中国啤酒产业动态并购的建模、仿真与预测研究
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摘要
并购活动往往不是孤立的行为,一个厂商发动并购常常会诱发竞争对手的并购动机,形成动态并购现象和并购潮特征。动态并购影响产业竞争结构演变,也影响厂商竞争交互策略,而产业竞争结构又是影响并购动机的重要变量。因此,研究产业动态并购模型、利用竞争结构预测并购行动倾向,在我国目前大规模产业结构调整与重组背景下具有重要的理论与实践意义。
尽管目前针对动态并购和并购潮的解释理论不少,但这些理论大多数关注产业冲击、股市波动、管理者动机和羊群效应等外生变量。从根本上来说,它们属于外生型动态并购和并购潮解释理论,忽视了产业内厂商间竞争交互和市场竞争结构变化等内生变量的影响,即内生型动态并购和并购潮解释理论还比较贫乏。在竞争对抗预测方面,除了陈明哲(Chen M. J)提出的“竞争性行动与竞争性响应”预测框架外,还没有出现过利用竞争结构来预测并购行为倾向的研究方法和思路。
因此,本文尝试利用复杂网络分析方法,提出产业竞争压力扩散诱发动态并购理论模型,并以我国啤酒产业为例,研究多市场竞争情景下的动态并购形成机理:即从厂商竞争交互与市场竞争结构演化角度分析厂商A并购厂商B为什么会诱发C并购D、E并购F等一连串的动态级联并购效应,最终形成产业层面的并购潮现象?同时,基于竞争结构与并购行动的相关性,提出“竞争结构—并购行动”预测框架。
具体说来,本文首先利用1997-2008年全球并购数据构建了跨国并购复杂网络模型,在分析全球并购规律基础上,分析了我国啤酒产业重组背景、动态并购和并购潮现象及其动因;其次,讨论了啤酒产业多市场竞争格局特征和形成原因,分别以该产业1992-2009年数据,构建了“市场—厂商”二分布尔和加权时间序列网络、产业竞争关系时间序列网络,通过分析网络拓扑结构变化揭示了并购行动对产业竞争结构演变的作用规律;紧接着,利用啤酒产业竞争关系和并购行动数据,构建了“竞争关系—并购行动”二层复杂网络模型,计算了网络的拓扑结构属性指标,并分析竞争结构变量与并购行动变量的相关性;随后,提出了竞争压力扩散驱动的动态并购理论模型,利用仿真手段分析了厂商竞争结构变量对动态并购和并购潮形成过程的影响,同时讨论了产业并购政策与厂商并购策略。最后,在前文实证研究的基础上,基于复杂网络结构相似性的链路预测思想和神经网络数据挖掘工具,提出“竞争结构—并购行动”预测框架和方法,以啤酒产业为例进行了相关预测。
通过对以上内容的研究,本文发现:(1)本文构建的“市场—厂商”二分网络、产业竞争关系网络、“竞争关系—并购行动”二层网络的大部分统计特性,都与复杂网络的无标度、小世界等特性相符,并购行动引起的产业竞争关系网络属于时变网络。(2)随着啤酒厂商跨市场动态并购行动增加,我国啤酒产业产业竞争关系也日趋复杂,动态并购行动使我国离散、分割的区域市场逐渐形成全国统一的啤酒市场,厂商竞争关系逐渐由地方单一市场竞争对抗转向多市场竞争对抗。(3)“竞争关系—并购行动”二层网络模型能综合整体网与局域网、无权网与加权网、无向网与有向网等,对分析厂商竞争关系与对抗行动具有重要价值,研究发现厂商竞争结构与并购行动之间存在显著相关性。(4)动态并购模型与仿真结果表明,产业竞争压力扩散能够触发级联动态并购效应,并形成产业并购潮,竞争结构变量对动态并购和并购潮的影响规模、持续时间和稳定状态都有重要影响。(5)结合复杂网络链路预测思想和神经网络数据挖掘工具,利用竞争结构变量能够预测厂商的市场进入倾向、发生竞争关系的可能性和厂商生存年限,这表明基于“竞争结构—并购行动”预测框架和方法具有可行性。
在创新方面,首先,本文尝试将复杂网络方法、多市场动态竞争和厂商并购理论结合起来,提出了产业竞争结构演化和竞争压力扩散驱动的动态并购模型,分析了竞争结构对动态并购形成过程的影响,从新的视角解释了内生并购潮现象。其次,结合复杂网络链路预测思想、神经网络数据挖掘工具,以啤酒产业数据验证了“竞争结构—并购行动”预测框架的可行性。第三,本文建立了多个时间序列网络、“竞争关系—并购行动”二层网络,揭示了啤酒产业动态并购行动与产业竞争关系演变的规律,解释了该产业近20年来的动态并购形成机制,为制定产业并购政策和厂商并购策略提供了理论依据。第四,产业竞争关系复杂网络方法的引入,既能考虑网络中节点厂商基于资源和能力观的理性并购决策因素,又能分析产业竞争环境对厂商并购决策的影响,从而将战略管理和产业组织理论衔接起来,这对现有的产业竞争与并购决策研究来说具有方法创新价值。
The merger is usually not an isolated activity. The launch of a firm’s merger will usually induce a rival’s motivation of merger, forms the phenomenon of dynamic merger, and macro to presents the characteristic of merger wave. Dynamic mergers will not only influence the evolution of the industry competitive strucuture, but also influence the firm’s competitive interaction tactic. Simultaneousl, industry competitive structure is a very important variable on firm’s merger motive. Thus, the research on the model of dynamic merger and predicting merger tendency by using of competive structure variables appears to be extraordinary important on theory and reality, under the background of Chinese high speed development and large scale industrial structure adjustment and restructure.
Even though there are some theories aim at explaining dynamic mergers and merger waves nowadays, most of those theories pay their attentions to the industrial shock, stock market’s fluctuation, manager’s motivation, herd action and so on. But fundamentally, they all emphasize the influence of exogenous variable to dynamic mergers and merger waves. And neglect the importance of endogenous variable such as competition interaction among firms of an industry, market competition structure and so on. That is to say, there are few of endogenous explaining theories on dynamic mergers and merger waves. On the side of predicting the rival action, there has not been ermerging the theory framework for predicting merger tendency by using of competitive structure variables. The only predict theory is Chen’s competitive action and competitive response.
