Does provincial green governance promote enterprise green investment? Based on the perspective of government vertical management
Journal of Cleaner Production,
Год журнала:
2023,
Номер
396, С. 136519 - 136519
Опубликована: Фев. 20, 2023
Язык: Английский
Evaluation of the environmental efficiency of China’s power generation industry considering carbon emissions and air pollution: an improved three-stage SBM-SE-DEA model
Environment Development and Sustainability,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 22, 2025
Язык: Английский
Navigating the Path to Sustainable Development: China's Revolution in Renewable Energy Through Technological Innovation and Geopolitical Risk Management
Renewable Energy,
Год журнала:
2025,
Номер
unknown, С. 122598 - 122598
Опубликована: Фев. 1, 2025
Язык: Английский
Does Digital Transformation Promote Green and Low-Carbon Synergistic Development in Enterprises? A Dynamic Analysis Based on the Perspective of Chinese Listed Enterprises in the Heavy Pollution Industry
Sustainability,
Год журнала:
2023,
Номер
15(21), С. 15600 - 15600
Опубликована: Ноя. 3, 2023
Digital
transformation
has
become
essential
in
promoting
and
upgrading
enterprise
elements
reshaping
the
market’s
competitive
landscape.
However,
whether
digital
can
further
promote
green
low-carbon
synergistic
development
is
still
being
determined.
Using
data
from
2008
to
2014
matched
between
A-share
listed
enterprises
China’s
heavily
polluting
industries
industrial
pollution
emission
database
(robustness
tests
were
used
city
panel
2013
2019
overcome
timeliness
of
enterprise-level
data),
we
measured
total
factor
productivity,
carbon
efficiency,
joint
reduction
efficiency
companies.
We
examined
dynamic
impact
corporate
on
reduction.
The
empirical
results
show
that
(1)
inhibits
enterprise’s
all-green
short
term
but
promotes
them
long
term.
improve
these
three
efficiencies
by
enhancing
technology
innovation
ability
optimizing
allocation
efficiency.
(2)
A
heterogeneity
analysis
found
that,
external
environment,
increase
environmental
regulation
enhances
efficiencies;
internal
improvement
competitiveness
products
strengthens
promotion
(3)
Further
research
shows
run,
effect
enterprises.
This
instructive
for
Chinese
achieve
green,
production.
Язык: Английский
Measurement of green innovation efficiency in Chinese listed energy-intensive enterprises based on the three stage Super-SBM model
International Review of Economics & Finance,
Год журнала:
2024,
Номер
unknown, С. 103819 - 103819
Опубликована: Дек. 1, 2024
Язык: Английский
Assessing the Static and Dynamic Efficiency of Digital Economy in China: Three Stage DEA–Malmquist Index Based Approach
Sustainability,
Год журнала:
2023,
Номер
15(6), С. 5270 - 5270
Опубликована: Март 16, 2023
The
digital
economy,
a
new
economic
form,
has
become
an
essential
development
engine
in
various
countries.
Recently,
less
research
been
conducted
on
the
efficiency
of
with
majority
studies
instead
concentrating
industrial
size
economy.
Therefore,
to
quantify
and
analyze
China’s
economy
from
2013
2020
both
static
dynamic
perspective,
this
utilized
three-stage
DEA
model
Malmquist
index.
findings
demonstrated
that
after
excluding
external
environmental
factors,
scale
value,
integrated
technical
pure
value
all
significantly
increased.
This
confirmed
factors
uniquely
influence
varies
by
location,
eastern
region
tending
perform
best,
central
worst.
decomposition
results
positive
growth
trend
is
primarily
due
technological
advancement.
Overall,
there
lot
room
for
Each
province
city
should
combine
their
own
capabilities
accelerate
construction.
Язык: Английский
Evaluation of the environmental efficiency of China's power generation industry considering carbon emissions and air pollution: An improved three-stage SBM-SE-DEA model
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 16, 2024
Abstract
Evaluating
and
enhancing
the
environmental
efficiency
of
power
generation
industry
is
an
effective
approach
for
addressing
challenges
climate
change
pollution.
Considering
influence
external
factors
stochastic
factors,
this
paper
proposes
improved
three-stage
slack-based
measure
with
superefficiency
data
envelopment
analysis
(SBM-SE-DEA)
model
to
evaluate
in
China’s
30
provincial
regions
during
2015–2021.
The
integrates
DEA
model,
SBM-DEA
SE-DEA
while
accounting
undesirable
outputs
such
as
carbon
emissions
air
pollutants.
results
show
that
(1)
a
high
proportion
renewable
energy
demonstrate
best
when
considering
constraints
from
However,
first
stage
are
evidently
overestimated
due
factors.
(2)
Rational
adjustments
economic
development
level,
structure,
industrial
structure
play
positive
role
improving
efficiency.
resource
endowment
does
not
yield
expected
results.
Additionally,
provinces
higher
electricity
often
bear
greater
pressure
(3)
third
exhibited
stable
trend
driven
by
internal
except
Northeast
Central-South
regions,
most
still
experienced
overestimation
stage.
Thus,
optimizing
promoting
restructuring,
strengthening
interregional
cooperation
coordination
imperative.
Язык: Английский