6.2.5.1 Factors Functioning in the Same Pattern
The impacts of indicators concerning regional economy conditions and science and
technology development on university research efficiency are similar between
NEAM and HSS disciplines. In this chapter, we choose the following variables to
measure regional economic conditions:if Capital cities in the province, if Eastern
211Us, if Central 211Us, if JU, if HSZU, PerGDP, SciTech, HighTech.It can be
found that, to NEAM disciplines, although the universities located in rich or
developed areas tend to be more efficient, but the correlation between per capital
GDP and efficiency is negative. And to HSS disciplines, the impact is also trivial,
and the association between economy conditions and research efficiency is not very
clear. It should pay more attention to coordinate between university research input
increases and efficiency improvement, and make more efforts to improve the uni-
versity innovation capacities.
“MOE”variable is used to measure the type of a university, more specifically, it
reflects the major funding body and institutional characteristics of a university. To
both NEAM and HSS disciplines, those MOE-administered universities are usually
scored lower in DEA results than other universities, although the differences are not
statistically significant. As we mentioned previously, those MOE universities are in
a less competitive environment, limiting their motivations to improve their research
efficiency.
According to theories in industrial economics, cluster effect appears where
inter-university cooperation and sharing of resources exert positive externality and
lower the costs. In theory, this effect would be an important channel for 211Us to
improve their research efficiency, especially those regions where more 211Us
gathered around. However, in our Tobit models, the number of 211Us or 985Us in a
particular province has no significantly positive impact on research efficiency. The
Chinese universities have the duty to enhance inter-university cooperation and
communication, to share their facilities and build a mutually beneficial research
networks.
In our Tobit models, we introduce the variable of“InterEx”to measure the
internationalization degree of university research activities. However, the results do
not meet our expectations, in both NEAM and HSS samples,“InterEx”has trivial
impact on research efficiency with no statistical significance, and in some models,
and it even has negative effect. This implies that to Chinese universities, interna-
tional cooperation and communication should go beyond the quantity aspects,
namely the times of international conferences or visits, to reach the quality aspects
that could enhance in-depth academic collaborations and improve research quality
and efficiency.
Among the demographic variables,“FePerc”has negative impact on research
efficiency. This conclusion is consistent with other empirical evidences from Porter
and Toutkoushian ( 2006 ) or Wolszczak-Derlacz and Parteka ( 2011 ). There are
many reasons which might result into this conclusion. First, gender related studies
show that females are better at language and speaking, which implies that female
teachers might perform better in teaching than their male peers. And in most
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