IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v68y2017i1d10.1057_s41274-016-0005-6.html
   My bibliography  Save this article

An approach to two-sided M&A fits based on a cross-efficiency evaluation with contrasting attitudes

Author

Listed:
  • Hai-Liu Shi

    (Fuzhou University
    Fujianjiangxia University)

  • Ying-Ming Wang

    (Fuzhou University)

  • Sheng-Qun Chen

    (Fuzhou University
    Fujianjiangxia University)

  • Yi-Xin Lan

    (Fuzhou University)

Abstract

Two-sided mergers and acquisitions (M&A) fits have been regarded as a critical step, which should always be taken by a bidder company when trying to identify suitable target companies prior to an M&A. This paper proposes an approach to two-sided M&A fits based on a cross-efficiency model with contrasting attitudes. In this approach, firstly, feasible M&A fits are screened using a preference function from an M&A fit matrix, according to the preferences of both the bidder companies and target companies in terms of efficiency and return to scale. Secondly, two-sided M&A fits are selected from a feasible M&A fit matrix, according to the value of cross-efficiency with contrasting attitudes. This allows for the existence of contrasting attitudes of peers toward an M&A fit, as opposed to the aggressive, benevolent or neutral cross-efficiency evaluation which consists of just one attitude (either aggressive, benevolent or indifferent). Finally, an illustrative example is given to explain the feasibility and validity of the two-sided M&A fit strategy.

