产业复杂网络：建模及应用
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摘要
产业关联是一种客观存在的重要的社会经济基础关系,是指产业分工体系中不同产业之间功能上相互支持和依存的经济技术关系。不仅产品与服务的生产与流通等环节发生的企业间交易关系是建立在产业关联关系的基础上,而且地区产业结构的“量”的状态也本质是由产业关联的“质”的性态所决定。因此,无论是企业层面的供应链管理与一体化战略、战略联盟等问题,还是区域或国家层面的经济产业结构优化调整、产业升级等问题,实质都是以产业关联关系为基础,产业关联是这些经济管理决策问题的客观约束性条件,也必然是管理学与经济学的重要研究主题,研究和描述产业关联具有重要理论和现实意义。
诞生于20世纪50年代的产业关联研究重视利用投入产出技术描述和研究产业关联,其理论模型与应用成果对经济发展战略提供了重要的政策支持,赫希曼关联效应理论不仅成为“不平衡”发展观点的重要理论依据,更决定了之后产业关联建模与应用研究的主流趋势——测度产业关联效应的强度并以部门在关联效应强度上的差异作为关键及非关键产业判定的基本标准。投入产出经济学(Input-Output Economics)是在30年代由里昂惕夫在吸收魁奈的经济表和新古典经济学的一般均衡理论思想基础上发展起的一门独立经济学科,由于其构建的结构化、标准化的投入产出表具有产业间投入产出关系定量化描述的优点,产业关联自然就同投入产出的技术方法密切结合起来,基于投入产出模型的赫希曼关联效应强度测量研究传统上成为关联建模研究发展和关联问题应用分析的基本框架及一般范式。
但是经典方法和模型中存在着一定局限或关键不足：(1)全部产业的关联关系是否具有同等意义。部分关联关系构成经济产业基础结构,但是由于信息过于分散,在投入产出表(无论是流量、投入产出系数还是里昂惕夫逆矩阵系数)中不能看到基础经济结构的轮廓；(2)相同数值的关联效应强度是否具有同等的意义。由于高数值的关联效应强度可能来自于较少部分的强关联关系,而相对低数值的关联效应强度来自于大小较为均衡的关联关系,这样单纯两个部门效应强度数值比较的意义就模糊了,由于信息过于集中,也是不能看到关联的关系结构。产业关联是一种二元关系,图或者网络是关系结构表达的有效工具,于是针对经典关联模型的不足,一些学者尝试利用图或者网络的方法描述产业关联,并根据实际问题挖掘其中的结构特征,如表现为特殊子图的产业集、表现为路径的产业链等。另一方面,产业系统也是一个特殊的复杂性系统,随着复杂性科学的兴起和复杂网络研究的深入,在关联研究领域也出现了以复杂网络拓扑指标描述关联结构特征的发展趋势。但是这两类研究都较为分散,且存在着较多的薄弱环节,如建立关联网络的关联关系临界值确定不完善,对关联关系类型的区分重视不够,以及复杂网络指标移植的经济意义解析不清晰等。
产业关联的研究描述具有重要现实价值与理论意义,针对现有关联建模与应用研究的局限,本文研究问题界定为以关联效应评价为中心的“产业关联关系”描述和“产业关联结构”描述,研究中心为产业复杂网络的建模与应用。关系描述是结构描述的基础,结构描述是关系描述的目的,采用关联关系-关联结构-关联效应的系统分析方法,通过产业复杂网络的建模和应用实现研究目的。建模研究包括2方面：(1)产业复杂网络(ICN)(基本模型)构建；(2)基于ICN的关联指标体系(纵向延伸模型)构建。应用研究也包括2方面：(1)对基本模型的延伸应用,即将ICN应用于关联结构特征的描述,具体包括基于ICN的关联结构特征研究和基于ICN的关联指标体系研究；(2)对ICN基本模型和延伸模型的现实应用,即将关联关系描述模型(ICN基本模型)和关联结构描述模型(ICN关联指标/ICN延伸模型)应用在关联效应(具体包括区域竞争优势效应和产业结构效应)的分析中。第2章对产业关联建模与应用的相关理论和研究成果进行了综合述评,是本文具有现实性与合理性的重要依据和研究基础。
基于产业关联系统内在的复杂性和二元关联关系特点,本文第3章提出了“产业复杂网络(Industry Complex Netwok, ICN)”的概念。产业复杂网络的核心是强关联关系的识别和描述,其以节点表示产业(部门),以边表示产业间的关联关系,边的方向则指示着产业链的延伸方向,即同上游产业的后向关联和同下游产业的前向关联。产业复杂网络实际是展示了区域经济的基础结构,根据其关系意义的不同,具有多种不同形态,最基本的是供给型和需求型网络的划分,而当处于供给方或需求方的不同位置,又存在主动视角和被动视角网络的划分。基础网络包含前向供给型(Forward Supplying-ICN)、后向供给型(Backward Supplying-ICN)、前向需求型(Forward Demanding-ICN)和后向需求型(BackwardDemanding-ICN)4类。由于投入产出系数矩阵提供了丰富的关联信息数据,而投入产出数据库也已较为成熟完善,因此ICN建模的关系数据基础是投入产出模型,利用投入系数矩阵与L矩阵和产出系数与G矩阵分别描述供给关系和需求关系。由于处于产品生产和商品交换的最前沿,产业对自身的分工地位和前后互动的关联关系状态具有强敏感性和最直接准确的反应,因此采用“产业认知”的方法进行强关联关系的搜索,即对产业自身所面临的关联关系进行比较,选择目前状态下对产业供给或需求关系具有重要影响的关联关系作为强关联关系。强关联关系客观上具有一个界限,由具体的临界值来表示,根据“产业认知”和关联关系分布的特点,采用威弗组合指数(Weaver Index)方法进行临界值的搜索,构建了过虑关联关系的多维临界值向量,有效克服传统方法主观性强和难以操作的不足,具有意义合理、处理灵活的优点。依据强关联关系进行连边,产业复杂网络可以0-1矩阵形式(如邻接矩阵、完全关联矩阵等)和不同类别的网络图进行表示。进一步通过基础网络的“并”或“交”投影,建立起组合型产业复杂网络,在基础型和组合型网络基础上利用Warshall二元关系运算法则得到聚合型产业复杂网络,同时依据一定的规则对基本有向网络作无向化处理,得到无向产业复杂网络(Indirectional ICN),而设置特定的边权数值则可得到赋边权产业复杂网络(Weighted ICN)。组合与聚合,无向与赋边权网络都是基础产业复杂网络的扩展模型,基础网络和扩展网络共同构成了一个多层次的产业复杂网络模型体系。应用两个实例验证了产业复杂网络建模的有效性。实例Ⅰ建立了山东省42部门产业复杂网络模型体系,并根据应用分析的不同目的和要求,分别以邻接矩阵形式、分离子图形式、聚合网络形式和(类)树图形式描述不同类型产业复杂网络的具体形态,验证了产业复杂网络建模方法的可行性以及基于经济管理决策的模型优化或应用的合理性。实例Ⅱ以山东省信息产业部门的产业链结构分析为例,通过不同类型基础ICN关系的对比,识别出信息产业的“全局”或者“局部”重要性的产业关联关系,进行供给／需求关系的“均衡性”分析,建立起信息部门的产业链模型,识别出山东省信息产业发展中存在的稳定性与不确定性以及有利性与制约性的关联关系因素,验证了多类别、多层次产业复杂网络在经济产业链描述和经济决策支持上的有效性。
