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Title: Intrachoice Dynamics Shape Social Decisions
Do people have well-defined social preferences waiting to be applied when making decisions? Or do they have to construct social decisions on the spot? If the latter, how are those decisions influenced by the way in which information is acquired and evaluated? These temporal dynamics are fundamental to understanding how people trade off selfishness and prosociality in organizations and societies. Here, we investigate how the temporal dynamics of the choice process shape social decisions in three studies using response times and mouse tracking. In the first study, participants made binary decisions in mini-dictator games with and without time constraints. Using mouse trajectories and a starting time drift diffusion model, we find that, regardless of time constraints, selfish participants were delayed in processing others’ payoffs, whereas the opposite was true for prosocial participants. The independent mouse trajectory and computational modeling analyses identified consistent measures of the delay between considering one’s own and others’ payoffs (self-onset delay, SOD). This measure correlated with individual differences in prosociality and predicted heterogeneous effects of time constraints on preferences. We confirmed these results in two additional studies, one a purely behavioral study in which participants made decisions by pressing computer keys, and the other a replication of the mouse-tracking study. Together, these results indicate that people preferentially process either self or others’ payoffs early in the choice process. The intrachoice dynamics are crucial in shaping social preferences and might be manipulated via nudge policies (e.g., manipulating the display order or saliency of self and others’ outcomes) for behavior in managerial or other contexts. This paper was accepted by Yan Chen, behavioral economics and decisions analysis. Funding: F. Chen acknowledges support from the National Natural Science Foundation of China [Grants 71803174 and 72173113]. Z. Zhu acknowledges support from the Ministry of Science and Technology [Grant STI 2030-Major Projects 2021ZD0200409]. Q. Shen acknowledges support from the National Natural Science Foundation of China [Grants 71971199 and 71942004]. I. Krajbich acknowledges support from the U.S. National Science Foundation [Grant 2148982]. This work was also supported by the James McKeen Cattell Fund. Supplemental Material: The online appendix and data are available at .  more » « less
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Chen, Yan
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Management Science
Medium: X
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National Science Foundation
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