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The Use of Artificial Neural Networks for Quantifying the Relative Importance of the Firms' Performance Determinants

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Listed:
  • Gholamhossein Mahdavi

    (Shiraz University, Iran)

  • Mohammad Sadeghzadeh Maharluie

    (Shiraz University, Iran)

  • Ahmad Shokrolahi

    (Shiraz University, Iran)

Abstract

Performance is the outcome of all plans and decisions of a company. It shows the ways companies are governed. Consequently, determining the relative importance (RI) of factors influencing the performance is important. Therefore, in this study, seven independent variables were determined based on the literature. Then, the significant variables were chosen using the Pearson's correlation test. Finally, an artificial neural network was designed to investigate the RI of the determinants. In total, 1340 company-year data were collected from Tehran stock exchange from 2001 to 2010. The research results revealed that institutional ownership concentration is the most important factor which is followed by state ownership, and managerial stock ownership. Debt policy and firm size are ranked in lower position.

Suggested Citation

  • Gholamhossein Mahdavi & Mohammad Sadeghzadeh Maharluie & Ahmad Shokrolahi, 2017. "The Use of Artificial Neural Networks for Quantifying the Relative Importance of the Firms' Performance Determinants," International Journal of Economics and Financial Issues, Econjournals, vol. 7(3), pages 119-127.
    • Handle: RePEc:eco:journ1:2017-03-17
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    More about this item

    Keywords

    Performance; Artificial Neural Networks; Tehran Stock Exchange;
    All these keywords.

    JEL classification:

    • M49 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Other

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