Papers by Valeria Scherger
Ungdomsstraffen - en fare for barns rettssikkerhet?
Kritisk juss, 2015
Contaduría y Administración, Sep 20, 2023
Dada la importancia de las MiPyMEs (Micro, Pequeñas y Medianas Empresas) en las economías y el im... more Dada la importancia de las MiPyMEs (Micro, Pequeñas y Medianas Empresas) en las economías y el impacto de las medidas abordadas por los gobiernos para sobrellevar los efectos de la pandemia de 2020, resulta relevante identificar los factores críticos que incidieron sobre el éxito empresarial. Se analiza la situación post-pandemia de 154 MiPyMEs argentinas teniendo en cuenta el perfil de los empresarios, las características de los emprendimientos y las medidas y estrategias abordadas durante el período de estudio. Se aplican modelos logit ordinales para detectar la incidencia de estos factores sobre la situación postpandemia. Se identifica una mayor incidencia de los factores internos frente a los externos sobre el desempeño empresarial, destacándose la capacidad de resiliencia, la capacidad del management para gestionar las MiPyMEs y las mejoras implementadas en el proceso productivo como determinantes positivos para que las empresas registren una situación post-pandemia buena.
Prediction of Business Failure with Fuzzy Models
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Dec 1, 2018
This paper extends the theory of fuzzy diseases predictions in order to detect the causes of busi... more This paper extends the theory of fuzzy diseases predictions in order to detect the causes of business failure. This extension is justified through the advantages of the reference model and its originality. Moreover, the fuzzy model is completed by this proposal and some parts of it have been published in isolated articles. For this purpose, the fuzzy theory is combined with the OWA operators to identify the factors that generate problems in firms. Also, a goodness index to validate its functionality and prediction capacity is introduced. The model estimates a matrix of economic- financial knowledge based on matrices of causes and symptoms. Knowing the symptoms makes it possible to estimate the causes, and managing them properly, allows monitoring and improving the company’s financial situation and forecasting its future. Also with this extension, the model can be useful to develop suitable computer systems for monitoring companies’ problems, warning of failures and facilitating decision-making.
Finding Business Failure Reasons Through a Fuzzy Model of Diagnosis
Fuzzy economic review, 2014
The aim of this paper is to find the causes of the failure and diagnose a group of small and medi... more The aim of this paper is to find the causes of the failure and diagnose a group of small and medium-sized enterprises (SMEs) through a fuzzy logic model. The application to a specific sector involves the adaptation of the methodological hypothesis presented in the theoretical model and the definition of the variables that interact in the estimation (causes and symptoms). In this approach is proposed the simulation of the fuzzy model to forecast firms’ health and find out the reasons that generate diseases. This supposes the use of the aggregate economic financial matrix to simulate the diseases of the set of SMEs in the construction sector and the estimation the causes of the diseases. In the research are presented the most common reasons of failure detected for the sector, the diseases relevant for each firm and a classification of business according to the impact of the causes between healthy and unhealthy firms.
Applied Soft Computing, May 1, 2017
The paper aims to develop an adjustment index based on OWA operators to enrich the results of dia... more 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.
The aim of this paper is to improve one of the limitations of the fuzzy models of business failur... more The aim of this paper is to improve one of the limitations of the fuzzy models of business failure. In this sense an application to a group of small and medium –sized enterprises (SMEs) from the construction sector is introduced in a given time horizon to test the diagnosis model capacity to predict diseases. This simulation involves the adaptation of the methodological hypothesis, and the definition of the main variables that interact in the estimation. This research presents the estimation of the matrix of economic–financial knowledge and verifies its capacity of diagnosis. Also, a goodness measure, through approximate solutions, is introduced to test the model ́s functionality with companies outside initial sample to demonstrate its ability to predict. Therefore, through this simulation some of the fuzzy model ́s restrictions are overcome, the theoretical postulates are adapted; the difficulties associated with the estimation are solved and new criteria and guidelines that enrich...
Credit Crunch or Loan Demand Shortage: What Is the Problem with the SMEs’ Financing?
