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Innovation efficiency of semiconductor industry in China: A new framework based on generalized three-stage DEA analysis

机译:中国半导体产业的创新效率:基于广义三阶段DEA分析的新框架

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Considering the interrelationships between periods and the influences of non-operational factors, a new framework based generalized three-stage DEA model, grey relational analysis theory and disparity disassembly model is proposed in this paper. Then, we measure the technical efficiency, scale efficiency, and pure technical efficiency of innovation in China's semiconductor industry between 2009 and 2014. In addition, we conducted projection analysis of the inputs to innovation and the disparities analysis in innovation efficiency across the industrial chain and within each segment. The results of our analyses reveal four key findings. The overall innovation efficiency of China's semiconductor industry is increasing; however, each segment of the industrial chain had different trends and different levels of innovation efficiency. All segments show a consistently upward trend except for package testing, which dipped in 2012 due to the time lag between the inputs and outputs associated with major technological advancements. The most efficient innovation is occurring in design and package testing, followed by manufacturing, materials, and equipment, in that order. Low levels of innovation efficiency were found to be the most significant factor restricting further improvement in the design, manufacturing, and equipment segments of the industrial chain. But the opposite is true for the package testing segment, where pure technical efficiency is the main factor. A range of redundancies in input were found across the industrial chain, mostly in manufacturing and equipment. These two segments are capital-intensive and characterized by a high level of technical complexity coupled with a long research cycle. The disparities in innovation efficiency in and between the segments decreased over the period. However, interestingly, the main disparities were found among the enterprises within each segment, which we attribute to the Chinese government's concerted efforts to support particular companies. Package testing and manufacturing had the highest levels of disparity due to relatively high agglomeration of these two segments. The materials segment had the lowest disparity, with equipment and design falling somewhere in-between.
机译:考虑到周期之间的相互关系和非运行因素的影响,提出了一种基于广义三阶段DEA模型,灰色关联分析理论和视差分解模型的新框架。然后,我们测量了2009年至2014年间中国半导体行业的技术效率,规模效率和创新的纯技术效率。此外,我们对创新投入进行了预测分析,并在整个产业链中进行了创新效率差异分析。在每个细分市场中我们的分析结果揭示了四个关键发现。中国半导体产业的整体创新效率不断提高。然而,产业链的每个环节都有不同的趋势和不同的创新效率水平。除包装测试外,所有细分市场均呈持续上升的趋势,由于主要技术进步,投入和产出之间的时间差使包装测试在2012年下降。最有效的创新发生在设计和包装测试中,其次是制造,材料和设备。人们发现,创新效率水平低是限制产业链设计,制造和设备领域进一步改善的最重要因素。但是,对于包装测试部门而言,情况恰恰相反,在这方面,纯技术效率是主要因素。在整个产业链中发现了大量的投入冗余,主要是在制造和设备方面。这两个部分是资本密集型的​​,其特点是技术水平高,研究周期长。在此期间,各部门之间以及各部门之间的创新效率差异有所减少。然而,有趣的是,在每个细分市场的企业之间发现了主要的差异,这归因于中国政府为支持特定企业所做的共同努力。由于这两个部分的集聚程度较高,因此包装测试和制造的差异最大。材料领域的差异最小,设备和设计介于两者之间。

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