Studies and practices in China unanimously ignored the additivity of
government performance evaluation index. In the present evaluation systems,
the total score of government performance is added by simply putting the
indexes values (numbers) together. Neither the researchers nor the
practitioners pay any attention to the reality that the government
performance evaluation indexes belong to high attribute dimensions, and they
cannot be added directly. To process these high attribute indexes of
government performance evaluation, we have to follow their clustering
features and reduce dimensions to convert high attribute dimensions to low
attribute dimensions. In this study, binary state variable was adopted to
reduce dimensions. We reduce the dimension of the performance evaluation
index by 4 steps: (1) separating the hazy description of into measurable
sub-indexes; (2) treating each sub-index as a binary variable by judging it
false or true; true and false are respectively indicated as 1 and 0 in the
statistical software or mathematical language; (3) using the methods of
aggregate degree, aggregate vector, and set theory to make the sub-indexes
aggregate in a same class; (4) nondimensionalising the values of sub-indexes
and realizing the additivity of all the sub-indexes.
Realizing the government performance evaluation index additivity in China: A probe into the aggregate degree and additivity of evaluation index