Thus, this document attempt to utilize the method of complex network analysis, raise the theory model of industry competition pressure’s diffusion inducing strategic merger. Take the beer industry of our country as an example, study the mechanism of strategic merger’s formation under the situation of multi-market competition, which means to analyze why the merger of firm A to firm B will induce the merger of firm C to firm D, firm E merger firm F and series of cascade merger effect in the point of view of strategic interaction and market competition structure evolution, and ultimately form the phenomenon of strategic merger. Beside this , this paper tries hard to put up a new predict framework of competitive structure and merger actions, on base of relevance of competive structure variables and merger actions.
Specifically, first, this document applies the status of global strategic merger of 1997-2008 to build the model of transnational merger complex network. On the basis of analyzing the law of global strategic merger structure, analyze the recombination background, the phenomenon of merger waves and its driver of our country’s beer industry. Secondly, discuss the cause of the formation of the situation of multi-market competition in our country’s beer industry, separately construct the“market-firm”dichotomy time series network, which are based on the data of our country’s beer industry from 1992 to 2009. Proclaims the law and characteristic of industrial competition structure evolution through network topology variation, the evolution is caused by beer firms’merger. After that, build the“competition relationship and merger action”double layer complex network model, using the data of beer industry’s competition relation and merger action. Calculate the attribute indexes of network’s topological structure, and analyze the relativity of competition structure variables and merger action variables. Then, on the basis of competition structure and rival action frame, put forward the model of dynamic merger model driven by competition pressure diffusion. And discuss the influence of firm competition structure variable to the forming process of dynamic mergers and merger waves through simulation. In addition, discuss the industry competition and merger policy, strategy of firm multi-market merger, aiming at the sensibility of competition variables’influence to merger action. Finally, on base of the empirical study and simulation results, this document put up a new forecst framework and method of“competitive structure-merger action”on the complex network link prediction and neural network data mining method, then make some relational prediction by taking the forecast analysis of beer industry as an example.
