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Evolution of insurance company service quality survey, using self-learning neural network

Author

Listed:
  • Vladimír Konečný

    (Ústav informatiky, Mendelova univerzita v Brně, Zemědělská 1, 613 00 Brno, Česká republika)

  • Oldřich Trenz

    (Ústav informatiky, Mendelova univerzita v Brně, Zemědělská 1, 613 00 Brno, Česká republika)

  • Dana Dvořáková

    (Ústav informatiky, Mendelova univerzita v Brně, Zemědělská 1, 613 00 Brno, Česká republika)

Abstract

The objective of the paper is to demonstrate the abilities and possible approaches to classification of set of objects using self-organizing maps. As the objects, clients of an insurance company that made an agreement regarding mandatory insurance of motor vehicles were selected. The opinions of the clients and their overall satisfaction reflected in responses to presented answers.The clients were classified into three groups. The first two contained satisfied clients (i.e. good clients for the company), the last group contained clients that could potentially switch to the competitors. Subsequent analysis enabled discovering the reasons of low customer satisfaction and critical factors of losing the least satisfied clients.For the analysis of the responses (one hundred fifty-one) and the insurance company, experimental model of self-organizing map realized at the Department of informatics was used. Used experimental model has proved very effective software tool.

Suggested Citation

  • Vladimír Konečný & Oldřich Trenz & Dana Dvořáková, 2011. "Evolution of insurance company service quality survey, using self-learning neural network," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 59(2), pages 149-154.
    • Handle: RePEc:mup:actaun:actaun_2011059020149
    DOI: 10.11118/actaun201159020149
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