关联结构描述是关联结构特征的提取和刻画,包括两个问题：(1)存在哪些需要提取和描述的“关联结构特征”；(2)这些“关联结构特征”如何提取和描述。产业关联效应是一种关联结构效应,关联结构研究需要以关联效应分析为中心。第4章将关联效应区分为直接结构效应和间接结构效应,直接结构效应直接决定于关联结构特征,而间接结构效应是不同直接结构效应的有机结合和综合发挥。从直接关联结构效应出发描述关联整体和关联个体两个层次的关联结构特征。关联整体特征包括关联整体稳定性、关联整体中心性、关联整体聚类性和关联整体循环性,关联个体特征则集中表现为产业的“中心性”,包括“产业连接”、“产业位置”和“产业流”三个方面。这一步解决了“关联结构特征”识别的问题。进一步将关联结构特征研究有机转化为产业复杂网络的优化研究,利用图论技术以及网络分析方法对不同关联结构特征构建了对应的提取和描述方法,解决了“关联结构特征”的提取和描述问题。山东省关联结构特征分析的验证性研究表明构建出的综合性结构特征描述方法实际可行,有较强区分性。
关联关系和结构研究的目的是关联效应评价,即从“关联特征分析→关联效应评价”,其沟通的桥梁是关联指标。产业关联系统等价由产业复杂网络来表达,这一问题转化为ICN关联指标的设计与应用问题。第5章以关联系统的分析和关联关系结构模式信息的挖掘为中心,依据产业关联效应可识别与可解析原则和已获得的产业关联结构特征的研究成果,基于ICN设计了一个综合性产业关联指标体系。它是由产业关联整体、产业关联结构和产业关联个体3个关联Ⅰ级指标和17个关联Ⅱ级指标所组成的多层次、多维度的指标体系,具有明确的经济意义、等价的网络意义和可比较的数值意义。以山东省三次产业关联效应分析为例验证了这一关联指标体系的可行性和应用上的灵活性、广泛性及适用性。
将ICN转入实际关联效应问题的应用研究中,第6章首先进行了“鲁苏粤”产业关联比较研究,从“鲁苏粤”三省经济发展的重要性、受关注度和内在差异性出发,选择山东、江苏和广东三省进行产业关联的地区横向比较研究,并着重于实现关联关系、关联结构特征和关联效应的综合性分析。关联关系的比较以三省的同构性和异构性产业复杂网络为基础,研究三省“竞争优势效应”共同性的经济关联基础。由于区域经济的首要特征是产业集聚性,因此重点分析三省关联整体中心性,通过比较关联整体中心结构指标,结合三省产业集聚形式和产业增加值、产业企业数与企业平均增加值等“产业属性”,对产业集聚效应所包含的产业分工协调性(产业分工体系同地区资源和区位特点的相适应性)和产业集聚绩效进行了研究分析。区域经济发展也需要明确“关键产业”,将产业关联个体指标同基于I-O的关联效应强度系数有机配合,界定“强度关键性产业”和“结构关键性产业”,区分出“高生产性产业”、“高加工性产业”、“高带动性产业”、“潜在高带动性产业”、“主导性产业”、“瓶颈性产业”、“高端类产业”和“基础类产业”,将三省产业进行对应归类,并进而结合“产业属性”(如一、二、三次产业类别,工业和服务业内部类别等)对三省相应“关键产业”发展的优势(关键产业正效应)与不足(关键产业负效应)进行了全面比较。
第7章基于纵向维度上产业关联效应的变化分析进行了中国产业结构升级的实证研究。从产业关联上看,结构升级主要体现在技术进步推动的整体技术结构优化、产业链延伸性提高和产业影响力改变三个层次上。提取建立在产业复杂网络上的关联整体中心性、关联整体聚类性、关联整体循环性、产业完全纵深度、关联个体宽广性、关联个体纵深性与关联个体主导性7个关联结构指标和关联技术敏感性与产业个体关联度2个经典I-O指标共同构成关联视角的产业结构升级指标体系。利用这一指标体系基于2002和2007年中国投入产出数据实证分析了中国产业结构升级状况。研究结果表明,2002-2007年中国技术进步推动下的技术结构变动趋势明显,产业链延伸性有较大提高而产业影响性的变化呈现不平衡性的特征,这三个层次关联特征体现了我国这一时期产业内在“质”的结构的新提升。
第8章将本文提出与论证的主要观点、完成的研究工作和关键问题进行了总结,并关注到研究中存在的局限,对进一步的研究方向进行了合理展望。
总之,本文在研究视角、研究模型和研究方法三个方面具有创新性,而研究创新最集中体现于威弗组合指数的强关联关系区分和能够实现关联效应评价分析的ICN关联指标体系的创建两点上。综合性的产业复杂网络建模与应用研究表明,产业复杂网络的相关研究成果能够对产业关联关系、关联结构和关联效应进行有效描述和深入解释,能够为进一步的关联结构优化和关联效应水平提升提供理论方法、可行思路和策略路径的有力支持。
Industrial linkage is one of the objective, important and foundational socio-economic relationships. It refers to the economic, technological and inter-industrial relationships, which are mutually and functionally supported and inter-depended in industrial system. Not only the trading relationships between the enterprises in the production and circulation of products and services are established on the basis of the industrial linkage, but also the state of the regional industrial structure in "quantity" is determined by the nature of the industrial linkage in "quality". Therefore, supplying chain management, integration strategies, strategic alliances and other issues in the enterprise level, and optimization and adjustment of industrial structure and industrial upgrading in regional or national level, are in real terms based on the industrial linkage. Industrial linkage presenting objective constraints on economic or management'decision problems, is bound to be an important research topic of Management and Economics.