Through the research we found the following: (1) the statistical property of marks-firm bipartite networks, industry competition relationship networks,“competition relationship-merger action”networks built in this document corresponded to the complex network’s character of scale free, small world. And competitive network driven by merger action belongs to a time-depent netowork. (2) As the more and more action of cross-market merger of beer firms, the“market-firms”bipartite network, industry competition relationship networks’structure is getting complicated. The action of cross-market merger makes the discrete, splitted regional market gradually forms the nationwide unified beer market. The competition relations among firm gradually turn from regional market to multi-market rivals. (3) the two network model of“competition relationship-merger action”could composite the ensemble network and the local area network, unweighted network and weighting network, undirected network and directed network, since the analysis of the firms’rival actions determined by objective industry competition relation has significant values, through the research we found the remarkable relativity between beer firms competition structure and merger action. (4) the results of modeling and simulation indicates that the diffusion of industry competition pressure could strike the dynamic merger and form the merger waves, variable such as the competition structure, and the multi-market merger strategy has important influence to the spread to the extends, duration and stable state. (5) combining the forecast thoughts of complex network link forecast and node similarity forecast, we can precisely predict the competition relation of beer firms, frequency of merger and average life through the data of competition structure and merger action. It indicates the feasibility of firm rival action prediction based on competition structure.
In the aspect of innovation, first of all, attempting to combine the industry competition relation analysis method of complex network analysis, the theory of multi-market dynamic competition, raise the model of dynamic merger driven by industry competition structure evolution and competition pressure diffusion. This is the expansion and supplement of merger waves theory’s explanation. Secondely, combining data excavate tools such as complex network prediction, neural network, using the beer industry data to verify the feasibility of using competition structure variable to predict merger action variable of“structure-action”prediction. Thirdly, time-depent complex networks and“competition relationship-merger action”double network excavate the character and law of beer industry’s competition relation and multi-market structure dynamic evolution, supply the new analytical framework to the research of industry organization and dynamic competition. Besides, in the process of simulation, we discuss the industry competition and merger policy, firm merger strategy under the environment of multi-market competition. Finaly, by introducing complex network theory to the industrial competitive relationship, which not only could take account the rational descion-making factors from the view of the manufacturing firm’s resources and capacity, but also could analyse industrial competitive envirment influence on their descion-making. Thus, this method could link the strategy management theory and industry organization theory together which put up a new method for industry competition and merger descion-making analysis.
