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DC poleHodnotaJazyk
dc.contributor.authorDraessler, Jan
dc.contributor.authorSoukal, Ivan
dc.contributor.authorHedvičáková, Martina
dc.date.accessioned2016-01-15T09:33:26Z
dc.date.available2016-01-15T09:33:26Z
dc.date.issued2011
dc.identifier.citationE+M. Ekonomie a Management = Economics and Management. 2011, č. 4, s. 102-114.cs
dc.identifier.issn1212-3609 (Print)
dc.identifier.issn2336-5604 (Online)
dc.identifier.urihttp://www.ekonomie-management.cz/download/1346067033_db25/2011_04_draessler_soukal_hedvicakova.pdf
dc.identifier.urihttp://hdl.handle.net/11025/17421
dc.format13 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isocscs
dc.publisherTechnická univerzita v Libercics
dc.relation.ispartofseriesE+M. Ekonomie a Management = Economics and Managementcs
dc.rights© Technická univerzita v Libercics
dc.rightsCC BY-NC 4.0cs
dc.subjectshluková analýzacs
dc.subjectinformační asymetriecs
dc.subjectmaloobchodní klíčový trh bankovních služebcs
dc.titleShluková analýza poptávkové strany trhu základních bankovních služebcs
dc.title.alternativeCluster analysis of the demand side of the retail core banking services marketen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedThis paper is focused on the retail core banking services market. The demand side of this market is affected by the negative effects of the information asymmetry. European Union authorities are aware of that as they monitor the situation as well as they set out possible solutions that should reduce the main sources of asymmetry – offer opacity and the lack of offer comparison tools. In the Czech Republic there was introduced independent comparison tool project in the 2010. This system’s database holds more than 15,000 answers about the day-to-day usage. This serves as a data source for our analysis. The aim is to classify the Czech working age e-banking clients, i.e. to identify basic retail core banking services usage patterns. As preparations there were performed verification-validation phase, logarithmical transformation and dimension reduction by principal component analysis. The two-step cluster analysis was performed on 8,549 members classified by 19 variables concerning the type of the service, moth usage frequency or average amount of mo- ney, communication channel used to order the service and the bank the money were transferred to. Analysis indentified as an optimal number of clusters 3. There were identified mainstream client, more active client and the client with the “at the desk” preference. Sub-optimal, but still accepta- ble, solution was consisted of 4 clusters: mainstream client with his or hers own bank preference, mainstream client with other bank preference, less active client and “at the desk” preference cli- ent. Identified clusters don’t just describe the demand side as standard marketing research output but they can be used again as an information asymmetry reduction tool.en
dc.subject.translatedcluster analysisen
dc.subject.translatedinformation asymmetryen
dc.subject.translatedretail core banking services marketen
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:Číslo 4 (2011)
Číslo 4 (2011)

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  1. DSpace at University of West Bohemia
  2. Publikace ZČU / UWB Publications
  3. Časopisy ZČU / UWB Journals
  4. Ekonomie a management
  5. 2011
  6. Číslo 4 (2011)