No Cover Image

Journal article 30 views 13 downloads

Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning

Dušan Mladenović Orcid Logo, Ellie Ismagilova Orcid Logo, Emmanuel Mogaji Orcid Logo, Yogesh K. Dwivedi Orcid Logo

Journal of Consumer Behaviour

Swansea University Author: Ellie Ismagilova Orcid Logo

Check full text

DOI (Published version): 10.1002/cb.70126

Abstract

This study aims to cultivate an initial understanding of travelers' engagement with generative artificial intelligence (GAI) during the travel planning phase. It focuses on its influence on decision-making and intentions for continuous usage in planning tourism activities. Utilizing the stimulu...

Full description

Published in: Journal of Consumer Behaviour
ISSN: 1472-0817 1479-1838
Published: Wiley 2026
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa71687
first_indexed 2026-03-30T13:53:30Z
last_indexed 2026-03-31T04:34:29Z
id cronfa71687
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2026-03-30T14:54:41.0576225</datestamp><bib-version>v2</bib-version><id>71687</id><entry>2026-03-30</entry><title>Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning</title><swanseaauthors><author><sid>978a0722ccb70c8c3816004d8a9f1567</sid><ORCID>0000-0001-9634-194X</ORCID><firstname>Ellie</firstname><surname>Ismagilova</surname><name>Ellie Ismagilova</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2026-03-30</date><deptcode>CBAE</deptcode><abstract>This study aims to cultivate an initial understanding of travelers' engagement with generative artificial intelligence (GAI) during the travel planning phase. It focuses on its influence on decision-making and intentions for continuous usage in planning tourism activities. Utilizing the stimulus-organism-response framework and domain literature, data were gathered through semi-structured interviews (UK) and scenario-based questionnaires (USA). The study reveals complex aspects of travelers' behavior, uncovering that while GAI recommendations mitigate the risk of information overload, their influence does not necessarily streamline decision-making. Trust and information retrieval skills surfaced as moderate determinants of the relationship between recommendations and information overload. This work is a pioneer in empirically exploring and quantifying continuance intentions of generative artificial intelligence (GAI) usage, contributing novel insights to electronic Word of Mouth and decision-making literature.</abstract><type>Journal Article</type><journal>Journal of Consumer Behaviour</journal><volume/><journalNumber/><paginationStart/><paginationEnd/><publisher>Wiley</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>1472-0817</issnPrint><issnElectronic>1479-1838</issnElectronic><keywords>recommendation quality, decision satisfaction, information overload, travel, hospitality, generative artificial intelligence</keywords><publishedDay>8</publishedDay><publishedMonth>2</publishedMonth><publishedYear>2026</publishedYear><publishedDate>2026-02-08</publishedDate><doi>10.1002/cb.70126</doi><url>https://doi.org/10.1002/cb.70126</url><notes/><college>COLLEGE NANME</college><department>Management School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>CBAE</DepartmentCode><institution>Swansea University</institution><apcterm/><funders/><projectreference/><lastEdited>2026-03-30T14:54:41.0576225</lastEdited><Created>2026-03-30T14:43:56.8432537</Created><path><level id="1">Faculty of Humanities and Social Sciences</level><level id="2">School of Management - Business Management</level></path><authors><author><firstname>Du&#x161;an</firstname><surname>Mladenovi&#x107;</surname><orcid>0000-0001-5101-2181</orcid><order>1</order></author><author><firstname>Ellie</firstname><surname>Ismagilova</surname><orcid>0000-0001-9634-194X</orcid><order>2</order></author><author><firstname>Emmanuel</firstname><surname>Mogaji</surname><orcid>0000-0003-0544-4842</orcid><order>3</order></author><author><firstname>Yogesh K.</firstname><surname>Dwivedi</surname><orcid>0000-0002-5547-9990</orcid><order>4</order></author></authors><documents><document><filename>71687__36460__4cffc35f9bd0425f8dd352b96749f35b.pdf</filename><originalFilename>Manuscript body text - without author details R4 - Anonymized main document.docx</originalFilename><uploaded>2026-03-30T14:50:21.2769090</uploaded><type>Output</type><contentLength>3380002</contentLength><contentType>application/vnd.openxmlformats-officedocument.wordprocessingml.document</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><copyrightCorrect>false</copyrightCorrect><language>English</language></document></documents><OutputDurs/></rfc1807>