Czech Journal of Economics and Finance, 2020
Teoría del Diagnóstico Fuzzy y del Balanced Scorecard
Goodness of Aggregation Operators in a Diagnostic Fuzzy Model of Business Failure
Advances in Intelligent Systems and Computing, 2015
The aim of the following paper is proposed a mechanism of analysis useful to verify the capacity ... more The aim of the following paper is proposed a mechanism of analysis useful to verify the capacity of the Vigier and Terceno (2008) diagnostic fuzzy model to predict diseases. The model is enriched by the inclusion of aggregation operators because this allows reducing the detected map of causes or diseases in strategic areas of continuous monitoring. And at the same time this causes can be disaggregated once some alert indicator is identified. The capacity of explanation and prediction of estimated diseases are measured through this mechanism; and also are detected the monitoring key areas that warning insolvency situations. In this approach are introduced aggregation operators of causes of business failure, and a goodness measure using approximate solutions. This index of goodness allows testing the degree of fit of the predictions of the model. Also, as an example, the empirical estimation and the verification of the improvement proposal to a set of small and medium- sized enterprises (SMEs) of the construction sector are presented.
Abuse and health in individuals with spinal cord injury and dysfunction
Individuals with spinal cord injury and dysfunction (SCI/D) are at risk for abuse in multiple and... more Individuals with spinal cord injury and dysfunction (SCI/D) are at risk for abuse in multiple and complex ways. This population experiences abuse from many sources, including but not limited to, intimate partners, caregivers, and health care providers (Hassouneh-Phillips, 2003; Hassouneh-Phillips & McNeff; 2004). Abuse of individuals with SCI/D is defined as any intentional act that results in, or is likely to result in harm or suffering, including threats of such acts, coercion or arbitrary deprivations of liberty, whether occurring in public or private life (United Nations, 1993; World Health Organization, 2002). Based on our previous work and review of the literature we conceptualized five distinct domains of abuse including physical, psychological, sexual, financial, and disability-related abuse (Hassouneh-Phillips & McNeff; 2004; Hassouneh-Phillips, 2005; McFarlane, Hughes, Nosek, Groff, Swedlund, & Mullen, 2001; Nosek, Foley & Howland, 2001; Oktay & Thompkins, 2004; Powers, Curry, Oschwald, Saxton, & Eckels, 2002; Saxton, Curry, Powers, Maley, Eckels, & Gross, 2001; Saxton, McNeff, Powers, Lilnont, & Benson, 2006). Disability-related abuse is a form of abuse that individuals are vulnerable to by virtue of having a disability. Examples of disability-related abuse include refusal to provide essential personal care and blaming an individual for his or her disability. The prevalence of abuse of individuals with SCI/D is unknown. However, studies of women with physical disabilities generally using convenience samples have reported lifetime rates for any type of abuse ranging from 40-66% (Powers, Curry, Oschwald, Saxton, & Eckels, 2002; Riddington, 1989; Young, Nosek, Howland, Changpon, & Rintala, 1997). Aside from studies of intimate partner abuse in men with HIV which typically do not include disability as a variable, we are aware of only one study that has estimated rates of abuse in men with physical disabilities. Powers and colleagues conducted a study of caregiver abuse in a convenience sample of 342 men with physical and cognitive disabilities (Powers, Curry, McNeff, Saxton, & Orstrogorsky, 2008). The authors reported that 37% of men in the study had been physically abused and greater than 12% had been sexually abused while disabled. Also of note, the lifetime incidence of caregiver abuse or neglect reported by men was 50.6%. Although little is known about abuse of individuals with SCI/D specifically, an in-depth qualitative study of abuse of women with SCI (n=12 with a total of 24 interviews) indicated that abuse negatively affected participants' abilities to optimally manage their disabilities and severely compromised their health, including the onset of co-morbid mood disorders and declining physical health resulting in a loss of functional ability, employment, and the ability to live independently (Hassouneh-Phillips, 2003; Hassouneh-Phillips & McNeff, 2004). Given these qualitative findings, we sought to further explore abuse of individuals with SCI/D, quantitatively. Theoretical Framework The variables explored in this study were derived from the Abuse Pathways Model (Hassouneh-Phillips, 2005). This model describes the abuse trajectories of women with physical disabilities, vulnerability factors for abuse, and negative health outcomes related to abuse. Key vulnerability factors and health outcomes were selected from the model for use in this study based on previous qualitative findings. Vulnerability factors included adult and child abuse history, physical dependency, health behavior, sexual and body-esteem, and substance abuse. Health outcomes included symptoms of depression and post-traumatic stress disorder (PTSD). In two previous qualitative studies of abuse of women with physical disabilities including women with SCI/D, we found that women who had been previously abused either during childhood or as an adult were more likely to report repeated victimization (Hassouneh-Phillips, 2005; Hassouneh-Phillips & McNeff, 2004). …
Application of a Fuzzy Model of Economicfinancial Diagnosis to Smes
Methods for Decision Making in an Uncertain Environment, 2012
Axioms
The paper aims to identify which variables related to capital structure theory predict business f... more The paper aims to identify which variables related to capital structure theory predict business failure in the Spanish construction sector during the subprime crisis. An artificial neural network (ANN) approach based on Self-Organizing Maps (SOM) is proposed, which allows one to cluster between default and active firms’ groups. The similarities and differences between the main features in each group determine the variables that explain the capacities of failure of the analyzed firms. The network tests whether the factors that explain leverage, such as profitability, growth opportunities, size of the company, risk, asset structure, and age of the firm, can be suitable to predict business failure. The sample is formed by 152 construction firms (76 default and 76 active) in the Spanish market. The results show that the SOM correctly predicts 97.4% of firms in the construction sector and classifies the firms in five groups with clear similarities inside the clusters. The study proves th...
