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论文编号：	6502
作者编号：	1120100748
上传时间：	2014/6/12 12:26:58
中文题目：	基于自组织理论的知识创新机理研究
英文题目：	Research on Knowledge Innovation Mechanism Based on Self-organization Theory
指导老师：	林润辉
中文关键字：	知识创新，自组织，混沌，涌现，自组织临界性
英文关键字：	Knowledge Innovation; Self-organization; Chaos; Emergence; Self-organized Criticality
中文摘要：	创新是社会发展和人类进步的不竭动力，是价值创造的根本途径，是理论界与实践界的长期议题。进入知识经济时代，激烈的竞争与复杂多元的环境，造就了更为紧迫的创新挑战。而知识是创新之源，知识创新是创新的基础，知识创新的探讨可以作为认识创新本质的突破口。通过相关学者对创新及知识创新的持续关注，形成了不同管理背景下逐渐细化的研究领域，但是知识创新的不确定性、涌现性等复杂性特征，使得知识创新的核心机制难以通过传统的研究方法加以解释。将知识创新作为复杂性问题，以复杂性科学视角进行研究成为一条可行途径。但是限于复杂性理论自身正在发展中，以及其抽象化的自然科学领域理论特点，存在直接将其应用在管理科学领域的困难，亦造成了这方面研究的不足。时至今日，有关知识创新的核心机理问题仍需继续探索。鉴于此，本文从复杂性科学视角研究知识创新问题，通过深入研究复杂性科学特别是其中的自组织理论领域的相关理论与模型，探索知识创新机理的描述与解释方法。本文以知识创新、创新机理已有的研究成果为基础，运用复杂性科学、自组织理论及系统论等理论方法，以还原论和整体论相结合的研究思路，综合理论推演、案例研究、数理建模和数值模拟方法，研究知识创新的内在机理问题，以进一步理解和认识知识创新的内核机制。通过知识创新生成过程、知识创新演化规律以及知识创新涌现机制三个逻辑关联的子问题，进行知识创新机理的系统深入探讨。通过研究，本文的主要发现与结论有：第一，通过ASQ学者的知识创新案例研究，包括单个学者的个体分析以及32位学者的整体归纳分析发现，作为典型的知识创新的科研过程，其成功需要知识创新主体具备交叉学科的知识背景或丰富的职业经历、有长时间的知识积累、持续进行着活跃的知识创新和学术交流活动并嵌入在大的学者合作网络中。第二，通过相关理论文献的系统梳理和基于自组织理论的深入探讨，知识创新是复杂性问题，知识创新主体是复杂系统；知识创新主体具有多层次性，且不同层次上的知识创新具有自相似特征；知识创新可看作多层次系统中低一层次到高一层次的涌现现象，知识创新系统演进过程中某个时刻可能会涌现之前的系统状态无法推测的创新状态。第三，进一步提炼了创新时间、知识积累、知识多样性和知识组合为知识创新过程中的关键要素，界定系统知识与结构基础上，分析知识创新过程基本逻辑，构建了知识创新过程模型。其中，新知识的产生、知识数量的扩张和知识的筛选是创新过程的核心机制，并据此设计了知识创新过程模型的组合模块、存储模块和筛选模块。第四，基于混沌理论及混沌动力学方法，分析知识创新迭代机制下的混沌演化特性并构建知识创新的Logistic混沌动力演化模型，分析了系统不同创新能力下，知识多样性程度的演化轨迹，及初始多样性对系统创新状态的影响，得以区分知识创新系统演化的创新匮乏、初步创新、规律创新和混沌创新四个阶段，并给出不同阶段的创新能力参数区间。第五，基于涌现理论、自组织临界性理论和元胞自动机模拟方法，构建了基于BTW模型的知识创新涌现模型，分析知识组合机制下，系统的微观知识互动到宏观知识结构形成的演变，系统持续知识量变积累到整体创新质变的进程。模拟知识创新系统达到创新混沌边缘的动力机制，并验证了系统混沌边缘的创新呈现时间上和空间上的幂律分布特征。本文的主要创新之处体现在：第一，对知识创新这个复杂性研究问题，本文借鉴复杂性科学，以还原论和整体论思想相结合，进行知识创新一般化的共性机制分析和整体研究系统构建。重点基于知识创新的迭代机制和组合机制进行分析，形成了以创新过程模型、创新演化模型以及创新涌现模型为核心的知识创新机理分析系统。第二，结合案例研究、理论推演和系统分析，设置抽象的知识创新系统，探讨不同层次上知识创新的共性机制，归纳一般化的创新关键要素，构建包含知识产生、知识扩张和知识筛选的创新逻辑过程。第三，通过构建知识创新演化机制，给出系统创新演化的阶段细化认识，提出描述知识创新状态的创新能力增长常数 ，分析知识创新过程中的蝴蝶效应阶段，论述渐进性创新与突破性创新的统一。第四，通过构建知识创新涌现模型，模拟创新的自组织临界状态，分析系统演化至持续创新涌现的知识组合机制和自组织机制，并分析系统混沌边缘的创新时空幂律分布特征。第五，本文以复杂性及自组织理论对知识创新进行了理论分析，并基于不同视角之间的相似性，进行自组织理论中的理论方法在知识创新领域的应用。包括，基于混沌动力学的知识创新演化动力机制的设计与模型探讨；基于自组织临界性的知识创新系统混沌边缘研究与涌现机制探讨。针对问题特点的跨领域研究，加深了知识创新认识的同时亦拓展了原有理论的应用研究。
英文摘要：	As driving force of social development and human progress, innovation is the central issue for both academic research and business practice. All value creation requires innovation. As the fierce competition and complexity environment, in the knowledge economy era innovation is in demand much more than before. Because of knowledge is the resource and foundation of innovation, knowledge innovation research is the central for understanding what is innovation and how to innovate. Concerns over innovation and knowledge innovation have grown significantly, and relevant achievements are rich, but for the uncertainty and emergent property of knowledge innovation, traditional research methods still cannot explain the core mechanism of knowledge innovation. Knowledge innovation should be viewed as complexity problem, and be studied from Complexity Science view. But as Complexity Science is abstract natural science and is still on developing, Management Science research cannot use it directly, so research on knowledge innovation mechanism based on Complexity perspective is not sufficient. Therefore, this paper aimed to studying knowledge innovation issue from the point view of Complexity Science, according to intensive study in Self-organization Theory, exploring theories and models to describe and explain knowledge innovation mechanism. Based on the existing knowledge innovation and innovation research, this paper applied Complexity Science, Self-organization Theory and System Theory, combined Reductionism and Holism, used theoretical deduction, case study, mathematical modeling and simulation, to carry out the core mechanism research of knowledge innovation. We built a logic analysis system for intensive study of knowledge innovation, including knowledge innovation process, knowledge innovation evolution rules, and knowledge innovation emergence mechanism. The main findings and conclusions drawing from this paper are showed as follows: Firstly, according to case study of ASQ scholars, containing of inductive analysis of individual scholar and the whole 32 scholar, we found that interdisciplinary knowledge background, rich work experience, longtime knowledge accumulation, persistent innovation output, active academic communication, and embedded in a large scholar collaboration network, are the outstanding characteristics of the scholars who has successful knowledge innovation. Secondly, according to systematic review of relative literatures and thorough discussion based on Self-organization Theory, we took