Revenue growth prediction for small and medium-sized enterprises: a data mining approach for the insurance industry
dc.contributor.author
Müller, Daniel
dc.contributor.supervisor
Fleisch, Elgar
dc.contributor.supervisor
von Wangenheim, Florian
dc.date.accessioned
2018-08-24T12:20:44Z
dc.date.available
2018-08-24T12:07:42Z
dc.date.available
2018-08-24T12:20:44Z
dc.date.issued
2018
dc.identifier.uri
http://hdl.handle.net/20.500.11850/284491
dc.identifier.doi
10.3929/ethz-b-000284491
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
ETH Zurich
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.title
Revenue growth prediction for small and medium-sized enterprises: a data mining approach for the insurance industry
en_US
dc.type
Doctoral Thesis
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2018-08-24
ethz.size
204 p.
en_US
ethz.code.ddc
DDC - DDC::3 - Social sciences::330 - Economics
ethz.identifier.diss
25244
en_US
ethz.publication.place
Zurich
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03681 - Fleisch, Elgar / Fleisch, Elgar
en_US
ethz.date.deposited
2018-08-24T12:07:43Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2018-08-24T12:20:49Z
ethz.rosetta.lastUpdated
2024-02-02T05:47:22Z
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true
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Publikationstyp
-
Doctoral Thesis [30262]