Abstract

According to the connotation and structure of science and technology resources and some relevant data of more than 286 cities at prefecture level and above during 2001–2010, using modified method—Data Envelopment Analysis (DEA), science and technology (S&T) resource allocation efficiency of different cities in different periods has been figured out, which, uncovers the distributional difference and change law of S&T resource allocation efficiency from the time-space dimension. Based on that, this paper has analyzed and discussed the spatial distribution pattern and evolution trend of S&T resource allocation efficiency in different cities by virtue of the Exploratory Spatial Data Analysis (ESDA). It turned out that: (1) the average of S&T resource allocation efficiency in cities at prefecture level and above has always stayed at low levels, moreover, with repeated fluctuations between high and low, which shows a decreasing trend year by year. Besides, the gap between the East and the West is widening. (2) The asymmetrical distribution of S&T resource allocation efficiency presents a spatial pattern of successively decreasing from Eastern China, Central China to Western China. The cities whose S&T resource allocation efficiency are at higher level and high level take on a cluster distribution, which fits well with the 23 forming urban agglomerations in China. (3) The coupling degree between S&T resource allocation efficiency and economic environment assumes a certain positive correlation, but not completely the same. The differentiation of S&T resource allocation efficiency is common in regional development, whose existence and evolution are directly or indirectly influenced by and regarded as the reflection of many elements, such as geographical location, the natural endowment and environment of S&T resources and so on. (4) In the perspective of the evolution of spatial structure, S&T resource allocation efficiency of the cities at prefecture level and above shows a notable spatial autocorrelation, which in every period presents a positive correlation. The spatial distribution of S&T resource allocation efficiency in neighboring cities seems to be similar in group, which tends to escalate stepwise. Meanwhile, the whole differentiation of geographical space has a diminishing tendency. (5) Viewed from LISA agglomeration map of S&T resource allocation efficiency in different periods, four agglomeration types have changed differently in spatial location and the range of spatial agglomeration. And the continuity of S&T resource allocation efficiency in geographical space is gradually increasing.

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