本文選題：大數(shù)據(jù)產(chǎn)業(yè) + 創(chuàng)新績(jī)效��； 參考：《北京郵電大學(xué)》2017年碩士論文

【摘要】：大數(shù)據(jù)開(kāi)啟了一次重大的產(chǎn)業(yè)變革時(shí)代,圍繞數(shù)據(jù)資源的開(kāi)發(fā)利用催生出一種新興業(yè)態(tài)——大數(shù)據(jù)產(chǎn)業(yè)。大數(shù)據(jù)既是傳統(tǒng)產(chǎn)業(yè)轉(zhuǎn)型升級(jí)的“催化劑”,同時(shí)也是經(jīng)濟(jì)發(fā)展的增長(zhǎng)熱點(diǎn),對(duì)我國(guó)經(jīng)濟(jì)社會(huì)產(chǎn)生了廣泛而深刻的影響。當(dāng)前,我國(guó)加快實(shí)施國(guó)家大數(shù)據(jù)戰(zhàn)略,將大數(shù)據(jù)產(chǎn)業(yè)作為新的經(jīng)濟(jì)增長(zhǎng)點(diǎn)加以培育,進(jìn)而推動(dòng)我國(guó)經(jīng)濟(jì)發(fā)展方式轉(zhuǎn)型升級(jí)。技術(shù)創(chuàng)新是大數(shù)據(jù)產(chǎn)業(yè)發(fā)展的源泉和不竭動(dòng)力,創(chuàng)新績(jī)效直接影響產(chǎn)業(yè)創(chuàng)新行為的實(shí)踐效果。以全面分析我國(guó)大數(shù)據(jù)產(chǎn)業(yè)發(fā)展現(xiàn)狀為切入點(diǎn),本文運(yùn)用DEA方法測(cè)度了大數(shù)據(jù)產(chǎn)業(yè)創(chuàng)新的綜合效率、純技術(shù)效率和規(guī)模效率,得出的主要結(jié)論有:創(chuàng)新績(jī)效總體水平不高,純技術(shù)效率偏低是主要誘因;產(chǎn)業(yè)總體處于規(guī)模收益遞減階段,創(chuàng)新要素投入過(guò)度化問(wèn)題嚴(yán)重;創(chuàng)新績(jī)效水平存在區(qū)域差異,珠三角最高,中西部地區(qū)最低。為了進(jìn)一步分析大數(shù)據(jù)產(chǎn)業(yè)創(chuàng)新績(jī)效影響因素,本文運(yùn)用隨機(jī)效應(yīng)模型分析了各個(gè)創(chuàng)新要素的影響系數(shù),得出的主要結(jié)論有:創(chuàng)新投入是影響大數(shù)據(jù)產(chǎn)業(yè)創(chuàng)新績(jī)效的主要因素,其中資本投入比人力投入影響力度大,但二者均呈負(fù)向效應(yīng);組織管理、市場(chǎng)需求和企業(yè)規(guī)模對(duì)創(chuàng)新績(jī)效均有顯著的正向影響;政府扶持對(duì)創(chuàng)新績(jī)效有微弱的負(fù)向影響�；谝陨戏治鼋Y(jié)果,本文提出了我國(guó)大數(shù)據(jù)產(chǎn)業(yè)創(chuàng)新績(jī)效提升的對(duì)策建議,包括明確政府功能定位,營(yíng)造良好創(chuàng)新環(huán)境;加強(qiáng)產(chǎn)業(yè)生態(tài)體系建設(shè),提高協(xié)同創(chuàng)新能力;優(yōu)化企業(yè)內(nèi)部創(chuàng)新機(jī)制,提升創(chuàng)新成果質(zhì)量。與同類(lèi)研究成果相比,本文有這樣兩個(gè)獨(dú)到之處:1.選題和研究視角新穎。大數(shù)據(jù)產(chǎn)業(yè)是一種新興業(yè)態(tài),相關(guān)研究處于探索階段,尤其是產(chǎn)業(yè)創(chuàng)新績(jī)效方面的研究文章實(shí)不多見(jiàn)。本文大膽探索、另辟蹊徑,從京津冀、長(zhǎng)三角、珠三角、中西部4個(gè)維度對(duì)大數(shù)據(jù)產(chǎn)業(yè)創(chuàng)新績(jī)效進(jìn)行評(píng)價(jià)分析,在國(guó)內(nèi)學(xué)術(shù)界尚屬首次。2.選用的分析方法新穎。盡管DEA方法和隨機(jī)效應(yīng)模型并非本人首創(chuàng),而且也有少數(shù)學(xué)者開(kāi)始對(duì)大數(shù)據(jù)產(chǎn)業(yè)創(chuàng)新績(jī)效問(wèn)題進(jìn)行實(shí)證研究,從現(xiàn)有的文獻(xiàn)來(lái)看,還沒(méi)有學(xué)者從多投入多產(chǎn)出視角構(gòu)建大數(shù)據(jù)產(chǎn)業(yè)創(chuàng)新績(jī)效評(píng)價(jià)指標(biāo)體系的先例。另外,本文基于波特國(guó)家創(chuàng)新系統(tǒng)鉆石理論構(gòu)建大數(shù)據(jù)產(chǎn)業(yè)創(chuàng)新績(jī)效影響因素體系,并運(yùn)用隨機(jī)效應(yīng)模型進(jìn)行回歸分析,也可以說(shuō)是本文研究的獨(dú)到之處。
[Abstract]:Big data has opened an important era of industrial transformation, and the development and utilization of data resources has given birth to a new type of industry-big data industry. Big data is not only a "catalyst" for the transformation and upgrading of traditional industries, but also a hot point of economic development, which has a wide and profound impact on the economy and society of our country. At present, our country speeds up the implementation of the national big data strategy, cultivates the big data industry as the new economic growth point, and then promotes the transformation and upgrading of our country's economic development mode. Technological innovation is the source and inexhaustible power of big data industry development, and innovation performance directly affects the practical effect of industrial innovation behavior. Based on the comprehensive analysis of