The Allocation of Time in Decision-Making

Chabris, Christopher F.; Laibson, David; Morris, Caroline; Schuldt, Jonathan P.; Taubinsky, Dmitry

doi:10.1162/jeea.2009.7.2-3.628

Cited by 93 publications

(80 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2 To date, however, only a few works in economics have explicitly incorporated response times in models of reasoning. Chabris et al (2009) study the allocation of time across decision problems. Their model is similar in spirit to ours in that it is motivated by the chronometric "closeness-1 Paradigms eliciting iterative thinking, and very specially "thinking about thinking," fall squarely within the domain of social neuroscience.…”

Section: Related Literaturementioning

confidence: 99%

Cognitive Sophistication and Deliberation Times

Alós–Ferrer

Buckenmaier

2018

SSRN Journal

View full text Add to dashboard Cite

Behavioral heterogeneity arising from cognitive differences among economic agents plays a fundamental role in the economy. To explain this heterogeneity, models of iterative thinking assume that certain choices indicate higher cognitive effort. That is, choices are used to infer the cognitive process behind the choices themselves. To establish this link choice data is insufficient, thus an individually-measurable correlate of cognitive effort is required. We argue that deliberation times provide this missing link. We present a simple model of heterogeneous cognitive depth, incorporating stylized facts from the psychophysical literature, which makes predictions on the relation between choices, cognitive effort, incentives, and deliberation times. In an experimental test, the predicted relations are readily observed in the data, but only when the features leading to iterative thinking are salient enough. Hence, the predicted relations become a tool to uncover the limits of models of iterative thinking. JEL Classification: C72 · C91 · D80 · D91.

show abstract

Section: Related Literaturementioning

confidence: 99%

Cognitive Sophistication and Deliberation Times

Alós–Ferrer

Buckenmaier

2018

SSRN Journal

View full text Add to dashboard Cite

show abstract

“…These models suppose that brain functions are based on quantum processes as almost all neuroscientific evidences suggest [17]- [19].…”

Section: Literature Reviewmentioning

confidence: 99%

Quantum Model of Decision-Making in Economics

Herzog¹

2015

JQIS

View full text Add to dashboard Cite

The paper designs a quantum model of decision-making (QMDM) that utilizes neuroscientific evidence. The new model provides both normative and positive implications to economics. First, it enhances the study of decision-making which is an extension of the expected utility theory (EUT) in mathematical economics. Second, we demonstrate how the quantum model mitigates drawbacks of the expected utility theory of today.

show abstract

“…Dumais et al [2010] show that these "gaze patterns" differ significantly from user to user, suggesting that different UIs may be optimal for different groups of users. In a study of the cognitive costs associated with decision making, Chabris et al [2009] show that users allocate time for a decision-making task according to cost-benefit principles. Because time is costly, more complex UIs put additional costs on users.…”

Section: Related Workmentioning

confidence: 99%

Market User Interface Design

Seuken

Parkes

Horvitz

et al. 2012

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

View full text Add to dashboard Cite

Despite the pervasiveness of markets in our lives, little is known about the role of user interfaces (UIs) in promoting good decisions in market domains. How does the way we display market information to end users, and the set of choices we offer, influence users' decisions? In this paper, we introduce a new research agenda on "market user interface design." Our goal is to find the optimal market UI, taking into account that users incur cognitive costs and are boundedly rational. Via lab experiments we systematically explore the market UI design space, and we study the automatic optimization of market UIs given a behavioral (quantal response) model of user behavior. Surprisingly, we find that the behaviorally-optimized UI performs worse than the standard UI, suggesting that the quantal response model did not predict user behavior well. Subsequently, we identify important behavioral factors that are missing from the user model, including loss aversion and position effects, which motivates follow-up studies. Furthermore, we find significant differences between individual users in terms of rationality. This suggests future research on personalized UI designs, with interfaces that are tailored towards each individual user's needs, capabilities, and preferences.

show abstract

The Allocation of Time in Decision-Making

Cited by 93 publications

References 10 publications

Cognitive Sophistication and Deliberation Times

Cognitive Sophistication and Deliberation Times

Quantum Model of Decision-Making in Economics

Market User Interface Design

Contact Info

Product

Resources

About