Assessing the development of green innovation in China through patent evolution: the hallmark of government policy and private enterprises
International Journal of Emerging Markets,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Feb. 16, 2024
Purpose
The
purpose
of
this
paper
is
to
develop
a
comprehensive
overview
green
innovation
(GI)
in
China,
which
carried
out
by
reviewing
the
evolution
GI
from
2000
2019,
and
main
type
technology,
actors
localizations.
When
appropriate,
compared
non-GI.
Design/methodology/approach
study
uses
patent
data
European
Patent
Office
database
(PATSTAT);
these
are
processed
map
trends
identify
contributors
location
such
innovation.
findings
then
discussed
complemented
with
academic
literature.
Findings
Key
reveal
an
increasing
divergence
between
nongreen
after
2008
crisis.
It
also
observed
that
solar
energy
appears
be
component
shift
photovoltaic
thermal
2008.
Other
areas,
as
waste
management,
greenhouse
gases
capture
climate
change
adaptation,
less
innovative.
Companies
play
essential
role
development
all
types
In
terms
location,
patents
mainly
filed
China’s
three
megacities.
highlights
significant
Chinese
state,
led
policies
shaping
trajectories
forms
GI.
Originality/value
This
expands
knowledge
on
highlighting
its
specificities
key
actors.
provides
reader
picture
realities.
results
can
therefore
used
improve
understanding
China
facilitate
formulation
new
research
questions.
Language: Английский
Analysis of the spatiotemporal evolution characteristics and policy factors of eco-innovation efficiency in Chinese urban agglomerations
Ecological Indicators,
Journal Year:
2024,
Volume and Issue:
163, P. 112106 - 112106
Published: May 15, 2024
These
studies
can't
explain
the
reality
of
China
well,
which
researched
on
spatiotemporal
changes
and
influencing
factors
ecological
innovation
efficiency
in
a
single
urban
agglomeration.
This
study
describes
evolutionary
characteristics
eco-innovation
eight
major
agglomerations
based
SE-U-SBM
(Super-Efficiency
Slacks-Based
Measure)
method
sequential
DEA,
Dagum
Gini
coefficient,
kernel
density
estimation,
coefficient
variation
method.
The
SDID
DID
models
were
constructed
to
identify
policy
causes
their
characteristics.
results
reveal
that
(1)
temporal
spatial
evolution
is
"U"
inverted
shapes
with
inflection
point
occurring
2012.
(2)
Among
agglomerations,
rest
them
have
"U"-shaped
trend
except
for
"N"-shaped
Harbin-Changchun
(HC)
Guanzhong
(GZ).
convergence
strongest
Yangtze
River's
midstream
(UMYR)
Beijing-Tianjin-Hebei
(BTH)
weakest
River
Delta
(YRD),
Guangdong-Hong
Kong-Macao
(GHM),
Chengdu-Chongqing
(CC).
(3)
Policies
such
as
Low-Carbon
City
Pilot
(LCCP),
National
Demonstration
Circular
Economy
(CEDC),
Ecological
Compensation
(ECP)
caused
increase
after
Additionally,
Civilization
Pioneer
Zone
(ECDAP)
LCCP
can
HC
GZ.
Improvements
UMYR
Central
Plains
(CP)
depend
ECP
implementation.
(4)
ECDAP
CEDC
agglomerations.
CP,
GZ,
depends
policies
other
than
CEDC.
strong
BTH
was
due
Language: Английский