Behavioral decision making and game theory (BDMGT) is the umbrella term for a set of methods aimed at recording the choices and eliciting the decision preferences of individuals (organizational agents like managers, employees, entrepreneurs, investors, or consumers). BDMGT comprises a set of well-defined decision problems that, in contrast to surveys or questionnaires that rely on self-assessment, evaluate actual behavioral choices with well-defined outcomes and choice parameters. Additionally, in contrast to idealized models, BDMGT focuses on actual decision-making processes. BDMGT allows for dynamic and complex decision scenarios that are nevertheless computationally tractable and have lower linguistic demands (thus making inter-group and cross-cultural comparisons easier).
BDMGT decision problems can be broadly categorized as either individual (i.e., where the agent acts against nature or luck, and all outcomes return to the agent) or social (i.e., where [at least one] another agent—“the partner”—is involved). Social decisions can be further defined as either non-strategic (i.e., where the partner makes no decisions, but some of the outcomes can be returned to them) or strategic (i.e., where the partner makes decisions that can affect the final outcomes returned to the agent). Examples of generic research questions for individual decision tasks include how risk influences decisions (i.e., measuring risk preferences) or (for social decision tasks) how agents interact with each other (i.e., how they allocate resources, what they consider fair, how they build trust, or how they coordinate to achieve common strategic goals).
The present entry focuses on the methodological aspects of BDMGT. There are major methodological considerations and common pitfalls associated with BDMGT that can bias results and their interpretation, including incentives and how participants should be paid, anonymity, double-blinding (and when this is not enough), social desirability, how the “partner” participant is explained, or what issues may arise with repeated decisions or trials. The field has also seen the introduction of newer but well-established developments in the field, such as computerized testing, decision neuroscience, and augmented and virtual reality.
