments, which examine the decision making of multiple interacting participants or groups of participants, as well as stand-alone experiments, which examine the decision making of individual participants. At present, we use three different pieces of software for executing and controlling our experiments:

Participant recruitment

Participant recruitment within the lab is administered using ORSEE (Online Recruitment System for Economic Experiments), a web-based Online Recruitment System specifically designed for organizing economic experiments. ORSEE is a software tool that allows researchers to schedule experiment sessions and recruit participants. It tracks experiment participation and provides information about the subject pool and recruitment procedures of a study. The software simplifies the organization of economic laboratory experiments, allows for the standardization of the procedures of experiment organization, and provides information and statistics about the subject pool and recruitment procedures. The software is published under an open source license and can be downloaded and used free of charge.

Data analysis & modelling

We also use MATLAB for data pre-processing, and computational and mathematical modelling, whereas data analysis is largely conducted using R. R is a language and environment for statistical computing and graphics. It provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering) and graphical techniques, and is highly extensible. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced. It is available on a wide variety of platforms as Free Software.