Purchase intention-based agent for customer behaviours

Simulating human activities remains a challenging problem because the decision-making mechanisms underlying these activities are difficult to reproduce and mimic. In this article, we are interested in the simulation of in-store shoppers whose activities are generally divided into two parts: a walkin...

Full description

Saved in:
Bibliographic Details
Published in:Information sciences 2020-06, Vol.521, p.380-397
Main Authors: Doniec, Arnaud, Lecoeuche, Stéphane, Mandiau, René, Sylvain, Antoine
Format: Article
Language:English
Subjects:
Agent-based modelling
Artificial Intelligence
Computer Science
Customer behaviours
Multiagent Systems
Purchase intention
Stores’ simulation
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c374t-e8b7636591b007f00abe449bab2f5a3f40bbcb9de0e10606461af6fdc6a0c1593
cites cdi_FETCH-LOGICAL-c374t-e8b7636591b007f00abe449bab2f5a3f40bbcb9de0e10606461af6fdc6a0c1593
container_end_page 397
container_issue
container_start_page 380
container_title Information sciences
container_volume 521
creator Doniec, Arnaud
Lecoeuche, Stéphane
Mandiau, René
Sylvain, Antoine
description Simulating human activities remains a challenging problem because the decision-making mechanisms underlying these activities are difficult to reproduce and mimic. In this article, we are interested in the simulation of in-store shoppers whose activities are generally divided into two parts: a walking activity and a purchase activity. Since the act of buying is more complex than simply following a shopping list, we propose here to model the attraction relationships that can exist between a product and a customer. This attraction model is used to build a multi-agent simulation whose realism is evaluated through various experiments.
doi_str_mv 10.1016/j.ins.2020.02.054
format article
fullrecord <record><control><sourceid>hal_cross</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_02496810v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0020025520301377</els_id><sourcerecordid>oai_HAL_hal_02496810v1</sourcerecordid><originalsourceid>FETCH-LOGICAL-c374t-e8b7636591b007f00abe449bab2f5a3f40bbcb9de0e10606461af6fdc6a0c1593</originalsourceid><addsrcrecordid>eNp9kMFKAzEQhoMoWKsP4G2vHnadyWazXTyVolYo6EHPIclObEq7kWRb8O1NqXj0NPwz8w3Mx9gtQoWA8n5T-SFVHDhUwCtoxBmb4KzlpeQdnrMJ5EkJvGku2VVKGwAQrZQTJt_20a51osIPIw2jD0NpcuwL_Zlj4UIs7D6NYUexMLTWBx_2MV2zC6e3iW5-65R9PD2-L5bl6vX5ZTFflbZuxVjSzLSylk2HBqB1ANqQEJ3RhrtG106AMdZ0PQEhSJBConbS9VZqsNh09ZTdne6u9VZ9Rb_T8VsF7dVyvlLHHnDRyRnCAfMunnZtDClFcn8AgjpKUhuVJamjpMypLCkzDyeG8hMHT1El62mw1PtIdlR98P_QPwcVbww</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Purchase intention-based agent for customer behaviours</title><source>ScienceDirect Freedom Collection 2022-2024</source><creator>Doniec, Arnaud ; Lecoeuche, Stéphane ; Mandiau, René ; Sylvain, Antoine</creator><creatorcontrib>Doniec, Arnaud ; Lecoeuche, Stéphane ; Mandiau, René ; Sylvain, Antoine</creatorcontrib><description>Simulating human activities remains a challenging problem because the decision-making mechanisms underlying these activities are difficult to reproduce and mimic. In this article, we are interested in the simulation of in-store shoppers whose activities are generally divided into two parts: a walking activity and a purchase activity. Since the act of buying is more complex than simply following a shopping list, we propose here to model the attraction relationships that can exist between a product and a customer. This attraction model is used to build a multi-agent simulation whose realism is evaluated through various experiments.</description><identifier>ISSN: 0020-0255</identifier><identifier>EISSN: 1872-6291</identifier><identifier>DOI: 10.1016/j.ins.2020.02.054</identifier><language>eng</language><publisher>Elsevier Inc</publisher><subject>Agent-based modelling ; Artificial Intelligence ; Computer Science ; Customer behaviours ; Multiagent Systems ; Purchase intention ; Stores’ simulation</subject><ispartof>Information sciences, 2020-06, Vol.521, p.380-397</ispartof><rights>2020 Elsevier Inc.</rights><rights>Attribution - NonCommercial</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c374t-e8b7636591b007f00abe449bab2f5a3f40bbcb9de0e10606461af6fdc6a0c1593</citedby><cites>FETCH-LOGICAL-c374t-e8b7636591b007f00abe449bab2f5a3f40bbcb9de0e10606461af6fdc6a0c1593</cites><orcidid>0000-0002-3843-6729 ; 0000-0002-5599-1185 ; 0000-0001-7722-9848</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,778,782,883,27907,27908</link.rule.ids><backlink>$$Uhttps://hal.science/hal-02496810$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Doniec, Arnaud</creatorcontrib><creatorcontrib>Lecoeuche, Stéphane</creatorcontrib><creatorcontrib>Mandiau, René</creatorcontrib><creatorcontrib>Sylvain, Antoine</creatorcontrib><title>Purchase intention-based agent for customer behaviours</title><title>Information sciences</title><description>Simulating human activities remains a challenging problem because the decision-making mechanisms underlying these activities are difficult to reproduce and mimic. In this article, we are interested in the simulation of in-store shoppers whose activities are generally divided into two parts: a walking activity and a purchase activity. Since the act of buying is more complex than simply following a shopping list, we propose here to model the attraction relationships that can exist between a product and a customer. This attraction model is used to build a multi-agent simulation whose realism is evaluated through various experiments.