An empirical study of the quantification of subsidy quota for science and technology planning projects

Science Research Management ›› 2015, Vol. 36 ›› Issue (12) : 146-154.

Huang Huiling

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Abstract

A research on the quantification of subsidy quota for sci-tech planning project is carried out in this paper,because in the management system there was fewer criteria to quantify scientifically and reasonably the subsidy quota of sci-tech planning projects. In the research, the SMART Method and Delphi Method are applied, various fuzzy mathematics methods such as Outlier Correction, Normalization, Empowerment Statistics, Result Adjustment and so on are also utilized to construct a subsidy quota quantification model of sci-tech planning project, and an empirical study is implemented. The proposed model of this research can quantify the subsidy amount of sci-tech planning project. By use of adjusting method, a balance can be obtained between the finance fund value of investment budget for sci-tech innovation research development and the subsidy amount of established project, in the meantime the funding guide on sci-tech innovation research-development fund and the sci-tech planning set by sci-tech management department can be embodied. The research achievement has already been adopted by the sci-tech management department, which can get rid sci-tech planning management staff of the puzzle caused by short of scientific quantification criterion in the fund allocation, and promote transformation of management mode of sci-tech innovation research-development fund from excessive dependency on subjective judgment to scientific and normative decision-making, and effectively improve the scientificity, normalization, and macroscopic controllability of the sci-tech planning management, thus it is a concrete practice of current sci-tech planning management reform.

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sci-tech project / subsidy quota / index system / quantification method

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Huang Huiling. An empirical study of the quantification of subsidy quota for science and technology planning projects[J]. Science Research Management. 2015, 36(12): 146-154

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