非合作博弈两阶段生产系统DEA并购效率评价

doi:10.16381/j.cnki.issn1003-207x.2015.07.008

中国管理科学 ›› 2015, Vol. 23 ›› Issue (7): 60-67.doi: 10.16381/j.cnki.issn1003-207x.2015.07.008

非合作博弈两阶段生产系统DEA并购效率评价

石晓¹, 谢建辉¹, 李勇军¹, 梁樑¹, 谢启伟²

1. 中国科学技术大学管理学院, 合肥 230026;
2. 中国科学院科技政策与管理科学研究所, 北京 100190

收稿日期:2013-11-30 修回日期:2014-07-30 出版日期:2015-07-20 发布日期:2015-07-22
作者简介:石晓(1988-),女(汉族),山东荷泽人,中国科学技术大学管理学院博士研究生,研究方向:数据包络分析.
基金资助:
国家自然科学基金资助项目(61101219, 71271196);国家创新研究群体科学基金资助项目(71121061);国际合作与交流资助项目(71110107024);中国科学技术大学创新研究群体科学基金资助(WK2040160008);国家杰出青年科学基金资助项目(71225002)

Merger Efficiency Evaluation of Two-Stage Production System Based on Non-Cooperative Game Theory

SHI Xiao¹, XIE Jian-hui¹, LI Yong-jun¹, LIANG Liang¹, XIE Qi-wei²

1. School of Business, University of Science and Technology of China, He Fei 230026, China;
2. Institute of Policy and Management, Chinese Academy of Sciences, Bejing 100190, China

Received:2013-11-30 Revised:2014-07-30 Online:2015-07-20 Published:2015-07-22

摘要/Abstract

摘要： 如何选择并购对象及预测并购可行性是企业管理者在并购决策过程中常面临的问题。针对企业并购预测问题,本文以两阶段生产系统的决策单元为研究对象,研究数据包络分析方法在预测并购可行性方面的应用。该生产系统有两个明显的特点:(1)决策单元由两个阶段串行子系统构成,(2)两个子系统一个处于主导地位,而另一个处于从属地位。两个或者两个以上决策单元并购为一个虚拟决策单元。本文在分析由决策单元整体效率与其子系统效率之间关系的基础上,引入非合作博弈的思想,提出了基于非合作博弈的DEA模型评估虚拟决策单元两阶段生产系统的并购效率:即在保持现有的产出水平和生产效率的前提下,分别求解虚拟决策单元及其子系统的并购效率,分析虚拟决策单元如何通过两个子系统实现整个系统的成本节约。最后,将模型应用于台湾24家非寿险保险公司的仿真分析。由于文章提出的方法能够有效地分析虚拟决策单元内部子系统的并购有效性水平,同时考虑子系统之间的主从关系,因此,能够发掘影响虚拟决策单元并购效率的内部因素,因而能够为管理者并购决策提供更精确有效的管理信息,提高并购决策的科学性。

关键词: DEA, 两阶段生产过程, 并购效率, 非合作博弈

Abstract: In terms of how to choose the candidate target companies and predicting the feasibility of M&As, data envelopment analysis is applied to predict the feasibility of M&As with a two-stage production system. The production system has two distinct characteristics: (1) a decision-making unit consists of two tandem components; (2) one component is in a dominant position, and the other is in a subordinate position. A hypothetical DMU is merged by two or more DMUs. To solve this kind of merger efficiency evaluation problem, a DEA approach is firstly applied to evaluate the DMU's efficiency of the overall system and both components simultaneously. Then based on the idea of non-cooperative game,a game DEA approach is provided to evaluate the hypothetical DMU's merger efficiency of the overall system and both components on the condition that the current output level and efficiency are constant, which is helpful to analyze how the merged hypothetical DMU to save cost from its components. Finally, the model is applied to the simulation analysis of Taiwan's 24 non-life insurance companies. Because the model can effectively analyze all internal sub-units' merger efficiencies of a hypothetical DMU with non-cooperative game concepts, the developed approach can imply more effective and veracious decision-making information for management.

Key words: DEA, two-stage production system, merger efficiency, non-cooperative game theory

中图分类号:

C934

石晓, 谢建辉, 李勇军, 梁樑, 谢启伟. 非合作博弈两阶段生产系统DEA并购效率评价[J]. 中国管理科学, 2015, 23(7): 60-67.

SHI Xiao, XIE Jian-hui, LI Yong-jun, LIANG Liang, XIE Qi-wei. Merger Efficiency Evaluation of Two-Stage Production System Based on Non-Cooperative Game Theory[J]. Chinese Journal of Management Science, 2015, 23(7): 60-67.

参考文献

[1] Ceausescu A. Merger and acquisition-a strategic option for companies[J]. Annals of the University of Petro?ani, Economics, 2008, 8(1), 59-64.

[2] Webber J A, Dholakia U M. Including marketing synergy in acquisition analysis: a step-wise approach[J]. Industrial Marketing Management, 2000, 29(2): 157-177.

[3] Dietrich J K, Sorensen E. An application of logit analysis to prediction of merger targets[J]. Journal of Business Research, 1984, 12(3): 393-402.

[4] Pasiouras F, Gaganis C. Financial characteristics of banks involved in acquisitions: evidence from: Asia[J]. Applied Financial Economics[J], 2007, 17(4): 329-341.

[5] Ragothaman S, Naik B, Ramakrishnan K. Predicting corporate acquisitions: An application of uncertain reasoning using rule induction[J]. Information Systems Frontiers, 2003, 5(4): 401-412.

[6] Wu Desheng, Birge J. Serial chain merger evaluation model and application to mortgage banking[J]. Decision Sciences, 2012,43(1): 5-36.

