Relaciones borrosas como herramienta de predicción de las causas del fracaso empresarial en el sector construcción
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Derechos de autor 2017 Semestre Económico Universidad de Medellín
Esta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial 4.0.
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Publicado: diciembre 30, 2016
Resumen
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.
Referencias
Altman, Edward (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. En: Journal of Finance, Vol. 23, No. 4, p. 589-609.
Argenti, John (1976). Corporate Collapse: The Causes and Symptoms, New York, John Wiley and Sons, 193p.
Argenti, John (1983). Prediction corporate failure. En: Accountants Digest, No. 138, p. 1-25.
Bahrammirzaee, Arash (2010). A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert systems and hybrid intelligent systems. En: Neural Computing and Applications, Vol. 19, No. 8, p. 1165-1195.
Balcaen, Sofie y Ooghe, Hubert (2006). 35 years of studies on business failure: An overview of the classic statistical methodologies and their related problems. En: British Accounting Review, Vol. 38, No. 1, p. 63-93.
Beaver, William (1966). Financial ratios as predictors of failure. En: Journal of Accounting Research, Vol. 4, Empirical Research in Accounting: Selected Studies, p. 71-111.
Becchetti, Leonardo y Sierra, Jaime (2003). Bankruptcy risk and productive efficiency in manufacturing firms. En: Journal of Banking and Finance, Vol. 27, No. 11, p. 2099-2120.
Behbood, Vahíd y Lu, Jie (2011). Intelligent financial warning model using fuzzy neural network and case-based reasoning. En: IEEE Symposium on CIFEr- Computational Intelligence for Financial Engineering and Economics, 6 p.
Campillo, José; Serer, Gregorio y Ferrer, Ernesto (2013). Validez de la información financiera en los procesos de insolvencia. Un estudio de la pequeña empresa española. En: Cuadernos de Economía y Dirección de la Empresa, Vol. 16, No. 1, enero-marzo, p. 29-40.
Delcea, Camelia y Dascalu, Maria (2009). Knowledge strategies tools for managing enterprise crisis. En: Actas del 4th International Conference on Knowledge Management: Projects, Systems and Technologies, Bucharest, Vol. 25, p. 1-25.
Delcea, Camelia y Scarlat, Emil (2010). Finding companies’ bankruptcy causes using a hybrid grey-fuzzy model. En: Economic Computation and Economic Cybernetics Studies and Research. Vol. 44, No. 2, p. 77-94.
Delcea, Camelia; Scarlat, Emil y Maracine, Virginia (2012). Grey relational analysis between firm’s current situation and its possible causes: A bankruptcy syndrome approach. En: Grey Systems: Theory and Application, Vol. 2, No. 2, p. 229-239.
Edmister, Robert (1972). An empirical test of financial ratio analysis for small business failure prediction. En: Journal of Financial and Quantitative Analysis, Vol. 7, No. 2, p. 1477-1493.
Elam, Rick (1975). The effect of lease data on the predictive ability of financial ratios. En: The Accounting Review, Vol. 50, No. 1, p. 25-43.
Fernández, María y Castaño, Francisco (2012). Variables y modelos para la identificación y predicción del fracaso empresarial: Revisión de la investigación empírica reciente. En: Revista de Contabilidad-Spanish Accounting Review, Vol. 15, No. 1, p. 7-58.
Ferrer, Ernesto; Serer, Gregorio y Campillo, José (2009). Hacia una ordenación de las pequeñas empresas atendiendo a su posible situación de fracaso. En: Estudios de Economía Aplicada, Vol. 27, No. 3, p. 1-18.
Flagg, James; Giroux, Gary y Wiggins, Casper (1991). Predicting corporate bankruptcy using failing firms. En: Review of Financial Economics, Vol. 1, No 1, p. 67-78.
Gabás, Francisco (1997). Predicción de la insolvencia empresarial. En: Predicción de la Insolvencia Empresarial, Madrid, AECA- Asociación Española de Contabilidad y Administración de Empresas, p. 11-32.
Gil Aluja, Jaume (1990). Ensayo sobre un modelo de diagnóstico económico-financiero. En: Actas de las V Jornadas Hispano- Lusas de Gestión Científica, Vigo, España, p. 26-29.
