Speed, Quality, and the Optimal Timing of Complex Decisions: Field Evidence
This addresses the problem of understanding optimal decision timing in cognitively demanding tasks for researchers in behavioral economics and decision science, but it is incremental as it applies existing models to a new domain.
The paper investigates the relationship between decision speed and quality in professional chess, finding that faster decisions are associated with better performance, as measured by a computational benchmark.
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.