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Measuring firm performance with DEA and prior information in Taiwan's banks

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  • Tser-Yieth Chen
Abstract
This paper combines data envelopment analysis (DEA) measurements and manager prior opinion measurements to generate a posterior measurement for an overall measurement of the technical efficiency of banks in Taiwan. The involvement of mutual participation of bank managers in the evaluation process provides refined evaluation results and explicit corporation atmosphere among bank's evaluation operations. The empirical results indicate that the posterior measurement differs from the original DEA efficiency scores and/or financial ratios, which in turn indicates that bank efficiency can be measured by applying the methodology of Bayesian concept.

Suggested Citation

  • Tser-Yieth Chen, 2002. "Measuring firm performance with DEA and prior information in Taiwan's banks," Applied Economics Letters, Taylor & Francis Journals, vol. 9(3), pages 201-204.
    • Handle: RePEc:taf:apeclt:v:9:y:2002:i:3:p:201-204
    DOI: 10.1080/13504850110057947
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    References listed on IDEAS

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    1. Boussofiane, A. & Dyson, R. G. & Thanassoulis, E., 1991. "Applied data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 52(1), pages 1-15, May.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
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    Cited by:

    1. Bai, Xue-jie & Zeng, Jin & Chiu, Yung-Ho, 2019. "Pre-evaluating efficiency gains from potential mergers and acquisitions based on the resampling DEA approach: Evidence from China's railway sector," Transport Policy, Elsevier, vol. 76(C), pages 46-56.
    2. Kong, Wei-Hsin & Fu, Tsu-Tan, 2012. "Assessing the performance of business colleges in Taiwan using data envelopment analysis and student based value-added performance indicators," Omega, Elsevier, vol. 40(5), pages 541-549.
    3. Imad Bou-Hamad & Abdel Latef Anouze & Ibrahim H. Osman, 2022. "A cognitive analytics management framework to select input and output variables for data envelopment analysis modeling of performance efficiency of banks using random forest and entropy of information," Annals of Operations Research, Springer, vol. 308(1), pages 63-92, January.
    4. Mohammad Pakkar, 2015. "An integrated approach based on DEA and AHP," Computational Management Science, Springer, vol. 12(1), pages 153-169, January.
    5. Heti Suryani Fitri Sulaeman & Sri Mulyantini Moelyono & Jubaedah Nawir, 2019. "Determinants of Banking Efficiency for Commercial Banks in Indonesia," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 13(2), June.
    6. Hsiang-Hsi Liu & Tser-Yieth Chen & Lin-Yen Pai, 2007. "The Influence of Merger and Acquisition Activities on Corporate Performance in the Taiwanese Telecommunications Industry," The Service Industries Journal, Taylor & Francis Journals, vol. 27(8), pages 1041-1051, December.
    7. Ali Shaddady & Faisal Alnori, 2020. "Do Ownership Structure, Political Connections and Executive Compensation Have Multifaceted Effects on Firm Performance? An Alternative Approach," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 12(10), pages 1-22, October.
    8. Yao, Shujie & Han, Zhongwei & Feng, Genfu, 2007. "On technical efficiency of China's insurance industry after WTO accession," China Economic Review, Elsevier, vol. 18(1), pages 66-86.

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