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The area of naturalistic decision making (NDM) emerged from concerns with classical decision making research and behavioral decision theory, where it was seen that people tended to systematically deviate from the rational choice even when presented with relatively simple tasks. Some researchers, such as Dr. Gary Klein, contended that real world settings include complexities that were being lost in studies of classical decision making. Therefore, the defining features of NDM became uncertain and dynamic environments, shifting vague or competing goals, multiple event feedback loops, time constraints, high stakes, and multiple actors (i.e., teams).
Decisions are broadly defined as committing to a course of action. NDM researchers discovered that people with domain expertise did not adhere to the normative, formal choice models of classical decision making. Experts were not comparing decision alternatives, but instead were more likely to use pattern matching and informal reasoning to quickly select a course of action that is typically appropriate for the situation and is therefore expected to be successful. Consequently, the aim of NDM became focused on describing the cognitive processes of proficient decision makers in context-bound scenarios by studying what information and cues these experts were actually using to reach a decision.
One of the primary contributions of NDM has been the recognition-primed decision (RPD) model. This model emerged from research examining experienced firefighters that demonstrated commanders were often not comparing any options when deciding how to attack a fire. How were they able to make good decisions with minimal time? It turns out, they typically carried out the first course of action identified. The RPD model states that experts recognize the current problem based on previously encountered situations. They identify a feasible course of action, and evaluate that possibility by performing mental simulation to imagine how the scenario would play out.
Naturalistic decision making methods aim to understand the conditions in which decisions are made, identify imperative skills and knowledge, and discover potential sources of error that lead to sub-optimal performance. Methods can be organized into three categories:
Field Studies - The majority of research is conducted in the natural domain environment. Knowledge elicitation may be accomplished through structured/unstructured interviews, retrospective analysis of critical incidents, expert drawing of domain maps, think-aloud protocols, and videos of task performance.
Critical Decision Method - Type of cognitive task analysis specifically focused on decision making that provides insights into challenging or unusual decisions. This technique utilizes multi-trial retrospection (i.e., three sweeps) of a specific incident identified by the participant from personal experience.
Simulations - When observation in the field is not possible due to concerns of task interference or safety, simulating the natural environment to elicit similar behavior in a controlled setting may be more appropriate. Simulations can be high-fidelity (i.e., closely resemble the real experience) or low-fidelity (i.e., leave out some elements of the real-life experience). Low-fidelity simulations are generally more static, but easier and cheaper to produce and often sufficient to elicit knowledge.
Laboratory techniques - Experimentation involves random assignment to experimental/control conditions, larger sample sizes, hypothesis testing, and statistical analysis. While these techniques may be considered more rigorous, most research questions relating to NDM are better addressed in the rich context of the unrestricted environment.
The recognition-primed decision model, from Klein (1993)
References
Gore, J., Flin, R., Stanton, N., & Wong, B. L. W. (2015). Applications for naturalistic decision-making. Journal of Occupational and Organizational Psychology, 88, 223-230. https://doi.org/10.1111/joop.12121
Klein, G. A. (1993). A recognition-primed decision (RPD) model of rapid decision making. In G.A. Klein, J. Orasanu, R. Calderwood, & C.E. Zsambok (Eds.). Decision making in action: models and methods. Norwood, CT: Ablex.
Lipshitz, R., Klein, G., Orasanu, J., & Salas, E. (2001). Taking stock of naturalistic decision making. Journal of Behavioral Decision Making, 14, 331-352. https://doi.org/10.1002/bdm.381
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