[7] Bogetoft P, Wang Dexiang. Estimating the potential gains from mergers[J]. Journal of Productivity Analysis, 2005,23(2): 145-171.

[8] Farrell M J. The measurement of productive efficiency[J]. Journal of the Royal Statistical Society,1957, 120(3): 253-281.

[9] Sherman H D, Rupert T J. Do bank mergers have hidden or foregone value? Realized and unrealized operating synergies in one bank merger[J]. European Journal of Operational Research, 2006, 168(1), 253-268.[ZK)]

[10] Halkos G E, Tzeremes N G. Estimating the degree of operating efficiency gains from a potential bank merger and acquisition: A DEA bootstrapped approach[J]. Journal of Banking & Finance, 2013, 37(5): 1658-1668.

[11] 刑俊.基于资源重置的企业并购效率综合评价的非参数方法[J].系统工程理论与实践,2011,31 (1):99-107.

[12] 刘星,蒋弘.异质预期下股权制衡对公司并购绩效的影响[J].中国管理科学,2013,21(4): 144-151.

[13] 易明阳,易振华.中资商业银行跨国并购现状、动因与效率影响——基于DEA测算及TOBIT模型的实证研究[J].浙江金融, 2011,6(1): 33-39.

[14] Seiford L M, Zhu J. Profitability and marketability of the top 55 US commercial banks[J], Management Science, 1999,45(9): 1270-1288.

[15] Lozano S, Villa G. DEA-based pre-merger planning tool[J]. Journal of the Operational Research Society, 2010, 61(10):1485-1497.

[16] Wu Desheng, Zhou Zhaoxin, Birge J R. Estimation of potential gains from mergers in multiple periods: A comparison of stochastic frontier analysis and Data Envelopment Analysis[J]. Annals of Operations Research, 2011, 186(1): 357-381.

[17] Charnes A, Cooper W, Rhodes E. Measuring the efficiency of decision making units[J]. European Journal of Operational Research, 1978,2(6): 429-444.

[18] Chen Yao, Cook W D, Zhu J. Deriving the DEA frontier for two-stage processes[J]. European Journal of Operational Research, 2012, 202(1): 138-142.

[19] Liang Liang, Cook W D, Zhu J. DEA models for two-stage processes: Game approach and efficiency decomposition[J]. Naval Research Logistics, 2008,55(7): 643-653.

[20] Kao C, Hwang S N. Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies inTaiwan[J]. European Journal of Operational Research, 2008, 185(1): 418-429.

非合作博弈两阶段生产系统DEA并购效率评价

Merger Efficiency Evaluation of Two-Stage Production System Based on Non-Cooperative Game Theory

PDF (PC)

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	喻寅昀,李从东,付业林,黎建强. 考虑决策者偏好结构的交叉效率评价方法[J]. 中国管理科学, 2024, 32(8): 117-126.
[2]	陆帅,李守伟,何建敏. 考虑基金网络地位的多阶段效率及其前瞻性预测能力[J]. 中国管理科学, 2023, 31(9): 22-34.
[3]	王美强, 常梅. 考虑资金运营方式的中国商业银行经营效率分析[J]. 中国管理科学, 2023, 31(7): 140-152.
[4]	耿心宇, 秦开大. 基于多物品委托拍卖的供应链协调研究[J]. 中国管理科学, 2023, 31(5): 260-268.
[5]	冯青, 吴志彬, 徐玖平. 基于投入产出规模的省际碳排放配额分配研究[J]. 中国管理科学, 2023, 31(3): 268-276.
[6]	戴前智,徐晓迟,雷西洋,赵茜. 基于动态非合作博弈超效率DEA的成本补偿激励方法研究[J]. 中国管理科学, 2023, 31(12): 185-192.
[7]	王晓磊,木仁,周黎,董进全. 一种兼顾效率与效果的决策单元投入产出绩效评价方法[J]. 中国管理科学, 2023, 31(10): 128-135.
[8]	金卫健,徐浩,黄传峰,蒋诚智. 基于前景理论的大规模传染疫情应急管理决策研究[J]. 中国管理科学, 2023, 31(10): 225-233.
[9]	肖和录, 王善平. 基于机会约束随机Index-DEA的投资组合效率评价[J]. 中国管理科学, 2022, 30(9): 94-104.
[10]	任腾, 李姝萱, 周忠宝, 李思迪, 肖和录. 基于满意度BLP-DEA的区域可持续发展系统效率评价研究[J]. 中国管理科学, 2022, 30(7): 99-109.
[11]	周忠宝, 邓莉, 肖和录, 吴士健, LIU Wenbin. 外商直接投资对中国经济高质量发展的影响——基于Index DEA和面板分位回归的分析[J]. 中国管理科学, 2022, 30(5): 118-130.
[12]	杨敏, 费锡玥, 魏宇琪, 梁樑. 基于资源共享与子系统交互的两阶段DEA评价方法——兼对我国“一流大学”科研绩效的评价[J]. 中国管理科学, 2022, 30(2): 256-263.
[13]	梁开荣, 李登峰. 竞合模式对平台供应链线上分销策略的影响研究*[J]. 中国管理科学, 2022, 30(12): 305-316.
[14]	南江霞, 王盼盼, 李登峰. 非合作-合作两型博弈的Shapley值纯策略纳什均衡解求解方法[J]. 中国管理科学, 2021, 29(5): 202-210.
[15]	王树强, 刘赫, 徐娜, 孟娣. 大气污染物排放权初始分配的区际协调方法研究[J]. 中国管理科学, 2021, 29(3): 37-48.