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Corporate Performance Measurement Using an Integrated Approach - A Mongolian Case

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  • Batchimeg Bayaraa
  • Tibor Tarnoczi
  • Veronika Fenyves

Abstract

The main goal of the study is to calculate the relevant efficiency scores of companies listed on the Mongolian Stock Exchange based on their efficiency scores. We apply an integrated principal component analysis (PCA) and data envelopment analysis (DEA) model to estimate corporate efficiency. The objective of using this integrated method to reduce the dimensionality of the dataset analysed and to evaluate companies’ efficiencies reliably. The number of variables using in the DEA model affects the results directly because of the DEA method is sensitive to the number of input and output variables. The PCA method can reduce the number of variables so that the information loss would be the smallest. The research uses one hundred publicly-listed Mongolian companies’ financial statements of 2015. Initially, DEA is applied conventionally using seven input and four output variables. Then, PCA is applied with the same variables to determine Principal Component (PC) scores, which are used for DEA as variables to improve its discrimination power.

Suggested Citation

  • Batchimeg Bayaraa & Tibor Tarnoczi & Veronika Fenyves, 2020. "Corporate Performance Measurement Using an Integrated Approach - A Mongolian Case," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 16(4), pages 123-134.
    • Handle: RePEc:mje:mjejnl:v:16:y:2020:i:4:123-134
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    References listed on IDEAS

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    6. Andras Takacs, 2015. "The explanatory power of appraised brand values on stock prices in the financial services sector," International Journal of Business Excellence, Inderscience Enterprises Ltd, vol. 8(3), pages 298-311.
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    Cited by:

    1. Liu, Haiyue & Zhang, Ruchuan & Zhou, Li & Li, Aijun, 2023. "Evaluating the financial performance of companies from the perspective of fund procurement and application: New strategy cross efficiency network data envelopment analysis models," Energy, Elsevier, vol. 269(C).
    2. Bruno Ricca & Massimiliano Ferrara & Salvatore Loprevite, 2023. "Searching for an effective accounting-based score of firm performance: a comparative study between different synthesis techniques," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3575-3602, August.

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