Application of a Fuzzy Model of Economicfinancial Diagnosis to Smes

Terceño, Antonio; Vigier, Hernán Pedro; Scherger, Valeria

doi:10.1142/9789814415774_0010

Cited by 3 publications

(3 citation statements)

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“…For the symptoms, the model mentions that financial economic ratios that arise from the financial statements of companies need to be used, without specifying which ones. A partial study [57] presents the list of symptoms selected for the analysis. d) Detection of causes.…”

Section: Limitationsmentioning

confidence: 99%

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An application of OWA operators in fuzzy business diagnosis

Vigier

Scherger

Terceño

2017

Applied Soft Computing

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The paper aims to develop an adjustment index based on OWA operators to enrich the results of diagnostic fuzzy models of business failure. A proposal to verify the diseases prediction accuracy of the models is also added. This allows a reduction of the map of causes or diseases detected in strategic defined areas. At the same time, these key areas can be disaggregated when an alert indicator is identified, and shows which of the causes need special attention. This application of OWA can encourage the development of suitable computer systems for monitoring companies' problems, warn of failures and facilitate decision-making. In addition, taking Vigier and Terceño's 2008 model as a benchmark, causes aggregation operators are introduced to evaluate alternative groupings, and the adjustment measure using approximate solutions is proposed to test the model's prediction.The empirical estimation and the verification of the improvement proposals in a set of small and medium-sized enterprises (SMEs) in the construction industry are also presented. The functionality and the prediction capacity are thus measured and detected by monitoring key areas that warn about insolvency situations in the firm.

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Section: Limitationsmentioning

confidence: 99%

“…The list and classification of symptoms are presented in Ref. [57] and are available at http://fuzzybusinessdiagnosis.blogspot.com.ar.…”

Section: Definition Of Causes and Symptomsmentioning

confidence: 99%

An application of OWA operators in fuzzy business diagnosis

Vigier

Scherger

Terceño

2017

Applied Soft Computing

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“…Regarding the symptoms, the model mentions that financial economic ratios that arise from the financial statements of companies need to be used without specifying which ones. In a partial study (Terceño et al , 2012), the list of symptoms selected for the analysis is presented.…”

Section: Advantages and Limitations Of Vigier And Terceño’s Modelmentioning

confidence: 99%

The OWA distance operator and its application in business failure

Scherger

Terceño

Vigier

2017

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Purpose The purpose of this paper is to develop a goodness index based on Hamming distance and ordered weighted averaging distance (OWAD), which is useful to make decisions. These alternative measures enrich the results of diagnostic fuzzy models and facilitate the experts’ task in decision-making. An application to a set of firms to verify the results is also presented. Design/methodology/approach The paper follows the basis of OWA operators to design a methodology to reduce the map of causes of business failure into monitoring key areas. Findings The present paper introduces two alternative measures to test the proposal of grouping. In the empirical application, the superiority of the minimum T-norm over other decision rules is verified. The ordered weighted averaging distance (OWAD) goodness index predicts a better adjustment over the index built using OWA and Hamming distance measures. Practical implications A useful mechanism to reduce the map of causes or diseases detected in key areas is added through this analysis. At the same time, these key areas can be disaggregated once some alert indicator is identified; this allows knowing the causes that require special attention. This application of OWA can encourage the development of suitable computer systems for monitoring the firm’s problems, alerting regarding failures and easing decision-making. Originality/value A comparison of grouping causes into key areas through a goodness index based on Hamming distance and OWAD is proposed. These contributions enrich the Vigier and Terceño (2008) model and could be applied to any model of fuzzy diagnosis to test the results.

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