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Analyzing the efficiency of small and medium-sized enterprises of a national technology innovation research and development program

机译:分析中小企业的一项国家技术创新研发计划的效率

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摘要

This study analyzes the efficiency of small and medium-sized enterprises (SMEs) of a national technology innovation research and development (R&D) program. In particular, an empirical analysis is presented that aims to answer the following question: “Is there a difference in the efficiency between R&D collaboration types and between government R&D subsidy sizes?” Methodologically, the efficiency of a government-sponsored R&D project (i.e., GSP) is measured by Data Envelopment Analysis (DEA), and a nonparametric analysis of variance method, the Kruskal-Wallis (KW) test is adopted to see if the efficiency differences between R&D collaboration types and between government R&D subsidy sizes are statistically significant. This study’s major findings are as follows. First, contrary to our hypothesis, when we controlled the influence of government R&D subsidy size, there was no statistically significant difference in the efficiency between R&D collaboration types. However, the R&D collaboration type, “SME-University-Laboratory” Joint-Venture was superior to the others, achieving the largest median and the smallest interquartile range of DEA efficiency scores. Second, the differences in the efficiency were statistically significant between government R&D subsidy sizes, and the phenomenon of diseconomies of scale was identified on the whole. As the government R&D subsidy size increases, the central measures of DEA efficiency scores were reduced, but the dispersion measures rather tended to get larger.
机译:这项研究分析了国家技术创新研究与开发(R&D)计划中的中小企业的效率。特别是,提出了一个经验分析,旨在回答以下问题:“研发合作类型之间的效率和政府研发补贴规模之间的效率是否存在差异?”从方法上讲,政府资助的研发项目(即GSP)的效率通过数据包络分析(DEA)进行衡量,并采用非参数方差分析方法,采用Kruskal-Wallis(KW)检验来查看效率差异R&D合作类型之间的差异以及政府R&D补贴规模之间的差异在统计上是显着的。这项研究的主要发现如下。首先,与我们的假设相反,当我们控制政府研发补贴规模的影响时,研发协作类型之间的效率没有统计学上的显着差异。但是,R&D协作类型“ SME-大学-实验室”联合风险管理优于其他类型,DEA效率得分的中位数最大,四分位间距最小。其次,政府R&D补贴规模之间的效率差异在统计学上具有显着性,并且总体上发现了规模不经济现象。随着政府R&D补贴规模的增加,DEA效率得分的中心指标有所降低,但分散指标却趋于扩大。

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