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A linguistic similarity method in case-based reasoning for performance evaluation in Tunisian banking sector

A linguistic similarity method in case-based reasoning for performance evaluation in Tunisian... The performance evaluation of banks is an essential task in the determination of banks’ capabilities to compete in the sector. The conventional method – a calculation by intuition – for devising such evaluations is often inaccurate. To overcome these difficulties, this paper proposes that case-based reasoning (CBR) could be employed to provide performance evaluations from historical banks of Tunisian banking sector. The main objective of these evaluations is to transform data and statistics into synthetic information easy to understand by several groups of people in the banking domain such as creditors, investors and stakeholders. The aim of this study is to propose a linguistic similarity method in the retrieval mechanism of CBR to evaluate the banks’ performances. By this way, the two-tuple linguistic representation model is integrated in the proposed model. The weights of criteria are determined based on the opinions of experts using the Choquet integral to model interactions between them. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Information and Decision Sciences Inderscience Publishers

A linguistic similarity method in case-based reasoning for performance evaluation in Tunisian banking sector

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1756-7017
eISSN
1756-7025
DOI
10.1504/IJIDS.2012.045128
Publisher site
See Article on Publisher Site

Abstract

The performance evaluation of banks is an essential task in the determination of banks’ capabilities to compete in the sector. The conventional method – a calculation by intuition – for devising such evaluations is often inaccurate. To overcome these difficulties, this paper proposes that case-based reasoning (CBR) could be employed to provide performance evaluations from historical banks of Tunisian banking sector. The main objective of these evaluations is to transform data and statistics into synthetic information easy to understand by several groups of people in the banking domain such as creditors, investors and stakeholders. The aim of this study is to propose a linguistic similarity method in the retrieval mechanism of CBR to evaluate the banks’ performances. By this way, the two-tuple linguistic representation model is integrated in the proposed model. The weights of criteria are determined based on the opinions of experts using the Choquet integral to model interactions between them.

Journal

International Journal of Information and Decision SciencesInderscience Publishers

Published: Jan 1, 2012

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