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http://dspace.mediu.edu.my:8181/xmlui/handle/10419/18082| Title: | Analyzing E-Learning Adoption via Recursive Partitioning |
| Keywords: | L29 C14 O30 ddc:330 Technology Adoption Path Dependence Interaction Between Different Technologies Regression Trees Predictive Segmentation Logistic Regression Computergestütztes Lernen Betriebliche Bildungsarbeit E-Business Innovationsdiffusion Schätzung EU-Staaten |
| Issue Date: | 16-Oct-2013 |
| Publisher: | Deutsches Institut für Wirtschaftsforschung (DIW) Berlin |
| Description: | 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. |
| URI: | http://koha.mediu.edu.my:8181/xmlui/handle/10419/18082 |
| Other Identifiers: | http://hdl.handle.net/10419/18082 ppn:371860725 |
| Appears in Collections: | EconStor |
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