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A Two-Stage Dynamic Model for Evaluating the Performance of Private Banks: Using DEA Approach (in Persian)

Author

Listed:
  • Sadeghi, Seyed Rasoul

    (University of Qom)

  • Maleki, Mohammad Hasan

    (University of Qom)

  • Motaghi, Peyman

    (University of Qom)

Abstract

This study evaluates performance of private banks through the Data Envelopment Analysis (DEA) method. Providing services in banks and converting available resources into outputs is composed of various stages and internal processes, and the performance of each of the banks varies over time. Typical DEA models are not able to measure the performance of internal and sequential processes, as well as performance measurement over different time periods. Therefore, in the present study, using a dynamic DEA approach, a two-stage model is designed to measure the efficiency and effectiveness of each bank in different time periods. The proposed model, taking into account the main and successive processes of bankschr('39') income generation, is to measure efficiency, effectiveness and the performance of each of the banks at each time period, as well as determining the overall performance and ranking of banks.The results show that banks that are quite effective or fully efficient in a given time period are not necessarily the best banks in terms of performance in that period. Also, in terms of overall performance, only one bank was able to achieve a complete score, while other banks have also been successful in some of the time in terms of efficiency and effectiveness.

Suggested Citation

  • Sadeghi, Seyed Rasoul & Maleki, Mohammad Hasan & Motaghi, Peyman, 2018. "A Two-Stage Dynamic Model for Evaluating the Performance of Private Banks: Using DEA Approach (in Persian)," Journal of Monetary and Banking Research (فصلنامه پژوهش‌های پولی-بانکی), Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 11(35), pages 55-82, April.
  • Handle: RePEc:mbr:jmbres:v:11:y:2018:i:35:p:55-82
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    More about this item

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics

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