Interdisciplinary Humanities and Communication Studies,
Год журнала:
2024,
Номер
1(6)
Опубликована: Апрель 16, 2024
From
the
perspective
of
Chinese
employees,
this
study
delves
into
evolving
employment
relationship
amidst
digital
transformation,
specifically
examining
impact
AI
on
job
satisfaction
and
psychological
contracts.
Utilizing
an
online
survey,
data
was
collected
from
321
subsequent
statistical
analysis
gathered
metrics
evaluated
foundations
behavioral
outcomes
associated
with
integration
in
workplace.
The
findings
reveal
that,
although
implementation
positively
correlates
reinforcement
contracts,
existence
transformational
leadership
tends
to
attenuate
positive
correlation.
Technology in Society,
Год журнала:
2023,
Номер
76, С. 102443 - 102443
Опубликована: Дек. 9, 2023
The
purpose
of
this
review
is
integrating
and
contextualizing
relevant
literature
on
the
factors
influencing
adoption
AI
in
healthcare
industry
into
a
comprehensive
framework.
Health
systems
are
considered
fundamental
to
creating
societal
value.
However,
global
health
challenged
by
increasing
number
patients
due
population
aging
growing
prevalence
chronic
diseases
cancer.
Meanwhile,
United
Nations
calls
for
equal
access
healthcare,
tackling
costs,
addressing
resource
constraints
foster
sustainable
development
societies.
In
context,
artificial
intelligence
(AI)
gaining
attention
as
it
constitutes
promising
technology
address
these
burgeoning
challenges.
Despite
opportunities,
specifically
fragmented
across
various
research
fields,
lacking
overview.
It
lacks
theoretically
grounded
integrating,
example,
that
influence
institutions.
Derived
from
multi-disciplinary
systematic
review,
building
130
studies,
we
propose
Adoption
Healthcare
Industry
Model.
This
model
encompasses
five
dimensions
contextualizes
them.
We
macro-economic,
regulatory,
technological
readiness
serve
external
antecedents
whereas
organizational
individual
constitute
internal
Our
has
implications
acceptance
related
healthcare.
Further,
provide
hands-on
guidance
providers,
institutions,
official
bodies
such
governments
leverage
Management Decision,
Год журнала:
2024,
Номер
unknown
Опубликована: Апрель 24, 2024
Purpose
This
study
aims
to
identify
and
assess
the
key
ethical
challenges
associated
with
integrating
artificial
intelligence
(AI)
in
knowledge-sharing
(KS)
practices
their
implications
for
decision-making
(DM)
processes
within
organisations.
Design/methodology/approach
The
employs
a
mixed-methods
approach,
beginning
comprehensive
literature
review
extract
background
information
on
AI
KS
potential
challenges.
Subsequently,
confirmatory
factor
analysis
(CFA)
is
conducted
using
data
collected
from
individuals
employed
business
settings
validate
identified
impact
DM
processes.
Findings
findings
reveal
that
related
privacy
protection,
bias
fairness
transparency
explainability
are
particularly
significant
DM.
Moreover,
accountability
responsibility
of
employment
also
show
relatively
high
coefficients,
highlighting
importance
process.
In
contrast,
such
as
intellectual
property
ownership,
algorithmic
manipulation
global
governance
regulation
found
be
less
central
Originality/value
research
contributes
ongoing
discourse
knowledge
management
(KM)
By
providing
insights
recommendations
researchers,
managers
policymakers,
emphasises
need
holistic
collaborative
approach
harness
benefits
technologies
whilst
mitigating
risks.
Sustainability,
Год журнала:
2024,
Номер
16(12), С. 4879 - 4879
Опубликована: Июнь 7, 2024
This
study
reviews
the
application
of
artificial
intelligence
(AI)
throughout
food
value
chain
and
how
it
can
be
leveraged
to
help
companies
become
more
sustainable.
A
literature
review
across
different
parts
was
conducted
provide
an
overview
main
themes
current
future
AI
applications
industry.
Moreover,
paper
focuses
on
benefits
challenges
change
management
when
integrating
AI.
documentary
Systematic
Review
using
PRISMA
research
find
analyze
aforementioned
applications.
The
key
insight
is
that
progress
varies
significantly.
Today’s
are
primarily
found
within
inspection
quality
assurance
due
relatively
straightforward
in
chain.
Such
technology
mainly
image-based.
Companies
use
interconnectedness
sustainability
by
becoming
efficient
through
simultaneously
saving
emissions
resources
optimizing
processes.