The industrial linkage theory formed in the1950s by the contribution of Hirschman, and has been providing important research support for the strategy of development on economy since its birth. The Hirschman Linkage Theory has not only become an important theoretical foundation of the "imbalanced" development on economy, but also determined the main research trend in industrial linkage-to measure the intensity of the industrial linkage's effect and to take the performance of the sector on the intensity of industrial linkage's effect as the critical standard on determining the key or non-key industries. The Input-Output Economics (I-O) is an independent economic subject developed by Leontief in the1930s on the absorption of Quesnay's economy table and neo-classical economics'general equilibrium theory. Because of the advantages of its structured and standardized input-output models with a quantitative description of inter-industrial input-output relations, the industrial linkage theory naturally is closely related with the input-output techniques. Therefore, the measurement on intensity of Hirschman linkage based on input-output models has become the basic framework and paradigm on the development of linkage theoris and the analysis of linkage.
But there are certain problems or critical shortage in the classical I-O methods and models.(1) Do all the linkage's relations are equally important? Part of the linkage's relations constitutes the infrastructure of the industrial system, but because information in the input-output table (regardless of the flow, input-output coefficients) is too scattered, the outline of the basic economic structure can not be seen.(2) Do the same effect's intensity values have the same meaning? The significance of the comparison on effect's intensity values of the sectors is blurred, because maybe high effect's intensity values are determined by some strong linkage's relations, and low effect's intensity values come from more strength-balanced relationships. And the relation's structure can also not be seen as the information is too concentrated. Essentially, linkage's relation is one kind of binary relationship and graph or network is an effective tool for the expression for the relation's structure. So in view of the deficiencies of the classic linkage models, some scholars tried to use graphs or networks to describe industrial linkage, and mined the characteristics of the structure according to the actual problems, such as industrial complexes and industrial chains, which can be expressed as special sub-graphs. On the other hand, the industrial system is a special complex system, with the rise of complexity science and complex networks, in the field of linkage's studies, there have been an associated trend that the topology indexes of complex network are applied to describing the characteristics of structure. However, due to a variety of reasons, these two types of research are fragmented and there are many limitations, such as the critical value of the relationship to establish the graphs or networks, the economic significance of the transplantation of the indicators on the complex network and so on.
Based on the experience of the industrial linkage's studies and learning from the limitations and shortcomings of the existing linkage's studies, the problems defined in this paper are "to describe the linkage's relations and to describe the linkage's structure, for the evaluation of linkage's effects". These two research questions are closely linked, the description of linkage's relations is the basis of the structure's description, and the description of linkage's structure is the purpose of the relationship's description. In this regard, by the method of systematic analysis, that is the linkage's relationships-the linkage's structure-the linkage's effects, the problems defined can be solved through the modeling of the Industry Complex Network (ICN) describing linkage's relationships and extension/optimization of the ICN models describing the linkage's structure to evaluate the linkage's effects. The research of modeling includes2aspects.(1) Modeling Industry Complex Networks (ICNs) that are the basic models of ICNs.(2) Modeling the system of ICN indicators that is the extension of the basic models of ICNs. The research of application includes2aspects.(1) Extensible applications of the basic models, which are ICN-based research on characteristics of linkage's structure and the ICN-based research on the system of linkage indicators.(2) Applications of the basic models and the extension models of ICNs in practical problems which are the analysis of linkage's effects. The relevant theory and research results of the modeling and applications on industry graphs or networks are reviewed in Chapter2and that is the realistic and reasonable basis for the research of this paper.
