【摘要】：復(fù)雜網(wǎng)絡(luò)理論是當(dāng)前科學(xué)理論的重要研究熱點(diǎn),其廣泛應(yīng)用的根本原因之一在于跨學(xué)科的良好交叉性。在復(fù)雜網(wǎng)絡(luò)研究中,通過(guò)建立合適的網(wǎng)絡(luò)模型來(lái)分析網(wǎng)絡(luò)統(tǒng)計(jì)性質(zhì)的產(chǎn)生機(jī)理并預(yù)測(cè)網(wǎng)絡(luò)的行為,可以使人們能夠更加合理地控制整個(gè)網(wǎng)絡(luò)的性能和設(shè)計(jì)更加合理的網(wǎng)絡(luò)結(jié)構(gòu)。而產(chǎn)業(yè)網(wǎng)絡(luò)本質(zhì)上是一個(gè)以資本、知識(shí)及技術(shù)為基礎(chǔ)進(jìn)行交流合作,在各種因素的共同促進(jìn)下形成一個(gè)動(dòng)態(tài)的、開放的復(fù)雜關(guān)系系統(tǒng),具有復(fù)雜網(wǎng)絡(luò)的結(jié)構(gòu)特征。本文在復(fù)雜網(wǎng)絡(luò)理論以及產(chǎn)業(yè)演化研究的基礎(chǔ)上,首先定性分析了產(chǎn)業(yè)演化機(jī)制,然后分別從橫向的創(chuàng)新擴(kuò)散和縱向的產(chǎn)業(yè)結(jié)構(gòu)演化兩個(gè)方面進(jìn)行了建模與仿真,最后以生物科技產(chǎn)業(yè)為實(shí)例,說(shuō)明模型的適用性及對(duì)政府策略的啟發(fā)性。本文主要研究工作如下:(1)在創(chuàng)新擴(kuò)散層面,綜合節(jié)點(diǎn)自身異質(zhì)性、網(wǎng)絡(luò)效應(yīng)以及政策市場(chǎng)環(huán)境三個(gè)方面的因素影響,在EWA學(xué)習(xí)模型的基礎(chǔ)上,對(duì)參數(shù)設(shè)置和效用函數(shù)都進(jìn)行了改進(jìn),使其針對(duì)產(chǎn)業(yè)網(wǎng)絡(luò)中企業(yè)主體的創(chuàng)新策略采納決策更具適用性;然后,運(yùn)用理論推導(dǎo)的方式計(jì)算出初始擴(kuò)散閾值,當(dāng)滿足條件時(shí)產(chǎn)業(yè)中創(chuàng)新將會(huì)出現(xiàn);最后,合理的設(shè)置參數(shù)值,運(yùn)用matlab,對(duì)影響擴(kuò)散的三個(gè)因素:網(wǎng)絡(luò)結(jié)構(gòu)、創(chuàng)新及學(xué)習(xí)失敗率以及政策扶植力度進(jìn)行了仿真與分析,并且就結(jié)果對(duì)政府如何根據(jù)產(chǎn)業(yè)情況采取相關(guān)政策給出建議。(2)在產(chǎn)業(yè)拓?fù)浣Y(jié)構(gòu)層面,首先,設(shè)置了原產(chǎn)業(yè)網(wǎng)絡(luò)中節(jié)點(diǎn)重連及斷邊機(jī)制以及新節(jié)點(diǎn)加入和連接機(jī)制;然后綜合創(chuàng)新擴(kuò)散過(guò)程,建立了一個(gè)混合的產(chǎn)業(yè)復(fù)雜網(wǎng)絡(luò)演化模型并設(shè)置了仿真規(guī)則;最后,運(yùn)用matlab仿真分別研究了重連及斷邊速度、新節(jié)點(diǎn)加入速度、擇優(yōu)和隨機(jī)連接概率等因素對(duì)創(chuàng)新擴(kuò)散均衡和網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)的影響,并就結(jié)論給出政策建議。(3)以美國(guó)生物科技產(chǎn)業(yè)為例進(jìn)行了案例分析,從理論上驗(yàn)證了模型的適用性,并且針對(duì)產(chǎn)業(yè)發(fā)展情況進(jìn)行總結(jié),對(duì)政府引扶持國(guó)內(nèi)高新技術(shù)產(chǎn)業(yè)健康發(fā)展具有較大借鑒意義。
[Abstract]:The theory of complex network is an important research hotspot in current scientific theory. One of the fundamental reasons for its wide application lies in the good intersectionality of disciplines. In the study of complex networks, by establishing appropriate network models to analyze the generation mechanism of network statistical properties and predict network behavior, people can more reasonably control the performance of the entire network and design a more reasonable network structure. In essence, industrial network is a dynamic and open complex relationship system based on capital, knowledge and technology. It has the structural characteristics of complex network. Based on the theory of complex network and the research of industrial evolution, this paper first analyzes the mechanism of industrial evolution qualitatively, and then models and simulates the horizontal innovation diffusion and vertical industrial structure evolution. Finally, take the biotechnology industry as an example to illustrate the applicability of the model and enlighten the government strategy. The main research work of this paper is as follows: (1) on the basis of EWA learning model, the main research work is as follows: (1) in the aspect of innovation diffusion, considering the heterogeneity of node itself, network effect and policy market environment, The parameter setting and utility function are improved to make it more applicable to the innovation strategy of the enterprise in the industrial network. Then, the initial diffusion threshold is calculated by theoretical derivation. When the conditions are satisfied, innovation in the industry will appear. Finally, by setting the parameter value reasonably and using matlab, the paper simulates and analyzes the three factors that influence diffusion: network structure, innovation and learning failure rate, and policy support. And on the basis of the results, some suggestions are given on how the government should adopt relevant policies according to the industrial situation. (2) at the level of industrial topology, firstly, the mechanism of node reconnection and disconnection and the mechanism of joining and connecting new nodes in the original industrial network are set up. Then a hybrid industrial complex network evolution model is established and simulation rules are set up by synthesizing innovation diffusion process. Finally, the effects of reconnection and breaking speed, new node adding speed, optimal selection and random connection probability on innovation diffusion equalization and network topology are studied by matlab simulation, respectively. Finally, some policy suggestions are given. (3) A case study of American biotech industry is given, which verifies the applicability of the model in theory, and summarizes the development of the industry. It is of great significance for the government to support the healthy development of domestic high-tech industry.
【學(xué)位授予單位】：南京航空航天大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：F124.3;F276.44

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