Yikun Liu, Sung Pil Moon, Mark Pfaff, Jill L. Drury, & Gary L. Klein. (2011). Collaborative option awareness for emergency response decision making. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: We have been using exploratory modeling to forecast multiple plausible outcomes for a set of decision options situated in the emergency response domain. Results were displayed as a set of box-plots illustrating outcome frequencies distributed across an evaluative dimension (e.g., cost, score, or utility). Our previous research showed that such displays provide what we termed “option awareness” – an ability to determine robust options that will have good outcomes across the broadest number of plausible futures. This paper describes an investigation into extending this approach to collaborative decision making by providing a visualization of both collaborative and individual decision spaces. We believe that providing such visualizations will be particularly important when each individuals decision space does not account for the synergy that may emerge from collaboration. We describe how providing collaborative decision spaces improves the robustness of joint decisions and engenders high confidence in these decisions.
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Jill L. Drury, Loretta More, Mark Pfaff, & Gary L. Klein. (2009). A principled method of scenario design for testing emergency response decision-making. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: We are investigating decision aids that present potential courses of action available to emergency responders. To determine whether these aids improve decision quality, however, we first developed test scenarios that were challenging in well-understood ways to ensure testing under the full breadth of representative decision-making situations. We devised a three-step method of developing scenarios: define the decision space, determine the cost components of each decision's potential consequences based on the principles of Robust Decision Making, then choose conflicting pairs of cost components (e.g., a small fire, implying low property damage, in a densely inhabited area, which implies high personal injury). In a validation of this approach, experiment participants made decisions faster in non-ambiguous cases versus cases that included this principled introduction of ambiguity. Our Principled Ambiguity Method of scenario design is also appropriate for other domains as long as they can be analyzed in terms of costs of decision alternatives.
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