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More Causes Less Effect: Destructive Interference in Decision Making
We present a new experiment demonstrating destructive interference in customers’ estimates of conditional probabilities of product failure. We take the perspective of a manufacturer of consumer products and consider two situations of cause and effect. Whereas, individually, the effect of the causes...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9141002/ https://www.ncbi.nlm.nih.gov/pubmed/35626608 http://dx.doi.org/10.3390/e24050725 |
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author | Basieva, Irina Pandey, Vijitashwa Khrennikova, Polina |
author_facet | Basieva, Irina Pandey, Vijitashwa Khrennikova, Polina |
author_sort | Basieva, Irina |
collection | PubMed |
description | We present a new experiment demonstrating destructive interference in customers’ estimates of conditional probabilities of product failure. We take the perspective of a manufacturer of consumer products and consider two situations of cause and effect. Whereas, individually, the effect of the causes is similar, it is observed that when combined, the two causes produce the opposite effect. Such negative interference of two or more product features may be exploited for better modeling of the cognitive processes taking place in customers’ minds. Doing so can enhance the likelihood that a manufacturer will be able to design a better product, or a feature within it. Quantum probability has been used to explain some commonly observed “non-classical” effects, such as the disjunction effect, question order effect, violation of the sure-thing principle, and the Machina and Ellsberg paradoxes. In this work, we present results from a survey on the impact of multiple observed symptoms on the drivability of a vehicle. The symptoms are assumed to be conditionally independent. We demonstrate that the response statistics cannot be directly explained using classical probability, but quantum formulation easily models it, as it allows for both positive and negative “interference” between events. Since quantum formalism also accounts for classical probability’s predictions, it serves as a richer paradigm for modeling decision making behavior in engineering design and behavioral economics. |
format | Online Article Text |
id | pubmed-9141002 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91410022022-05-28 More Causes Less Effect: Destructive Interference in Decision Making Basieva, Irina Pandey, Vijitashwa Khrennikova, Polina Entropy (Basel) Article We present a new experiment demonstrating destructive interference in customers’ estimates of conditional probabilities of product failure. We take the perspective of a manufacturer of consumer products and consider two situations of cause and effect. Whereas, individually, the effect of the causes is similar, it is observed that when combined, the two causes produce the opposite effect. Such negative interference of two or more product features may be exploited for better modeling of the cognitive processes taking place in customers’ minds. Doing so can enhance the likelihood that a manufacturer will be able to design a better product, or a feature within it. Quantum probability has been used to explain some commonly observed “non-classical” effects, such as the disjunction effect, question order effect, violation of the sure-thing principle, and the Machina and Ellsberg paradoxes. In this work, we present results from a survey on the impact of multiple observed symptoms on the drivability of a vehicle. The symptoms are assumed to be conditionally independent. We demonstrate that the response statistics cannot be directly explained using classical probability, but quantum formulation easily models it, as it allows for both positive and negative “interference” between events. Since quantum formalism also accounts for classical probability’s predictions, it serves as a richer paradigm for modeling decision making behavior in engineering design and behavioral economics. MDPI 2022-05-20 /pmc/articles/PMC9141002/ /pubmed/35626608 http://dx.doi.org/10.3390/e24050725 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Basieva, Irina Pandey, Vijitashwa Khrennikova, Polina More Causes Less Effect: Destructive Interference in Decision Making |
title | More Causes Less Effect: Destructive Interference in Decision Making |
title_full | More Causes Less Effect: Destructive Interference in Decision Making |
title_fullStr | More Causes Less Effect: Destructive Interference in Decision Making |
title_full_unstemmed | More Causes Less Effect: Destructive Interference in Decision Making |
title_short | More Causes Less Effect: Destructive Interference in Decision Making |
title_sort | more causes less effect: destructive interference in decision making |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9141002/ https://www.ncbi.nlm.nih.gov/pubmed/35626608 http://dx.doi.org/10.3390/e24050725 |
work_keys_str_mv | AT basievairina morecauseslesseffectdestructiveinterferenceindecisionmaking AT pandeyvijitashwa morecauseslesseffectdestructiveinterferenceindecisionmaking AT khrennikovapolina morecauseslesseffectdestructiveinterferenceindecisionmaking |