knowledge innovation as complexity issue, while knowledge innovation subject as complex system. Knowledge innovation subject has multi-level structure, and there is self-similarity in different levels. Knowledge innovation is the emergence phenomenon from a lower level to a higher level in complex system, the emergent behavior of innovation cannot be captured by the properties of the parts of the system, and innovation emerges at some historical time without in some way being captured in the previously existing system. Thirdly, we summarized innovation time, knowledge accumulation, knowledge diversity, and knowledge combination as critical factors, defined system knowledge and structure, then depicted the logic of knowledge innovation process, and built knowledge innovation prototypical process model. In the model, knowledge generating, knowledge number expanding, and knowledge filtrating, are core mechanisms, accordingly combination, storage and filtration modularization were proposed, and corresponding algorithms were designed. Fourthly, based on Chaos Theory and chaotic dynamic models, we analyzed the chaotic evolution characteristic under iteration mechanism of knowledge innovation in knowledge innovation system, and built Logistic chaotic dynamic model of knowledge innovation evolution. Through model simulating, we studied the different system knowledge diversity evolution tendency, and the different influences of initial condition on the innovation state, under different innovation capacity parameters. In condition of different innovation states and system evolution, we proposed four stages in knowledge innovation: deficient innovation stage, preliminary innovation stage, regular innovation stage and chaotic innovation stage. Fifthly, took advantage of Emergence Theory, Self-organized Criticality Theory and Cellular Automata simulation method, we built knowledge innovation emergence model based on BTW model. Through model simulating, we studied the process in the system from microscopic knowledge interaction to macroscopic knowledge structure formation, from knowledge quantitative accumulation to qualitative change, under combination mechanism of knowledge innovation. We simulated the dynamic mechanism of how knowledge innovation system attains chaos edge of innovation, and tested the Power-law distribution characteristic both in temporal and spatial of innovation on the chaos edge. The main innovation and theory contributions of this study are showed as follows: First of all, in confront of the complex knowledge innovation problem, combined Reductionism and Holism, this paper analyzed general knowledge innovation mechanism and built innovation research system from the perspective of Complexity Science. With emphasizing the iteration and combination mechanisms of knowledge innovation, we constructed the knowledge innovation research system, which composed by knowledge innovation process model, evolution model and emergence model. Secondly, according to the combination of case study, theoretical deduction and system analysis, we abstracted the knowledge innovation system, analyzed the core general mechanism over different innovation levels, concluded critical innovation factors, and built the knowledge innovation prototypical process. Thirdly, based the knowledge innovation evolution mechanism proposed in this paper, we refined the understanding of innovation evolution with different stages, provided the innovation capacity increasing contant , analyzed butterfly effect in knowledge innovation process, and discussed the consistency of incremental innovation and radical innovation. Fourthly, based the knowledge innovation emergence model proposed in this paper, we simulated Self-organized Criticality state of innovation, analyzed the knowledge combination mechanism and Self-organization mechanism, and studied the innovation Power-law distribution on system chaos edge. Fifthly, except the knowledge innovation theoretical analysis using Complexity and Self-organization Theory, based on the similarity between different theory perspectives, this paper explored the application of theories and models from Self-organization Theory in knowledge innovation study, worked on the modeling and simulating of knowledge innovation mechanism, including the design and simulation of knowledge innovation evolution dynamic mechanism based on Chaos Theory, and the analysis of knowledge innovation emergent property and knowledge innovation system chaos edge study based on Self-organized Criticality Theory. The interdisciplinary approach seeking in knowledge innovation research, deepened knowledge innovation understanding, as well as extended the application of Self-organization Theory.
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