阻塞条件下科学基金项目方向规模收益研究

A research on directional returns to scale of science funding program under congestion

目前对于规模收益的研究,一类基于经济学中投入等比例变化假设前提,另一类针对投入不等比例变化,分别研究方向规模收益变化和方向阻塞。本文根据NSFC面上项目资助中项目资助强度与团队规模不成比例变化且存在阻塞的现象,研究阻塞存在条件下的方向规模收益变化,构建了阻塞条件下的方向DEA模型。为避免DEA方向规模收益研究中随机选取方向问题,本研究首先通过模型拟合不同方向阻塞率变化,并以阻塞率最低方向为相对最佳投入方向,并在此基础上确定最佳投入区间。本文以2011年NSFC不同学部的三个学科面上项目进行了实证分析。研究发现:基于阻塞情况下规模收益研究对实践更具指导价值;其次,不同学科提高资助绩效相对最佳的投入方向和资助区间并不一致,未来不同学科进一步提升面上资助绩效策略也不相同。

There are two types of study on returns to scale,one is based on the basic concept of economics that inputs change in proportion,and the other is based on the concept that inputs do not change in proportion,and they study directional returns to scale or directional congestion respectively. Based on the fact that the funding scale and team size are disproportionate in the general program of NSFC with congestion,we construct the directional DEA model under congestion and study the directional returns to scale with congestion. In order to avoid choosing directions randomly in the study of the directional DEA model,we fit congestion rates of different directions and we consider the direction of least congestion rate as the relative best investment direction.Then we determine the optimal investment interval. At last,by taking the general program of three disciplines in 2011 as example,we conduct an empirical analysis and the result shows that the research on returns to scale under congestion has more practical value. We also find different disciplines are different between the relative best investment direction and the optimal investment interval to improve performance and they are also different strategies for further enhancing the performance of the general program of NSFC in the future.