SMEs capital structure: trade-off or pecking order theory: a systematic review
Journal of Small Business and Enterprise Development
PurposeThe purpose of this paper is to organize and present the literature related to firm’s capi... more PurposeThe purpose of this paper is to organize and present the literature related to firm’s capital structure across the years and find the most relevant publications and authors in the research area. Moreover, the authors pretend to fill the gap in the literature by studying different works and their compatibility with the main theories.Design/methodology/approachThe systematic literature review is conducted by using the Scopus database. The methodology applied is through a concise searching considering keywords, the most cited papers, the latest publications and theories that explain small and medium enterprises (SMEs) capital structure.FindingsSome key aspects about the capital structure of firms and SMEs are identified, such as documents per year, type of publications, the most used languages, the top journals, the most cited papers, the most productive and influential authors and the latest published papers.Research limitations/implicationsThe information presented is only inf...
Prediction of Business Failure with Fuzzy Models
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
This paper extends the theory of fuzzy diseases predictions in order to detect the causes of busi... more This paper extends the theory of fuzzy diseases predictions in order to detect the causes of business failure. This extension is justified through the advantages of the reference model and its originality. Moreover, the fuzzy model is completed by this proposal and some parts of it have been published in isolated articles. For this purpose, the fuzzy theory is combined with the OWA operators to identify the factors that generate problems in firms. Also, a goodness index to validate its functionality and prediction capacity is introduced. The model estimates a matrix of economic- financial knowledge based on matrices of causes and symptoms. Knowing the symptoms makes it possible to estimate the causes, and managing them properly, allows monitoring and improving the company’s financial situation and forecasting its future. Also with this extension, the model can be useful to develop suitable computer systems for monitoring companies’ problems, warning of failures and facilitating deci...
Semestre Económico
Este artículo evalúa las técnicas utilizadas para la detección y predicción de las causas del fra... more Este artículo evalúa las técnicas utilizadas para la detección y predicción de las causas del fracaso empresarial. Se exponen las principales limitaciones de los modelos clásicos de predicción de insolvencia empresarial y se incorpora el análisis fuzzy como alternativa para identificar la relación entre las causas del fracaso y los síntomas visibles en las empresas. En forma complementaria se utiliza el Balanced Scorecard como herramienta de análisis global de la empresa y base para la detección de las causas del fracaso. La aplicación del Balanced Scorecard permite definir un listado de causas originarias de los problemas en las empresas. Estas son valoradas a través de etiquetas lingüísticas para detectar las enfermedades más frecuentes que pueden conducir al fracaso empresarial. Respecto a los modelos tradicionales, la metodología aplicada en este trabajo permite predecir el posible fracaso de una empresa e identificar las causas del mismo. PALABRAS CLAVE Fracaso empresarial, relaciones borrosas, tablero de comando, ratios económico financieros CLASIFICACIÓN JEL G33, L25, M21 CONTENIDO Introducción; 1. Principales aportes al análisis de causas; 2. El Balanced Scorecard como fuente de análisis de causas; 3. El modelo de diagnóstico fuzzy; 4. Identificación de causas; 5. Detección y valuación de causas; 6. Consideraciones finales; Bibliografía.
The OWA distance operator and its application in business failure
Kybernetes, 2017
Purpose The purpose of this paper is to develop a goodness index based on Hamming distance and or... more 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 ...
Applied Soft Computing, 2016
The paper aims to develop an adjustment index based on OWA operators to enrich the results of dia... more 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.
Diagnóstico económico financiero de empresas: un enfoque desde la teoría de diagnóstico fuzzy y del Balanced Scorecard
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Papers by Valeria Scherger