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Separating successful and unsuccessful firms using multiple attribute decision-making methods

Separating successful and unsuccessful firms using multiple attribute decision-making methods Due to less efficiency in Tehran Stock Market, the common methods employed for ranking firms are not reliable enough. In this paper, combined decision-making models are presented which can evaluate the companies’ financial performance by means of financial ratios. One of the considered approaches is based on ‘analytical hierarchy process (AHP)’ and ‘technique for order preference by similarity to ideal solution (TOPSIS)’ and the other one, which is proposed similarly in this paper, is based on ‘fuzzy analytical hierarchy process (FAHP)’ and ‘TOPSIS’. Comparisons of these methods would specify the similarities or differences between them and also examine the superiority of FAHP over AHP which is widely accepted as the result of using fuzzy numbers. These methods were applied for ranking and evaluating financial performances of cement firms in Tehran Stock Exchange using their financial tables from 2002 to 2008. Eventually through statistical tests, the results obtained from these methods and their powers were compared. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Information and Decision Sciences Inderscience Publishers

Separating successful and unsuccessful firms using multiple attribute decision-making methods

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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.2012.045126
Publisher site
See Article on Publisher Site

Abstract

Due to less efficiency in Tehran Stock Market, the common methods employed for ranking firms are not reliable enough. In this paper, combined decision-making models are presented which can evaluate the companies’ financial performance by means of financial ratios. One of the considered approaches is based on ‘analytical hierarchy process (AHP)’ and ‘technique for order preference by similarity to ideal solution (TOPSIS)’ and the other one, which is proposed similarly in this paper, is based on ‘fuzzy analytical hierarchy process (FAHP)’ and ‘TOPSIS’. Comparisons of these methods would specify the similarities or differences between them and also examine the superiority of FAHP over AHP which is widely accepted as the result of using fuzzy numbers. These methods were applied for ranking and evaluating financial performances of cement firms in Tehran Stock Exchange using their financial tables from 2002 to 2008. Eventually through statistical tests, the results obtained from these methods and their powers were compared.

Journal

International Journal of Information and Decision SciencesInderscience Publishers

Published: Jan 1, 2012

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