Predicting how much a consumer is willing to pay for a bottle of wine: A preliminary study

Hugo Alonso; Teresa Candeias

doi:10.1016/j.procs.2022.08.101

Predicting how much a consumer is willing to pay for a bottle of wine: A preliminary study

Hugo Alonso, Teresa Candeias

University of Aveiro

Research output: Contribution to journal › Conference article › peer-review

Abstract

The wine industry is an important business sector, generating billions in annual revenue. In the last year, there were several lockdowns due to the COVID-19 pandemic and wine consumption at home has increased. This paper considers the problem of predicting how much a consumer is willing to pay for a bottle of wine to drink at home, in a regular occasion. As far as we know, this is the first study on the subject. The problem is treated as a classification task and several prediction models, based on artificial neural networks, support vector machines and decisions trees, are proposed and compared.

Original language	English
Pages (from-to)	836-843
Number of pages	8
Journal	Procedia Computer Science
Volume	204
DOIs	https://doi.org/10.1016/j.procs.2022.08.101
Publication status	Published - 2022
Event	2022 International Conference on Industry Sciences and Computer Science Innovation, iSCSi 2022 - Porto, Portugal Duration: 9 Mar 2022 → 11 Mar 2022

Bibliographical note

Publisher Copyright:
© 2022 The Author(s).

Funding

This work was partially supported by the Center for Research and Development in Mathematics and Applications (CIDMA) through the Portuguese Foundation for Science and Technology (FCT – Fundação para a Ciência e a Tecnologia), references UIDB/04106/2020 and UIDP/04106/2020.

Funders	Funder number
Fundação para a Ciência e a Tecnologia	UIDB/04106/2020, UIDP/04106/2020
Center for Research and Development in Mathematics and Applications

Keywords

Artificial neural networks
Classification
Decision trees
Support vector machines
Wine

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10.1016/j.procs.2022.08.101

Cite this

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title = "Predicting how much a consumer is willing to pay for a bottle of wine: A preliminary study",

abstract = "The wine industry is an important business sector, generating billions in annual revenue. In the last year, there were several lockdowns due to the COVID-19 pandemic and wine consumption at home has increased. This paper considers the problem of predicting how much a consumer is willing to pay for a bottle of wine to drink at home, in a regular occasion. As far as we know, this is the first study on the subject. The problem is treated as a classification task and several prediction models, based on artificial neural networks, support vector machines and decisions trees, are proposed and compared.",

keywords = "Artificial neural networks, Classification, Decision trees, Support vector machines, Wine",

author = "Hugo Alonso and Teresa Candeias",

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AU - Candeias, Teresa

PY - 2022

Y1 - 2022

N2 - The wine industry is an important business sector, generating billions in annual revenue. In the last year, there were several lockdowns due to the COVID-19 pandemic and wine consumption at home has increased. This paper considers the problem of predicting how much a consumer is willing to pay for a bottle of wine to drink at home, in a regular occasion. As far as we know, this is the first study on the subject. The problem is treated as a classification task and several prediction models, based on artificial neural networks, support vector machines and decisions trees, are proposed and compared.

AB - The wine industry is an important business sector, generating billions in annual revenue. In the last year, there were several lockdowns due to the COVID-19 pandemic and wine consumption at home has increased. This paper considers the problem of predicting how much a consumer is willing to pay for a bottle of wine to drink at home, in a regular occasion. As far as we know, this is the first study on the subject. The problem is treated as a classification task and several prediction models, based on artificial neural networks, support vector machines and decisions trees, are proposed and compared.

KW - Artificial neural networks

KW - Classification

KW - Decision trees

KW - Support vector machines

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EP - 843

JO - Procedia Computer Science

JF - Procedia Computer Science

Y2 - 9 March 2022 through 11 March 2022

ER -

Predicting how much a consumer is willing to pay for a bottle of wine: A preliminary study

Abstract

Bibliographical note

Funding

Keywords

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