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Segmentacijska analiza poslovnih klijenata banaka pomoću samo-organizirajućih mapa

  • Sandro Juković

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    Samo-organizirajuće mape (SOM) su dvoslojne umjetne neuronske mreže koje su inicijalno kreirane za rješavanje problema klaster analize, vizualizacije i apstrakcije podataka. Njihov najveći doprinos je u području vizualizacije više-dimenzionalnih podataka na dvo-dimenzionalnu mapu, koja odražava eventualne veze među ulaznim podacima. Cilj ovog rada je prezentirati teorijsku osnovu SOM-a i prikazati primjenu metode u svrhu segmentacije tržišta. U radu je objašnjen algoritam SOM-Ward koji je implementiran u softveru Viscovery SOMine. Tada je u istom softveru provedena klaster analiza prema anketi poslovnih klijenata banaka. Nakon toga su prikazani i interpretirani rezultati te analize kao tri segmenta. Segmenti se razlikuju s obzirom na atribute trgovinskog poslovanja s inozemstvom (uvoz/izvoz), godišnje prihod, podrijetlo kapitala, stavove o odabiru kredita, planove zapošljavanja itd. Tako kreirani segmenti mogu biti korišteni za daljnje odlučivanje o poduzimanju marketinških aktivnosti.

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    File URL: http://web.efzg.hr/repec/pdf/Clanak%2010-08.pdf
    File Function: First version, 2010
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    Paper provided by Faculty of Economics and Business, University of Zagreb in its series EFZG Working Papers Series with number 1008.

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    Length: 16
    Date of creation: 15 Nov 2010
    Date of revision:
    Handle: RePEc:zag:wpaper:1008
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