Suggested Citation

  • Hai-Liu Shi & Ying-Ming Wang & Sheng-Qun Chen & Yi-Xin Lan, 2017. "An approach to two-sided M&A fits based on a cross-efficiency evaluation with contrasting attitudes," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(1), pages 41-52, January.
  • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:1:d:10.1057_s41274-016-0005-6
    DOI: 10.1057/s41274-016-0005-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41274-016-0005-6
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41274-016-0005-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Banker, Rajiv D. & Thrall, R. M., 1992. "Estimation of returns to scale using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 62(1), pages 74-84, October.
    2. Marina Martynova & Luc Renneboog, 2010. "Spillover of Corporate Governance Standards in Cross-Border Mergers and Acquisition," Chapters, in: Alessio M. Pacces (ed.), The Law and Economics of Corporate Governance, chapter 3, Edward Elgar Publishing.
    3. 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.
    4. Michael Lubatkin & Hugh O'Neill, 1988. "Merger Strategies, Economic Cycles, and Stockholder Value," Interfaces, INFORMS, vol. 18(6), pages 65-71, December.
    5. Ronan G. Powell, 2001. "Takeover Prediction and Portfolio Performance: A Note," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 28(7‐8), pages 993-1011, September.
    6. Dietrich, J. Kimball & Sorensen, Eric, 1984. "An application of logit analysis to prediction of merger targets," Journal of Business Research, Elsevier, vol. 12(3), pages 393-402, September.
    7. Lin Lin & Hsien-Chang Kuo & I-Liang Lin, 2008. "Merger and optimal number of firms: an integrated simulation approach," Applied Economics, Taylor & Francis Journals, vol. 40(18), pages 2413-2421.
    8. Bernad, Cristina & Fuentelsaz, Lucio & Gómez, Jaime, 2010. "The effect of mergers and acquisitions on productivity: An empirical application to Spanish banking," Omega, Elsevier, vol. 38(5), pages 283-293, October.
    9. Liang Liang & Jie Wu & Wade D. Cook & Joe Zhu, 2008. "The DEA Game Cross-Efficiency Model and Its Nash Equilibrium," Operations Research, INFORMS, vol. 56(5), pages 1278-1288, October.
    10. John G. Matsusaka, 1993. "Takeover Motives during the Conglomerate Merger Wave," RAND Journal of Economics, The RAND Corporation, vol. 24(3), pages 357-379, Autumn.
    11. Chung-Piaw Teo & Jay Sethuraman & Wee-Peng Tan, 2001. "Gale-Shapley Stable Marriage Problem Revisited: Strategic Issues and Applications," Management Science, INFORMS, vol. 47(9), pages 1252-1267, September.
    12. Behr, Andreas & Heid, Frank, 2011. "The success of bank mergers revisited. An assessment based on a matching strategy," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 117-135, January.
    13. Peyrache, Antonio, 2013. "Industry structural inefficiency and potential gains from mergers and break-ups: A comprehensive approach," European Journal of Operational Research, Elsevier, vol. 230(2), pages 422-430.
    14. S Lozano & G Villa, 2010. "DEA-based pre-merger planning tool," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(10), pages 1485-1497, October.
    15. Fotios Pasiouras & Chrysovalantis Gaganis, 2007. "Financial characteristics of banks involved in acquisitions: evidence from Asia," Applied Financial Economics, Taylor & Francis Journals, vol. 17(4), pages 329-341.
    16. Johnes, Jill & Yu, Li, 2008. "Measuring the research performance of Chinese higher education institutions using data envelopment analysis," China Economic Review, Elsevier, vol. 19(4), pages 679-696, December.
    17. Jie Wu & Qingxian An & Liang Liang, 2011. "Mergers and acquisitions based on DEA approach," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 3(3), pages 227-240.
    18. Halkos, George E. & Tzeremes, Nickolaos G., 2013. "Estimating the degree of operating efficiency gains from a potential bank merger and acquisition: A DEA bootstrapped approach," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1658-1668.
    19. Peter Bogetoft & Dexiang Wang, 2005. "Estimating the Potential Gains from Mergers," Journal of Productivity Analysis, Springer, vol. 23(2), pages 145-171, May.
    20. J Harris & H Ozgen & Y Ozcan, 2000. "Do mergers enhance the performance of hospital efficiency?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(7), pages 801-811, July.
    21. Ronan G. Powell, 2001. "Takeover Prediction and Portfolio Performance: A Note," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 28(7‐8), pages 993-1011, September.
    22. 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.
    23. Fried, Harold O. & Lovell, C. A. Knox & Yaisawarng, Suthathip, 1999. "The impact of mergers on credit union service provision," Journal of Banking & Finance, Elsevier, vol. 23(2-4), pages 367-386, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shiang-Tai Liu & Yueh-Chiang Lee, 2021. "Fuzzy measures for fuzzy cross efficiency in data envelopment analysis," Annals of Operations Research, Springer, vol. 300(2), pages 369-398, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. Goodness C. Aye & Giray Gozgor & Rangan Gupta, 2020. "Dynamic and Asymmetric Response of Inequality to Income Volatility: The Case of the United Kingdom," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(3), pages 747-762, February.
    4. Peter Wanke & Carlos P. Barros & Md. Abul Kalam Azad & Dercio Constantino, 2016. "The Development of the Mozambican Banking Sector and Strategic Fit of Mergers and Acquisitions: A Two†Stage DEA Approach," African Development Review, African Development Bank, vol. 28(4), pages 444-461, December.
    5. Gholam R. Amin & Ali Emrouznejad & Said Gattoufi, 2017. "Modelling generalized firms’ restructuring using inverse DEA," Journal of Productivity Analysis, Springer, vol. 48(1), pages 51-61, August.
    6. Yan He & Yung-ho Chiu & Bin Zhang, 2020. "Prevaluating Technical Efficiency Gains From Potential Mergers and Acquisitions in China’s Coal Industry," SAGE Open, , vol. 10(3), pages 21582440209, July.
    7. 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.
    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. 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.
    10. 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.
    11. Mattsson, Pontus & Tidanå, Claes, 2019. "Potential efficiency effects of merging the Swedish district courts," Socio-Economic Planning Sciences, Elsevier, vol. 67(C), pages 58-68.
    12. Valentin Zelenyuk, 2018. "Some Mathematical and Historical Clarifications on Aggregation in Efficiency and Productivity Analysis and Connection to Economic Theory," CEPA Working Papers Series WP032018, School of Economics, University of Queensland, Australia.
    13. Ying Li & Yung-Ho Chiu & Tai-Yu Lin & Tzu-Han Chang, 2020. "Pre-Evaluating the Technical Efficiency Gains from Potential Mergers and Acquisitions in the IC Design Industry," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 525-559, April.
    14. Lozano, S., 2013. "DEA production games," European Journal of Operational Research, Elsevier, vol. 231(2), pages 405-413.
    15. Stefan Seifert, 2016. "Semi-Parametric Measures of Scale Characteristics of German Natural Gas-Fired Electricity Generation," Discussion Papers of DIW Berlin 1571, DIW Berlin, German Institute for Economic Research.
    16. O'Neill, Liam & Rauner, Marion & Heidenberger, Kurt & Kraus, Markus, 2008. "A cross-national comparison and taxonomy of DEA-based hospital efficiency studies," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 158-189, September.
    17. 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.
    18. Toumi Hassen & Issaoui Fakhri & Ammouri Bilel & Touili Wassim & Hamdi Faouzi, 2018. "Dynamic Effects of Mergers and Acquisitions on the Performance of Commercial European Banks," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(3), pages 1032-1048, September.
    19. Ma-Lin Song & Ron Fisher & Jian-Lin Wang & Lian-Biao Cui, 2018. "Environmental performance evaluation with big data: theories and methods," Annals of Operations Research, Springer, vol. 270(1), pages 459-472, November.
    20. Walheer, Barnabé, 2018. "Scale efficiency for multi-output cost minimizing producers: The case of the US electricity plants," Energy Economics, Elsevier, vol. 70(C), pages 26-36.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jorsoc:v:68:y:2017:i:1:d:10.1057_s41274-016-0005-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.