the current situation of big data industry development in China, this paper measures the comprehensive efficiency, pure technical efficiency and scale efficiency of big data industry innovation by using DEA method. The main conclusions are as follows: the overall level of innovation performance is not high. The low efficiency of pure technology is the main inducement; the industry is in the stage of diminishing returns on scale in general, the problem of excessive investment of innovation elements is serious; the level of innovation performance exists regional differences, the Pearl River Delta is the highest, and the central and western regions are the lowest. In order to further analyze the influencing factors of industrial innovation performance of big data, this paper analyzes the influence coefficient of each innovation factor by using stochastic effect model. The main conclusions are as follows: innovation investment is the main factor influencing the innovation performance of big data industry. Among them, capital investment has more influence than manpower input, but both have negative effect; organizational management, market demand and enterprise scale have significant positive influence on innovation performance; government support has weak negative effect on innovation performance. Based on the above analysis results, this paper puts forward the countermeasures and suggestions for improving the industrial innovation performance of big data in China, including defining the function of the government, creating a good innovation environment, strengthening the construction of industrial ecological system and improving the ability of collaborative innovation. Optimize the internal innovation mechanism and improve the quality of innovation results. Compared with similar research results, this paper has two unique features: 1. The selection of topics and the perspective of research are novel. Big data industry is a new type of industry. The related research is still in the exploratory stage, especially in the field of industrial innovation performance. This article boldly explores, another way, from the Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta, the central and western four dimensions of big data industry innovation performance evaluation analysis, in domestic academia is the first. 2. The analytical method selected is novel. Although DEA method and stochastic effect model are not the first by myself, and a few scholars have begun to do empirical research on the performance of big data industry innovation, from the existing literature, There is no precedent for scholars to construct the performance evaluation index system of big data industry innovation from the perspective of multi-input and multi-output. In addition, this paper based on Porter National Innovation system Diamond theory to construct the big data industry innovation performance impact factors system, and the use of stochastic effect model for regression analysis, it can be said that this study is unique.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：F273.1;F49

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