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dc.contributor.authorKöllinger, Philippen
dc.contributor.authorSchade, Christianen
dc.date.accessioned2009-01-28T15:39:15Z-
dc.date.available2009-01-28T15:39:15Z-
dc.date.issued2003-
dc.identifier.urihttp://hdl.handle.net/10419/18082-
dc.description.abstractThe paper analyzes factors that influence the adoption of e-learning and gives an example of how to forecast technology adoption based on a post-hoc predictive segmentation using a classification and regression tree (CART). We find strong evidence for the existence of technological interdependencies and organizational learning effects. Furthermore, we find different paths to e-learning adoption. The results of the analysis suggest a growing ?digital divide? among firms. We use cross-sectional data from a European survey about e-business in June 2002, covering almost 6,000 enterprises in 15 industry sectors and 4 countries. Comparing the predictive quality of CART, we find that CART outperforms a traditional logistic regression. The results are more parsimo-nious, i. e. CARTs use less explanatory variables, better interpretable since different paths of adoption are detected, and from a statistical standpoint, because interactions between the covariates are taken into account.en
dc.language.isoengen
dc.publisher|aDeutsches Institut für Wirtschaftsforschung (DIW) |cBerlinen
dc.relation.ispartofseries|aDIW Discussion Papers |x346en
dc.subject.jelL29en
dc.subject.jelC14en
dc.subject.jelO30en
dc.subject.ddc330en
dc.subject.keywordTechnology Adoptionen
dc.subject.keywordPath Dependenceen
dc.subject.keywordInteraction Between Different Technologiesen
dc.subject.keywordRegression Treesen
dc.subject.keywordPredictive Segmentationen
dc.subject.keywordLogistic Regressionen
dc.subject.stwComputergestütztes Lernenen
dc.subject.stwBetriebliche Bildungsarbeiten
dc.subject.stwE-Businessen
dc.subject.stwInnovationsdiffusionen
dc.subject.stwSchätzungen
dc.subject.stwEU-Staatenen
dc.titleAnalyzing E-Learning Adoption via Recursive Partitioning-
dc.typeWorking Paperen
dc.identifier.ppn850618606en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:diw:diwwpp:dp346en

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