大数据类上市公司技术创新效率研究

发布时间：2018-04-15 23:02

本文选题：大数据 + 上市公司　；参考：《安徽大学》2017年硕士论文

【摘要】：科学技术是第一生产力,随着互联网、物联网和云计算等信息科学技术的迅猛发展,人类物质文化生活产生了大量的数据,人们开始意识到海量的数据当中蕴藏着丰富的经济和政治价值,因此,大数据产业应运而生,并且在2012年进入了大数据市场成长时期,同年,我国政府推出了相关的大数据发展扶持计划,促进了大数据产业的发展。我国大数据市场规模逐年增大,并且占国内生产总值的比例逐年增大,到2015年则高达69.16%,对我国经济具有重大影响,此外大数据市场规模同比增长率也很大,这说明我国大数据产业发展速度越来越快,成为经济发展新的增长点,因此要大力发展大数据产业。而技术创新效率水平的高低决定着企业发展的好坏,大数据类上市公司是大数据产业的主体,因此要提升大数据类上市公司的技术创新效率,进而促进大数据产业发展,并在最终推动我国国民经济的增长。在推动国民经济发展的需求下,本文运用三阶段DEA方法对2012-2015年30家大数据类上市公司进行技术创新效率研究。在第一阶段,将环境因素和随机误差项考虑在内,建立创新效率评价体系,从经费投入和人员投入以及经济效益和科技成果产出两个维度测算大数据类上市公司的技术创新效率;在第二阶段,将环境因素和随机误差项剥离;在第三阶段,测算剔除了环境因素和随机误差项后的技术创新效率。结果表明:环境因素和随机误差项对大数据类上市公司技术创新效率具有显著的影响。在第二阶段,剥离环境因素和随机误差项后,第三阶段测算的综合效率、纯技术效率和规模效率,大部分企业的技术创新效率所提高,并且DEA有效的企业数量增加。这说明环境因素和随机误差项对大数据类上市公司的技术创新效率在整体上表现为不利影响,同时测算的结果表明,纯技术效率均值整体上低于规模效率均值,这说明,导致企业技术创新效率水平低下主要是纯技术效率。最后,根据得出的结论,本文针对提升大数据类上市公司技术创新效率,提出了优化资源配置、创造有利环境条件和提升经营管理和技术水平三个建议,以期促进我国经济的发展。本文的创新点在于研究领域新颖,切合时代发展实际;同时所用三阶段DEA研究方法避免了很多学者目前较多使用的传统DEA和随机前沿分析法的缺点。然而,由于研究水平有限,本文存在着研究样本数量较少、样本筛选存在主观性、数据获取不全等不足之处。
[Abstract]:Science and technology is the first productivity, with the rapid development of information science and technology, such as the Internet of things, Internet of things and cloud computing, human material and cultural life has produced a large number of data.People began to realize that there were abundant economic and political values in the huge amount of data. Therefore, big data industry came into being, and in 2012 it entered the period of market growth of big data, the same year.China's government launched the relevant big data development support plan, promoted the big data industry's development.The market scale of big data in China has increased year by year, and the proportion of GDP has increased year by year. By 2015, it will be as high as 69.16, which has a significant impact on the economy of our country. In addition, the market scale of big data is also growing at a very large rate from the same period last year.This shows that big data's industry is developing more and more rapidly and becomes a new growth point of economic development.The level of technological innovation efficiency determines the quality of enterprise development. Big data listed company is the main body of big data industry. Therefore, we should improve the efficiency of technological innovation of big data listed companies, and then promote the industrial development of big data.And in the end promote the growth of our national economy.Under the demand of promoting the development of national economy, this paper studies the technological innovation efficiency of 30 big data listed companies in 2012-2015 by using the three-stage DEA method.In the first stage, environmental factors and random errors are taken into account to establish an innovation efficiency evaluation system.The technological innovation efficiency of big data listed companies is measured from the aspects of investment of funds and personnel, economic benefits and output of scientific and technological achievements. In the second stage, environmental factors and random errors are separated. In the third stage,The efficiency of technological innovation is calculated after excluding environmental factors and random errors.The results show that environmental factors and random errors have a significant impact on the efficiency of technological innovation of big data listed companies.In the second stage, after stripping off the environmental factors and random errors, the comprehensive efficiency, pure technical efficiency and scale efficiency of the third stage are increased, the technological innovation efficiency of most enterprises is improved, and the number of DEA efficient enterprises increases.This shows that environmental factors and random errors have a negative impact on the efficiency of technological innovation of big data listed companies on the whole, and the results of the calculation show that the average value of pure technical efficiency is lower than the average of scale efficiency as a whole.The low level of technological innovation efficiency of enterprises is mainly pure technical efficiency.Finally, according to the conclusions, this paper puts forward three suggestions to improve the efficiency of technological innovation of big data listed companies, such as optimizing the allocation of resources, creating favorable environmental conditions and enhancing the management and technology level.With a view to promoting the economic development of our country.The innovation of this paper is that the research field is novel and suitable for the development of the times, and the three-stage DEA research method avoids the disadvantages of traditional DEA and stochastic frontier analysis, which are widely used by many scholars at present.However, due to the limited level of research, there are some shortcomings in this paper, such as the small number of samples, the subjectivity of sample selection and the incomplete data acquisition.
【学位授予单位】：安徽大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F49;F273.1

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