Evaluating simulation-derived scenarios for effective decision support

Scenario planning traditionally relies on qualitative methods to choose its scenarios. Recently, quantitative decision support tools have also begun to facilitate such choices. This study uses behavioral experiments and structured decision-maker interviews to evaluate the results of “scenario discov...

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Vydáno v:Technological forecasting & social change Ročník 91; s. 64 - 77
Hlavní autoři: Parker, Andrew M., Srinivasan, Sinduja V., Lempert, Robert J., Berry, Sandra H.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Elsevier Inc 01.02.2015
Elsevier Science Ltd
Témata:
Algorithms
Computer based modeling
Computer simulation
Decision making
Decision support
Decision support systems
Decisions
Experiments
Interviews
Qualitative research
Quantitative analysis
Robust decision making
Scenario
Scenario discovery
Scenario planning
Simplicity
Simulation
Studies
Robust decision making
ANCOVA
SD
St.Dev
IL
PRIM
Decision making
IRP
Scenario discovery
PCA
Scenario
Decision support
ISSN:0040-1625, 1873-5509
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Shrnutí:Scenario planning traditionally relies on qualitative methods to choose its scenarios. Recently, quantitative decision support tools have also begun to facilitate such choices. This study uses behavioral experiments and structured decision-maker interviews to evaluate the results of “scenario discovery,” a quantitative method that defines scenarios as sets of future states of the world in which proposed policies fail to meet their goals. Statistical cluster-finding and principal component algorithms applied to large databases of computer simulation model results then help users to identify such scenarios. The two experiments examine the results of this process and demonstrate a user preference for increased accuracy and simplicity achieved through rotating the space of uncertain model input parameters, but primarily when the rotated parameters are conceptually similar. Interviews with experts suggest utility for both qualitatively- and quantitatively-derived scenarios. The former were easier to understand and had the most utility for scoping. The latter were perceived as containing more relevant information and having more utility for understanding tradeoffs and making choices among them. Overall, this study suggests the value of quantitative tools for facilitating scenario choice, while also highlighting the importance of formal evaluation in judging the utility of new methods for decision support. •Experiments and interviews evaluated utility of simulation-derived scenarios.•Dimensional rotation increased scenario accuracy and simplicity.•Subjects found these gains attractive, but only if rotating similar dimensions.•Experts found qualitative scenarios easier to understand and good for scoping.•Experts found quantitative scenarios more informative and decision relevant.
Bibliografie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0040-1625
1873-5509
DOI:10.1016/j.techfore.2014.01.010