安徽省战略性新兴产业绿色创新能力的统计研究

发布时间：2018-01-07 08:20

本文关键词：安徽省战略性新兴产业绿色创新能力的统计研究　出处：《安徽财经大学》2016年硕士论文　论文类型：学位论文

【摘要】：2008年金融危机的爆发,对世界经济带来了深远的消极影响。世界各国为应对这场危机,都纷纷提出战略转型,出台新兴产业发展战略规划,主动地改善产业结构,增强产业的科技创新能力和综合竞争力,积极抢占新的世界科技经济竞争制高点。在此背景下,在国务院出台战略性新兴产业的相关政策之后,我国各省市、自治区结合各地区特点,也相继颁布本地区的战略性新兴产业的政策,以推进本地区的发展。安徽省作为我国东部内陆省份之一,也积极主动地响应国家战略的号召,大力发展和培育本地区战略性新兴产业。在此政策背景下,本文基于创新和环境问题的考虑,将绿色创新能力引入到对安徽省战略性新兴产业研究之中。本文基于国家统计局公布的《战略性新兴产业分类(2012)(试行)》及战略性新兴产业依托部门的定义,选取出安徽省战略性新兴产业依托部门。在战略性新兴产业绿色创新能力评价指标体系的设计原则的指导下,完成了战略性新兴产业绿色创新能力评价指标体系的设计,结合安徽省规模以上工业企业分行业数据,选择出相应的指标数据,并利用SPSS软件对选取出的指标数据进行因子分析,依据分析结果对2013年安徽省战略性新兴产业绿色创新能力进行综合评价。在此基础上,将因子分析提取出的主因子和综合得分作为?-支持向量回归机的训练样本,并对该评价模型进行了训练,建立了基于因子分析和支持向量回归机的安徽省战略性新兴产业绿色创新能力评价模型,并运用训练好的评价模型对2014年安徽省战略性新兴产业绿色创新能力进行评价应用。研究显示,此模型能够在很大程度上减少计算量,适用于非线性的战略性新兴产业绿色创新能力评价问题。接着,本文采用非期望超效率SBM模型与Malmquist指数相结合的方法对安徽省战略性新兴产业依托行业绿色创新效率进行动态分析,结果表明战略性新兴产业依托行业之间存在差异,从整体来看,情况是在向好的方向发展。最后本文给出了研究的主要结论以及对未来的展望。
[Abstract]:In 2008 the outbreak of the financial crisis, brought a far-reaching negative impact on the world economy. All the countries in the world to cope with the crisis, have put forward the strategic transformation, the introduction of planning and development of strategic emerging industries, and actively improve the industrial structure, enhance industrial technology innovation ability and competitiveness, and actively seize the new science and technology in the world economic competition in this ground. Under the background, after the State Council promulgated the policy of strategic emerging industries, China's provinces and regions according to the characteristics of the autonomous region, has promulgated the region's strategic emerging industry policy, in order to promote the development of the region. Anhui province is one of the inland provinces in eastern China, but also actively respond to national call strategy and vigorously develop and cultivate local strategic emerging industries. In the context of this policy, the innovation and environmental problems based on the consideration of the green innovation approach Into the study of strategic emerging industries in Anhui province. The "classification of strategic emerging industry released by the National Bureau of statistics based on (2012) (Trial)" and the definition of strategic emerging industry relying on the Department, selected Anhui province strategic emerging industry relying on the Department. The design principle of the evaluation index system of green innovation in strategic emerging industries. Under the guidance, completed the design of evaluation index system of strategic emerging industry green innovation ability, combined with Anhui Industrial Enterprises above the scale of industry data, select the corresponding index data, and factor analysis of the data selected by SPSS software, based on the results of the analysis of Anhui Province in 2013, strategic emerging industry green innovation ability comprehensively evaluation. On this basis, the main factor analysis and factor scores extracted as? - support vector regression training This, and the evaluation model of training, establish the evaluation of strategic emerging industries in Anhui province green innovation ability factor analysis and support vector regression model based on the evaluation, and using the trained model of Anhui Province in 2014, strategic emerging industry of green innovation ability evaluation application. Research shows that this model can reduce the amount of computation a large extent, the problem of evaluation for nonlinear strategic emerging industries green innovation ability. Then, the dynamic analysis method this paper adopts non expected super efficiency SBM model and Malmquist index of a combination of strategic and emerging industries in Anhui Province Based on green industry innovation efficiency, results show that there are differences between the strategic emerging industry based on the industry, on the whole, the situation is in the right direction. Finally, this paper gives the main research conclusions and outlook for the future.

【学位授予单位】：安徽财经大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：F276.44

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