Technological and Economic Development of Economy,
Journal Year:
2025,
Volume and Issue:
0(0), P. 1 - 32
Published: Feb. 12, 2025
The
aim
of
this
paper
is
to
explore
the
technological
innovation
mechanism
by
which
digital
transformation
(DT)
influences
total
factor
productivity
(TFP).
We
take
Chinese
listed
firms
from
2007
2020
as
research
samples,
and
con-
tribute
above
goals
based
on
fixed-effect
models,
instrumental
variables,
mediation
effect,
moderating
effect
models.
It
has
been
found
that
(1)
while
DT
contributes
positively
productivity,
enhancement
TFP
in
current
primarily
attributed
artificial
intelligence
(AI)
technology
rather
than
other
techno-
logical
innovation.
(2)
From
an
innovation-directed
perspective,
impact
may
be
offset
forms
innovation,
such
green
energy
technology.
Specifically,
non-AI
direction
not
align
with
implications
DT.
(3)
Intellectual
property
protection
impedes
constrains
deployment
AI
Conversely,
business
strategic
radicalism
corporate
intangible
asset
have
yielded
favorable
outcomes.
This
study
only
verifies
channel
for
enhancing
mainly
stems
technology,
but
also
implies
might
exert
a
negative
technologies.
First
published
online
12
February
2025
Managerial and Decision Economics,
Journal Year:
2024,
Volume and Issue:
45(4), P. 2321 - 2335
Published: Feb. 17, 2024
Abstract
In
a
highly
informative
society,
digital
transformation
has
become
new
driving
force
to
enhance
enterprise
competitiveness
and
promote
high‐quality
economic
development.
This
paper
examines
the
impact
of
on
firms'
resource
allocation
efficiency
using
sample
Chinese
A‐share
listed
companies
in
manufacturing
industry
from
2007
2019.
The
research
findings
are
as
follows:
significantly
improved
efficiency.
Mechanisms
suggest
that
enhances
by
attracting
external
financing,
both
equity
debt
financing.
Furthermore,
contribution
is
more
pronounced
eastern
region,
high‐tech
industries,
non‐state‐owned
enterprises.
provides
evidence
for
exploring
effective
paths
improve
perspective.
It
significant
accelerating
achieving
cost
reduction
enhancement.
Journal of Innovation & Knowledge,
Journal Year:
2024,
Volume and Issue:
9(2), P. 100481 - 100481
Published: March 23, 2024
Knowledge
creation
is
the
foundation
for
indigenous
innovation
in
manufacturing
enterprises;
however,
effects
of
digital
transformation
on
knowledge
are
still
not
well
understood.
Nonaka
put
forward
model
creation,
which
includes
four
processes:
socialization,
externalization,
combination,
and
internalization,
known
as
famous
SECI
model.
Based
model,
this
study
analyzes
processes,
using
panel
data
from
Chinese
listed
enterprises
2007
to
2020.
The
provides
several
novel
findings.
First,
positively
affects
all
with
combination
capability
being
particularly
notable.
Second,
digitalization
inputs
externalization
insignificant
but
exert
a
negative
impact
socialization
internalization.
Third,
heterogeneity
analysis
reveals
that
facilitating
effect
more
significant
state-owned
large
enterprises.
Moreover,
it
primarily
acts
"cherry
top,"
significantly
benefiting
already
have
strong
capabilities.
A
low
level
technology
development
region
where
an
enterprise
located
will
inhibit
role
promoting
socialization.
Furthermore,
culture
regional
environments
play
positive
moderating
roles.
This
contributes
further
understanding
how
enterprises'
activities.