spelling 2026-03-30T14:54:41.0576225 v2 71687 2026-03-30 Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning 978a0722ccb70c8c3816004d8a9f1567 0000-0001-9634-194X Ellie Ismagilova Ellie Ismagilova true false 2026-03-30 CBAE This study aims to cultivate an initial understanding of travelers' engagement with generative artificial intelligence (GAI) during the travel planning phase. It focuses on its influence on decision-making and intentions for continuous usage in planning tourism activities. Utilizing the stimulus-organism-response framework and domain literature, data were gathered through semi-structured interviews (UK) and scenario-based questionnaires (USA). The study reveals complex aspects of travelers' behavior, uncovering that while GAI recommendations mitigate the risk of information overload, their influence does not necessarily streamline decision-making. Trust and information retrieval skills surfaced as moderate determinants of the relationship between recommendations and information overload. This work is a pioneer in empirically exploring and quantifying continuance intentions of generative artificial intelligence (GAI) usage, contributing novel insights to electronic Word of Mouth and decision-making literature. Journal Article Journal of Consumer Behaviour Wiley 1472-0817 1479-1838 recommendation quality, decision satisfaction, information overload, travel, hospitality, generative artificial intelligence 8 2 2026 2026-02-08 10.1002/cb.70126 https://doi.org/10.1002/cb.70126 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University 2026-03-30T14:54:41.0576225 2026-03-30T14:43:56.8432537 Faculty of Humanities and Social Sciences School of Management - Business Management Dušan Mladenović 0000-0001-5101-2181 1 Ellie Ismagilova 0000-0001-9634-194X 2 Emmanuel Mogaji 0000-0003-0544-4842 3 Yogesh K. Dwivedi 0000-0002-5547-9990 4 71687__36460__4cffc35f9bd0425f8dd352b96749f35b.pdf Manuscript body text - without author details R4 - Anonymized main document.docx 2026-03-30T14:50:21.2769090 Output 3380002 application/vnd.openxmlformats-officedocument.wordprocessingml.document Accepted Manuscript true false English
title Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning
spellingShingle Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning
Ellie Ismagilova
title_short Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning
title_full Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning
title_fullStr Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning
title_full_unstemmed Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning
title_sort Travel Recommendations of Tomorrow: Generative Artificial Intelligence and Travel Planning
author_id_str_mv 978a0722ccb70c8c3816004d8a9f1567
author_id_fullname_str_mv 978a0722ccb70c8c3816004d8a9f1567_***_Ellie Ismagilova
author Ellie Ismagilova
author2 Dušan Mladenović
Ellie Ismagilova
Emmanuel Mogaji
Yogesh K. Dwivedi
format Journal article
container_title Journal of Consumer Behaviour
publishDate 2026
institution Swansea University
issn 1472-0817
1479-1838
doi_str_mv 10.1002/cb.70126
publisher Wiley
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
url https://doi.org/10.1002/cb.70126
document_store_str 1
active_str 0
description This study aims to cultivate an initial understanding of travelers' engagement with generative artificial intelligence (GAI) during the travel planning phase. It focuses on its influence on decision-making and intentions for continuous usage in planning tourism activities. Utilizing the stimulus-organism-response framework and domain literature, data were gathered through semi-structured interviews (UK) and scenario-based questionnaires (USA). The study reveals complex aspects of travelers' behavior, uncovering that while GAI recommendations mitigate the risk of information overload, their influence does not necessarily streamline decision-making. Trust and information retrieval skills surfaced as moderate determinants of the relationship between recommendations and information overload. This work is a pioneer in empirically exploring and quantifying continuance intentions of generative artificial intelligence (GAI) usage, contributing novel insights to electronic Word of Mouth and decision-making literature.
published_date 2026-02-08T07:01:26Z
_version_ 1861428012140986368
score 11.1007185

Similar Items