Management Decision,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 8, 2025
Purpose
This
paper
identifies
consumer
acceptance
criteria
of
artificial
intelligence
(AI)-enabled
products
and
services
in
the
business.
We
first
investigate
existing
three
models.
They
are
technology
model
(TAM),
unified
theory
use
(UTAUT)
(CAT).
then
discuss
applicability
these
models
for
AI-enabled
services.
Finally,
we
outline
shortcomings
propose
an
product
service
(AIEPSAM).
also
validate
proposed
AIEPSAM
with
empirical
results
using
primary
survey
data.
Design/methodology/approach
To
understand
customer’s
point
view
on
AI
applications
services,
identify
some
critical
factors
present
a
conceptual
framework
consumers'
based
literature,
prior
research
prominent
management
theories.
Then,
study
broadens
horizon
beyond
established
principles
associated
to
accommodate
AI-specific
factors/variables
like
data
privacy,
explainability
apparent
opacity
algorithms.
In
this
paper,
that
Findings
argue
although
TAM,
UTAUT
CAT
generally
applicable
explain
attitudes
towards
technology,
alone
insufficient
encompass
entire
spectrum
AI-related
issues
must
not
be
ignored.
The
model,
namely
AIEPSAM,
accommodates
limitations
modifies
make
it
suitable
technology.
Originality/value
attempt
articulate
discover
useful
insights,
leading
examination
formulating
validation
through
is
criticize
TAM
other
but
incorporate
into
those
Through
study,
required
modifications
considering
additional
factors.
will
assist
companies
building
better
understanding
emergence
(TE)
opportunities
(TO).
Sustainability,
Год журнала:
2025,
Номер
17(4), С. 1754 - 1754
Опубликована: Фев. 19, 2025
This
study
investigates
the
complex
duality
of
automation
and
its
impact
on
sustainable
development,
encompassing
factors
economic
growth,
social
equity,
environmental
sustainability.
Innovations
in
artificial
intelligence,
robotics,
machine
learning
are
driving
transforming
industries
through
improved
production,
operational
efficiency,
resource
optimization.
However,
rapid
integration
has
created
a
paradox.
While
it
offers
opportunities
for
optimization
technological
advancement,
exacerbates
challenges
such
as
income
inequality,
degradation,
displacement.
These
issues
underline
need
balanced
inclusive
approaches
to
automation’s
implementation.
Automation
contributes
substantively
GDP
growth
because
raises
labor
productivity,
yet
arguably
enhanced
inequality
by
eliminating
low-skilled
jobs.
improves
energy
efficiency
aids
renewable
but
increases
overall
effectiveness,
leading
concerns
regarding
ecological
applied
quantitative
methodology
using
longitudinal
data
from
2000
2023
regression
models
examine
sustainability
metrics
influenced
automation.
The
findings
highlight
potential
reform
effective
forms
manufacturing,
encourage
innovation,
identify
systemic
governmental
policies.
Specifically,
results
indicate
that
contributed
25%
increase
productivity
across
sectors,
15%
reduction
intensity
per
unit
GDP,
12%
rise
Gini
index,
signaling
growing
inequality.
outcomes
emphasize
both
posed
By
integrating
advancements
with
goals,
can
act
transformative
instrument
promote
conservation,
equitable
justice.
paper
concludes
recommendations
governments
industry
leaders
incorporate
into
development
objectives,
ensuring
distribution
advantages,
while
alleviating
socio-environmental
hazards.
East African Journal of Engineering,
Год журнала:
2023,
Номер
6(1), С. 104 - 112
Опубликована: Июнь 28, 2023
Artificial
Intelligence,
machine
learning,
and
the
Internet
of
Things
(IoT)
are
changing
way
tasks
accomplished.
CHATGPT
is
a
well-known
conversational
artificial
intelligence
(AI)
system
based
on
generative
pre-trained
transformer
(GPT)
architecture,
launched
by
OpenAI.
trained
through
reinforcement
learning
human
feedback.
There
advantages
to
use
in
Civil
engineering,
including
but
not
limited
design
planning:
structural
analysis
simulation,
code
compliance
regulations
construction
management,
knowledge
repository
information
retrieval,
education,
research.
The
limitation
bias
datasets
used
training,
requirement
sufficient
input
information,
as
well
risk
transparency
issues,
negative
consequences
if
generating
inaccurate
content.
other
language
models
civil
engineering
requires
careful
consideration
ensure
bypassing
expert
consultation
particular
cases.
Deep
Learning
would
have
positive
impact
rather
than
replacing
expertise
improving
infrastructure
development
world
solving
challenges
facing
mankind
