Sequential search behavior changes according to distribution shape despite having a rank-based goal

In the area of sequential choice, the 'Secretary Problem' has been a prominent paradigm within the study of optimal stopping for sequential search tasks. Most recent studies of the Secretary Problem present decision makers with the relative ranks of options. A recurring finding is that decision makers tend to end their search earlier than optimal decision strategies (e.g. Helversen, Wilke, Johnson, & Schmid, 2011; Seale & Rapoport, 1997, 2000). By revealing only relative ranks of options or items, issues of learning and incomplete knowledge are avoided; however, this leaves open the question of how sensible human decision makers are when they know more about the distribution of items. Rather than presenting merely ranks to decision makers, we presented numerical values drawn from three distinct distributions in which relatively high value items were scarce, evenly distributed, or abundant. We found that they selected their items earlier than they would if they utilized the optimal selection rule. More importantly, in contrast to the conclusion of Kahan, et al. (1967), we found the selection points of decision makers were sensitive to the underlying distribution. In contrast, the optimal strategy is totally based on quantile ranks regardless of the type of distributions.