Research on the Spatio-Temporal Evolution and Impact of China’s Digital Economy and Green Innovation
Chunshan Zhou,
No information about this author
Xiaoli Wei,
No information about this author
Xiangjun Dai
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et al.
Land,
Journal Year:
2025,
Volume and Issue:
14(3), P. 633 - 633
Published: March 17, 2025
It
is
of
great
significance
to
study
the
impact
China’s
digital
economy
on
green
innovation
under
present
conditions.
In
this
work,
panel
data
were
used,
and
research
tools
such
as
entropy
method,
Markov
chain
with
a
spatial
probability
transition
matrix,
Durbin
model
applied
analyze
temporal
evolution
in
287
Chinese
cities
from
2011
2021,
exploring
influence
innovation.
The
results
show
that
exhibited
an
upward
trend.
There
was
basic
pattern
consisting
“high
levels
east
low
west”
regarding
innovation,
aggregation
types
primarily
being
“HH”
“LH”.
Moreover,
are
relatively
stable,
neighboring
areas
influencing
local
changes.
has
significant
promotional
effect
well
spillover
effects;
differing
influences
over
time
can
be
used
categorize
into
four
groups,
most
falling
within
first
two
categories.
Based
these
findings,
relevant
countermeasures
proposed,
seeking
further
enhance
role
promoting
This
work
provides
basis
policy
suggestions
contribute
continuous
improvements
leveraging
effects
former
latter.
Language: Английский
Can Government Procurement Drive Corporate Green Technology Innovation? Evidence from Chinese Listed Companies
Evaluation and Program Planning,
Journal Year:
2025,
Volume and Issue:
unknown, P. 102592 - 102592
Published: March 1, 2025
Language: Английский
Generative AI and Labour Market Research Interest Framework
Adriana Grigorescu,
No information about this author
Florina Joita
No information about this author
HOLISTICA – Journal of Business and Public Administration,
Journal Year:
2024,
Volume and Issue:
15(2), P. 1 - 14
Published: Dec. 1, 2024
Abstract
This
study
investigates
the
intersection
between
generative
artificial
intelligence
(GenAI)
and
labour
market
by
developing
a
comprehensive
framework
to
analyse
current
state
of
scientific
interest
in
this
emerging
topic.
The
research
employs
quantitative
methodology,
using
comparatively
implemented
bibliometric
analysis,
thus
examining
two
major
databases,
Web
Science
Scopus
with
aim
provide
deeper
understanding
academic
landscape.
focuses
on
database
largest
number
relevant
papers,
providing
insight
into
concentration
activity
field,
both
terms
evolution
over
time,
trends,
countries,
keywords
authors
highest
impact.
reveals
significant
gap
literature
concerning
impact
GenAI
market,
only
one
small
percentage
papers
addressing
Key
findings
include
rise
publications
post-2018,
particularly
from
USA,
Russia
China,
lack
developed
networks.
article
concludes
further
exploration
implication
is
needed,
potential
directions
for
future
research.
Language: Английский