Based on the inherent complexity and binary-related characteristics of linkage, the concept of "Industry Complex Network (ICN)" is presented in Chapter3. The core of modeling the Industry Complex Network is the identification and description of the strong linkage's relationships. The ICNs are comprised with "nodes" denoting industries (sectors) and "directional edges" which indicate the direction of the linkage's relations or extension of industrial chains, which are the backward linkage with upstream industries and the forward linkage with downstream industries. Industry Complex Networks actually showing the regional economic infrastructure, have a variety of different forms, depending on the significance of their linkage's relationships. The supplying and demanding Industry Complex Networks are separated into different networks, on the position of the supplying or demanding and on the active or passive perspective. So the basic/foundational Industry Complex Networks are constituted of forward supplying-ICN (FS-ICN), backward supplying-ICN (BS-ICN), forward demanding-ICN (FD-CN) and backward demanding-ICN (BD-ICN). Because input-output coefficient matrixes provide a wealth of related information and data base, and input-output database also is build successfully, ICNs'modeling is based on the input-output models. Input coefficient matrix and Leontief inverse matrix can be applied in the supplying-ICNs'modeling, and output coefficient matrix and Ghosh inverse matrix in the demanding-ICNs' modeling. Because industries are in the forefront of exchange of production and commodity, so they have the strongest sensitivity of relationship's status and can make the most direct and accurate response with interaction, a method called "industry cognition" is introduced to search the strong relationships. The strong relationships have an upper limit. Weaver Index is made use of to fix the upper limit, which can effectively overcome the subjectivity and the difficulty to operate in traditional methods, and possesses the advantages of flexibility and practicality. Edges are determined by strong relations and ICNs are presented by the form of matrix and graph. Moreover, through some transformation, the extended Industry Complex Networks, such as "united ICNs","aggregated ICNs","weighted ICNs" and "undirected ICNs" can be developed. So foundational ICNs and extended ICNs constitute a multi-level ICN system. In this part, two examples are applied. Feasibility of modeling ICNs is conformed by example I that is the ICN system in Shandong Province on the I-O models containing42sectors. These Industry Complex Networks are presented in the forms of adjacent matrixes, detached sub-graphs, tree or tree class diagrams and so on, which can be applied to different context. In example II, to verify the good supporting role of multi-class and multi-level industry complex networks on the decision and strategy making, industrial chain's structure of information sectors in Shandong Province is analyzed, by the comparison of the "globally"/"locally" important supplying/demanding relationships in the foundational ICNs, identifying the stability and uncertainties of linkage's relationships, as well as advantageous and disadvantageous factors of linkage in Shandong'information industry.
The description of linkage's structure means the extraction of the characteristics of linkage's structure. It includes2aspects.(1) Make sure what the characteristics of linkage's structure to be extracted are.(2) The method of extracting these characteristics of linkage'structure is explored and determined. Linkage's effects are determined by the linkage's structure, so the analysis of characteristics of linkage's structure needs to be according to linkage's effects. Linkage's effects are classified into direct effects and indirect effects. The direct effects are directly associated with characteristics of structure, and the indirect effects are the combination of direct effects. Characteristics of linkage's structure are identified from the direct effects. Overall characteristics of linkage's structure include stability, centrality, classification and circularity. Individual characteristics of linkage's structure include connection, position and flow. So the first problem is solved. For characteristics of linkage's structure can be extracted from the ICNs, the methods of Graph Theory and Network Analysis are taken advantages of on the ICNs. So the second problem is solved on this idea. In Chapter4, the effectiveness of the methods is conformed by the example of analysis of characteristics of linkage's structure in Shandong Province.
The objective of the study on linkage's relationships and linkage's structure is to evaluate linkage's effects, which can be achieved by the help of linkage indicators. When industrial system is turned into Industry Complex Networks, this problem is transformed into the design and application of the ICN linkage indicators. Based on effective information mining and the research results of the characteristics of linkage's structure, a multi-level and multi-dimensional ICN indicator system is developed in Chapter5, which is comprised of3lever I indicators and17lever II indicators. This system of ICN indicator has clear economic significance, equivalent network significance and is comparable numerically. The feasibility, flexibility and applicability are conformed by the example of analysis on linkage's effects of three industries in Shandong Province in the part.
The methodological framework of linkage analysis is applied in practical research. From the importance of development of economy, social concern and inherent differences in the structure and efficient in regional economy, the provinces of Shandong, Jiangsu and Guangdong are selected for the horizontal comparative studies in Chapter6. The research focuses are on achieving the comprehensive analysis of linkage's relationships, linkage's structure and linkage's effects. The comparison of relationships is based on the homogeneous and heterogeneous ICNs to explore the structural basis of the effect of competitive advantage in the three provinces. Since the primary feature of the regional economy is the industrial agglomeration, overall centrality of linkage is one of the research focuses. By the comparison of indicators of overall centrality of linkage, combined with'industrial properties', such as the added value, the number of enterprises, the average of the added value of enterprises and so on, the coordination of industrial system (adaptability to regional resources and location) and performance of agglomeration are analyzed. For regional development of economy also requires a clear definition of "key industries", so the individual ICN-linkage indicators are integrated with the measurement on intensity of linkage's effects to identify the "key sectors in intensity" and "key sectors in structure". Comprehensive classification of sectors in the three provinces is made based on the individual characteristics of industrial linkage such as "high-productive","high-processing","high-driving","high-driving potentially","dominant","constraining","high-end" and "basic". Moreover, supplemented by the "industrial property"(industry category), advantages (positive effects) and disadvantages (negative effects) on the key sectors in the three provinces are compared.
An empirical study of the industrial structure's upgrading in China based on the analysis of changes of industrial linkage's effects is made in Chapter7. From the perspective of linkage, industrial structure's upgrading is reflected in the changes of overall technical structure, the extension of industrial chains and the industries' influence.7ICN linkage indicators including overall centrality, overall classification, overall circularity, total extensibility, individual broadness, individual extensibility, and individual dominant, and2I-O indicators construct the indicator system of industrial structure's upgrading. On the indicator system, the empirical analysis of the industrial structure's upgrading in China is made. The results show that, from2002to2007, the trend of the technological progress driven by changes in the technical structure is clear, the extension of industrial chains has been improved greatly and the changes of the industries'influence are heterogeneous. The changes in these three levels reflect the China's industrial structure's upgrading in inherent "quality" in this period.
The main ideas, the arguments, the key issues and the completion of the research work are summarized in Chapter8. Besides, the limitations and a reasonable outlook on future research are presented.
