Systems,
Journal Year:
2024,
Volume and Issue:
12(8), P. 296 - 296
Published: Aug. 11, 2024
Connected
and
automated
vehicles
(CAVs)
are
poised
to
revolutionize
mobility.
The
relocation
feature
of
CAVs
enhances
parking
convenience
for
the
public.
Users
can
instruct
arrive
at
their
work
destination,
drop
them
off,
then
assign
a
cost-effective
facility
through
an
optimized
itinerary.
However,
realizing
benefits
depends
on
user
acceptance,
impact
features
CAV
acceptance
remains
area
that
is
yet
be
explored.
This
study
introduces
novel
model
mainly
investigate
effects
relocation-related
factors
717
valid
responses.
results
indicate
perceived
(PCOR)
indirectly
increases
human
three
determinants,
initial
trust,
usefulness
(PU),
ease
use
(PEOU),
while
PU,
PEOU
directly
increase
acceptance.
public
expectations
saving
fees
(EOSPF)
enhance
PCOR.
Additionally,
multigroup
analysis
revealed
PCOR
exerts
more
positive
PU
or
in
subgroups
including
males,
pre-Generation-Z
individuals,
experienced
drivers,
those
with
autopilot
riding
experience.
findings
mediators
also
discussed.
provides
valuable
insights
further
research
practical
adoption
emerging
CAVs.
Fashion and Textiles,
Journal Year:
2023,
Volume and Issue:
10(1)
Published: Oct. 24, 2023
Abstract
With
the
recent
expansion
of
applicability
artificial
intelligence
into
creative
realm,
attempts
are
being
made
to
use
AI
(artificial
intelligence)
in
garment
development
system
various
ways,
both
academia
and
fashion
business.
Several
IT
companies
have
developed
possess
AI-based
design
technologies
that
utilize
StyleGAN2
for
image
transformation.
However,
they
not
widely
utilized
Since
brands
need
create
numerous
designs
launch
new
products
at
least
two
seasons
per
year,
adoption
generation
technology
can
be
one
way
increase
work
efficiency.
Therefore,
this
research
aims
collect
analyze
existing
cases
tools
order
identify
similarities
differences
between
processes
human
designers
tools.
Based
on
analysis,
develop
an
takes
consideration
process
designers,
incorporating
domain
knowledge.
Systems,
Journal Year:
2024,
Volume and Issue:
12(5), P. 176 - 176
Published: May 15, 2024
The
application
of
artificial
intelligence
(AI)
in
programming
assistance
has
garnered
researchers’
attention
for
its
potential
to
reduce
learning
costs
users,
increase
work
efficiency,
and
decrease
repetitive
coding
tasks.
However,
given
the
novelty
AI
Coding
Assistant
Tools
(AICATs),
user
acceptance
is
currently
limited,
factors
influencing
this
phenomenon
are
unclear.
This
study
proposes
an
expanded
model
based
on
Technology
Acceptance
Model
(TAM)
that
incorporates
characteristics
AICAT
users
explore
key
affecting
college
students’
willingness
use
AICATs.
Utilizing
a
survey
methodology,
303
Chinese
participants
completed
questionnaire.
Factor
analysis
Structural
Equation
Modeling
(SEM)
results
indicate
users’
dependence
worry
(DW)
about
AICATs
positively
affects
perceived
risk
(PR),
which
turn
negatively
impacts
usefulness
(PU)
ease
(PEOU),
thus
reducing
use.
Dependence
concerns
also
impact
trust
(PT),
while
PT
PU
PEOU,
thereby
enhancing
Additionally,
user’s
self-efficacy
(SE)
DW
PEOU.
discusses
significance
these
findings
offers
suggestions
developers
foster
promote
widespread
International Journal of Human-Computer Interaction,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 13
Published: Feb. 7, 2024
Artificial
intelligence
(AI)-based
text-to-image
technologies
have
recently
gained
considerable
attention,
but
their
specific
applications
for
educational
purposes
remain
relatively
unexplored.
