TITLE:
Research on the Influence of Industrial Upgrading on Independent Innovation Ability in China—Based on Inter-Provincial Panel Data
AUTHORS:
Tianhao Fu, Pengbo Shao
KEYWORDS:
Industrial Upgrading, Independent Innovation, Principal Component Analysis, Cluster Analysis, Panel Data Model
JOURNAL NAME:
Open Journal of Business and Management,
Vol.7 No.4,
October
18,
2019
ABSTRACT: According to the different levels of economic development in China’s provinces,
this paper uses principal component analysis to establish a comprehensive index
system for evaluating the level of economic development, and then uses cluster
analysis to classify 31 provinces in China into economically developed regions,
economically relatively developed regions, and economically underdeveloped
regions. Next, based on the results of regional division, this paper uses the
fixed panel data model to empirically analyze the impact of national and
regional industrial upgrading on independent innovation capability, and the
model is tested for robustness by systematic generalized moment estimation. The
results show that: Industrial upgrading can effectively promote the improvement
of national and regional independent innovation capabilities. On the whole, the
industrial upgrading transferred to the tertiary industry can effectively
promote the improvement of independent innovation capability; moreover, in both
economically developed regions and economically
underdeveloped regions, the process of industrial upgrading to the secondary
and tertiary industries can effectively promote the improvement of
regional independent innovation capabilities. Finally, according to the results
of empirical analysis, the paper puts forward policy enlightenment of
industrial upgrading and suggestions on improving independent innovation
ability.