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A Comparison of Ratios and Data Envelopment Analysis: Efficiency Assessment of Taiwan Public Listed Companies

Author

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  • Yaw-Shun Yu
  • Ambrosio Barros
  • Chih-Hung Tsai
  • Kuo-Hsiung Liao

Abstract

The need to assess business firm’s efficiency is important for all players involved in a business. Efficiency assessment has previously been conducted using financial ratio analysis. However, it failed when simultaneously considering multiple inputs and outputs. Because of this difficulty the data envelopment analysis (DEA) is proposed as an alternative approach for handling multiple inputs and outputs. This study introduces financial ratio analysis and the DEA model for assessing performance and uses panel data of 24 Taiwan public listed companies to demonstrate the merit of the model in assessing efficiency with quantitative guidance for policy formulation.

Suggested Citation

  • Yaw-Shun Yu & Ambrosio Barros & Chih-Hung Tsai & Kuo-Hsiung Liao, 2014. "A Comparison of Ratios and Data Envelopment Analysis: Efficiency Assessment of Taiwan Public Listed Companies," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 4(1), pages 212-219, January.
    • Handle: RePEc:hur:ijaraf:v:4:y:2014:i:1:p:212-219
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    Citations

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    Cited by:

    1. Margareta Gardijan & Zrinka Lukač, 2018. "Measuring the relative efficiency of the food and drink industry in the chosen EU countries using the data envelopment analysis with missing data," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 695-713, September.
    2. Philip Odewole Olawale, 2020. "Adequacy of DEA in Measuring the Efficiency of Public Sector Entities in Nigeria: A Comparative Analysis Approach," Journal of Economics and Behavioral Studies, AMH International, vol. 12(5), pages 13-22.
    3. Gehan A. Mousa & Elsayed A. H. Elamir & Khaled Hussainey, 2022. "Using machine learning methods to predict financial performance: Does disclosure tone matter?," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 19(1), pages 93-112, March.

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