Adoption and impact of generative artificial intelligence on blockchain-enabled supply chain efficiency
Journal of Systems and Information Technology,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 14, 2025
Purpose
The
purpose
of
this
study
is
to
investigate
the
primary
determinants
influencing
acceptance
generative
artificial
intelligence
(GAI)
adoption
within
Blockchain-enabled
environments.
Further
research
will
examine
impact
GAI
on
supply
chain
efficiency
(SCE)
through
enhancement
Blockchain.
Design/methodology/approach
Drawing
innovation
diffusion
theory
(IDT),
used
partial
least
square
structural
equation
modelling
(PLS-SEM)
look
into
hypotheses.
data
were
gathered
via
online
questionnaires
from
employers
Chinese
enterprises
that
have
already
integrated
Findings
findings
demonstrate
relative
advantages
(RAs),
compatibility,
trialability
and
observability
a
significant
positive
effect
adoption,
while
complexity
harms
adoption.
Above
all,
has
significantly
enhanced
Blockchain,
thus
effectively
improving
SCE.
Practical
implications
outcomes
furnish
organizations
with
valuable
insights
proficiently
integrate
Blockchain
capability,
optimize
management
bolster
market
competitiveness.
Also,
help
accelerate
successful
integration
business
processes
attain
Sustainability
Development
Goals
9,
industrial
growth
diversification.
Originality/value
To
extent
author’s
knowledge,
current
status
remains
largely
exploratory,
there
limited
empirical
evidence
integrating
capability
GAI.
This
bridges
knowledge
gap
by
fully
revealing
optimal
these
two
transformative
technologies
leverage
their
potential
in
management.
Язык: Английский
GENERATIVE AI: A TOOL FOR ADDRESSING DATA SCARCITY IN SCIENTIFIC RESEARCH
ГРААЛЬ НАУКИ,
Год журнала:
2024,
Номер
43, С. 301 - 307
Опубликована: Сен. 15, 2024
Generative
AI,
a
pivotal
advancement
in
data
science,
addresses
scarcity
by
producing
high-quality
synthetic
that
mirrors
real-world
data.
This
article
explores
AI's
capabilities,
including
augmentation,
privacy-preserving
anonymization,
simulation
of
rare
events,
and
cost-efficient
collection.
Techniques
such
as
Adversarial
Networks
(GANs)
Variational
Autoencoders
(VAEs)
are
discussed,
highlighting
their
role
creating
realistic
diverse
The
practical
applications
span
healthcare,
finance,
climate
demonstrating
transformative
potential
enhancing
research
across
various
scientific
disciplines.
Язык: Английский
Generative Artificial Intelligence (GenAI) in Business: A Systematic Review on the Threshold of Transformation
Journal of Smart Systems Research,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 17, 2024
This
systematic
review
examines
the
transformative
potential
of
Generative
Artificial
Intelligence
(GenAI)
across
diverse
sectors,
including
information
technology,
education,
manufacturing,
creative
industries,
healthcare,
transportation,
management,
marketing,
finance,
energy,
law,
media,
agriculture,
and
e-commerce.
By
analyzing
its
applications,
study
highlights
how
GenAI
enhances
efficiency,
fosters
innovation,
addresses
sector-specific
challenges.
Key
benefits
include
automation
complex
processes,
optimization
resource
use,
acceleration
decision-making.
However,
delayed
adoption
risks
such
as
workforce
displacement
ethical
dilemmas
are
also
discussed.
The
identifies
critical
barriers
like
data
privacy
concerns,
algorithmic
bias,
regulatory
Practical
strategies
for
successful
integration
explored,
emphasizing
infrastructure
readiness,
upskilling,
governance.
includes
leveraging
generative
models
Adversarial
Networks
(GANs),
Transformer-based
models,
Variational
Autoencoders
(VAEs),
diffusion
to
adapt
industry-specific
demands.
Furthermore,
underscores
necessity
balancing
technological
advancements
with
responsible
AI
deployment
minimize
maximize
societal
benefits.
synthesizing
existing
research,
this
provides
actionable
insights
stakeholders
aiming
leverage
GenAI's
capabilities
responsibly.
It
emphasizes
urgency
adopting
technologies
maintain
competitiveness
sustainability
in
rapidly
evolving
markets.
As
concludes,
it
advocates
cross-sectoral
collaboration
address
challenges
posed
by
paradigm-shifting
technology
calls
adaptive
policies
align
innovation
principles
values.
Язык: Английский
GenAI Tools to Improve Data Science Project Outcomes
2021 IEEE International Conference on Big Data (Big Data),
Год журнала:
2024,
Номер
unknown, С. 3143 - 3152
Опубликована: Дек. 15, 2024
Язык: Английский
Using generative AI as decision-support tools: unraveling users’ trust and AI appreciation
Journal of Decision System,
Год журнала:
2024,
Номер
unknown, С. 1 - 32
Опубликована: Ноя. 26, 2024
This
study
examines
how
organisational
users
accept
recommendations
when
collaborating
with
Generative
Artificial
Intelligence
(GenAI)
to
inform
decisions,
balancing
perceived
benefits
and
privacy
concerns.
Combining
the
theory
of
consumption
values
calculus
theory,
this
work
develops
a
research
model
capturing
key
factors
driving
users'
trust
in
GenAI
AI
appreciation.
Structural
equation
modelling
analysis
(N
=
211)
reveals
that
functional,
social,
emotional,
epistemic
positively
impact
disclosing
information
for
advice.
Information
sensitivity
increases
risks,
while
control
reduces
perception.
Perceived
influence
trust,
risks
negatively
affect
it.
Trust
is
significant
predictor
contributes
human-AI
collaboration
by
illuminating
mechanism
leading
appreciation
addressing
The
findings
offer
actionable
insights
managers
organisations
seeking
adopt
their
decision
support
system.
Язык: Английский