Sustainability,
Journal Year:
2024,
Volume and Issue:
16(23), P. 10472 - 10472
Published: Nov. 29, 2024
The
imbalance
in
the
development
of
digital
economy
hinders
effective
formation
economies
scale
and
synergies,
thereby
constraining
high-quality
growth
China’s
overall
economy.
This
study
employs
panel
data
from
31
Chinese
provinces
spanning
2013
to
2021,
using
exploratory
spatial
analysis
(ESDA)
Geodetector
investigate
differentiation
characteristics
driving
factors
findings
reveal
a
gradient
pattern
development,
decreasing
east
central,
west,
northeast
China,
with
high-value
clusters
concentrated
spatially
locked
eastern
region.
Analysis
gravity
center
standard
deviation
ellipse
indicates
distribution
dynamic
“longitudinal
clustering
lateral
expansion”,
significant
“westward
migration”
center.
Spatial
disparities
are
driven
by
both
inter-regional
intra-regional
differences,
discrepancies
between
region
other
three
regions
being
primary
source
variation.
identifies
human
capital,
foreign
direct
investment,
R&D
expenditure
as
main
contributing
spatial-temporal
Last,
offers
policy
recommendations
regarding
infrastructure,
resource
allocation,
institutional
mechanisms
promote
balanced
China.
Computational Urban Science,
Journal Year:
2025,
Volume and Issue:
5(1)
Published: April 11, 2025
Abstract
The
digital
economy
drives
economic
growth
and
regional
competitiveness.
Understanding
the
evolution
of
county-level
economies
is
essential
for
transformation,
upgrading,
long-term
development.
Traditional
assessment
methodologies
have
several
shortcomings
representing
county
economy,
especially
data
availability
reliability.
In
this
paper,
we
develop
a
multi-scale
analytic
framework
using
complex
network
indicators
including
average
clustering
coefficient,
$$k$$
k
-core,
weighted
degree
at
macro,
meso,
micro
scales.
allows
us
to
establish
enterprise
investment
from
Fujian
Province,
China,
study
development
2000
2021.
outcomes
are:
1)
economy's
scale
connection
in
grew
stages,
with
expansion
aligning
concept
of"the
rich
leading
whole,
whole
poor."2)
interconnectivity
hot
zones,
which
made
up
less
than
9%
counties,
had
major
impact
on
gotten
stronger.
Investment
linkage
control
increased
24.64%
41.56%
2021,
focus
areas
shifted
outside
province
within
province.
3)
Over
time,
top
six
key
counties
increasingly
controlled
more
30%
total
quota.
when
2%
60%
investment,
developmental
imbalances
became
important.
Journal of Economics Research and Policy Studies,
Journal Year:
2025,
Volume and Issue:
5(1), P. 147 - 159
Published: April 24, 2025
This
study
examines
the
influence
of
tourism
development
and
Information
Communication
Technology
(ICT)
on
regional
competitiveness
across
Indonesian
provinces.
Using
cross-sectional
data
from
all
provinces
in
2022,
research
employs
multiple
regression
analysis
with
comprehensive
classical
assumption
testing
to
assess
these
relationships.
Data
was
sourced
three
national
institutions:
Regional
Competitiveness
Index
BRIN,
Ministry
Tourism
Creative
Economy,
ICT
Central
Bureau
Statistics.
The
reveals
significant
positive
relationships
between
both
predictors
competitiveness,
emerging
as
stronger
predictor.
findings
demonstrate
that
investing
infrastructure
gain
substantial
competitive
advantages.
These
results
provide
important
implications
for
policymakers,
suggesting
an
integrated
approach
incorporating
initiatives
might
yield
optimal
enhancing
competitiveness.
contributes
understanding
dynamics
developing
economies,
particularly
context,
offering
valuable
insights
policy
formulation
strategic
planning
development.
Sustainability,
Journal Year:
2025,
Volume and Issue:
17(9), P. 3828 - 3828
Published: April 24, 2025
Life
cycle
carbon
emissions
from
the
construction
industry
(CE)
have
a
profound
impact
on
China’s
“dual
carbon”
goals,
with
significant
posing
severe
challenges
to
environment.
In
this
paper,
four
prediction
models
were
trained
and
compared,
optimal
model,
Genetic
Algorithm
Optimized
BP
Neural
Network
(GA-BP),
was
finally
selected
for
multi-scenario
of
CE.
Firstly,
study
performs
comprehensive
accounting
indicator
analysis
CE
over
its
entire
life
cycle.
addition,
paper
further
conducts
spatial
differentiation
Subsequently,
parameter
conducted
using
an
improved
STIRPAT
followed
by
LMDI
factor
decomposition
based
model.
Finally,
model
performance
verified
three
evaluation
metrics:
coefficient
determination
(R2),
mean
absolute
error
(MAE),
percentage
(MAPE).
The
results
indicate
that
(1)
in
emission
assessment,
reached
peak
42.52
t
per
capita
annually
8.90
CO2/m2
unit
area;
(2)
year-end
resident
population
has
greatest
influence
CE,
other
related
variables
also
contributing
positively;
(3)
GA-BP
outperforms
models,
R2
increasing
0.0435
0.0981,
MAE
reducing
63%
76%,
MAPE
decreasing
23%
68%.