In short, this paper achieves innovative perspectives, innovative models and innovative methods. And the Identification of strong linkage relationships by Weaver Index and the construction of system of linkage indicators are the concentrated research innovations. The results have shown that the related research on Industy Complex Networks can make systematic description and explanation on the linkage's relationships, linkage's structure and linkage's effects and can provide strong support of theoretical methods, feasible ideas and strategies for further optimization of relationship's structure and upgrading of linkage's effects.
诞生于20世纪50年代的产业关联研究重视利用投入产出技术描述和研究产业关联,其理论模型与应用成果对经济发展战略提供了重要的政策支持,赫希曼关联效应理论不仅成为“不平衡”发展观点的重要理论依据,更决定了之后产业关联建模与应用研究的主流趋势——测度产业关联效应的强度并以部门在关联效应强度上的差异作为关键及非关键产业判定的基本标准。投入产出经济学(Input-Output Economics)是在30年代由里昂惕夫在吸收魁奈的经济表和新古典经济学的一般均衡理论思想基础上发展起的一门独立经济学科,由于其构建的结构化、标准化的投入产出表具有产业间投入产出关系定量化描述的优点,产业关联自然就同投入产出的技术方法密切结合起来,基于投入产出模型的赫希曼关联效应强度测量研究传统上成为关联建模研究发展和关联问题应用分析的基本框架及一般范式。
但是经典方法和模型中存在着一定局限或关键不足：(1)全部产业的关联关系是否具有同等意义。部分关联关系构成经济产业基础结构,但是由于信息过于分散,在投入产出表(无论是流量、投入产出系数还是里昂惕夫逆矩阵系数)中不能看到基础经济结构的轮廓；(2)相同数值的关联效应强度是否具有同等的意义。由于高数值的关联效应强度可能来自于较少部分的强关联关系,而相对低数值的关联效应强度来自于大小较为均衡的关联关系,这样单纯两个部门效应强度数值比较的意义就模糊了,由于信息过于集中,也是不能看到关联的关系结构。产业关联是一种二元关系,图或者网络是关系结构表达的有效工具,于是针对经典关联模型的不足,一些学者尝试利用图或者网络的方法描述产业关联,并根据实际问题挖掘其中的结构特征,如表现为特殊子图的产业集、表现为路径的产业链等。另一方面,产业系统也是一个特殊的复杂性系统,随着复杂性科学的兴起和复杂网络研究的深入,在关联研究领域也出现了以复杂网络拓扑指标描述关联结构特征的发展趋势。但是这两类研究都较为分散,且存在着较多的薄弱环节,如建立关联网络的关联关系临界值确定不完善,对关联关系类型的区分重视不够,以及复杂网络指标移植的经济意义解析不清晰等。
产业关联的研究描述具有重要现实价值与理论意义,针对现有关联建模与应用研究的局限,本文研究问题界定为以关联效应评价为中心的“产业关联关系”描述和“产业关联结构”描述,研究中心为产业复杂网络的建模与应用。关系描述是结构描述的基础,结构描述是关系描述的目的,采用关联关系-关联结构-关联效应的系统分析方法,通过产业复杂网络的建模和应用实现研究目的。建模研究包括2方面：(1)产业复杂网络(ICN)(基本模型)构建；(2)基于ICN的关联指标体系(纵向延伸模型)构建。应用研究也包括2方面：(1)对基本模型的延伸应用,即将ICN应用于关联结构特征的描述,具体包括基于ICN的关联结构特征研究和基于ICN的关联指标体系研究；(2)对ICN基本模型和延伸模型的现实应用,即将关联关系描述模型(ICN基本模型)和关联结构描述模型(ICN关联指标/ICN延伸模型)应用在关联效应(具体包括区域竞争优势效应和产业结构效应)的分析中。第2章对产业关联建模与应用的相关理论和研究成果进行了综合述评,是本文具有现实性与合理性的重要依据和研究基础。
基于产业关联系统内在的复杂性和二元关联关系特点,本文第3章提出了“产业复杂网络(Industry Complex Netwok, ICN)”的概念。产业复杂网络的核心是强关联关系的识别和描述,其以节点表示产业(部门),以边表示产业间的关联关系,边的方向则指示着产业链的延伸方向,即同上游产业的后向关联和同下游产业的前向关联。产业复杂网络实际是展示了区域经济的基础结构,根据其关系意义的不同,具有多种不同形态,最基本的是供给型和需求型网络的划分,而当处于供给方或需求方的不同位置,又存在主动视角和被动视角网络的划分。基础网络包含前向供给型(Forward Supplying-ICN)、后向供给型(Backward Supplying-ICN)、前向需求型(Forward Demanding-ICN)和后向需求型(BackwardDemanding-ICN)4类。由于投入产出系数矩阵提供了丰富的关联信息数据,而投入产出数据库也已较为成熟完善,因此ICN建模的关系数据基础是投入产出模型,利用投入系数矩阵与L矩阵和产出系数与G矩阵分别描述供给关系和需求关系。由于处于产品生产和商品交换的最前沿,产业对自身的分工地位和前后互动的关联关系状态具有强敏感性和最直接准确的反应,因此采用“产业认知”的方法进行强关联关系的搜索,即对产业自身所面临的关联关系进行比较,选择目前状态下对产业供给或需求关系具有重要影响的关联关系作为强关联关系。强关联关系客观上具有一个界限,由具体的临界值来表示,根据“产业认知”和关联关系分布的特点,采用威弗组合指数(Weaver Index)方法进行临界值的搜索,构建了过虑关联关系的多维临界值向量,有效克服传统方法主观性强和难以操作的不足,具有意义合理、处理灵活的优点。依据强关联关系进行连边,产业复杂网络可以0-1矩阵形式(如邻接矩阵、完全关联矩阵等)和不同类别的网络图进行表示。进一步通过基础网络的“并”或“交”投影,建立起组合型产业复杂网络,在基础型和组合型网络基础上利用Warshall二元关系运算法则得到聚合型产业复杂网络,同时依据一定的规则对基本有向网络作无向化处理,得到无向产业复杂网络(Indirectional ICN),而设置特定的边权数值则可得到赋边权产业复杂网络(Weighted ICN)。组合与聚合,无向与赋边权网络都是基础产业复杂网络的扩展模型,基础网络和扩展网络共同构成了一个多层次的产业复杂网络模型体系。应用两个实例验证了产业复杂网络建模的有效性。实例Ⅰ建立了山东省42部门产业复杂网络模型体系,并根据应用分析的不同目的和要求,分别以邻接矩阵形式、分离子图形式、聚合网络形式和(类)树图形式描述不同类型产业复杂网络的具体形态,验证了产业复杂网络建模方法的可行性以及基于经济管理决策的模型优化或应用的合理性。实例Ⅱ以山东省信息产业部门的产业链结构分析为例,通过不同类型基础ICN关系的对比,识别出信息产业的“全局”或者“局部”重要性的产业关联关系,进行供给／需求关系的“均衡性”分析,建立起信息部门的产业链模型,识别出山东省信息产业发展中存在的稳定性与不确定性以及有利性与制约性的关联关系因素,验证了多类别、多层次产业复杂网络在经济产业链描述和经济决策支持上的有效性。