Gil Lafuente, Jaume (1996). El control de las actividades de marketing. En: Actas del III SIGEF Congress, Buenos Aires, Argentina, Vol. 244, p. 1-21.
Grunert, Jens; Norden, Lars y Weber, Martin (2005). The role of non-financial factors in internal credit ratings. En: Journal of Banking and Finance, Vol. 29, No. 2, p. 509-531.
Hillegeist, Stephen; Keating, Elizabeth; Cram, D. y Lundstedt, K. (2004). Assessing the probability of bankruptcy. En: Review of Accounting Studies, Vol. 9, No. 1, p. 5-34.
Kaplan, Robert y Norton, David (1992). The Balanced Scorecard: measures that drivers performance. En: Harvard Business Review, Vol. 70, No. 1, p. 71-79.
Kaplan, Robert y Norton, David (1996a). Using the Balanced Scorecard as a strategic management system. En: Harvard Business Review, Vol. 74, No. 1, p. 75-85.
Kaplan, Robert y Norton, David (1996b). Linking the Balanced Scorecard to strategy. En: California Management, Vol. 39, No. 1, p. 53-79.
Keasey, Kevin y Watson, Robert (1987). Non-financial symptoms and the prediction of small company failure: a test of Argenti’s hypothesis. En: Journal of Business, Finance and Accounting, Vol. 14, No. 3, p. 335-354.
Korol, Tomasz y Korodi, Adrian (2011). An evaluation of effectiveness of fuzzy logic model in predicting the business bankruptcy. En: Romanian Journal of Economic Forecasting, Vol. 3, No. 1, p. 92-107.
Kumar, P. Ravi y Ravi, Vadlamani (2007), Bankruptcy prediction in banks and firms via statistical and intelligent techniques: A review. En: European Journal of Operational Research, Vol. 180, No. 1, p. 1-28.
López, José; Gandía, Juan y Molina, Rafael (1998). La suspensión de pagos en las PyMEs: una aproximación empírica. En: Revista Española de Financiación y Contabilidad, Vol. 27, No. 94, p. 71-97.
Madrid, Antonia y García, Domingo Perez de Lema (2006). Factores que explican el fracaso empresarial en la PyME. En: Gestión: Revista de Economía, No. 36, p. 5-9.
Maracine, Virginia y Delcea, Camelia (2009). How we can diagnose the firm’s diseases using grey systems theory. En: Economic Computation and Economic Cybernetics Studies and Research, Vol. 3, p. 39-55.
McGahan, Anita y Porter, Michael (1997). How much does industry matter really? En: Strategic Management Journal, Vol. 18 (Summer Special Issue), p. 15-30.
Mensah, Yaw (1984). An examination of the stationary of multivariate bankruptcy prediction models: A methodological study. En: Journal of Accounting Research, Vol. 22, No. 1, p. 380-395.
Mora Enguídanos, Araceli (1994). Limitaciones metodológicas de los trabajos empíricos sobre la predicción del fracaso empresarial. En: Revista Española de Financiación y Contabilidad, Vol. 24, No. 80, p. 709-732.
Ng, Geok; Quek, Chai y Jiang, H. (2008). FCMAC-EWS: A bank failure early warning system based on a novel localized pattern learning and semantically associative fuzzy neural network. En: Expert Systems with Applications, Vol. 34, No. 2, p. 989-1003.
Ohlson, James (1980). Financial ratios and the probabilistic prediction of bankruptcy. En: Journal of Accounting Research, Vol. 18, No. 1, p. 109-131.
Ooghe, Hubert y De Prijcker, Sofie (2008), Failure processes and causes of company bankruptcy: A typology. En: Management Decision, Vol. 46, No. 2, p. 223-242.
Peel, Michael; Peel, David y Pope, Peter (1986), Predicting corporate failure. Some results for the UK corporate sector. En: Omega, Vol. 14, No. 1, p. 5-12.
Pérez, Ana; Rodríguez, Alicia y Acosta Molina, Miguel. (2002). Factores determinantes de la rentabilidad financiera de las PyMEs. En: Journal of Finance and Accounting/ Revista Española de Financiación y Contabilidad, Vol. 31, No. 112, p. 395-429.
Platt, Harlan; Platt, Majorie y Pedersen, Jon (1994). Bankruptcy discrimination with real variables. En: Journal of Business Finance and Accounting, Vol. 21, No. 4, p. 491-510.
