Environmental Research Communications,
Journal Year:
2024,
Volume and Issue:
6(3), P. 035001 - 035001
Published: Feb. 21, 2024
Abstract
The
digital
transformation
in
developing
countries
is
crucial
determining
whether
environmental
regulations
can
better
facilitate
green
technological
innovation.
This
paper
constructs
a
theoretical
model
to
deduce
the
relationships
among
transformation,
regulations,
and
Empirical
research
conducted
using
two-way
fixed-effects
threshold
regression
approach,
based
on
provincial
panel
data
from
China
spanning
years
2013
2020.
results
indicate
that
regulation
inhibits
However,
by
reducing
cost
pathways,
promote
efficiency
of
innovation
under
regulation.
moderating
effect
exhibits
nonlinear
characteristic.
Regarding
dimensions
level
investment
shows
no
threshold,
while
both
application
scale
integration
exhibit
effects.
Presently,
China,
effectively
incentivizes
Therefore,
increasing
investment,
advancing
applications,
fostering
are
inevitable
choices
drive
pressure
Managerial and Decision Economics,
Journal Year:
2024,
Volume and Issue:
45(5), P. 2727 - 2738
Published: March 6, 2024
Abstract
Artificial
intelligence
(AI)
plays
a
crucial
role
in
addressing
resource
and
environmental
constraints
achieving
sustainable
economic
social
development.
This
study
examines
the
impact
mechanisms
of
AI
on
green
low‐carbon
transformation
enterprises
using
sample
companies
listed
Shanghai
Shenzhen
stock
exchanges
from
2009
to
2021.
The
research
findings
indicate
that
has
capability
effectively
mitigate
corporate
carbon
emissions
(CCE)
enhance
level
innovation
(GI)
enterprises.
Mechanism
analysis
reveals
energy
consumption
mediating
relationship
between
CCE.
Heterogeneity
inhibitory
effect
CCE
is
more
pronounced
private
non‐heavy
polluting
industries.
However,
GI
greater
state‐owned
heavy‐polluting
sheds
light
influence
enterprises,
as
well
its
transmission
mechanisms.
It
provides
theoretical
empirical
insights
for
promoting
GI,
reducing
emissions,
improving
efficiency
Frontiers in Psychology,
Journal Year:
2023,
Volume and Issue:
14
Published: Nov. 3, 2023
Digital
transformation
has
become
an
important
engine
for
economic
high-quality
development
and
environment
high-level
protection.
However,
green
total
factor
productivity
(GTFP),
as
indicator
that
comprehensively
reflects
environmental
benefits,
there
is
a
lack
of
studies
analyze
the
effect
digital
on
heavily
polluting
enterprises'
GTFP
from
micro
perspective,
its
impact
mechanism
still
unclear.
Therefore,
we
aim
to
study
mechanism,
explore
heterogeneity
impact.We
use
Chinese
A-share
listed
enterprises
in
industry
data
2007
2019,
measure
enterprise
using
text
analysis,
GML
index
based
SBM
directional
distance
function,
investigate
GTFP.Digital
can
significantly
enhance
GTFP,
this
finding
holds
after
considering
endogenous
problem
conducting
robustness
tests.
by
promoting
innovation,
improving
management
efficiency,
reducing
external
transaction
costs.
The
improvement
role
more
obvious
samples
non-state-owned
enterprises,
non-high-tech
industries,
eastern
region.
Compared
with
blockchain
technology,
artificial
intelligence
cloud
computing
big
technology
application
improve
GTFP.Our
paper
breaks
through
limitations
existing
research,
which
not
only
theoretically
enriches
literature
related
but
also
practically
provides
policy
implications
continuously
facilitating
their
development.