</description><subject>Agent-based modelling</subject><subject>Artificial Intelligence</subject><subject>Computer Science</subject><subject>Customer behaviours</subject><subject>Multiagent Systems</subject><subject>Purchase intention</subject><subject>Stores’ simulation</subject><issn>0020-0255</issn><issn>1872-6291</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kMFKAzEQhoMoWKsP4G2vHnadyWazXTyVolYo6EHPIclObEq7kWRb8O1NqXj0NPwz8w3Mx9gtQoWA8n5T-SFVHDhUwCtoxBmb4KzlpeQdnrMJ5EkJvGku2VVKGwAQrZQTJt_20a51osIPIw2jD0NpcuwL_Zlj4UIs7D6NYUexMLTWBx_2MV2zC6e3iW5-65R9PD2-L5bl6vX5ZTFflbZuxVjSzLSylk2HBqB1ANqQEJ3RhrtG106AMdZ0PQEhSJBConbS9VZqsNh09ZTdne6u9VZ9Rb_T8VsF7dVyvlLHHnDRyRnCAfMunnZtDClFcn8AgjpKUhuVJamjpMypLCkzDyeG8hMHT1El62mw1PtIdlR98P_QPwcVbww</recordid><startdate>202006</startdate><enddate>202006</enddate><creator>Doniec, Arnaud</creator><creator>Lecoeuche, Stéphane</creator><creator>Mandiau, René</creator><creator>Sylvain, Antoine</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>AAYXX</scope><scope>CITATION</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0002-3843-6729</orcidid><orcidid>https://orcid.org/0000-0002-5599-1185</orcidid><orcidid>https://orcid.org/0000-0001-7722-9848</orcidid></search><sort><creationdate>202006</creationdate><title>Purchase intention-based agent for customer behaviours</title><author>Doniec, Arnaud ; Lecoeuche, Stéphane ; Mandiau, René ; Sylvain, Antoine</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c374t-e8b7636591b007f00abe449bab2f5a3f40bbcb9de0e10606461af6fdc6a0c1593</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Agent-based modelling</topic><topic>Artificial Intelligence</topic><topic>Computer Science</topic><topic>Customer behaviours</topic><topic>Multiagent Systems</topic><topic>Purchase intention</topic><topic>Stores’ simulation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Doniec, Arnaud</creatorcontrib><creatorcontrib>Lecoeuche, Stéphane</creatorcontrib><creatorcontrib>Mandiau, René</creatorcontrib><creatorcontrib>Sylvain, Antoine</creatorcontrib><collection>CrossRef</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Information sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Doniec, Arnaud</au><au>Lecoeuche, Stéphane</au><au>Mandiau, René</au><au>Sylvain, Antoine</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Purchase intention-based agent for customer behaviours</atitle><jtitle>Information sciences</jtitle><date>2020-06</date><risdate>2020</risdate><volume>521</volume><spage>380</spage><epage>397</epage><pages>380-397</pages><issn>0020-0255</issn><eissn>1872-6291</eissn><abstract>Simulating human activities remains a challenging problem because the decision-making mechanisms underlying these activities are difficult to reproduce and mimic. In this article, we are interested in the simulation of in-store shoppers whose activities are generally divided into two parts: a walking activity and a purchase activity. Since the act of buying is more complex than simply following a shopping list, we propose here to model the attraction relationships that can exist between a product and a customer. This attraction model is used to build a multi-agent simulation whose realism is evaluated through various experiments.</abstract><pub>Elsevier Inc</pub><doi>10.1016/j.ins.2020.02.054</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0002-3843-6729</orcidid><orcidid>https://orcid.org/0000-0002-5599-1185</orcidid><orcidid>https://orcid.org/0000-0001-7722-9848</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0020-0255
ispartof Information sciences, 2020-06, Vol.521, p.380-397
issn 0020-0255
1872-6291
language eng
recordid cdi_hal_primary_oai_HAL_hal_02496810v1
source ScienceDirect Freedom Collection 2022-2024
subjects Agent-based modelling
Artificial Intelligence
Computer Science
Customer behaviours
Multiagent Systems
Purchase intention
Stores’ simulation
title Purchase intention-based agent for customer behaviours
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-17T04%3A09%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-hal_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Purchase%20intention-based%20agent%20for%20customer%20behaviours&rft.jtitle=Information%20sciences&rft.au=Doniec,%20Arnaud&rft.date=2020-06&rft.volume=521&rft.spage=380&rft.epage=397&rft.pages=380-397&rft.issn=0020-0255&rft.eissn=1872-6291&rft_id=info:doi/10.1016/j.ins.2020.02.054&rft_dat=%3Chal_cross%3Eoai_HAL_hal_02496810v1%3C/hal_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c374t-e8b7636591b007f00abe449bab2f5a3f40bbcb9de0e10606461af6fdc6a0c1593%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true