Parallel Constraint Satisfaction in Memory-Based Decisions

31 Pages Posted: 7 Jul 2009

See all articles by Andreas Glöckner

Andreas Glöckner

Max Planck Institute for Research on Collective Goods; University of Cologne

Sara D. Hodges

University of Oregon

Date Written: June 2009


Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time pressure conditions and even with decision times as short as 1.7 seconds. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

Keywords: Memory-Based Decision Making, Parallel Constraint Satisfaction, Fast and Frugal Heuristics, Automatic Information Integration

Suggested Citation

Glöckner, Andreas and Hodges, Sara D., Parallel Constraint Satisfaction in Memory-Based Decisions (June 2009). MPI Collective Goods Preprint, No. 2009/17. Available at SSRN: or

Andreas Glöckner (Contact Author)

Max Planck Institute for Research on Collective Goods ( email )

Kurt-Schumacher-Str. 10
D-53113 Bonn, 53113


University of Cologne ( email )

Richard-Strauss-Str. 2
Köln, 50931


Sara D. Hodges

University of Oregon ( email )

1280 University of Oregon
Eugene, OR 97403
United States

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