A semantic fuzzy expert system for a fuzzy balanced scorecard

  • Authors:

  • Fernando Bobillo;Miguel Delgado;Juan Gómez-Romero;Enrique López

  • Affiliations:

  • Department of Computer Science and Artificial Intelligence, E.T.S.I. Informática, University of Granada, C. Periodista Daniel Saucedo Aranda, 18071 Granada, Spain;Department of Computer Science and Artificial Intelligence, E.T.S.I. Informática, University of Granada, C. Periodista Daniel Saucedo Aranda, 18071 Granada, Spain;Department of Computer Science and Artificial Intelligence, E.T.S.I. Informática, University of Granada, C. Periodista Daniel Saucedo Aranda, 18071 Granada, Spain;Economy and Business Management Department, University of León, Campus de Vegazana s/n, 24071 León, Spain

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

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Abstract

Balanced scorecard is a widely recognized tool to support decision making in business management. Unfortunately, current balanced scorecard-based systems present two drawbacks: they do not allow to define explicitly the semantics of the underlying knowledge and they are not able to deal with imprecision and vagueness. To overcome these limitations, in this paper we propose a semantic fuzzy expert system which implements a generic framework for the balanced scorecard. In our approach, knowledge about balanced scorecard variables is represented using an OWL ontology, therefore allowing reuse and sharing of the model among different companies. The ontology acts as the basis for the fuzzy expert system, which uses highly interpretable fuzzy IF-THEN rules to infer new knowledge. Results are valuable pieces of information to help managers to improve the achievement of the strategic objectives of the company. A main contribution of this work it that the system is general and can be customized to adapt to different scenarios.