{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T14:41:17Z","timestamp":1780065677077,"version":"3.54.0"},"reference-count":45,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2018,4,18]],"date-time":"2018-04-18T00:00:00Z","timestamp":1524009600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Games and Culture"],"published-print":{"date-parts":[[2020,5]]},"abstract":"<jats:p>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\u2019 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\u2019 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.<\/jats:p>","DOI":"10.1177\/1555412018766786","type":"journal-article","created":{"date-parts":[[2018,4,18]],"date-time":"2018-04-18T22:05:17Z","timestamp":1524089117000},"page":"227-247","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":14,"title":["A Posteriori Segmentation of Personal Profiles of Online Video Games\u2019 Players"],"prefix":"10.1177","volume":"15","author":[{"given":"Patricio E.","family":"Ram\u00edrez-Correa","sequence":"first","affiliation":[{"name":"School of Engineering, Universidad Cat\u00f3lica del Norte, Coquimbo, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0368-5335","authenticated-orcid":false,"given":"F. 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