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. 2022 Dec 1;17(12):e0278409.
doi: 10.1371/journal.pone.0278409. eCollection 2022.

Information acquisition and cognitive processes during strategic decision-making: Combining a policy-capturing study with eye-tracking data

Alice Pizzo  1 , Toke R Fosgaard  2 , Beverly B Tyler  3 , Karin Beukel  2
Affiliations

Information acquisition and cognitive processes during strategic decision-making: Combining a policy-capturing study with eye-tracking data

Alice Pizzo et al. PLoS One. .

Abstract

Policy-capturing (PC) methodologies have been employed to study decision-making, and to assess how decision-makers use available information when asked to evaluate hypothetical situations. An important assumption of the PC techniques is that respondents develop cognitive models to help them efficiently process the many information cues provided while reviewing a large number of decision scenarios. With this study, we seek to analyze the process of answering a PC study. We do this by investigating the information acquisition and the cognitive processes behind policy-capturing, building on cognitive and attention research and exploiting the tools of eye-tracking. Additionally, we investigate the role of experience in mediating the relationship between the information processed and judgments in order to determine how the cognitive models of student samples differ from those of professionals. We find evidence of increasing efficiency as a function of practice when respondents undergo the PC experiment. We also detect a selective process on information acquisition; such selection is consistent with the respondents' evaluation. While some differences are found in the information processing among the split sample of students and professionals, remarkable similarities are detected. Our study adds confidence to the assumption that respondents build cognitive models to handle the large amounts of information presented in PC experiments, and the defection of such models is not substantially affected by the applied sample.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Attention.
Pattern of attention measured in time spent (seconds) for attributes (Panel A) and degrees (Panel B) over the 30 repeated collaboration scenarios, by professionals and students. The logarithmic form of the variable of interest is depicted in the graph.
Fig 2
Fig 2. Zero-fixations attributes and degrees.
Distribution of zero-fixations attributes over the succeeding scenarios for attributes (Panel A) and degrees (Panel B). The error bars are depicted in dark red.
Fig 3
Fig 3. Policy-capturing vs. ranked data.
The relationship between Policy-capturing data and Ranked data.
Fig 4
Fig 4. Policy-capturing vs. ranked data by sample.
The relationship between Policy-capturing data and Ranked data by sample group.
See this image and copyright information in PMC

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