国内外学者对科研投入与企业绩效之间的关系进行了大量研究和实证工作，现有研究多以定性研究为主，分析研发投入与企业绩效之间的关系以及影响这两者关系的直接和间接变量，有少量学者用定量分析的方法表达某个或者某几个变量与这两者关系之间的数学关系，但由于企业绩效及科研成果结果显现的影响变量太多，这种定量分析方法的局限性大。为探索一种对大量因素同时进行定量分析的方法，尝试采用对高纬稀疏数据进行分析，对沪深两市327家制造企业2011~2016年的数据进行分析，以“研发投入增长率>0 & 营业收入增长率>0 & 人均营业收入增长率>0”为分析目标，对影响目标实现的十类74个变量进行定量分析，并得到达到这一分析目标的定量优化规则：当期和上期单位研发人员研发投入、研发人员投入增长率、盈利能力、产品市场竞争度这五个变量处于一定范围内时，分析目标达成概率有较大幅度提升。这一分析结果既可以用于衡量企业研发水平是否达到规模边界，又可作为对企业研发投入行为对企业绩效结果的预判。

Large amount of research and empirical work have been done on the relationship between R&D investment and Enterprise performance by domestic and international scholars. However, most of the existing works focus on qualitative research of their relationship and the direct and indirect interactive effects affecting the relationship, which mainly came up with qualitative conclusion. A small number of scholars applied quantitative analysis to express the mathematical relationship between the relationship between R&D investment and Enterprise performance, but in terms of the large number of influencing factors, this quantitative analysis method has its own limitation. In order to explore a method of quantitative analysis of a large number of factors at the same time, this paper tries to analyze 327 manufacturing enterprises in stock markets of Shanghai and Shenzhen in 2011~2016 by using the analysis method of big data. The analysis target is set as more than zero the growth of R&D input and revenue per capita income to get quantitative optimization rules.

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