A Scanpath Analysis of the Risky Decision‐Making Process. (5th February 2016)

• Record Type: Journal Article
• Authors: Zhou, Lei; Zhang, Yang‐Yang; Wang, Zuo‐Jun; Rao, Li‐Lin; Wang, Wei; Li, Shu; Li, Xingshan; Liang, Zhu‐Yuan
• Is Part Of: Journal of behavioral decision making. Volume 29:Number 2/3(2016)
• Page Start: 169
• Page End: 182
• Publication Date: 2016-02-05
• Subjects: risky choice -- scanpath analysis -- similarity score -- typical trial -- eye tracking -- process testing; Decision making -- Periodicals; Managerial economics -- Periodicals; Behavior -- Periodicals; Decision Making -- Periodicals; Prise de décision -- Périodiques; Économie d'entreprise -- Périodiques; 153.83
• DOI: 10.1002/bdm.1943
• Languages: English
• ISSNs: 0894-3257

Abstract

Abstract: In the field of eye tracking, scanpath analysis can reflect the sequential and temporal properties of the cognitive process. However, the advantages of scanpath analysis have not yet been utilized in the study of risky decision making. We explored the methodological applicability of scanpath analysis to test models of risky decision making by analyzing published data from the eye‐tracking studies of Su et al. (2013); Wang and Li (2012), and Sun, Rao, Zhou, and Li (2014). These studies used a proportion task, an outcome‐matched presentation condition, and a multiple‐play condition as the baseline for comparison with information search and processing in the risky decision‐making condition. We found that (i) the similarity scores of the intra‐conditions were significantly higher than those of the inter‐condition; (ii) the scanpaths of the two conditions were separable; and (iii) based on an inspection of typical trials, the patterns of the scanpaths differed between the two conditions. These findings suggest that scanpath analysis is reliable and valid for examining the process of risky decision making. In line with the findings of the three original studies, our results indicate that risky decision making is unlikely to be based on a weighting and summing process, as hypothesized by the family of expectation models. The findings highlight a new methodological direction for research on decision making. Copyright © 2016 John Wiley & Sons, Ltd.