Geodesic
Dea-based models for best partner selection for merger
Zhu, Qingyuan1 ; Wu, Jie1  ; Chu, Junfei1  ; Amirteimoori, Alireza2 ; Sun, Jiasen3
1 School of Management, University of Science and Technology of China, Hefei, Anhui Province 230026, P.R. China.
2 Department of Applied Mathematics, Islamic Azad University, Rasht branch, Rasht, Iran.
3 DongWu Business School (Finance and Economics School), Soochow University, Jiang Su Province 215000, P.R. China.
RAIRO - Operations Research - Recherche Opérationnelle, Tome 51 (2017) no. 4, pp. 1345-1357

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Mergers and Acquisitions (M&A) is a process whereby two or more companies merge into one company to improve their efficiency and strengthen their market positions. Previous studies about best partner selection for M&A simply consider one factor independently among several relevant factors. In this paper, DEA is applied to support decision making for best partner selection in M&A for decision making units (DMUs), i.e., the companies. According to the different perspectives of efficiency, revenue, and cost, three models based on DEA approach are firstly introduced to select the best partner for M&A. By compositing these different perspectives, we further propose a new DEA model, which has comprehensively considered input cost, output revenue and efficiency to select the best partner among many candidates. 0–1 integer linear programming models are built to implement the process. Finally, an example is given to verify the applicability to this model.

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Accepté le :
DOI : 10.1051/ro/2017031
Classification : 90B50
Keywords: Merger and acquisitions, data envelopment analysis, efficiency, decision making units, 0-1integer linear programming

Zhu, Qingyuan 1 ; Wu, Jie 1 ; Chu, Junfei 1 ; Amirteimoori, Alireza 2 ; Sun, Jiasen 3

1 School of Management, University of Science and Technology of China, Hefei, Anhui Province 230026, P.R. China.
2 Department of Applied Mathematics, Islamic Azad University, Rasht branch, Rasht, Iran.
3 DongWu Business School (Finance and Economics School), Soochow University, Jiang Su Province 215000, P.R. China. 
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     author = {Zhu, Qingyuan and Wu, Jie and Chu, Junfei and Amirteimoori, Alireza and Sun, Jiasen},
     title = {Dea-based models for best partner selection for merger},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {1345--1357},
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Zhu, Qingyuan; Wu, Jie; Chu, Junfei; Amirteimoori, Alireza; Sun, Jiasen. Dea-based models for best partner selection for merger. RAIRO - Operations Research - Recherche Opérationnelle, Tome 51 (2017) no. 4, pp. 1345-1357. doi: 10.1051/ro/2017031

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