Share:


An idiosyncratic decision support system for credit risk analysis of small and medium-sized enterprises

    Tânia S. H. Gonçalves Affiliation
    ; Fernando A. F. Ferreira Affiliation
    ; Marjan S. Jalali Affiliation
    ; Ieva Meidutė-Kavaliauskienė Affiliation

Abstract

Small and medium-sized enterprises (SMEs) are currently considered an important driving force of economic growth. Several studies have been developed to analyse this issue and, in particular, to assess the credit risk of SMEs. Most of these applications, however, share the same methodological limitations, such as the manner by which criteria are selected, or the methods used for calculating the weights between them. Based on the integrated use of cognitive mapping techniques and the Interactive Multiple Criteria Decision Making (TODIM) approach, this study aims to create an idiosyncratic decision support system for the identification of multiple criteria and the calculation of their respective weights (i.e. the trade-offs) in the evaluation of SME credit risk. The results show that the model created in this study allows for simple and straightforward credit concession decisions, facilitating the evaluation of SME credit applications through more informed and transparent risk assessments. Practical implications, strengths and weaknesses of the proposed framework are analysed and discussed.


First published online: 02 Nov 2015

Keyword : credit risk analysis, multiple criteria decision analysis (MCDA), small and mediumsized enterprises (SMEs), TODIM (Portuguese acronym for interactive multiple criteria decision making)

How to Cite
Gonçalves, T. S. H., Ferreira, F. A. F., Jalali, M. S., & Meidutė-Kavaliauskienė, I. (2016). An idiosyncratic decision support system for credit risk analysis of small and medium-sized enterprises. Technological and Economic Development of Economy, 22(4), 598-616. https://doi.org/10.3846/20294913.2015.1074125
Published in Issue
Jun 27, 2016
Abstract Views
1593
PDF Downloads
913
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.