This
research
aims
to
bridge
this
gap
by
developing
a
theoretical
model
that
combines
constructs
from
the
Expectation
Confirmation
Model
(ECM)
with
Technology
Acceptance
(TAM)
understand
sustainable
use
of
AI-driven
visual
synthesis
in
design
ideation.
Data
was
collected
via
survey
involving
106
vocational
university
students
who
were
enrolled
user
interface
(UI)
course
test
proposed
model.
The
hypotheses
analysis
demonstrated
confirmation
positively
influenced
perceived
usefulness,
ease
use,
and
satisfaction.
Furthermore,
usefulness
had
positive
impact
on
Students'
perceptions
utility,
usability,
satisfaction
also
affected
intention
continue
using
technology.
However,
hypothesis
proposing
relationship
between
did
not
find
support.
A
moderation
revealed
novice
susceptible
effort
expectancy,
negatively
affecting
These
findings
offer
valuable
practical
implications
developers,
designers,
instructors
interested
utilizing
UI
design.
IEEE Access,
Journal Year:
2023,
Volume and Issue:
11, P. 143272 - 143284
Published: Jan. 1, 2023
The
integration
of
generative
artificial
intelligence
(GenAI)
technology
in
the
realm
art
and
design
has
demonstrated
significant
positive
effects
on
designers
related
industries.
current
study
aimed
to
explore
evaluate
factors
personal
traits
that
drive
Generation
Z
embrace
GenAI-assisted
design.
model
incorporated
derived
from
Unified
Theory
Acceptance
Use
Technology
2
(UTAUT2),
Readiness
Index,
concept
trait
curiosity.
Empirical
validation
was
conducted
using
data
collected
326
participants
southeast
Chinese
Mainland.
results
structural
equation
modeling
indicated
that:
(1)
Factors
such
as
effort
expectancy,
price
value,
hedonic
motivation
UTAUT2
have
a
influence
intention
use
GenAI,
while
performance
expectancy
does
not
show
statistically
effect.
(2)
Both
optimism
creativity
significantly
contribute
motivation.
(3)
Trait
curiosity
impact
both
GenAI.
research
findings
suggest
need
for
further
improvements
construction
operational
strategies
GenAI
platforms
provide
practical
insights
enhancing
Z's
utilize
platforms.
Electronics,
Journal Year:
2024,
Volume and Issue:
13(6), P. 1023 - 1023
Published: March 8, 2024
With
the
rise
of
metaverse,
digital
transformation
is
profoundly
affecting
field
art
exhibitions.
Museums
and
galleries
are
actively
adopting
metaverse
technologies
to
present
artworks
through
virtual
platforms,
providing
audiences
with
novel
opportunities
for
immersive
engagement
experiences
shaping
high-quality
user
experiences.
However,
factors
influencing
in
exhibition
platform
(MeAEP)
remain
unclear
current
research.
This
research
combines
information
systems
success
model
(ISSM)
hedonic
motivation
system
adoption
(HMSAM)
construct
a
theoretical
that
provides
insights
into
MeAEP
users’
intention
engage
their
immersion
behavior,
focus
on
sustainability
exhibition.
We
quantitatively
analyzed
370
users
experienced
data
measurement
using
SPSS
27
partial
least
squares
structural
equation
modeling
(PLS-SEM).
The
results
showed
quality
(IQ),
(SQ),
perceived
ease
use
(PEOU)
significantly
positively
influenced
usefulness
(PU),
curiosity
(CUR),
joy
(JOY),
control
(CON).
PU,
JOY,
CON
have
positive
significant
effect
Immersion
(IM).
Finally,
CUR,
had
behavioral
(BI).
In
conclusion,
only
one
twenty
hypotheses
was
not
supported.
findings
enrich
academic
managerial
theories
related
but
also
provide
practical
administrators,
developers,
designers
create
higher-quality
more
content,
as
well
constructive
ideas
exhibitions
further
enhance
experience.