尽管目前针对动态并购和并购潮的解释理论不少,但这些理论大多数关注产业冲击、股市波动、管理者动机和羊群效应等外生变量。从根本上来说,它们属于外生型动态并购和并购潮解释理论,忽视了产业内厂商间竞争交互和市场竞争结构变化等内生变量的影响,即内生型动态并购和并购潮解释理论还比较贫乏。在竞争对抗预测方面,除了陈明哲(Chen M. J)提出的“竞争性行动与竞争性响应”预测框架外,还没有出现过利用竞争结构来预测并购行为倾向的研究方法和思路。
因此,本文尝试利用复杂网络分析方法,提出产业竞争压力扩散诱发动态并购理论模型,并以我国啤酒产业为例,研究多市场竞争情景下的动态并购形成机理:即从厂商竞争交互与市场竞争结构演化角度分析厂商A并购厂商B为什么会诱发C并购D、E并购F等一连串的动态级联并购效应,最终形成产业层面的并购潮现象?同时,基于竞争结构与并购行动的相关性,提出“竞争结构—并购行动”预测框架。
具体说来,本文首先利用1997-2008年全球并购数据构建了跨国并购复杂网络模型,在分析全球并购规律基础上,分析了我国啤酒产业重组背景、动态并购和并购潮现象及其动因;其次,讨论了啤酒产业多市场竞争格局特征和形成原因,分别以该产业1992-2009年数据,构建了“市场—厂商”二分布尔和加权时间序列网络、产业竞争关系时间序列网络,通过分析网络拓扑结构变化揭示了并购行动对产业竞争结构演变的作用规律;紧接着,利用啤酒产业竞争关系和并购行动数据,构建了“竞争关系—并购行动”二层复杂网络模型,计算了网络的拓扑结构属性指标,并分析竞争结构变量与并购行动变量的相关性;随后,提出了竞争压力扩散驱动的动态并购理论模型,利用仿真手段分析了厂商竞争结构变量对动态并购和并购潮形成过程的影响,同时讨论了产业并购政策与厂商并购策略。最后,在前文实证研究的基础上,基于复杂网络结构相似性的链路预测思想和神经网络数据挖掘工具,提出“竞争结构—并购行动”预测框架和方法,以啤酒产业为例进行了相关预测。
通过对以上内容的研究,本文发现:(1)本文构建的“市场—厂商”二分网络、产业竞争关系网络、“竞争关系—并购行动”二层网络的大部分统计特性,都与复杂网络的无标度、小世界等特性相符,并购行动引起的产业竞争关系网络属于时变网络。(2)随着啤酒厂商跨市场动态并购行动增加,我国啤酒产业产业竞争关系也日趋复杂,动态并购行动使我国离散、分割的区域市场逐渐形成全国统一的啤酒市场,厂商竞争关系逐渐由地方单一市场竞争对抗转向多市场竞争对抗。(3)“竞争关系—并购行动”二层网络模型能综合整体网与局域网、无权网与加权网、无向网与有向网等,对分析厂商竞争关系与对抗行动具有重要价值,研究发现厂商竞争结构与并购行动之间存在显著相关性。(4)动态并购模型与仿真结果表明,产业竞争压力扩散能够触发级联动态并购效应,并形成产业并购潮,竞争结构变量对动态并购和并购潮的影响规模、持续时间和稳定状态都有重要影响。(5)结合复杂网络链路预测思想和神经网络数据挖掘工具,利用竞争结构变量能够预测厂商的市场进入倾向、发生竞争关系的可能性和厂商生存年限,这表明基于“竞争结构—并购行动”预测框架和方法具有可行性。
在创新方面,首先,本文尝试将复杂网络方法、多市场动态竞争和厂商并购理论结合起来,提出了产业竞争结构演化和竞争压力扩散驱动的动态并购模型,分析了竞争结构对动态并购形成过程的影响,从新的视角解释了内生并购潮现象。其次,结合复杂网络链路预测思想、神经网络数据挖掘工具,以啤酒产业数据验证了“竞争结构—并购行动”预测框架的可行性。第三,本文建立了多个时间序列网络、“竞争关系—并购行动”二层网络,揭示了啤酒产业动态并购行动与产业竞争关系演变的规律,解释了该产业近20年来的动态并购形成机制,为制定产业并购政策和厂商并购策略提供了理论依据。第四,产业竞争关系复杂网络方法的引入,既能考虑网络中节点厂商基于资源和能力观的理性并购决策因素,又能分析产业竞争环境对厂商并购决策的影响,从而将战略管理和产业组织理论衔接起来,这对现有的产业竞争与并购决策研究来说具有方法创新价值。
The merger is usually not an isolated activity. The launch of a firm’s merger will usually induce a rival’s motivation of merger, forms the phenomenon of dynamic merger, and macro to presents the characteristic of merger wave. Dynamic mergers will not only influence the evolution of the industry competitive strucuture, but also influence the firm’s competitive interaction tactic. Simultaneousl, industry competitive structure is a very important variable on firm’s merger motive. Thus, the research on the model of dynamic merger and predicting merger tendency by using of competive structure variables appears to be extraordinary important on theory and reality, under the background of Chinese high speed development and large scale industrial structure adjustment and restructure.
Even though there are some theories aim at explaining dynamic mergers and merger waves nowadays, most of those theories pay their attentions to the industrial shock, stock market’s fluctuation, manager’s motivation, herd action and so on. But fundamentally, they all emphasize the influence of exogenous variable to dynamic mergers and merger waves. And neglect the importance of endogenous variable such as competition interaction among firms of an industry, market competition structure and so on. That is to say, there are few of endogenous explaining theories on dynamic mergers and merger waves. On the side of predicting the rival action, there has not been ermerging the theory framework for predicting merger tendency by using of competitive structure variables. The only predict theory is Chen’s competitive action and competitive response.