Porter, Michael (1991). La Ventaja Competitiva de las Naciones, Buenos Aires, Ed. Vergara, 1025 p.
Quek, Chai; Zhou, R. y Lee, C. (2009). A novel fuzzy neural approach to data reconstruction and failure prediction. En: Intelligent in Accounting, Finance and Management, Vol. 16, No. 1-2, p. 165-187.
Quintana, María y García Gallego, Ana (2004). Factores determinantes del fracaso empresarial en Castilla y León. En: Revista de Economía y Empresa, Vol. 51, No. 21, p. 95-116.
Rose, Peter; Andrews, Wesley y Girox, Gary (1982). Predicting business failure: A macroeconomics perspective. En: Journal of Accounting Auditing and Finance, Vol. 6, No. 1, p. 20-31.
Rumelt, Richard (1997). Towards a strategic theory of the firm, p. 131-145. En: Nicolai J. Foss (Edit.) Resources, firms, and strategies: A reader in the resource-based perspective. Oxford University Press, 1 edition Oxford, Serie: Management Readers, 400p.
Scarlat, Emil; Delcea, Camelia y Maracine, Virginia (2010). Genetic Fuzzy Grey Algorithms: A Hybrid Model for Establishing Companies Failure Reasons. En: Actas de International Conference on SMC- Systems Man and Cybernetics, IEEE, p. 955- 962.
Scherger, Valeria; Vigier, Hernán y Barberá-Mariné, Gloria (2014). Finding business failure reasons through a fuzzy model of diagnosis. En: Fuzzy Economic Review, Vol. 19, No. 1, p. 45-62.
Scherger, Valeria; Terceño, Antonio; Vigier, Hernán y Barberá-Mariné, Gloria (2015). Detection and assessment of causes in business diagnosis. En: Economic Computation and Economic Cybernetics Studies and Research, Vol. 49, No. 4, p. 211-229.
Somoza López, Antonio (2001). La consideración de factores cualitativos, macroeconómicos y sectoriales en los modelos de predicción de la solvencia empresarial. En: Papeles de Economía Española, No. 89-90, p. 402-426.
Sun, Jie; Li, H.; Huang, Q. H. y He, K. Y. (2014). Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches. En: Knowledge-Based Systems, Vol. 57, p. 41-56.
Thapar, Antika; Pandey, Dhaneshwar y Gaur, S. (2009). Optimization of linear objective function with max-t fuzzy relation equations. En: Applied Soft Computing, Vol. 9, No. 3, p. 1097-1101.
Terceño, Antonio; Vigier, Hernán; Barberá- Marinè, Gloria y Scherger, Valeria (2009). Hacia una integración de la teoría del diagnóstico fuzzy y del Balanced Scorecard. En: Actas XV SIGEF Conference, Lugo, España, p. 364-379.
Terceño, Antonio; Vigier, Hernán y Scherger, Valeria (2014). Identificación de las causas en el diagnóstico empresarial mediante relaciones fuzzy y el BSC. En: Actualidad Contable Fases, Vol. 17, No. 28, p. 101-118.
Vigier, Hernán y Terceño, Antonio (2008). A model for the prediction of diseases of firms by means of fuzzy relations. En: Fuzzy Sets and System, Vol. 159, No. 1, p. 2299-2316.
Vigier, Hernán; Scherger, Valeria y Terceño, Antonio (2016). An application of OWA operators in fuzzy business diagnosis. En: Applied Soft Computing, http://dx.doi.org/10.1016/j.asoc.2016.06.026.
Xiu-ying, Liu y Zhong-chun, Mi (2009). The Application of grey relational analysis in credit evaluation of group enterprises. En: Actas de International Conference IEEE GSIS, Nanjing, China, p. 236-241.
Zavgren, Christine (1983). The prediction of Corporate Failure: The state of art. En: Journal of Accounting Literature, Vol. 2, p. 1-37.
Zimmermann, Hans (1987). Fuzzy Set Decision Making and Expert Systems. Volumen 10 de International Series in Management Science Operations Research, Kluwer Academic Publishers, Massachusetts, Norwell, 336p.
Zmijewski, Mark (1984). Methodological Issues Related to the Estimation of Financial Distress Prediction Models. En: Journal of Accounting Research, Vol. 22, p. 59-86.
