When exploring the possible outcomes of different choice options (e.g., sampling reviews on Tripadvisor when deciding between two hotels), the degree of pre-decisional search required to identify advantageous options hinges strongly on the statistical properties of the choice environments: In "kind" environments without any rare events, frugal search is sufficient to identify advantageous options. Conversely, in "wicked" environments with skewed outcome distributions, ample exploration is required to identify rare outcomes that may have large positive or negative consequences.
To what extent is people's pre-decisional search adaptive to different choice environments? And what if other people simultaneously pursue the same goal, giving rise to competitive pressure ("only one room left at this price")? In this project, I adopted an ecological perspective and systematically varied the statistical properties of different choice environments, in order to pit two theoretical perspectives on the role of competitive pressure against each other: An optimistic view assumes that competitive pressure triggers adaptive search and may thus lead to increased efficiency; conversely, a pessimistic view assumes that competitive pressure triggers agency-related concerns and may thus lead to minimal search across choice environments. The latter prediction implies that competitive pressure has a particularly negative effect on choice performance in wicked environments.
Search effort as a function of the experimental conditions (i.e., three different choice environments; two different search modes).
As the figure above illustrates, under competitive pressure pre-decisional search indeed tended to be minimal in all three choice environments – in line with the more pessimistic theoretical perspective. As a consequence, choice performance was particularly low in the (extremely) wicked environment. However, from the perspective of a cost-benefit framework that takes search costs into account (see figure below), competitive pressure may actually render search efficient in the kind and in the wicked environments.
Average-cost curves for each participant. Search is efficient if the empirical sample size is at the lowest point on each participant's idiosyncratic average-cost curve.
On a side note, in this project I was up for some exploration myself: In the spirit of trying out new avenues for promoting transparent and reproducible research, I was committed to publish this paper as a registered report (RR). The idea of this relatively new publication format is to run the paper's theoretical rationale through the full peer-review process at a scientific journal, with the goal of obtaining "in-principle acceptance" before the empirical studies are conducted. It was a very interesting but sometimes also difficult process, as it may be particularly hard to convince reviewers of the soundness and importance of the research questions a-priori, without being able to present fancy results yet. So I am glad that this paper found a nice home at JDM, and I hope that more psychological journals will adopt the format of RRs soon!
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