Speed, Quality, and the Optimal Timing of Complex Decisions: Field Evidence

01/26/2022
by   Uwe Sunde, et al.
0

This paper presents an empirical investigation of the relation between decision speed and decision quality for a real-world setting of cognitively-demanding decisions in which the timing of decisions is endogenous: professional chess. Move-by-move data provide exceptionally detailed and precise information about decision times and decision quality, based on a comparison of actual decisions to a computational benchmark of best moves constructed using the artificial intelligence of a chess engine. The results reveal that faster decisions are associated with better performance. The findings are consistent with the predictions of procedural decision models like drift-diffusion-models in which decision makers sequentially acquire information about decision alternatives with uncertain valuations.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/26/2020

On the Causes and Consequences of Deviations from Rational Behavior

This paper presents novel evidence for the prevalence of deviations from...
research
08/29/2023

From DDMs to DNNs: Using process data and models of decision-making to improve human-AI interactions

Over the past decades, cognitive neuroscientists and behavioral economis...
research
06/10/2021

A modular framework for object-based saccadic decisions in dynamic scenes

Visually exploring the world around us is not a passive process. Instead...
research
06/15/2016

Assessing Human Error Against a Benchmark of Perfection

An increasing number of domains are providing us with detailed trace dat...
research
07/23/2020

Time Perception: A Review on Psychological, Computational and Robotic Models

Animals exploit time to survive in the world. Temporal information is re...
research
07/31/2020

Lookahead and Hybrid Sample Allocation Procedures for Multiple Attribute Selection Decisions

Attributes provide critical information about the alternatives that a de...
research
09/11/2023

Know What Not To Know: Users' Perception of Abstaining Classifiers

Machine learning systems can help humans to make decisions by providing ...

Please sign up or login with your details

Forgot password? Click here to reset