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Modeling business partnerships: A data envelopment analysis approach

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  • Amin, Gholam R.
  • Ibn Boamah, Mustapha

Abstract

Strategic alliances and partnerships including mergers and acquisitions have been a growing trend in many industries in the past decades. There are many studies in the literature emphasizing the importance of business partnerships. However, literature on partnership optimization is quite limited. This paper defines various types of strategic alliance collaborations and partnerships between different decision making units (DMUs) and develops data envelopment analysis (DEA) models to guide partners on how redistributing their inputs and outputs could enhance their performance. The results of this study are useful for companies considering strategic alliances and partnerships to improve competitiveness. An application in banking is used to highlight the advantages of the proposed method in this paper.

Suggested Citation

  • Amin, Gholam R. & Ibn Boamah, Mustapha, 2023. "Modeling business partnerships: A data envelopment analysis approach," European Journal of Operational Research, Elsevier, vol. 305(1), pages 329-337.
    • Handle: RePEc:eee:ejores:v:305:y:2023:i:1:p:329-337
    DOI: 10.1016/j.ejor.2022.05.036
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    1. Arslan, Okan & Archetti, Claudia & Jabali, Ola & Laporte, Gilbert & Grazia Speranza, Maria, 2020. "Minimum cost network design in strategic alliances," Omega, Elsevier, vol. 96(C).
    2. Iacocca, Kathleen & Mahar, Stephen & Daniel Wright, P., 2022. "Strategic horizontal integration for drug cost reduction in the pharmaceutical supply chain," Omega, Elsevier, vol. 108(C).
    3. Zhang, Jingxiao & Jin, Weixing & Yang, Guo-liang & Li, Hui & Ke, Yongjian & Philbin, Simon Patrick, 2021. "Optimizing regional allocation of CO2 emissions considering output under overall efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    4. Jie Wu & Qingyuan Zhu & Wade D Cook & Joe Zhu, 2016. "Best cooperative partner selection and input resource reallocation using DEA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(9), pages 1221-1237, September.
    5. Yilmaz, Ozhan & Savasaneril, Secil, 2012. "Collaboration among small shippers in a transportation market," European Journal of Operational Research, Elsevier, vol. 218(2), pages 408-415.
    6. Zeng, Amy Z. & Xia, Yu, 2015. "Building a mutually beneficial partnership to ensure backup supply," Omega, Elsevier, vol. 52(C), pages 77-91.
    7. Korhonen, Pekka & Voutilainen, Raimo, 2006. "Finding the most preferred alliance structure between banks and insurance companies," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1285-1299, December.
    8. Manzini, Paola & Mariotti, Marco, 2005. "Alliances and negotiations," Journal of Economic Theory, Elsevier, vol. 121(1), pages 128-141, March.
    9. Ghadimi, Pezhman & Ghassemi Toosi, Farshad & Heavey, Cathal, 2018. "A multi-agent systems approach for sustainable supplier selection and order allocation in a partnership supply chain," European Journal of Operational Research, Elsevier, vol. 269(1), pages 286-301.
    10. Pun, Hubert & Ghamat, Salar, 2016. "The value of partnership under competition: When competitors may be R&D joint-venture and supply-chain partners for a critical component," International Journal of Production Economics, Elsevier, vol. 177(C), pages 1-11.
    11. Wang, Chia-Nan & Nguyen, Xuan-Tho & Le, Thi-Dao & Hsueh, Ming-Hsien, 2018. "A partner selection approach for strategic alliance in the global aerospace and defense industry," Journal of Air Transport Management, Elsevier, vol. 69(C), pages 190-204.
    12. Wei, Quanling & Zhang, Jianzhong & Zhang, Xiangsun, 2000. "An inverse DEA model for inputs/outputs estimate," European Journal of Operational Research, Elsevier, vol. 121(1), pages 151-163, February.
    13. Yan, Hong & Wei, Quanling & Hao, Gang, 2002. "DEA models for resource reallocation and production input/output estimation," European Journal of Operational Research, Elsevier, vol. 136(1), pages 19-31, January.
    14. Toumasatos, Evangelos & Sandal, Leif Kristoffer & Steinshamn, Stein Ivar, 2022. "Keep it in house or sell it abroad? A framework to evaluate fairness," European Journal of Operational Research, Elsevier, vol. 297(2), pages 709-728.
    15. Büyüközkan, Gülçin & Feyzioglu, Orhan & Nebol, Erdal, 2008. "Selection of the strategic alliance partner in logistics value chain," International Journal of Production Economics, Elsevier, vol. 113(1), pages 148-158, May.
    16. Marciukaityte, Dalia & Roskelley, Kenneth & Wang, Hua, 2009. "Strategic alliances by financial services firms," Journal of Business Research, Elsevier, vol. 62(11), pages 1193-1199, November.
    17. Chauhan, Satyaveer S. & Proth, Jean-Marie, 2005. "Analysis of a supply chain partnership with revenue sharing," International Journal of Production Economics, Elsevier, vol. 97(1), pages 44-51, July.
    18. 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.
    19. Dai, Qianzhi & Li, Yongjun & Lei, Xiyang & Wu, Dengsheng, 2021. "A DEA-based incentive approach for allocating common revenues or fixed costs," European Journal of Operational Research, Elsevier, vol. 292(2), pages 675-686.
    20. Eksoz, Can & Mansouri, S. Afshin & Bourlakis, Michael & Önkal, Dilek, 2019. "Judgmental adjustments through supply integration for strategic partnerships in food chains," Omega, Elsevier, vol. 87(C), pages 20-33.
    21. 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.
    22. Mojtaba Ghiyasi, 2018. "Efficiency improvement and resource estimation: a tradeoff analysis," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 25(2), pages 151-169.
    23. Su, Han Chan & Kensinger, John W. & Keown, Arthur J. & Martin, John D., 1997. "Do strategic alliances create value?," Journal of Financial Economics, Elsevier, vol. 46(2), pages 199-221, November.
    24. Dyckhoff, Harald & Souren, Rainer, 2022. "Integrating multiple criteria decision analysis and production theory for performance evaluation: Framework and review," European Journal of Operational Research, Elsevier, vol. 297(3), pages 795-816.
    25. Li, Yongjun & Xie, Jianhui & Wang, Meiqiang & Liang, Liang, 2016. "Super efficiency evaluation using a common platform on a cooperative game," European Journal of Operational Research, Elsevier, vol. 255(3), pages 884-892.
    26. Ali Emrouznejad & Guo-liang Yang & Gholam R. Amin, 2019. "A novel inverse DEA model with application to allocate the CO2 emissions quota to different regions in Chinese manufacturing industries," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(7), pages 1079-1090, July.
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