Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/81384
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dc.contributor.authorCho, Gyeongcheol-
dc.contributor.authorHwang, Heungsun-
dc.contributor.authorSarstedt, Marko-
dc.contributor.authorRingle, Christian M.-
dc.date.accessioned2022-04-05T09:30:45Z-
dc.date.available2022-04-05T09:30:45Z-
dc.date.issued2020-
dc.date.submitted2020-
dc.identifier.urihttps://opendata.uni-halle.de//handle/1981185920/83339-
dc.identifier.urihttp://dx.doi.org/10.25673/81384-
dc.description.abstractGeneralized structured component analysis (GSCA) is a technically well-established approach to component-based structural equation modeling that allows for specifying and examining the relationships between observed variables and components thereof. GSCA provides overall fit indexes for model evaluation, including the goodness-of-fit index (GFI) and the standardized root mean square residual (SRMR). While these indexes have a solid standing in factor-based structural equation modeling, nothing is known about their performance in GSCA. Addressing this limitation, we present a simulation study’s results, which confirm that both GFI and SRMR indexes distinguish effectively between correct and misspecified models. Based on our findings, we propose rules-of-thumb cutoff criteria for each index in different sample sizes, which researchers could use to assess model fit in practice.eng
dc.description.sponsorshipProjekt DEAL 2020-
dc.language.isoeng-
dc.relation.ispartofhttp://link.springer.com/journal/41270-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectComponent-based structural equation modelingeng
dc.subjectGeneralized structured component analysiseng
dc.subjectModel fiteng
dc.subjectGFIeng
dc.subjectSRMReng
dc.subject.ddc650: Management-
dc.titleCutoff Criteria for Overall Model Fit Indexes in Generalized Structured Component Analysiseng
dc.typeArticle-
dc.identifier.urnurn:nbn:de:gbv:830-882.0106459-
dc.identifier.urnurn:nbn:de:gbv:ma9:1-1981185920-833398-
local.versionTypepublishedVersion-
local.bibliographicCitation.journaltitleJournal of marketing analytics-
local.bibliographicCitation.volume8-
local.bibliographicCitation.issue3-
local.bibliographicCitation.pagestart189-
local.bibliographicCitation.pageend202-
local.bibliographicCitation.publishernamePalgrave Macmillan-
local.bibliographicCitation.publisherplaceHoundmills-
local.bibliographicCitation.doi10.15480/882.2916-
local.openaccesstrue-
dc.identifier.ppn1733746412-
local.bibliographicCitation.year2020-
cbs.sru.importDate2022-04-05T09:27:20Z-
local.bibliographicCitationEnthalten in Journal of marketing analytics - Houndmills : Palgrave Macmillan, 2013-
local.accessrights.dnbfree-
Appears in Collections:Fakultät für Wirtschaftswissenschaft (OA)

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