Argenti, John (1976). Corporate Collapse: The Causes and Symptoms, New York, John Wiley and Sons, 193p.
Argenti, John (1983). Prediction corporate failure. En: Accountants Digest, No. 138, p. 1-25.
Bahrammirzaee, Arash (2010). A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert systems and hybrid intelligent systems. En: Neural Computing and Applications, Vol. 19, No. 8, p. 1165-1195.
Balcaen, Sofie y Ooghe, Hubert (2006). 35 years of studies on business failure: An overview of the classic statistical methodologies and their related problems. En: British Accounting Review, Vol. 38, No. 1, p. 63-93.
Beaver, William (1966). Financial ratios as predictors of failure. En: Journal of Accounting Research, Vol. 4, Empirical Research in Accounting: Selected Studies, p. 71-111.
Becchetti, Leonardo y Sierra, Jaime (2003). Bankruptcy risk and productive efficiency in manufacturing firms. En: Journal of Banking and Finance, Vol. 27, No. 11, p. 2099-2120.
Behbood, Vahíd y Lu, Jie (2011). Intelligent financial warning model using fuzzy neural network and case-based reasoning. En: IEEE Symposium on CIFEr- Computational Intelligence for Financial Engineering and Economics, 6 p.
Campillo, José; Serer, Gregorio y Ferrer, Ernesto (2013). Validez de la información financiera en los procesos de insolvencia. Un estudio de la pequeña empresa española. En: Cuadernos de Economía y Dirección de la Empresa, Vol. 16, No. 1, enero-marzo, p. 29-40.
Delcea, Camelia y Dascalu, Maria (2009). Knowledge strategies tools for managing enterprise crisis. En: Actas del 4th International Conference on Knowledge Management: Projects, Systems and Technologies, Bucharest, Vol. 25, p. 1-25.
Delcea, Camelia y Scarlat, Emil (2010). Finding companies’ bankruptcy causes using a hybrid grey-fuzzy model. En: Economic Computation and Economic Cybernetics Studies and Research. Vol. 44, No. 2, p. 77-94.
Delcea, Camelia; Scarlat, Emil y Maracine, Virginia (2012). Grey relational analysis between firm’s current situation and its possible causes: A bankruptcy syndrome approach. En: Grey Systems: Theory and Application, Vol. 2, No. 2, p. 229-239.
Edmister, Robert (1972). An empirical test of financial ratio analysis for small business failure prediction. En: Journal of Financial and Quantitative Analysis, Vol. 7, No. 2, p. 1477-1493.
Elam, Rick (1975). The effect of lease data on the predictive ability of financial ratios. En: The Accounting Review, Vol. 50, No. 1, p. 25-43.
Fernández, María y Castaño, Francisco (2012). Variables y modelos para la identificación y predicción del fracaso empresarial: Revisión de la investigación empírica reciente. En: Revista de Contabilidad-Spanish Accounting Review, Vol. 15, No. 1, p. 7-58.
Ferrer, Ernesto; Serer, Gregorio y Campillo, José (2009). Hacia una ordenación de las pequeñas empresas atendiendo a su posible situación de fracaso. En: Estudios de Economía Aplicada, Vol. 27, No. 3, p. 1-18.
Flagg, James; Giroux, Gary y Wiggins, Casper (1991). Predicting corporate bankruptcy using failing firms. En: Review of Financial Economics, Vol. 1, No 1, p. 67-78.
Gabás, Francisco (1997). Predicción de la insolvencia empresarial. En: Predicción de la Insolvencia Empresarial, Madrid, AECA- Asociación Española de Contabilidad y Administración de Empresas, p. 11-32.
Gil Aluja, Jaume (1990). Ensayo sobre un modelo de diagnóstico económico-financiero. En: Actas de las V Jornadas Hispano- Lusas de Gestión Científica, Vigo, España, p. 26-29.
Gil Lafuente, Jaume (1996). El control de las actividades de marketing. En: Actas del III SIGEF Congress, Buenos Aires, Argentina, Vol. 244, p. 1-21.
Grunert, Jens; Norden, Lars y Weber, Martin (2005). The role of non-financial factors in internal credit ratings. En: Journal of Banking and Finance, Vol. 29, No. 2, p. 509-531.
