2017
DOI: 10.1073/pnas.1707040114
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Search predicts and changes patience in intertemporal choice

Abstract: SignificancePeople often make decisions with consequences that unfold over time. When facing such intertemporal choices, people use different search strategies. We examine how these search strategies differ and how they relate to patience in intertemporal choice. We demonstrate that search varies substantially across individuals and identify two main search strategies—comparative or integrative search. Importantly, comparative search correlates with greater patience and higher susceptibility to contextual infl… Show more

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Cited by 90 publications
(120 citation statements)
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References 44 publications
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“…Importantly, our eye tracking data indicated that this bias was not universal; there is not one best-fitting approach, but rather both attribute-wise and option-wise strategies may be employed in different contexts, p. 11 with substantial individual variability. This result builds upon the similar finding (using mousetracking methods) from Reeck and colleagues 36 ; we extend their results by showing that the attribute-wise model fits best for those at the most patient end of the spectrum whereas the option-wise model fits better for those who are less patient. Therefore, while the attribute-wise model fits better overall, individuals may still differ in the mechanisms by which they make these choices, given the clear individual differences both in choice behavior and in processes of information acquisition.…”
Section: Psupporting
confidence: 88%
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“…Importantly, our eye tracking data indicated that this bias was not universal; there is not one best-fitting approach, but rather both attribute-wise and option-wise strategies may be employed in different contexts, p. 11 with substantial individual variability. This result builds upon the similar finding (using mousetracking methods) from Reeck and colleagues 36 ; we extend their results by showing that the attribute-wise model fits best for those at the most patient end of the spectrum whereas the option-wise model fits better for those who are less patient. Therefore, while the attribute-wise model fits better overall, individuals may still differ in the mechanisms by which they make these choices, given the clear individual differences both in choice behavior and in processes of information acquisition.…”
Section: Psupporting
confidence: 88%
“…While participants performed the task, we sampled their gaze position at high temporal resolution using eye-tracking, so that we could obtain real-time assessments of information processing in advance of each decision [28][29][30][31][32][33] . We examined not only the relative gaze bias between the SS and p. 4 LL options, which has been linked to overall patience in intertemporal choice 34 , but also the pattern of eye movements between elements in the display, which can reveal variation in decision heuristics across individuals 35,36 . Successful analyses in the primary sample determined which analyses were conducted in the replication sample -and all analyses are reported in this paper, regardless of replication success.…”
Section: Pmentioning
confidence: 99%
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“…In our current work, for example, we found that the relative importance given to a specific attribute, as well as its speed in entering into the choice process, could be altered by instructions that directed attention to that attribute. Although a large body of work has established that value construction and comparison processes are malleable and subject to attention, perceptual constraints, and other contextual factors [9][10][11]56,57 , the influence of attribute consideration timing within a given decision is rarely discussed or directly tested. Query theory 58,59 is a notable exception in that it explicitly posits that the order in which attribute values are queried from memory or external sources will bias value construction and choice processes because the recall of initial attributes reduces the accessibility of values is assumed to yield the "correct" choice 60 .…”
Section: Discussionmentioning
confidence: 99%
“…Uncovering such features of the decision process allows us to discriminate between and evaluate the plausibility of different models that seek to explain choice behaviour 5 . For example, choice models utilizing not only decision outcomes but also response times and eye-or mouse-tracking data have provided insights into how and why decision-making is influenced by visual attention, time delays or pressure, additional alternatives, and earlier versus later occurring external evidence [6][7][8][9][10][11][12][13] . Moreover, it has been shown that dynamic accumulation models utilizing response-time data provide a deeper understanding of decisions and make better out-of-sample predictions than reduced form models such as logistic regressions 14,15 .…”
Section: Introductionmentioning
confidence: 99%