Development of a Catastrophe Model to Assess the Allocation Efficiency of Competitive Sports Resources in China - Advanced Research on Computer Education, Simulation and Modeling - page 402

Table 1. Summary description of catastrophe models [8]

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2.4 Score Transformation

The synthetic values of catastrophe assessment are generally high and the differences
are not obvious and it is difficult to determine the actual level directly using the re-
sults obtained by catastrophe assessment [9-10]. Usually, the synthetic values of
multi-attribute assessment are divided into five grades and the allocation efficiency of
competitive sports resources accordingly can be divided into five grades: 0.2 (low),
0.4 (relatively low), 0.6 (middle), 0.8 (relatively high) and 1.0 (high). The problem is
how to find a way to transform the results obtained by catastrophe assessment into the
ordinary-used synthetic values. This paper used the method proposed by Su et al.
(2011) [2] for score transformation as follows: Suppose the relative membership de-
gree for all indices equals n, then the relative membership degree for higher level
indices should also equal n. Consequently, the synthetic membership degree can be
obtained by applying suitable catastrophe model. The catastrophe value for each se-
cure grade was thus calculated (Table 2).

Table 2. Corresponding values between assessment results of catastrophe model and ordinary-
used values at different levels

Low Relatively

low

Middle Relatively

high

High

Relative membership degree
obtained by catastrophe model

0.799-
0.879

0.879-
0.930

0.930-
0.969

>0.969

<0.799

Corresponding ordinary-used <0.2 0.2-0.4 0.4-0.6 0.6-0.8 >0.8

values

3 Results and Discussion

Spatial patterns of allocation efficiency of competitive sports resources in China be-
tween 2003 and 2008 were displayed in Fig.1. The allocation efficiency of competi-
tive sports resources in China generally descended from east to west. The allocation
efficiencies of the eastern coastal regions were significantly higher than those of the
central and western regions. Specifically, Guangdong, Shandong, Jiangsu, Beijing and