Hillegeist, Stephen; Keating, Elizabeth; Cram, D. y Lundstedt, K. (2004). Assessing the probability of bankruptcy. En: Review of Accounting Studies, Vol. 9, No. 1, p. 5-34.
Kaplan, Robert y Norton, David (1992). The Balanced Scorecard: measures that drivers performance. En: Harvard Business Review, Vol. 70, No. 1, p. 71-79.
Kaplan, Robert y Norton, David (1996a). Using the Balanced Scorecard as a strategic management system. En: Harvard Business Review, Vol. 74, No. 1, p. 75-85.
Kaplan, Robert y Norton, David (1996b). Linking the Balanced Scorecard to strategy. En: California Management, Vol. 39, No. 1, p. 53-79.
Keasey, Kevin y Watson, Robert (1987). Non-financial symptoms and the prediction of small company failure: a test of Argenti’s hypothesis. En: Journal of Business, Finance and Accounting, Vol. 14, No. 3, p. 335-354.
Korol, Tomasz y Korodi, Adrian (2011). An evaluation of effectiveness of fuzzy logic model in predicting the business bankruptcy. En: Romanian Journal of Economic Forecasting, Vol. 3, No. 1, p. 92-107.
Kumar, P. Ravi y Ravi, Vadlamani (2007), Bankruptcy prediction in banks and firms via statistical and intelligent techniques: A review. En: European Journal of Operational Research, Vol. 180, No. 1, p. 1-28.
López, José; Gandía, Juan y Molina, Rafael (1998). La suspensión de pagos en las PyMEs: una aproximación empírica. En: Revista Española de Financiación y Contabilidad, Vol. 27, No. 94, p. 71-97.
Madrid, Antonia y García, Domingo Perez de Lema (2006). Factores que explican el fracaso empresarial en la PyME. En: Gestión: Revista de Economía, No. 36, p. 5-9.
Maracine, Virginia y Delcea, Camelia (2009). How we can diagnose the firm’s diseases using grey systems theory. En: Economic Computation and Economic Cybernetics Studies and Research, Vol. 3, p. 39-55.
McGahan, Anita y Porter, Michael (1997). How much does industry matter really? En: Strategic Management Journal, Vol. 18 (Summer Special Issue), p. 15-30.
Mensah, Yaw (1984). An examination of the stationary of multivariate bankruptcy prediction models: A methodological study. En: Journal of Accounting Research, Vol. 22, No. 1, p. 380-395.
Mora Enguídanos, Araceli (1994). Limitaciones metodológicas de los trabajos empíricos sobre la predicción del fracaso empresarial. En: Revista Española de Financiación y Contabilidad, Vol. 24, No. 80, p. 709-732.
Ng, Geok; Quek, Chai y Jiang, H. (2008). FCMAC-EWS: A bank failure early warning system based on a novel localized pattern learning and semantically associative fuzzy neural network. En: Expert Systems with Applications, Vol. 34, No. 2, p. 989-1003.
Ohlson, James (1980). Financial ratios and the probabilistic prediction of bankruptcy. En: Journal of Accounting Research, Vol. 18, No. 1, p. 109-131.
Ooghe, Hubert y De Prijcker, Sofie (2008), Failure processes and causes of company bankruptcy: A typology. En: Management Decision, Vol. 46, No. 2, p. 223-242.
Peel, Michael; Peel, David y Pope, Peter (1986), Predicting corporate failure. Some results for the UK corporate sector. En: Omega, Vol. 14, No. 1, p. 5-12.
Pérez, Ana; Rodríguez, Alicia y Acosta Molina, Miguel. (2002). Factores determinantes de la rentabilidad financiera de las PyMEs. En: Journal of Finance and Accounting/ Revista Española de Financiación y Contabilidad, Vol. 31, No. 112, p. 395-429.
Platt, Harlan; Platt, Majorie y Pedersen, Jon (1994). Bankruptcy discrimination with real variables. En: Journal of Business Finance and Accounting, Vol. 21, No. 4, p. 491-510.
Porter, Michael (1991). La Ventaja Competitiva de las Naciones, Buenos Aires, Ed. Vergara, 1025 p.
Quek, Chai; Zhou, R. y Lee, C. (2009). A novel fuzzy neural approach to data reconstruction and failure prediction. En: Intelligent in Accounting, Finance and Management, Vol. 16, No. 1-2, p. 165-187.
