Asia-Pacific Journal of Business Administration,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 25, 2024
Purpose
In
this
research,
we
seek
to
understand
the
effects
of
artificial
intelligence
(AI)
and
knowledge
management
(KM)
processes
in
enhancing
proactive
green
innovation
(PGI)
within
oil
gas
organizations.
It
also
aims
investigate
moderator
role
trust
sustainability
these
relationships.
Design/methodology/approach
This
paper
employs
a
quantitative
analysis.
Surveys
have
been
gathered
from
middle-line
managers
twenty-four
government
organizations
evaluate
perceptions
towards
AI,
KM
processes,
trust,
measures
toward
innovation.
Analytical
statistical
tools
that
were
employed
study,
including
structural
equation
modeling
with
SmartPLSv3.9,
used
analyze
data
examine
measurement
models
study.
Findings
The
study
results
reveal
significant
positive
impact
AI
utilization,
PGI
Furthermore,
turn
out
be
viable
moderators
affecting,
influencing
strength
direction
particular,
higher
levels
more
substantial
commitments
enhance
on
outcomes.
Practical
implications
Understanding
KM,
offers
valuable
insights
for
organizational
leaders
policymakers
seeking
promote
industry.
Thus,
can
increase
efficiency
sustainable
product
development,
process
improvement
environmental
by
using
robust
technologies
effective
systems.
fostering
among
stakeholders
embedding
principles
into
culture
amplify
effectiveness
initiatives
driving
Originality/value
extends
current
assessing
effect
while
accounting
as
moderators.
Utilizing
methods
nuanced
understanding
complex
interactions
between
variables,
thereby
advancing
theoretical
fields
management,
behavior.
Additionally,
identification
specific
mechanisms
contextual
factors
enriches
practical
practitioners
striving
dynamics
complexities
an
AI-driven
era.
Journal of Innovation & Knowledge,
Год журнала:
2024,
Номер
9(2), С. 100481 - 100481
Опубликована: Март 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.
Technological Forecasting and Social Change,
Год журнала:
2024,
Номер
208, С. 123653 - 123653
Опубликована: Авг. 24, 2024
In
today's
data-driven
era,
ubiquitous
concern
about
environmental
issues
pushes
more
startups
to
engage
in
business
model
innovation
that
promotes
environmentally
friendly
technologies.
The
goal
of
these
is
create
technology-based
products
and
services
enhance
sustainability.
this
context,
artificial
intelligence
promises
be
a
key
instrument
create,
capture,
deliver
value.
However,
the
existing
literature
lacks
deep
understanding
how
using
AI
innovate
their
models
achieve
positive
impact.
Therefore,
paper
investigates
green
technology
utilize
from
perspective
for
We
conduct
qualitative,
exploratory
multiple-case
study
Eisenhardt
methodology,
based
on
interview
data
analyzed
qualitative
content
analysis.
derive
five
predominant
manifestations
AI-driven
identify
archetypical
connections
between
dimensions.
Further,
we
establish
three
overarching
associations
among
cases.
doing
so,
contribute
theory
practice
by
providing
deeper
account
attempt
maximize
impact
through
AI.
results
also
highlight
driven
can
support
society
securing
sustainable
future.