Thus, this document attempt to utilize the method of complex network analysis, raise the theory model of industry competition pressure’s diffusion inducing strategic merger. Take the beer industry of our country as an example, study the mechanism of strategic merger’s formation under the situation of multi-market competition, which means to analyze why the merger of firm A to firm B will induce the merger of firm C to firm D, firm E merger firm F and series of cascade merger effect in the point of view of strategic interaction and market competition structure evolution, and ultimately form the phenomenon of strategic merger. Beside this , this paper tries hard to put up a new predict framework of competitive structure and merger actions, on base of relevance of competive structure variables and merger actions.
Specifically, first, this document applies the status of global strategic merger of 1997-2008 to build the model of transnational merger complex network. On the basis of analyzing the law of global strategic merger structure, analyze the recombination background, the phenomenon of merger waves and its driver of our country’s beer industry. Secondly, discuss the cause of the formation of the situation of multi-market competition in our country’s beer industry, separately construct the“market-firm”dichotomy time series network, which are based on the data of our country’s beer industry from 1992 to 2009. Proclaims the law and characteristic of industrial competition structure evolution through network topology variation, the evolution is caused by beer firms’merger. After that, build the“competition relationship and merger action”double layer complex network model, using the data of beer industry’s competition relation and merger action. Calculate the attribute indexes of network’s topological structure, and analyze the relativity of competition structure variables and merger action variables. Then, on the basis of competition structure and rival action frame, put forward the model of dynamic merger model driven by competition pressure diffusion. And discuss the influence of firm competition structure variable to the forming process of dynamic mergers and merger waves through simulation. In addition, discuss the industry competition and merger policy, strategy of firm multi-market merger, aiming at the sensibility of competition variables’influence to merger action. Finally, on base of the empirical study and simulation results, this document put up a new forecst framework and method of“competitive structure-merger action”on the complex network link prediction and neural network data mining method, then make some relational prediction by taking the forecast analysis of beer industry as an example.
Through the research we found the following: (1) the statistical property of marks-firm bipartite networks, industry competition relationship networks,“competition relationship-merger action”networks built in this document corresponded to the complex network’s character of scale free, small world. And competitive network driven by merger action belongs to a time-depent netowork. (2) As the more and more action of cross-market merger of beer firms, the“market-firms”bipartite network, industry competition relationship networks’structure is getting complicated. The action of cross-market merger makes the discrete, splitted regional market gradually forms the nationwide unified beer market. The competition relations among firm gradually turn from regional market to multi-market rivals. (3) the two network model of“competition relationship-merger action”could composite the ensemble network and the local area network, unweighted network and weighting network, undirected network and directed network, since the analysis of the firms’rival actions determined by objective industry competition relation has significant values, through the research we found the remarkable relativity between beer firms competition structure and merger action. (4) the results of modeling and simulation indicates that the diffusion of industry competition pressure could strike the dynamic merger and form the merger waves, variable such as the competition structure, and the multi-market merger strategy has important influence to the spread to the extends, duration and stable state. (5) combining the forecast thoughts of complex network link forecast and node similarity forecast, we can precisely predict the competition relation of beer firms, frequency of merger and average life through the data of competition structure and merger action. It indicates the feasibility of firm rival action prediction based on competition structure.
In the aspect of innovation, first of all, attempting to combine the industry competition relation analysis method of complex network analysis, the theory of multi-market dynamic competition, raise the model of dynamic merger driven by industry competition structure evolution and competition pressure diffusion. This is the expansion and supplement of merger waves theory’s explanation. Secondely, combining data excavate tools such as complex network prediction, neural network, using the beer industry data to verify the feasibility of using competition structure variable to predict merger action variable of“structure-action”prediction. Thirdly, time-depent complex networks and“competition relationship-merger action”double network excavate the character and law of beer industry’s competition relation and multi-market structure dynamic evolution, supply the new analytical framework to the research of industry organization and dynamic competition. Besides, in the process of simulation, we discuss the industry competition and merger policy, firm merger strategy under the environment of multi-market competition. Finaly, by introducing complex network theory to the industrial competitive relationship, which not only could take account the rational descion-making factors from the view of the manufacturing firm’s resources and capacity, but also could analyse industrial competitive envirment influence on their descion-making. Thus, this method could link the strategy management theory and industry organization theory together which put up a new method for industry competition and merger descion-making analysis.
引文
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