关联结构描述是关联结构特征的提取和刻画,包括两个问题：(1)存在哪些需要提取和描述的“关联结构特征”；(2)这些“关联结构特征”如何提取和描述。产业关联效应是一种关联结构效应,关联结构研究需要以关联效应分析为中心。第4章将关联效应区分为直接结构效应和间接结构效应,直接结构效应直接决定于关联结构特征,而间接结构效应是不同直接结构效应的有机结合和综合发挥。从直接关联结构效应出发描述关联整体和关联个体两个层次的关联结构特征。关联整体特征包括关联整体稳定性、关联整体中心性、关联整体聚类性和关联整体循环性,关联个体特征则集中表现为产业的“中心性”,包括“产业连接”、“产业位置”和“产业流”三个方面。这一步解决了“关联结构特征”识别的问题。进一步将关联结构特征研究有机转化为产业复杂网络的优化研究,利用图论技术以及网络分析方法对不同关联结构特征构建了对应的提取和描述方法,解决了“关联结构特征”的提取和描述问题。山东省关联结构特征分析的验证性研究表明构建出的综合性结构特征描述方法实际可行,有较强区分性。
关联关系和结构研究的目的是关联效应评价,即从“关联特征分析→关联效应评价”,其沟通的桥梁是关联指标。产业关联系统等价由产业复杂网络来表达,这一问题转化为ICN关联指标的设计与应用问题。第5章以关联系统的分析和关联关系结构模式信息的挖掘为中心,依据产业关联效应可识别与可解析原则和已获得的产业关联结构特征的研究成果,基于ICN设计了一个综合性产业关联指标体系。它是由产业关联整体、产业关联结构和产业关联个体3个关联Ⅰ级指标和17个关联Ⅱ级指标所组成的多层次、多维度的指标体系,具有明确的经济意义、等价的网络意义和可比较的数值意义。以山东省三次产业关联效应分析为例验证了这一关联指标体系的可行性和应用上的灵活性、广泛性及适用性。
将ICN转入实际关联效应问题的应用研究中,第6章首先进行了“鲁苏粤”产业关联比较研究,从“鲁苏粤”三省经济发展的重要性、受关注度和内在差异性出发,选择山东、江苏和广东三省进行产业关联的地区横向比较研究,并着重于实现关联关系、关联结构特征和关联效应的综合性分析。关联关系的比较以三省的同构性和异构性产业复杂网络为基础,研究三省“竞争优势效应”共同性的经济关联基础。由于区域经济的首要特征是产业集聚性,因此重点分析三省关联整体中心性,通过比较关联整体中心结构指标,结合三省产业集聚形式和产业增加值、产业企业数与企业平均增加值等“产业属性”,对产业集聚效应所包含的产业分工协调性(产业分工体系同地区资源和区位特点的相适应性)和产业集聚绩效进行了研究分析。区域经济发展也需要明确“关键产业”,将产业关联个体指标同基于I-O的关联效应强度系数有机配合,界定“强度关键性产业”和“结构关键性产业”,区分出“高生产性产业”、“高加工性产业”、“高带动性产业”、“潜在高带动性产业”、“主导性产业”、“瓶颈性产业”、“高端类产业”和“基础类产业”,将三省产业进行对应归类,并进而结合“产业属性”(如一、二、三次产业类别,工业和服务业内部类别等)对三省相应“关键产业”发展的优势(关键产业正效应)与不足(关键产业负效应)进行了全面比较。
第7章基于纵向维度上产业关联效应的变化分析进行了中国产业结构升级的实证研究。从产业关联上看,结构升级主要体现在技术进步推动的整体技术结构优化、产业链延伸性提高和产业影响力改变三个层次上。提取建立在产业复杂网络上的关联整体中心性、关联整体聚类性、关联整体循环性、产业完全纵深度、关联个体宽广性、关联个体纵深性与关联个体主导性7个关联结构指标和关联技术敏感性与产业个体关联度2个经典I-O指标共同构成关联视角的产业结构升级指标体系。利用这一指标体系基于2002和2007年中国投入产出数据实证分析了中国产业结构升级状况。研究结果表明,2002-2007年中国技术进步推动下的技术结构变动趋势明显,产业链延伸性有较大提高而产业影响性的变化呈现不平衡性的特征,这三个层次关联特征体现了我国这一时期产业内在“质”的结构的新提升。
第8章将本文提出与论证的主要观点、完成的研究工作和关键问题进行了总结,并关注到研究中存在的局限,对进一步的研究方向进行了合理展望。
总之,本文在研究视角、研究模型和研究方法三个方面具有创新性,而研究创新最集中体现于威弗组合指数的强关联关系区分和能够实现关联效应评价分析的ICN关联指标体系的创建两点上。综合性的产业复杂网络建模与应用研究表明,产业复杂网络的相关研究成果能够对产业关联关系、关联结构和关联效应进行有效描述和深入解释,能够为进一步的关联结构优化和关联效应水平提升提供理论方法、可行思路和策略路径的有力支持。
Industrial linkage is one of the objective, important and foundational socio-economic relationships. It refers to the economic, technological and inter-industrial relationships, which are mutually and functionally supported and inter-depended in industrial system. Not only the trading relationships between the enterprises in the production and circulation of products and services are established on the basis of the industrial linkage, but also the state of the regional industrial structure in "quantity" is determined by the nature of the industrial linkage in "quality". Therefore, supplying chain management, integration strategies, strategic alliances and other issues in the enterprise level, and optimization and adjustment of industrial structure and industrial upgrading in regional or national level, are in real terms based on the industrial linkage. Industrial linkage presenting objective constraints on economic or management'decision problems, is bound to be an important research topic of Management and Economics.
