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European Insurance Market Analysis: A Multivariate Clustering approach

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12510%2F18%3A43898943" target="_blank" >RIV/60076658:12510/18:43898943 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    European Insurance Market Analysis: A Multivariate Clustering approach

  • Original language description

    Clustering has been proved to extract valuable information resided in complex and massive data sets. Motivated by this evidence, this paper is aimed to provide a multivariate clustering of European insurance market in terms of the insurance penetration curves of European countries. Yet, at the same time, this clustering is provided through two different cases, where the first case considers only the magnitude (size) of these curves, and the second considers only their shape. In this paper, two partitional clustering methods are utilized, k-means and Gaussian mixture model, with two distance measures, the Euclidean and Mahalanobis distance, respectively. Both clustering methods form clusters within a sample of 34 European countries observed between 2004 and 2016; that is before, during and post-financial and sovereign debt crises. The clustering solutions also reveal the extent to which the employed clustering methods and distance measures are being able to capture the distinctive properties of the original curves as depicted during the period under examination.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    50204 - Business and management

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 12th International Scientific Conference INPROFORUM. Innovations, Enterprises, Regions and Management

  • ISBN

    978-80-7394-726-2

  • ISSN

  • e-ISSN

    neuvedeno

  • Number of pages

    7

  • Pages from-to

    328-334

  • Publisher name

    Jihočeská univerzita v Českých Budějovicích, Ekonomická fakulta

  • Place of publication

    České Budějovice

  • Event location

    České Budějovice

  • Event date

    Nov 1, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article