Quintana, María y García Gallego, Ana (2004). Factores determinantes del fracaso empresarial en Castilla y León. En: Revista de Economía y Empresa, Vol. 51, No. 21, p. 95-116.
Rose, Peter; Andrews, Wesley y Girox, Gary (1982). Predicting business failure: A macroeconomics perspective. En: Journal of Accounting Auditing and Finance, Vol. 6, No. 1, p. 20-31.
Rumelt, Richard (1997). Towards a strategic theory of the firm, p. 131-145. En: Nicolai J. Foss (Edit.) Resources, firms, and strategies: A reader in the resource-based perspective. Oxford University Press, 1 edition Oxford, Serie: Management Readers, 400p.
Scarlat, Emil; Delcea, Camelia y Maracine, Virginia (2010). Genetic Fuzzy Grey Algorithms: A Hybrid Model for Establishing Companies Failure Reasons. En: Actas de International Conference on SMC- Systems Man and Cybernetics, IEEE, p. 955- 962.
Scherger, Valeria; Vigier, Hernán y Barberá-Mariné, Gloria (2014). Finding business failure reasons through a fuzzy model of diagnosis. En: Fuzzy Economic Review, Vol. 19, No. 1, p. 45-62.
Scherger, Valeria; Terceño, Antonio; Vigier, Hernán y Barberá-Mariné, Gloria (2015). Detection and assessment of causes in business diagnosis. En: Economic Computation and Economic Cybernetics Studies and Research, Vol. 49, No. 4, p. 211-229.
Somoza López, Antonio (2001). La consideración de factores cualitativos, macroeconómicos y sectoriales en los modelos de predicción de la solvencia empresarial. En: Papeles de Economía Española, No. 89-90, p. 402-426.
Sun, Jie; Li, H.; Huang, Q. H. y He, K. Y. (2014). Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches. En: Knowledge-Based Systems, Vol. 57, p. 41-56.
Thapar, Antika; Pandey, Dhaneshwar y Gaur, S. (2009). Optimization of linear objective function with max-t fuzzy relation equations. En: Applied Soft Computing, Vol. 9, No. 3, p. 1097-1101.
Terceño, Antonio; Vigier, Hernán; Barberá- Marinè, Gloria y Scherger, Valeria (2009). Hacia una integración de la teoría del diagnóstico fuzzy y del Balanced Scorecard. En: Actas XV SIGEF Conference, Lugo, España, p. 364-379.
Terceño, Antonio; Vigier, Hernán y Scherger, Valeria (2014). Identificación de las causas en el diagnóstico empresarial mediante relaciones fuzzy y el BSC. En: Actualidad Contable Fases, Vol. 17, No. 28, p. 101-118.
Vigier, Hernán y Terceño, Antonio (2008). A model for the prediction of diseases of firms by means of fuzzy relations. En: Fuzzy Sets and System, Vol. 159, No. 1, p. 2299-2316.
Vigier, Hernán; Scherger, Valeria y Terceño, Antonio (2016). An application of OWA operators in fuzzy business diagnosis. En: Applied Soft Computing, http://dx.doi.org/10.1016/j.asoc.2016.06.026.
Xiu-ying, Liu y Zhong-chun, Mi (2009). The Application of grey relational analysis in credit evaluation of group enterprises. En: Actas de International Conference IEEE GSIS, Nanjing, China, p. 236-241.
Zavgren, Christine (1983). The prediction of Corporate Failure: The state of art. En: Journal of Accounting Literature, Vol. 2, p. 1-37.
Zimmermann, Hans (1987). Fuzzy Set Decision Making and Expert Systems. Volumen 10 de International Series in Management Science Operations Research, Kluwer Academic Publishers, Massachusetts, Norwell, 336p.
Zmijewski, Mark (1984). Methodological Issues Related to the Estimation of Financial Distress Prediction Models. En: Journal of Accounting Research, Vol. 22, p. 59-86.
Cómo citar
Scherger, V., Terceño, A., & Vigier, H. (2016). Relaciones borrosas como herramienta de predicción de las causas del fracaso empresarial en el sector construcción. Semestre Económico, 19(41), 191-228. https://doi.org/10.22395/seec.v19n41a8
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