The industrial linkage theory formed in the1950s by the contribution of Hirschman, and has been providing important research support for the strategy of development on economy since its birth. The Hirschman Linkage Theory has not only become an important theoretical foundation of the "imbalanced" development on economy, but also determined the main research trend in industrial linkage-to measure the intensity of the industrial linkage's effect and to take the performance of the sector on the intensity of industrial linkage's effect as the critical standard on determining the key or non-key industries. The Input-Output Economics (I-O) is an independent economic subject developed by Leontief in the1930s on the absorption of Quesnay's economy table and neo-classical economics'general equilibrium theory. Because of the advantages of its structured and standardized input-output models with a quantitative description of inter-industrial input-output relations, the industrial linkage theory naturally is closely related with the input-output techniques. Therefore, the measurement on intensity of Hirschman linkage based on input-output models has become the basic framework and paradigm on the development of linkage theoris and the analysis of linkage.
But there are certain problems or critical shortage in the classical I-O methods and models.(1) Do all the linkage's relations are equally important? Part of the linkage's relations constitutes the infrastructure of the industrial system, but because information in the input-output table (regardless of the flow, input-output coefficients) is too scattered, the outline of the basic economic structure can not be seen.(2) Do the same effect's intensity values have the same meaning? The significance of the comparison on effect's intensity values of the sectors is blurred, because maybe high effect's intensity values are determined by some strong linkage's relations, and low effect's intensity values come from more strength-balanced relationships. And the relation's structure can also not be seen as the information is too concentrated. Essentially, linkage's relation is one kind of binary relationship and graph or network is an effective tool for the expression for the relation's structure. So in view of the deficiencies of the classic linkage models, some scholars tried to use graphs or networks to describe industrial linkage, and mined the characteristics of the structure according to the actual problems, such as industrial complexes and industrial chains, which can be expressed as special sub-graphs. On the other hand, the industrial system is a special complex system, with the rise of complexity science and complex networks, in the field of linkage's studies, there have been an associated trend that the topology indexes of complex network are applied to describing the characteristics of structure. However, due to a variety of reasons, these two types of research are fragmented and there are many limitations, such as the critical value of the relationship to establish the graphs or networks, the economic significance of the transplantation of the indicators on the complex network and so on.
Based on the experience of the industrial linkage's studies and learning from the limitations and shortcomings of the existing linkage's studies, the problems defined in this paper are "to describe the linkage's relations and to describe the linkage's structure, for the evaluation of linkage's effects". These two research questions are closely linked, the description of linkage's relations is the basis of the structure's description, and the description of linkage's structure is the purpose of the relationship's description. In this regard, by the method of systematic analysis, that is the linkage's relationships-the linkage's structure-the linkage's effects, the problems defined can be solved through the modeling of the Industry Complex Network (ICN) describing linkage's relationships and extension/optimization of the ICN models describing the linkage's structure to evaluate the linkage's effects. The research of modeling includes2aspects.(1) Modeling Industry Complex Networks (ICNs) that are the basic models of ICNs.(2) Modeling the system of ICN indicators that is the extension of the basic models of ICNs. The research of application includes2aspects.(1) Extensible applications of the basic models, which are ICN-based research on characteristics of linkage's structure and the ICN-based research on the system of linkage indicators.(2) Applications of the basic models and the extension models of ICNs in practical problems which are the analysis of linkage's effects. The relevant theory and research results of the modeling and applications on industry graphs or networks are reviewed in Chapter2and that is the realistic and reasonable basis for the research of this paper.
