ABSTRACT
Consistent with technological advances, the role of the operator in many human factors domains has evolved from one characterized primarily by sensory and motor skills to one characterized primarily by cognitive skills and decision making. Decision making is a primary component in problem solving, human-automation interaction, response to alarms and warnings, and error mitigation. In this chapter we discuss decision making in terms of both front-end judgment processes (e.g., attending to and evaluating the significance of cues and information, formulating a diagnosis, or assessing the situation) and back-end decision processes (e.g., retrieving a course of action, weighing one’s options, or mentally simulating a possible response). Two important metatheories—correspondence (empirical accuracy) and coherence (rationality and consistency)—provide ways to assess the goodness of each phase (e.g., Hammond, 1996, 2000; Mosier, 2009). We present several models of decision making, including Brunswik’s lens model, naturalistic decision making, and decision ladders, and discuss them in terms of their point of focus and their primary strategies and goals. Next, we turn the discussion to layers in the decision context: individual variables, team decision making, technology, and organizational influences. Last, we focus on applications and lessons learned: investigating, enhancing, designing, and training for decision making. Drawing heavily on sources such as the Human Factors journal, we present recent human factors research exploring these issues, models, and applications.
