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Article: Predicting the survival or failure of click-and-mortar corporations: A knowledge discovery approach

TitlePredicting the survival or failure of click-and-mortar corporations: A knowledge discovery approach
Authors
KeywordsArtificial intelligence
Discriminant analysis
Knowledge discovery
Neural networks
Support vector machines
Issue Date2006
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/ejor
Citation
European Journal Of Operational Research, 2006, v. 174 n. 2, p. 959-982 How to Cite?
AbstractWith the boom in e-business, several corporations have emerged in the late 1990s that have primarily conducted their business through the Internet and the Web. They have come to be known as the dotcoms or click-and-mortar corporations. The success of these companies has been short lived. This research is an investigation of the burst of the dotcom bubble from a financial perspective. Data from the financial statements of several survived and failed dotcom companies is used to compute financial ratios, which are analyzed using three classification techniques-discriminant analysis, neural networks, and support vector machines to find out whether they can predict the financial fate of companies. Neural networks perform the task better than other techniques. Using discriminant analysis and neural networks, the key financial ratios that play a major role in the process of prediction are identified. Statistical tests are conducted to validate the findings. © 2005 Elsevier B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/85877
ISSN
2015 Impact Factor: 2.679
2015 SCImago Journal Rankings: 2.595
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorBose, Ien_HK
dc.contributor.authorPal, Ren_HK
dc.date.accessioned2010-09-06T09:10:16Z-
dc.date.available2010-09-06T09:10:16Z-
dc.date.issued2006en_HK
dc.identifier.citationEuropean Journal Of Operational Research, 2006, v. 174 n. 2, p. 959-982en_HK
dc.identifier.issn0377-2217en_HK
dc.identifier.urihttp://hdl.handle.net/10722/85877-
dc.description.abstractWith the boom in e-business, several corporations have emerged in the late 1990s that have primarily conducted their business through the Internet and the Web. They have come to be known as the dotcoms or click-and-mortar corporations. The success of these companies has been short lived. This research is an investigation of the burst of the dotcom bubble from a financial perspective. Data from the financial statements of several survived and failed dotcom companies is used to compute financial ratios, which are analyzed using three classification techniques-discriminant analysis, neural networks, and support vector machines to find out whether they can predict the financial fate of companies. Neural networks perform the task better than other techniques. Using discriminant analysis and neural networks, the key financial ratios that play a major role in the process of prediction are identified. Statistical tests are conducted to validate the findings. © 2005 Elsevier B.V. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/ejoren_HK
dc.relation.ispartofEuropean Journal of Operational Researchen_HK
dc.rightsEuropean Journal Of Operational Research. Copyright © Elsevier BV.en_HK
dc.subjectArtificial intelligenceen_HK
dc.subjectDiscriminant analysisen_HK
dc.subjectKnowledge discoveryen_HK
dc.subjectNeural networksen_HK
dc.subjectSupport vector machinesen_HK
dc.titlePredicting the survival or failure of click-and-mortar corporations: A knowledge discovery approachen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0377-2217&volume=174&spage=959&epage=982&date=2006&atitle=Predicting+the+Survival+or+Failure+of+Click-and-Mortar+Corporations:+A+Knowledge+Discovery+Approachen_HK
dc.identifier.emailBose, I: bose@business.hku.hken_HK
dc.identifier.authorityBose, I=rp01041en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.ejor.2005.05.009en_HK
dc.identifier.scopuseid_2-s2.0-33746377912en_HK
dc.identifier.hkuros122549en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33746377912&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume174en_HK
dc.identifier.issue2en_HK
dc.identifier.spage959en_HK
dc.identifier.epage982en_HK
dc.identifier.isiWOS:000239751300018-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridBose, I=7003751502en_HK
dc.identifier.scopusauthoridPal, R=55435080500en_HK

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