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Minería de datos y lógica difusa.Una aplicación al estudio de la rentabilidad económica de las empresas agroalimentarias en Andalucía

Author

Listed:
  • Bárbara Díaz

    (Universidad de Málaga)

  • Antonio Morillas

    (Universidad de Málaga)

Abstract

En este trabajo se estudia la rentabilidad de la empresa agroalimentaria en Andalucía (España)mediante un conjunto de ratios, elaborados por el Instituto de Estadística de Andalucía a partir de la Central de Balances de Actividades Empresariales de Andalucía. El objeto es encontrar las características contables de las empresas más rentables. Los aspectos metodológicos que se contemplan en la aplicación comprenden algunas técnicas estadísticas avanzadas y nuevos métodos de extracción de conocimiento en grandes bases de datos (knowledge discovery y data mining). Las conclusiones a que se llega, expresadas en forma de reglas difusas obtenidas de la base de datos mediante la “teoría computacional de la percepción” (Zadeh, 2001; Last, Klein y Kandel, 2001), parecen plenamente congruentes con los postulados del análisis financiero.Si la rotación de activos es baja, no hay altas rentabilidades. Por el contrario, una importante rotación del activo, acompañada por una aceptable situación de liquidez, es lo que caracteriza a las empresas más rentables.

Suggested Citation

  • Bárbara Díaz & Antonio Morillas, 2005. "Minería de datos y lógica difusa.Una aplicación al estudio de la rentabilidad económica de las empresas agroalimentarias en Andalucía," GE, Growth, Math methods 0512003, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpge:0512003
    Note: Type of Document - pdf; pages: 22
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/ge/papers/0512/0512003.pdf
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    References listed on IDEAS

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    1. Berger, Allen N. & Humphrey, David B., 1991. "The dominance of inefficiencies over scale and product mix economies in banking," Journal of Monetary Economics, Elsevier, vol. 28(1), pages 117-148, August.
    2. Altman, Edward I. & Marco, Giancarlo & Varetto, Franco, 1994. "Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)," Journal of Banking & Finance, Elsevier, vol. 18(3), pages 505-529, May.
    3. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 1993. "The Measurement of Productive Efficiency: Techniques and Applications," OUP Catalogue, Oxford University Press, number 9780195072181.
    4. Allen N. Berger & David B. Humphrey, 1992. "Measurement and Efficiency Issues in Commercial Banking," NBER Chapters,in: Output Measurement in the Service Sectors, pages 245-300 National Bureau of Economic Research, Inc.
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    Cited by:

    1. Morillas, Antonio & Díaz, Bárbara, 2007. "Qualitative Answering Surveys And Soft Computing," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 0(1), pages 3-19, May.

    More about this item

    Keywords

    Data mining; knowledge discovery; exploratory data analysis; neural networks; decision trees; accounting ratios; return of assets.;

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D5 - Microeconomics - - General Equilibrium and Disequilibrium
    • D9 - Microeconomics - - Micro-Based Behavioral Economics

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