PLoS ONE,
Journal Year:
2024,
Volume and Issue:
19(5), P. e0301821 - e0301821
Published: May 15, 2024
With
the
rapid
advancement
of
technology,
Artificial
Intelligence
(AI)
painting
has
emerged
as
a
leading
intelligence
service.
This
study
aims
to
empirically
investigate
users’
continuance
intention
toward
AI
applications
by
utilizing
and
expanding
Expectation
Confirmation
Model
(ECM),
Technology
Acceptance
(TAM),
Unified
Theory
Use
(UTAUT),
Flow
Theory.
A
comprehensive
research
model
is
proposed.
total
443
questionnaires
were
distributed
users
with
experiences
for
data
collection.
The
hypotheses
tested
through
structural
equation
modeling.
primary
conclusions
drawn
from
this
include:
1)
plays
crucial
role,
significantly
positively
predicting
satisfaction
social
impact.
2)
Personal
innovativeness
significant
effect
on
confirmation.
3)
Satisfaction,
flow
experience,
influence
directly
predict
intention,
showing
most
impact,
while
perceived
usefulness,
enjoyment,
performance
expectancy
show
no
impact
intention.
4)
Habit
negative
moderating
role
in
association
between
continued
use.
These
findings
offer
valuable
insights
inspiration
seeking
understand
appropriate
utilization
provide
actionable
directions
development
painting.
Sustainability,
Journal Year:
2024,
Volume and Issue:
16(12), P. 5173 - 5173
Published: June 18, 2024
The
present
research
aims
to
explore
the
dual
potential
of
artificial
intelligence-generated
content
(AIGC)
technology
in
esthetic
reproduction
Ming-style
furniture
and
its
innovative
design
while
promoting
sustainable
practices
cultural
heritage
preservation.
For
this
purpose,
a
combination
methodologies
integrating
principles
grounded
theory,
empirical
research,
design,
practice
evaluation
techniques
is
employed.
results
are
as
follows:
First,
three-level
coding
method
theory
used
construct
multi-dimensional
feature
library
furniture,
including
6
dimensions
102
groups
elements.
Second,
set
databases
specifically
for
developed
based
on
Midjourney
platform.
AIGC
exclusive
toolkit
(MFMP)
contains
language
package
61
keywords
basic
formula
design.
MFMP
accurately
reproduces
esthetics
through
validation.
Finally,
combined
with
principles,
new
path
explored
order
utilize
Chinese-style
furniture.
demonstrate
that
enhances
traditional
modern
offering
tools
industry
growth
way
preserving
heritage.
PLoS ONE,
Journal Year:
2025,
Volume and Issue:
20(2), P. e0314306 - e0314306
Published: Feb. 19, 2025
With
the
rapid
development
of
AI
intelligent
technology,
AIGC
can
bring
an
innovative
revolution
to
art
creation,
providing
designers
with
unlimited
possibilities
but
also
challenges.
These
challenges
affect
willingness
adopt
and
constrain
sustainable
AIGC.
The
purpose
this
study
is
analyse
factors
designers’
adoption
intention
behaviours.
This
reconstructed
research
model
by
combining
technology
characteristics
interactivity,
acceptance
model,
readiness
etc.
empirical
was
conducted
from
dual
perspectives
application
psychology,
in
order
predict
that
behavioural
intentions
use
In
study,
a
questionnaire
survey
among
China
462
valuable
responses
were
received.
Through
structural
equation
modelling
(SEM)
analysis,
found
that:
(1)
AIGC’s
technical
features
interactivity
positively
perceived
ease
use,
usefulness,
interactive
do
not
directly
usefulness;
usefulness
applications;
(2)
optimism
innovation
adopt;
Insecurity
negatively
affects
adopt,
insecurity
does
features;
discomfort
adopt.
further
extends
theoretical
models
TAM(Technology
Acceptance
Model)
TRI(Technology
Readiness
Model),
provides
basis
for
studying
behaviour
AIGC,
enriches
groups
domains
TAM
TRI.
results
provide
inspiration
development,
design,
marketing
applications,
contributing
realisation
as
well
professional
designers.
