AI recommendations : impact of product type and number of options on users’ purchase intention and attitude toward the brand
Main Author: | |
---|---|
Publication Date: | 2024 |
Format: | Master thesis |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10400.14/45175 |
Summary: | In a time of ever-growing options and information available, the introduction of AI recommender systems in brands’ websites emerged as a guiding tool for users’ decision-making process. While the complexity in consumer information is managed, still little is known about the impact of product type and the number of options of the recommendation in the users’ purchase intention and attitude toward the brand. To uncover the design that leads to a more successful AI recommendation, an experiment was ran with the manipulation of product type and number of alternatives provided. The results confirm the better adequacy of AI recommender systems for utilitarian products, in comparison to hedonic products, regarding purchase intention. As for the number of options, there is no one-size-fits-all rule for all products. However, for utilitarian products, this study suggests that providing larger choice sets of recommendations is beneficial to attain higher purchase intention in the website shops and to generate more favorable attitudes toward the brand. Both the familiarity and the expertise with AI recommender systems showed some positive influence on the findings above, however, much remains to be explored in this topic to understand how to boost the levels of purchase intention and attitude toward the brand. |
id |
RCAP_db136c80158acdb8b2ea61b4ae43a778 |
---|---|
oai_identifier_str |
oai:repositorio.ucp.pt:10400.14/45175 |
network_acronym_str |
RCAP |
network_name_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository_id_str |
https://opendoar.ac.uk/repository/7160 |
spelling |
AI recommendations : impact of product type and number of options on users’ purchase intention and attitude toward the brandRecomendações de IA : impacto do tipo de produto e do número de opções na intenção de compra e atitude perante a marca dos utilizadoresAI recommender systemsChoice overloadHedonic vs. utilitarianNumber of optionsSistemas de recomendação de IASobrecarga de escolhaHedónico vs. utilitárioNúmero de opçõesIn a time of ever-growing options and information available, the introduction of AI recommender systems in brands’ websites emerged as a guiding tool for users’ decision-making process. While the complexity in consumer information is managed, still little is known about the impact of product type and the number of options of the recommendation in the users’ purchase intention and attitude toward the brand. To uncover the design that leads to a more successful AI recommendation, an experiment was ran with the manipulation of product type and number of alternatives provided. The results confirm the better adequacy of AI recommender systems for utilitarian products, in comparison to hedonic products, regarding purchase intention. As for the number of options, there is no one-size-fits-all rule for all products. However, for utilitarian products, this study suggests that providing larger choice sets of recommendations is beneficial to attain higher purchase intention in the website shops and to generate more favorable attitudes toward the brand. Both the familiarity and the expertise with AI recommender systems showed some positive influence on the findings above, however, much remains to be explored in this topic to understand how to boost the levels of purchase intention and attitude toward the brand.Mendonça, CristinaVeritatiRibeiro, Francisca2024-05-17T15:00:15Z2024-01-222024-012024-01-22T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.14/45175urn:tid:203534565enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-13T12:10:38Zoai:repositorio.ucp.pt:10400.14/45175Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T01:47:09.974927Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
AI recommendations : impact of product type and number of options on users’ purchase intention and attitude toward the brand Recomendações de IA : impacto do tipo de produto e do número de opções na intenção de compra e atitude perante a marca dos utilizadores |
title |
AI recommendations : impact of product type and number of options on users’ purchase intention and attitude toward the brand |
spellingShingle |
AI recommendations : impact of product type and number of options on users’ purchase intention and attitude toward the brand Ribeiro, Francisca AI recommender systems Choice overload Hedonic vs. utilitarian Number of options Sistemas de recomendação de IA Sobrecarga de escolha Hedónico vs. utilitário Número de opções |
title_short |
AI recommendations : impact of product type and number of options on users’ purchase intention and attitude toward the brand |
title_full |
AI recommendations : impact of product type and number of options on users’ purchase intention and attitude toward the brand |
title_fullStr |
AI recommendations : impact of product type and number of options on users’ purchase intention and attitude toward the brand |
title_full_unstemmed |
AI recommendations : impact of product type and number of options on users’ purchase intention and attitude toward the brand |
title_sort |
AI recommendations : impact of product type and number of options on users’ purchase intention and attitude toward the brand |
author |
Ribeiro, Francisca |
author_facet |
Ribeiro, Francisca |
author_role |
author |
dc.contributor.none.fl_str_mv |
Mendonça, Cristina Veritati |
dc.contributor.author.fl_str_mv |
Ribeiro, Francisca |
dc.subject.por.fl_str_mv |
AI recommender systems Choice overload Hedonic vs. utilitarian Number of options Sistemas de recomendação de IA Sobrecarga de escolha Hedónico vs. utilitário Número de opções |
topic |
AI recommender systems Choice overload Hedonic vs. utilitarian Number of options Sistemas de recomendação de IA Sobrecarga de escolha Hedónico vs. utilitário Número de opções |
description |
In a time of ever-growing options and information available, the introduction of AI recommender systems in brands’ websites emerged as a guiding tool for users’ decision-making process. While the complexity in consumer information is managed, still little is known about the impact of product type and the number of options of the recommendation in the users’ purchase intention and attitude toward the brand. To uncover the design that leads to a more successful AI recommendation, an experiment was ran with the manipulation of product type and number of alternatives provided. The results confirm the better adequacy of AI recommender systems for utilitarian products, in comparison to hedonic products, regarding purchase intention. As for the number of options, there is no one-size-fits-all rule for all products. However, for utilitarian products, this study suggests that providing larger choice sets of recommendations is beneficial to attain higher purchase intention in the website shops and to generate more favorable attitudes toward the brand. Both the familiarity and the expertise with AI recommender systems showed some positive influence on the findings above, however, much remains to be explored in this topic to understand how to boost the levels of purchase intention and attitude toward the brand. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024-05-17T15:00:15Z 2024-01-22 2024-01 2024-01-22T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.14/45175 urn:tid:203534565 |
url |
http://hdl.handle.net/10400.14/45175 |
identifier_str_mv |
urn:tid:203534565 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
instname_str |
FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository.name.fl_str_mv |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
repository.mail.fl_str_mv |
info@rcaap.pt |
_version_ |
1833601120967065600 |