| dc.creator |
Köllinger, Philipp |
|
| dc.creator |
Schade, Christian |
|
| dc.date |
2003 |
|
| dc.date.accessioned |
2013-10-16T06:58:11Z |
|
| dc.date.available |
2013-10-16T06:58:11Z |
|
| dc.date.issued |
2013-10-16 |
|
| dc.identifier |
http://hdl.handle.net/10419/18082 |
|
| dc.identifier |
ppn:371860725 |
|
| dc.identifier.uri |
http://koha.mediu.edu.my:8181/xmlui/handle/10419/18082 |
|
| dc.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. |
|
| dc.language |
eng |
|
| dc.publisher |
Deutsches Institut für Wirtschaftsforschung (DIW) Berlin |
|
| dc.relation |
DIW-Diskussionspapiere 346 |
|
| dc.rights |
http://www.econstor.eu/dspace/Nutzungsbedingungen |
|
| dc.subject |
L29 |
|
| dc.subject |
C14 |
|
| dc.subject |
O30 |
|
| dc.subject |
ddc:330 |
|
| dc.subject |
Technology Adoption |
|
| dc.subject |
Path Dependence |
|
| dc.subject |
Interaction Between Different Technologies |
|
| dc.subject |
Regression Trees |
|
| dc.subject |
Predictive Segmentation |
|
| dc.subject |
Logistic Regression |
|
| dc.subject |
Computergestütztes Lernen |
|
| dc.subject |
Betriebliche Bildungsarbeit |
|
| dc.subject |
E-Business |
|
| dc.subject |
Innovationsdiffusion |
|
| dc.subject |
Schätzung |
|
| dc.subject |
EU-Staaten |
|
| dc.title |
Analyzing E-Learning Adoption via Recursive Partitioning |
|
| dc.type |
doc-type:workingPaper |
|