SHS Web of Conferences,
Год журнала:
2024,
Номер
208, С. 01013 - 01013
Опубликована: Янв. 1, 2024
This
paper
deeply
discusses
the
background,
concept
and
path
of
enterprise
digital
transformation,
takes
Alibaba
Group
as
a
typical
case
for
detailed
analysis.
In
context
economy,
enterprises
realize
comprehensive
transformation
economic
model
through
digitalization,
networking
intelligent
technologies,
which
promotes
wide
application
cloud
computing,
big
data
analysis,
artificial
intelligence
Internet
Things.
Digital
requires
companies
to
fundamentally
reshape
their
core
business
processes,
management
systems,
models
service
approaches
in
response
rapidly
changing
market
environment.
As
has
successfully
achieved
continuous
innovation
leadership
by
building
platform
ecosystem,
diversified
layout,
analysis
globalization
strategy.
summarizes
basic
principles
strategies
emphasizes
importance
data-driven
decision-making,
culture,
organizational
structure
optimization
technology
process,
provides
valuable
experience
reference
other
enterprises’
transformation.
Advances in logistics, operations, and management science book series,
Год журнала:
2025,
Номер
unknown, С. 83 - 110
Опубликована: Фев. 7, 2025
This
chapter
focuses
on
investigating
digital
intelligence
within
supply
chain
management,
with
a
focus
economic
diversification
and
sustainability.
The
importance
of
technology
innovation
in
improving
the
efficiency
effectiveness
system
is
widely
studied
analyzed.
However,
intricated
relationships
subsequent
impact
sustainability
need
more
form
identification
key
enablers,
barriers
research
lacunas.
study
addresses
this
gap
existing
literature
by
focussing
an
extensive
scoping
review
related
to
area.
For
this,
209
documents
were
selected
reviewed
through
framework-based
process.
findings
resulted
conceptual
framework
detailing
different
aspects
topic
future
propositions
domain
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Апрель 12, 2025
As
a
critical
aspect
of
the
industry
4.0
era,
application
artificial
intelligence
(AI)
is
significant
to
environmental
governance.
It
serves
as
crucial
driving
force
in
assisting
enterprises
transition
toward
low-carbon
practices.
This
paper
examines
China's
A-share
industrial
from
2011
2022,
constructs
and
trains
word
vector
model
extract
AI-related
terms,
impact
AI
applications
on
carbon
emission
intensity
these
investigated.
The
findings
reveal
that
enhancing
level
can
effectively
decrease
intensity.
Specifically,
1%
increase
leads
reduction
0.0395%
Further
analysis
indicates
diminish
their
by
optimization
supply
chain
green
technology
innovation.
Heterogeneity
suggests
utilizing
beneficial
for
reducing
manufacturing,
high-tech,
high-pollution
enterprises.
results
this
study
enrich
micro-level
research
relationship
between
intensity,
offering
valuable
insights
aiming
achieve
sustainable
development.
Meditari Accountancy Research,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 17, 2025
Purpose
Risk
management
(RM)
functions
are
expected
to
become
more
involved
in
environmental
and
sustainability
activities,
yet
a
serious
lack
of
quantitative
evidence
exists
on
these
links.
This
study
aims
explore
the
direct
link
between
RM
as
one
aspect
internal
audit
green
process
innovation
(GP),
performance
(SP)
indirect
audits
SP
through
mediation
GP.
The
also
explores
whether
impact
GP
strengthens
with
emergence
transformational
leadership
(GT)
knowledge
sharing
(GK).
Design/methodology/approach
Primary
data
were
collected
survey
opinions
197
managers
Vietnamese
manufacturing
firms
analyzed
by
partial
least
squares
structural
equation
modeling.
Findings
results
revealed
interesting
findings.
First,
driving
force
for
sector
strengthen
SP.
Second,
relationship
is
strengthened
when
own
GT
well
promote
GK.
Third,
like
bridge
transform
value
toward
result
an
important
basis
role
identifying
risks,
thereby
enhancing
sustainable
development.
encourage
GK
exert
positive
effects
catalysts
improve
influence
Originality/value
contributes
significantly
existing
literature
audits,
SP,
moderating
roles
this
relationship.
Furthermore,
few
studies
that
has
successfully
investigated
mediating
function
effect
