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Evolving Classifiers to Model the Relationship between Strategy and Corporate Performance Using Grammatical Evolution

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Book cover Genetic Programming (EuroGP 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2278))

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Abstract

This study examines the potential of grammatical evolution to construct a linear classifier to predict whether a firm’s corporate strategy will increase or decrease shareholder wealth. Shareholder wealth is measured using a relative fitness criterion, the change in a firm’s marketvalue- added ranking in the Stern-Stewart Performance 1000 list, over a four year period, 1992-1996. Model inputs and structure are selected by means of grammatical evolution. The best classifier correctly categorised the direction of performance ranking change in 66.38% of the firms in the training set and 65% in the out-of-sample validation set providing support for a hypothesis that changes in corporate strategy are linked to changes in corporate performance.

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Author information

Authors and Affiliations

  1. Dept. Of Accountancy, University College Dublin, Ireland

    Anthony Brabazon

  2. Dept. Of Computer Science And Information Systems, University of Limerick, Ireland

    Michael O’Neill & Conor Ryan

  3. Centre for International Business Policy, Kingston Business School, London

    Robin Matthews

Authors
  1. Anthony Brabazon
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  2. Michael O’Neill
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  3. Conor Ryan
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  4. Robin Matthews
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Idaho, 83844-1010, Moscow, ID, USA

    James A. Foster

  2. INRIA Rocquencourt, B.P. 105, 78153, Le Chesnay Cedex, France

    Evelyne Lutton

  3. School of Computer Science, University of Birmingham, B15 2TT, Birmingham, UK

    Julian Miller

  4. Department of Computer Science and Information Systems, University of Limerick, Schuman Building, Limerick, Ireland

    Conor Ryan

  5. Dip. Tecnologie dell’Informazione, Università degli Studi di Milano, Via Bramante 65, 26013, Crema, Italy

    Andrea Tettamanzi

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© 2002 Springer-Verlag Berlin Heidelberg

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Brabazon, A., O’Neill, M., Ryan, C., Matthews, R. (2002). Evolving Classifiers to Model the Relationship between Strategy and Corporate Performance Using Grammatical Evolution. In: Foster, J.A., Lutton, E., Miller, J., Ryan, C., Tettamanzi, A. (eds) Genetic Programming. EuroGP 2002. Lecture Notes in Computer Science, vol 2278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45984-7_10

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  • DOI: https://doi.org/10.1007/3-540-45984-7_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43378-1

  • Online ISBN: 978-3-540-45984-2

  • eBook Packages: Springer Book Archive

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