Management Decision,
Год журнала:
2024,
Номер
unknown
Опубликована: Июнь 12, 2024
Purpose
This
study
investigates
the
profound
impact
of
artificial
intelligence
(AI)
capabilities
on
decision-making
processes
and
organizational
performance,
addressing
a
crucial
gap
in
literature
by
exploring
mediating
role
speed
quality.
Design/methodology/approach
Drawing
upon
resource-based
theory
prior
research,
this
constructs
comprehensive
model
hypotheses
to
illuminate
influence
AI
within
organizations
speed,
decision
quality,
and,
ultimately,
performance.
A
dataset
comprising
230
responses
from
diverse
forms
basis
analysis,
with
employing
partial
least
squares
structural
equation
(PLS-SEM)
for
robust
data
examination.
Findings
The
results
demonstrate
pivotal
shaping
capability
significantly
positively
affects
overall
Notably,
is
critical
factor
contributing
enhanced
further
uncovered
mediation
effects,
suggesting
that
partially
mediate
relationship
between
performance
through
speed.
Originality/value
contributes
existing
body
providing
empirical
evidence
multifaceted
Elucidating
advances
our
understanding
complex
mechanisms
which
drive
success.
Journal of Small Business Management,
Год журнала:
2024,
Номер
unknown, С. 1 - 35
Опубликована: Авг. 13, 2024
The
recent
surge
in
the
adoption
of
artificial
intelligence
(AI)
by
small
and
medium-sized
enterprises
(SMEs)
has
garnered
significant
research
attention.
However,
existing
literature
reveals
a
fragmented
landscape
that
hinders
our
understanding
how
SMEs
use
AI.
We
address
this
through
systematic
review
wherein
we
analyze
106
peer-reviewed
articles
on
AI
categorize
states
trends
into
eight
clusters:
(1)
compatibility,
(2)
infrastructure,
(3)
knowledge,
(4)
resources,
(5)
culture,
(6)
competition,
(7)
regulation,
(8)
ecosystem:
according
to
technology–organization–environment
model.
Our
provides
valuable
insights
identifies
gaps
literature,
notably
overlooking
identification
as
pivotal
driver
neglecting
legal
requirements.
study
clarifies
implementation
within
SMEs,
offering
holistic
theoretically
grounded
perspective
empower
researchers
practitioners
facilitate
more
effective
application
SME
sector.
Thunderbird International Business Review,
Год журнала:
2024,
Номер
66(2), С. 185 - 200
Опубликована: Фев. 9, 2024
Abstract
The
emergence
of
artificial
intelligence
(AI)
has
transformed
global
business,
aiding
operational
efficiency
and
innovation.
It
utilizes
machine
learning
big
data
analytics,
driving
predictive
market
trends
strategic
decision‐making.
However,
despite
the
rising
discussion
accessibility
AI
tools,
understanding
its
impact
on
international
business
remains
limited.
This
article
explores
AI's
potential
in
strategies,
practices,
activities.
To
address
this
aim,
we
reviewed
37
articles
existing
literature
to
critically
explore
within
context
business.
More
specifically,
explored
how
can
be
applied
innovation
approaches
selection,
entry
modes,
foreign
exchange,
human
resource
management,
supply
chains,
managing
across
cultures,
more
topics.
necessitated
changes
workplace
configurations
need
for
organizational
employee
adjustments
response
technology.
As
a
result
foregoing
issues
integration
our
analysis
provided
an
exploratory
around
use,
challenges,
managerial
implications,
suggested
areas
requiring
future
studies.
World Journal of Advanced Research and Reviews,
Год журнала:
2024,
Номер
22(1), С. 1920 - 1929
Опубликована: Апрель 30, 2024
Offshore
platforms
are
vital
assets
for
the
oil
and
gas
industry,
serving
as
primary
facilities
exploration,
extraction,
processing.
Maintenance
logistics
plays
a
crucial
role
in
ensuring
these
operate
efficiently
safely.
However,
remote
harsh
environments
of
offshore
present
significant
challenges
maintenance
activities.
Traditional
strategies
often
struggle
to
meet
demands
environments,
leading
inefficiencies,
increased
costs,
potential
safety
risks.
This
review
discusses
application
Artificial
Intelligence
(AI)
optimizing
on
platforms.
Current
involve
combination
preventive,
predictive,
corrective
approaches.
Preventive
schedules
regular
inspections
replacements
based
predetermined
intervals,
while
predictive
utilizes
data
analytics
predict
equipment
failures
plan
activities
accordingly.
Corrective
addresses
issues
they
arise,
response
unexpected
failures.
AI
offers
opportunities
enhance
by
leveraging
advanced
analytics,
machine
learning,
optimization
algorithms.
AI-enabled
can
analyze
vast
amounts
from
sensors,
historical
records,
environmental
factors
forecast
with
greater
accuracy.
allows
proactive
planning,
minimizing
downtime
reducing
costs.
Furthermore,
optimize
improving
resource
allocation
scheduling.
Through
real-time
monitoring
analysis,
systems
prioritize
tasks
urgency,
criticality,
availability.
ensures
that
crews
deployed
efficiently,
idle
time
overall
productivity.
Future
innovations
include
integration
Internet
Things
(IoT)
devices
autonomous
systems.
IoT
sensors
provide
condition
factors,
enabling
more
precise
models.
Autonomous
robots
equipped
algorithms
perform
routine
minor
repairs,
need
human
intervention
hazardous
environments.
implementing
also
poses
challenges,
including
quality,
cybersecurity,
workforce
readiness.
Ensuring
accuracy
reliability
is
effective
models,
requiring
robust
collection
management
processes.
Cybersecurity
measures
must
be
strengthened
protect
malicious
attacks
could
disrupt
operations
or
compromise
safety.
Additionally,
training
education
essential
prepare
personnel
working
alongside
interpreting
AI-generated
insights.
Optimizing
benefits
terms
efficiency,
cost
savings,
By
technologies,
current
enhanced,
future
revolutionize
practices,
making
sustainable
resilient
face
evolving
challenges.
Management Decision,
Год журнала:
2024,
Номер
unknown
Опубликована: Июнь 12, 2024
Purpose
This
study
investigates
the
profound
impact
of
artificial
intelligence
(AI)
capabilities
on
decision-making
processes
and
organizational
performance,
addressing
a
crucial
gap
in
literature
by
exploring
mediating
role
speed
quality.
Design/methodology/approach
Drawing
upon
resource-based
theory
prior
research,
this
constructs
comprehensive
model
hypotheses
to
illuminate
influence
AI
within
organizations
speed,
decision
quality,
and,
ultimately,
performance.
A
dataset
comprising
230
responses
from
diverse
forms
basis
analysis,
with
employing
partial
least
squares
structural
equation
(PLS-SEM)
for
robust
data
examination.
Findings
The
results
demonstrate
pivotal
shaping
capability
significantly
positively
affects
overall
Notably,
is
critical
factor
contributing
enhanced
further
uncovered
mediation
effects,
suggesting
that
partially
mediate
relationship
between
performance
through
speed.
Originality/value
contributes
existing
body
providing
empirical
evidence
multifaceted
Elucidating
advances
our
understanding
complex
mechanisms
which
drive
success.
