摘要
基于中国大数据产业上市公司的面板数据,采用DEA方法测度并分析技术效率及其分解指标的变动趋势。结果表明,中国大数据产业技术效率较为低下,其主要原因在于纯技术效率增长拖累;东部地区技术效率和纯技术效率均高于中西部地区,但规模效率水平低于中西部地区;从变动趋势看,考察期内中国大数据产业技术效率及其构成总体均呈现波动下降的"U"型动态演变趋势,但不同区域的变动存在一定差异。进一步分析发现,盈利水平对纯技术效率起到了显著的促进作用,但阻碍了规模效率的提高;资本结构显著抑制了纯技术效率提升,却不利于规模效率改善;资金运用能力对纯技术效率和规模效率均有促进作用;成长能力不足和收益质量不高均在一定程度上抑制了纯技术效率和规模效率的提升。
Based on the panel data of China big - data industrial listed companies and using DEA method, this paper evaluates and analyzes the changing tendency of the technology efficiency and the decomposition indicator. The study shows that the technology efficiency of big - data industry is relatively low, which is mainly caused by the drag of the pure technology efficiency; both technology efficiency and the pure technology efficiency in western China are higher than central and western regions, while the scale efficiency is lower. From the perspective of tendency, there is the fluctuating decreased "U" type dynamic evolution trend on the China big - data industrial technology efficiency and its components. However, the changes in different regions differ. From the further analysis, we found that: the profitability highly promotes the pure technology efficiency, while blocks the improvement of scale efficiency; the capital structure significantly inhibits the pure tech- nical efficiency and is not conducive to improve scale efficiency; utilizing ability of the capital promotes both the pure technology efficiency and scale efficiency; to a certain extent, the inefficient growth and the poor profitability hinder the improvement of the pure technology efficiency and the scale efficiency.
出处
《科技管理研究》
CSSCI
北大核心
2016年第14期107-112,共6页
Science and Technology Management Research
基金
国家自然科学基金项目"西部区域创新环境质量评价
监测与空间差异研究"(71273209)
关键词
大数据
技术效率
纯技术效率
规模效率
影响因素
big- data
technology efficiency
pure technology efficiency
scale efficiency
affecting factors