A Posteriori Segmentation of Personal Profiles of Online Video Games’ Players

There are diverse segmentations of online players in the literature. Most of them are proposed a priori, and there are no segmentations based on the acceptance of technology and the personal values of the players. The foremost purpose of this study is to obtain a posteriori segmentation of online vi...

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Authors: Ramírez Correa, Patricio E., Rondán Cataluña, Francisco Javier, Arenas Gaitán, Jorge
Format: article
Status:Versión aceptada para publicación
Publication Date:2020
Country:España
Institution:Universidad de Sevilla (US)
Repository:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/180437
Online Access:https://hdl.handle.net/11441/180437
https://doi.org/10.1177/1555412018766786
Access Level:Open access
Keyword:Online video games
PLS-POS
UTAUT model
Personal value
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spelling A Posteriori Segmentation of Personal Profiles of Online Video Games’ PlayersRamírez Correa, Patricio E.Rondán Cataluña, Francisco JavierArenas Gaitán, JorgeOnline video gamesPLS-POSUTAUT modelPersonal valueThere are diverse segmentations of online players in the literature. Most of them are proposed a priori, and there are no segmentations based on the acceptance of technology and the personal values of the players. The foremost purpose of this study is to obtain a posteriori segmentation of online video games’ players, founded on unified theory of acceptance and use of technology model, and to describe the subsequent segments consistent with the personal values of Schwartz. The measurement model and the structural model were analyzed with partial least squares (PLS). Subsequently, the PLS-prediction-oriented segmentation technique has been devoted to inspecting unobserved heterogeneity and to find players’ segments. Four segments are obtained from the statistical analysis, and data analysis shown that in each of the segments, the explained variance of both use and behavioral intention (which are the endogenous variables of the model) is significantly improved by comparing the results of the global sample.SageAdministración de Empresas y Marketing2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/180437https://doi.org/10.1177/1555412018766786reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésGames and Culture, 15 (3), 227-247.https://doi.org/10.1177/1555412018766786info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1804372026-06-17T12:51:07Z
dc.title.none.fl_str_mv A Posteriori Segmentation of Personal Profiles of Online Video Games’ Players
title A Posteriori Segmentation of Personal Profiles of Online Video Games’ Players
spellingShingle A Posteriori Segmentation of Personal Profiles of Online Video Games’ Players
Ramírez Correa, Patricio E.
Online video games
PLS-POS
UTAUT model
Personal value
title_short A Posteriori Segmentation of Personal Profiles of Online Video Games’ Players
title_full A Posteriori Segmentation of Personal Profiles of Online Video Games’ Players
title_fullStr A Posteriori Segmentation of Personal Profiles of Online Video Games’ Players
title_full_unstemmed A Posteriori Segmentation of Personal Profiles of Online Video Games’ Players
title_sort A Posteriori Segmentation of Personal Profiles of Online Video Games’ Players
dc.creator.none.fl_str_mv Ramírez Correa, Patricio E.
Rondán Cataluña, Francisco Javier
Arenas Gaitán, Jorge
author Ramírez Correa, Patricio E.
author_facet Ramírez Correa, Patricio E.
Rondán Cataluña, Francisco Javier
Arenas Gaitán, Jorge
author_role author
author2 Rondán Cataluña, Francisco Javier
Arenas Gaitán, Jorge
author2_role author
author
dc.contributor.none.fl_str_mv Administración de Empresas y Marketing
dc.subject.none.fl_str_mv Online video games
PLS-POS
UTAUT model
Personal value
topic Online video games
PLS-POS
UTAUT model
Personal value
description There are diverse segmentations of online players in the literature. Most of them are proposed a priori, and there are no segmentations based on the acceptance of technology and the personal values of the players. The foremost purpose of this study is to obtain a posteriori segmentation of online video games’ players, founded on unified theory of acceptance and use of technology model, and to describe the subsequent segments consistent with the personal values of Schwartz. The measurement model and the structural model were analyzed with partial least squares (PLS). Subsequently, the PLS-prediction-oriented segmentation technique has been devoted to inspecting unobserved heterogeneity and to find players’ segments. Four segments are obtained from the statistical analysis, and data analysis shown that in each of the segments, the explained variance of both use and behavioral intention (which are the endogenous variables of the model) is significantly improved by comparing the results of the global sample.
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/180437
https://doi.org/10.1177/1555412018766786
url https://hdl.handle.net/11441/180437
https://doi.org/10.1177/1555412018766786
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Games and Culture, 15 (3), 227-247.
https://doi.org/10.1177/1555412018766786
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Sage
publisher.none.fl_str_mv Sage
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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