Goodness of Aggregation Operators in a Diagnostic Fuzzy Model of Business Failure

Scherger, Valeria; Vigier, Hernán Pedro; Terceño, Antonio; Barberà-Mariné, M. Glòria

doi:10.1007/978-3-319-19704-3_12

Cited by 2 publications

(4 citation statements)

References 23 publications

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“…Thus, rigorous theoretical analysis is warranted to conceptualize financial failure. The extant literature considers a single criterion of financial distress (yes or no) rather than its intensity (Åstebro & Winter, 2012;Scherger et al, 2015). In future studies, researchers could explore a metric that can better classify failed companies into several degrees of seriousness, such as mild, intermediate, and seriously (permanently) failed (as does Back, 2005).…”

Section: Heterogeneous Failure Conceptmentioning

confidence: 99%

A review of the limitations of financial failure prediction research

2023

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The objective of this paper is to critically evaluate the main weaknesses associated with the limitations of financial failure prediction research studies. For more than 80 years, researchers have unsuccessfully studied ways to create a general theory of financial failure, which is useful for prediction. In this paper, we review the main boundaries of failure prediction research through a critical evaluation of previous papers and our own approach from the research experience. Our findings corroborate that these studies suffer from a lack of theoretical and dynamic research, an unclear definition of failure, deficiencies with the quality of financial statement data and a shortfall in the diagnostic analyses of failure. The most relevant implications for future research in this area are also outlined. This is the first study to analyse in deep the caveats of financial failure prediction studies, a crucial topic nowadays due to the hints of an economic crisis caused by the Covid-19 pandemic. El objetivo de este artículo es evaluar críticamente los principales puntos débiles asociados a las limitaciones de los estudios de investigación sobre predicción de quiebras financieras. Durante más de 80 años, los investigadores han estudiado sin éxito la forma de crear una teoría general del fracaso financiero que sea útil para la predicción. En este artículo, revisamos los principales límites de la investigación sobre predicción de quiebras mediante una evaluación crítica de trabajos anteriores y nuestro propio enfoque a partir de la experiencia investigadora. Nuestras conclusiones corroboran que estos estudios adolecen de una falta de investigación teórica y dinámica, una definición poco clara del fracaso, deficiencias con la calidad de los datos de los estados financieros y un déficit en los análisis de diagnóstico del fracaso. También se esbozan las implicaciones más relevantes para futuras investigaciones en este ámbito. Se trata del primer estudio que analiza en profundidad las salvedades de los estudios de predicción de la quiebra financiera, un tema crucial en la actualidad debido a los atisbos de crisis económica provocados por la pandemia del Covid-19.

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Section: Heterogeneous Failure Conceptmentioning

confidence: 99%

A review of the limitations of financial failure prediction research

2023

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“…Once causes and symptoms are defined, the empirical estimation is carried out. This application to a set of small and medium enterprises (SMEs) is presented by Scherger et al (2015a).…”

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

confidence: 99%

“…Therefore, given P′ , estimated by the inverse operation between Q and ℜ, that shows the multiple causes (or diseases) that a firm can undergo, a reduction mechanism of the map of causes through OWA operators is introduced. In the empirical estimation presented by Scherger et al (2015a), the R matrix with 2,952 r ij coefficients per year is estimated. That is a sum of 8,856 coefficients in the aggregated matrix ℜ that shows the true relationship between causes and symptoms.…”

Section: Owa Causes Aggregationmentioning

confidence: 99%

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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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Goodness of Aggregation Operators in a Diagnostic Fuzzy Model of Business Failure

Cited by 2 publications

References 23 publications

A review of the limitations of financial failure prediction research

A review of the limitations of financial failure prediction research

The OWA distance operator and its application in business failure

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