Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen:
https://hdl.handle.net/10419/18082
Kompletter Metadatensatz
DublinCore-Feld | Wert | Sprache |
---|---|---|
dc.contributor.author | Köllinger, Philipp | en |
dc.contributor.author | Schade, Christian | en |
dc.date.accessioned | 2009-01-28T15:39:15Z | - |
dc.date.available | 2009-01-28T15:39:15Z | - |
dc.date.issued | 2003 | - |
dc.identifier.uri | http://hdl.handle.net/10419/18082 | - |
dc.description.abstract | The 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.iso | eng | en |
dc.publisher | |aDeutsches Institut für Wirtschaftsforschung (DIW) |cBerlin | en |
dc.relation.ispartofseries | |aDIW Discussion Papers |x346 | en |
dc.subject.jel | L29 | en |
dc.subject.jel | C14 | en |
dc.subject.jel | O30 | en |
dc.subject.ddc | 330 | en |
dc.subject.keyword | Technology Adoption | en |
dc.subject.keyword | Path Dependence | en |
dc.subject.keyword | Interaction Between Different Technologies | en |
dc.subject.keyword | Regression Trees | en |
dc.subject.keyword | Predictive Segmentation | en |
dc.subject.keyword | Logistic Regression | en |
dc.subject.stw | Computergestütztes Lernen | en |
dc.subject.stw | Betriebliche Bildungsarbeit | en |
dc.subject.stw | E-Business | en |
dc.subject.stw | Innovationsdiffusion | en |
dc.subject.stw | Schätzung | en |
dc.subject.stw | EU-Staaten | en |
dc.title | Analyzing E-Learning Adoption via Recursive Partitioning | - |
dc.type | Working Paper | en |
dc.identifier.ppn | 850618606 | en |
dc.rights | http://www.econstor.eu/dspace/Nutzungsbedingungen | en |
dc.identifier.repec | RePEc:diw:diwwpp:dp346 | en |
Datei(en):
Publikationen in EconStor sind urheberrechtlich geschützt.