Quantum Experimental Data in Psychology and Economics
Diederik Aerts, Bart D'Hooghe, Emmanuel Haven

TL;DR
This paper demonstrates that certain psychological and economic decision-making data exhibiting the disjunction effect cannot be modeled with classical probability, and instead supports using quantum formalism for such data.
Contribution
It provides a no-go theorem showing classical probabilistic models fail for disjunction effect data, advocating quantum models as a better alternative.
Findings
Disjunction effect violates classical probability structures.
A geometric criterion reveals non-classicality of data.
Quantum formalism better models disjunction effect data.
Abstract
We prove a theorem which shows that a collection of experimental data of probabilistic weights related to decisions with respect to situations and their disjunction cannot be modeled within a classical probabilistic weight structure in case the experimental data contain the effect referred to as the 'disjunction effect' in psychology. We identify different experimental situations in psychology, more specifically in concept theory and in decision theory, and in economics (namely situations where Savage's Sure-Thing Principle is violated) where the disjunction effect appears and we point out the common nature of the effect. We analyze how our theorem constitutes a no-go theorem for classical probabilistic weight structures for common experimental data when the disjunction effect is affecting the values of these data. We put forward a simple geometric criterion that reveals the non…
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Quantum Mechanics and Applications