Based on the inherent complexity and binary-related characteristics of linkage, the concept of "Industry Complex Network (ICN)" is presented in Chapter3. The core of modeling the Industry Complex Network is the identification and description of the strong linkage's relationships. The ICNs are comprised with "nodes" denoting industries (sectors) and "directional edges" which indicate the direction of the linkage's relations or extension of industrial chains, which are the backward linkage with upstream industries and the forward linkage with downstream industries. Industry Complex Networks actually showing the regional economic infrastructure, have a variety of different forms, depending on the significance of their linkage's relationships. The supplying and demanding Industry Complex Networks are separated into different networks, on the position of the supplying or demanding and on the active or passive perspective. So the basic/foundational Industry Complex Networks are constituted of forward supplying-ICN (FS-ICN), backward supplying-ICN (BS-ICN), forward demanding-ICN (FD-CN) and backward demanding-ICN (BD-ICN). Because input-output coefficient matrixes provide a wealth of related information and data base, and input-output database also is build successfully, ICNs'modeling is based on the input-output models. Input coefficient matrix and Leontief inverse matrix can be applied in the supplying-ICNs'modeling, and output coefficient matrix and Ghosh inverse matrix in the demanding-ICNs' modeling. Because industries are in the forefront of exchange of production and commodity, so they have the strongest sensitivity of relationship's status and can make the most direct and accurate response with interaction, a method called "industry cognition" is introduced to search the strong relationships. The strong relationships have an upper limit. Weaver Index is made use of to fix the upper limit, which can effectively overcome the subjectivity and the difficulty to operate in traditional methods, and possesses the advantages of flexibility and practicality. Edges are determined by strong relations and ICNs are presented by the form of matrix and graph. Moreover, through some transformation, the extended Industry Complex Networks, such as "united ICNs","aggregated ICNs","weighted ICNs" and "undirected ICNs" can be developed. So foundational ICNs and extended ICNs constitute a multi-level ICN system. In this part, two examples are applied. Feasibility of modeling ICNs is conformed by example I that is the ICN system in Shandong Province on the I-O models containing42sectors. These Industry Complex Networks are presented in the forms of adjacent matrixes, detached sub-graphs, tree or tree class diagrams and so on, which can be applied to different context. In example II, to verify the good supporting role of multi-class and multi-level industry complex networks on the decision and strategy making, industrial chain's structure of information sectors in Shandong Province is analyzed, by the comparison of the "globally"/"locally" important supplying/demanding relationships in the foundational ICNs, identifying the stability and uncertainties of linkage's relationships, as well as advantageous and disadvantageous factors of linkage in Shandong'information industry.
The description of linkage's structure means the extraction of the characteristics of linkage's structure. It includes2aspects.(1) Make sure what the characteristics of linkage's structure to be extracted are.(2) The method of extracting these characteristics of linkage'structure is explored and determined. Linkage's effects are determined by the linkage's structure, so the analysis of characteristics of linkage's structure needs to be according to linkage's effects. Linkage's effects are classified into direct effects and indirect effects. The direct effects are directly associated with characteristics of structure, and the indirect effects are the combination of direct effects. Characteristics of linkage's structure are identified from the direct effects. Overall characteristics of linkage's structure include stability, centrality, classification and circularity. Individual characteristics of linkage's structure include connection, position and flow. So the first problem is solved. For characteristics of linkage's structure can be extracted from the ICNs, the methods of Graph Theory and Network Analysis are taken advantages of on the ICNs. So the second problem is solved on this idea. In Chapter4, the effectiveness of the methods is conformed by the example of analysis of characteristics of linkage's structure in Shandong Province.
The objective of the study on linkage's relationships and linkage's structure is to evaluate linkage's effects, which can be achieved by the help of linkage indicators. When industrial system is turned into Industry Complex Networks, this problem is transformed into the design and application of the ICN linkage indicators. Based on effective information mining and the research results of the characteristics of linkage's structure, a multi-level and multi-dimensional ICN indicator system is developed in Chapter5, which is comprised of3lever I indicators and17lever II indicators. This system of ICN indicator has clear economic significance, equivalent network significance and is comparable numerically. The feasibility, flexibility and applicability are conformed by the example of analysis on linkage's effects of three industries in Shandong Province in the part.
The methodological framework of linkage analysis is applied in practical research. From the importance of development of economy, social concern and inherent differences in the structure and efficient in regional economy, the provinces of Shandong, Jiangsu and Guangdong are selected for the horizontal comparative studies in Chapter6. The research focuses are on achieving the comprehensive analysis of linkage's relationships, linkage's structure and linkage's effects. The comparison of relationships is based on the homogeneous and heterogeneous ICNs to explore the structural basis of the effect of competitive advantage in the three provinces. Since the primary feature of the regional economy is the industrial agglomeration, overall centrality of linkage is one of the research focuses. By the comparison of indicators of overall centrality of linkage, combined with'industrial properties', such as the added value, the number of enterprises, the average of the added value of enterprises and so on, the coordination of industrial system (adaptability to regional resources and location) and performance of agglomeration are analyzed. For regional development of economy also requires a clear definition of "key industries", so the individual ICN-linkage indicators are integrated with the measurement on intensity of linkage's effects to identify the "key sectors in intensity" and "key sectors in structure". Comprehensive classification of sectors in the three provinces is made based on the individual characteristics of industrial linkage such as "high-productive","high-processing","high-driving","high-driving potentially","dominant","constraining","high-end" and "basic". Moreover, supplemented by the "industrial property"(industry category), advantages (positive effects) and disadvantages (negative effects) on the key sectors in the three provinces are compared.
An empirical study of the industrial structure's upgrading in China based on the analysis of changes of industrial linkage's effects is made in Chapter7. From the perspective of linkage, industrial structure's upgrading is reflected in the changes of overall technical structure, the extension of industrial chains and the industries' influence.7ICN linkage indicators including overall centrality, overall classification, overall circularity, total extensibility, individual broadness, individual extensibility, and individual dominant, and2I-O indicators construct the indicator system of industrial structure's upgrading. On the indicator system, the empirical analysis of the industrial structure's upgrading in China is made. The results show that, from2002to2007, the trend of the technological progress driven by changes in the technical structure is clear, the extension of industrial chains has been improved greatly and the changes of the industries'influence are heterogeneous. The changes in these three levels reflect the China's industrial structure's upgrading in inherent "quality" in this period.
The main ideas, the arguments, the key issues and the completion of the research work are summarized in Chapter8. Besides, the limitations and a reasonable outlook on future research are presented.
In short, this paper achieves innovative perspectives, innovative models and innovative methods. And the Identification of strong linkage relationships by Weaver Index and the construction of system of linkage indicators are the concentrated research innovations. The results have shown that the related research on Industy Complex Networks can make systematic description and explanation on the linkage's relationships, linkage's structure and linkage's effects and can provide strong support of theoretical methods, feasible ideas and strategies for further optimization of relationship's structure and upgrading of linkage's effects.
引文
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