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Estimation of potential gains from bank mergers: A novel two-stage cost efficiency DEA model

Author

Listed:
  • Xiao Shi

    (University of Science and Technology of China
    Shandong University of Finance and Economics)

  • Yongjun Li

    (University of Science and Technology of China)

  • Ali Emrouznejad

    (Aston University)

  • Jianhui Xie

    (University of Science and Technology of China
    Sun Yat-Sen University)

  • Liang Liang

    (University of Science and Technology of China)

Abstract

This paper develops a novel two-stage cost efficiency model to estimate and decompose the potential gains from Mergers and Acquisitions (M&As). In this model, a hypothetical DMU is defined as a combination of two or more candidate DMUs. The hypothetical DMU would surpass the traditional Production Possibility Set (PPS). In order to solve the problem, a Merger Production Possibility Set (PPSM) is constructed. The model minimizes the total cost of the hypothetical DMU while maintaining its outputs at the current level, and estimates the overall merger efficiency by comparing its minimal total cost with its actual cost. Moreover, the overall merger efficiency could be decomposed into technical efficiency, harmony efficiency, and scale efficiency. We show that the model can be extended to a two-stage structure and these efficiencies can be decomposed to both sub-systems. To show the usefulness of the proposed approach, we applied it to a real dataset of top 20 most competitive Chinese City Commercial Banks (CCBs). We concluded that (1) there exist considerably potential gains for the proposed merged banks. (2) It is also shown that the main impact on potential merger gains are from technical and harmony efficiency. (3) As an interesting result we found that the scale effect works against the merger, indicating that it is not favorable for a full-scale merger.

Suggested Citation

  • Xiao Shi & Yongjun Li & Ali Emrouznejad & Jianhui Xie & Liang Liang, 2017. "Estimation of potential gains from bank mergers: A novel two-stage cost efficiency DEA model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(9), pages 1045-1055, September.
    • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:9:d:10.1057_s41274-016-0106-2
    DOI: 10.1057/s41274-016-0106-2
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    Cited by:

    1. Ofori, Eric Makafui & Yeager, Elizabeth & Briggeman, Brian, "undated". "Agricultural Cooperative mergers and efficiency gains: An ex-ante analysis," 2020 Annual Meeting, February 1-4, 2020, Louisville, Kentucky 302323, Southern Agricultural Economics Association.
    2. Gholam R. Amin & Mustapha Ibn Boamah, 2021. "A two‐stage inverse data envelopment analysis approach for estimating potential merger gains in the US banking sector," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(6), pages 1454-1465, September.
    3. Fukuyama, Hirofumi & Tan, Yong, 2022. "Implementing strategic disposability for performance evaluation: Innovation, stability, profitability and corporate social responsibility in Chinese banking," European Journal of Operational Research, Elsevier, vol. 296(2), pages 652-668.
    4. Wanke, Peter & Maredza, Andrew & Gupta, Rangan, 2017. "Merger and acquisitions in South African banking: A network DEA model," Research in International Business and Finance, Elsevier, vol. 41(C), pages 362-376.
    5. Chen, Zhongfei & Wanke, Peter & Tsionas, Mike G., 2018. "Assessing the strategic fit of potential M&As in Chinese banking: A novel Bayesian stochastic frontier approach," Economic Modelling, Elsevier, vol. 73(C), pages 254-263.
    6. Svetlana V. Ratner & Artem M. Shaposhnikov & Andrey V. Lychev, 2023. "Network DEA and Its Applications (2017–2022): A Systematic Literature Review," Mathematics, MDPI, vol. 11(9), pages 1-24, May.
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    8. Jianhui Xie & Xiaoxuan Zhu & Liang Liang, 2020. "A multiplicative method for estimating the potential gains from two-stage production system mergers," Annals of Operations Research, Springer, vol. 288(1), pages 475-493, May.
    9. Huaqing Wu & Jingyu Yang & Wensheng Wu & Ya Chen, 2023. "Interest rate liberalization and bank efficiency: A DEA analysis of Chinese commercial banks," 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. 31(2), pages 467-498, June.
    10. Subhash C. Ray & Shilpa Sethia, 2022. "Nonparametric measurement of potential gains from mergers: an additive decomposition and application to Indian bank mergers," Journal of Productivity Analysis, Springer, vol. 57(2), pages 115-130, April.
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    12. Thierry Warin & Aleksandar Stojkov, 2021. "Banks’ Foreign Claims in the Aftermath of the 2008 Crisis: Institutional Response, Financial Efficiency, and Integration of Cross-Border Banking in the Euro Area," JRFM, MDPI, vol. 14(2), pages 1-17, February.
    13. Xiaohong Liu & Feng Yang & Jie Wu, 2020. "DEA considering technological heterogeneity and intermediate output target setting: the performance analysis of Chinese commercial banks," Annals of Operations Research, Springer, vol. 291(1), pages 605-626, August.
    14. Biresh K. Sahoo & Kaoru Tone, 2022. "Evaluating the potential efficiency gains from optimal industry configuration: A case of life insurance industry of India," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(8), pages 3996-4009, December.
    15. Yung‐ho Chiu & Tai‐Yu Lin & Tzu‐Han Chang & Yi‐Nuo Lin & Shih‐Yung Chiu, 2021. "Prevaluating efficiency gains from potential mergers and acquisitions in the financial industry with the Resample Past–Present–Future data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(2), pages 369-384, March.
    16. Yuan, Zhennan & Chen, Frank Y. & Yan, Xiaoming & Yu, Yugang, 2020. "Operational implications of yield uncertainty in mergers and acquisitions," International Journal of Production Economics, Elsevier, vol. 219(C), pages 248-258.
    17. Hirofumi Fukuyama & Yong Tan, 2021. "Corporate social behaviour: Is it good for efficiency in the Chinese banking industry?," Annals of Operations Research, Springer, vol. 306(1), pages 383-413, November.
    18. Gholam R. Amin & Mustapha Ibn Boamah, 2020. "A new inverse DEA cost efficiency model for estimating potential merger gains: a case of Canadian banks," Annals of Operations Research, Springer, vol. 295(1), pages 21-36, December.
    19. Chang, Tsung-Sheng & Lin, Ji-Gang & Ouenniche, Jamal, 2023. "DEA-based Nash bargaining approach to merger target selection," European Journal of Operational Research, Elsevier, vol. 305(2), pages 930-945.
    20. Li, Feng & Zhu, Qingyuan & Chen, Zhi, 2019. "Allocating a fixed cost across the decision making units with two-stage network structures," Omega, Elsevier, vol. 83(C), pages 139-154.
    21. Vitor Miguel Ribeiro & Lei Bao, 2021. "Impact of next‐generation access networks on the innovation efficiency of Portuguese municipalities: A spatial econometrics approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(5), pages 1615-1637, October.
    22. Mohammad Khoveyni & Robabeh Eslami, 2022. "Merging two-stage series network structures: A DEA-based approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 273-302, March.
    23. Li Jia & Wang Ping & Tao Xiangyang & Wen Yao, 2021. "Productivity Analysis for Banks’ Merger and Acquisition Using Two-Stage DEA: Evidence from China," Journal of Systems Science and Information, De Gruyter, vol. 9(6), pages 627-659, December.

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