Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Март 2, 2024
Abstract
This
paper
examines
the
coupling
coordination
degree
between
digital
economy
and
green
technology
innovation
in
19
urban
agglomerations
across
China
from
2011
to
2020.
Through
analysis
of
model,
spatial
autocorrelation,
multi-distance
clustering
analysis,
kernel
density
grey
correlation
this
study
uncovers
mechanism
Chinese
agglomerations.
Data
revealed
a
significant
increase
within
However,
there
are
noticeable
imbalances
trend.
Additionally,
distance
highlights
shift
random
distribution
clustered
characteristics.
The
polarization
features
vary
among
each
agglomeration
exhibit
positive
correlation.
Factors
such
as
economic
sustainability,
creative
talent,
policy
support,
impetus,
technological
support
will
affect
China's
Policy
recommendations
proposed
foster
development
economy,
promote
coordinated
growth
beyond
clusters,
ultimately
build
ecological
civilization
that
is
both
intelligent.
Innovation and Green Development,
Год журнала:
2023,
Номер
3(1), С. 100094 - 100094
Опубликована: Авг. 24, 2023
Digital
economy
has
been
the
essential
driving
force
for
green
development
and
energy
transition,
while
role
of
digital
in
renewable
remains
limited.
This
paper
explores
how
alters
China.
Based
on
panel
data
31
provinces
fixed
effects
model,
this
finds
a
positive
association
between
development.
The
exhibits
stronger
impact
hydro
compared
to
wind
solar
energy.
Local
government
intervention
can
enhance
development,
reducing
effect
We
also
find
that
produces
larger
promoting
central
western
with
eastern
provinces.
Journal of Cleaner Production,
Год журнала:
2024,
Номер
451, С. 141946 - 141946
Опубликована: Март 25, 2024
Prior
research
has
primarily
concentrated
on
non-digital
and
process-oriented
methods
for
achieving
carbon
neutrality
(CN)
in
the
context
of
mitigating
climate
change
(CC),
while
potential
digital
technology
(DT)
hardly
been
investigated.
This
study
addresses
this
gap
by
answering
four
questions:
How
are
firms
utilizing
DT
to
achieve
CN?
What
drives
adoption
barriers
that
prevent
risk
mitigation
strategies
can
be
adopted
overcome
these
barriers?
An
inductive
method
using
open-ended
essays
gather
data
from
have
already
implemented
CN.
The
findings
revealed
distinct
dimensions.
Utilization
CN
includes
enhancing
business
value,
managing
one's
footprint,
enabling
smart
solutions,
efficiency.
drivers
adopting
included
driving
growth,
external
pressures,
competitive
advantage,
environmental
consciousness.
Key
financial
barriers,
technological
human
resource
barriers.
Risk
pre-implementation
strategies,
detailed
planning
evaluation,
ensuring
employees'
buy-in
readiness,
stakeholder
engagement.
offers
a
broad-based
foundation
designing
