Theoretical Economics Letters,
Год журнала:
2023,
Номер
13(05), С. 1203 - 1223
Опубликована: Янв. 1, 2023
The
recent
global
changes
in
Information
and
Communications
Technology
(ICT),
have
demonstrated
a
tremendous
range
of
technological
use
cases
including
the
Artificial
Intelligent
(AI)
applications
(apps)
for
financial
services.
In
light
latest
developments
generative
AI
tools
such
as
ChatGPT,
this
study
develops
an
innovative
research
model
used
prediction
most
significant
factors
influencing
consumers'
willingness
to
accept
buy
banking
apps,
under
theory
Value-based
Adoption
Model
(VAM).
authors
conducted
online
survey
Greek
consumers
apps
using
Structural
Equation
Modeling
(SEM)
determine
which
variables
enhance
customers'
perceived
value
performing
influence
on
adoption
purchase.
This
found
that
trust
happiness
are
impacting
intention
conversational
apps.
likely
outcome
is
mediating
role
pay
conclusions
implications
marketing
can
help
institutions
augment
accuracy
audit
advisory
services,
enhancing
customer
satisfaction
engagement
increasing
bank
competitiveness.
Technological Forecasting and Social Change,
Год журнала:
2024,
Номер
201, С. 123242 - 123242
Опубликована: Фев. 2, 2024
The
pace
of
technological
development
is
exceeding
expectations
and
transforming
the
landscape
last-mile
delivery.
This
study
investigates
how
users'
post-adoption
behavior
in
using
delivery
robots
formed.
Based
on
task-technology
fit
(TTF)
model,
we
present
a
research
model
that
includes
both
direct
indirect
factors
have
been
previously
overlooked
literature.
We
collected
data
from
550
users
robots.
Our
structural
equation
modelling
results
show
two
hedonic-
(i.e.,
gratification
anthropomorphism)
three
utilitarian-
service
quality
experience,
task
requirements,
user-facing
technology
performance)
driven
predict
perceived
TTF
Value-in-use
trust
sequential
mediating
effects
connect
reuse
likelihood
word-of-mouth
recommendation.
findings
suggest
ways
to
improve
robot
strategies
provide
practical
implications
for
industry.
Journal of Enterprise Information Management,
Год журнала:
2024,
Номер
37(1), С. 307 - 325
Опубликована: Янв. 27, 2024
Purpose
In
the
reduction
of
food
waste
and
provision
to
hungry,
banks
play
critical
roles.
However,
as
they
are
generally
run
by
charitable
organisations
that
chronically
short
human
other
resources,
their
inbound
logistics
efforts
commonly
experience
difficulties
in
two
key
areas:
1)
how
organise
stocks
donated
food,
2)
assess
items
quality
fitness
for
purpose.
To
address
both
these
problems,
authors
aimed
develop
a
novel
artificial
intelligence
(AI)-based
approach
warehousing
management
banks.
Design/methodology/approach
For
diagnosing
items,
designed
convolutional
neural
network
(CNN);
ascertain
best
arrange
such
within
banks'
available
space,
reinforcement
learning
was
used.
Findings
Testing
proposed
innovative
CNN
demonstrated
its
ability
provide
consistent,
accurate
assessments
five
species
fruit.
The
reinforcement-learning
approach,
well
being
capable
devising
effective
storage
schemes
required
fewer
computational
resources
some
approaches
have
been
proposed.
Research
limitations/implications
Viewed
through
lens
expectation-confirmation
theory,
which
found
useful
framework
research
this
kind,
AI-based
inbound-logistics
techniques
exceeded
normal
expectations
achieved
positive
disconfirmation.
Practical
implications
As
enabling
machines
learn
handed
operators,
pioneering
study
showed
could
achieve
excellent
performance:
i.e.,
consistency
provided
AI
operations
future
dramatically
enhance
logistics'
quality,
specific
case
Originality/value
This
paper’s
differs
considerably
from
others,
able
effectively
manage
food-quality
food-storage
decisions
more
rapidly
than
counterparts.
Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Март 19, 2024
Popularization
of
knowledge
is
considerable
importance
and
necessity,
traditional
popularization
activities
suffer
from
high
cost
low
acceptance,
which
affect
their
effectiveness
coverage.
Applying
virtual
avatars
to
educational
videos
may
be
an
effective
way
solve
the
problem.
This
study
investigates
impact
applying
on
user
experience.
Constructed
a
model
experience
with
avatars,
collected
data
target
population,
analyzed
it
empirically.
The
video
quality
avatar
expressiveness
dimensions
influencing
factors
have
significant
positive
effect
learning
effect,
emotional
engagement
experience;
content
dimension
has
negative
three
Frontiers in Health Services,
Год журнала:
2024,
Номер
4
Опубликована: Май 1, 2024
Introduction
The
number
of
mHealth
apps
has
increased
rapidly
during
recent
years.
Literature
suggests
a
problems
and
barriers
to
the
adoption
apps,
including
issues
such
as
validity,
usability,
well
data
privacy
security.
Continuous
quality
assessment
assurance
systems
might
help
overcome
these
barriers.
Aim
this
scoping
review
was
collate
literature
on
tools
for
compile
components
tools,
derive
overarching
dimensions,
which
are
potentially
relevant
continuous
apps.
Methods
searches
were
performed
in
Medline,
EMBASE
PsycInfo.
Articles
English
or
German
language
included
if
they
contained
information
development,
application,
validation
generic
concepts
Screening
extraction
carried
out
by
two
researchers
independently.
Identified
criteria
aspects
extracted
clustered
into
dimensions.
Results
A
total
70
publications
met
inclusion
criteria.
Included
contain
five
further
24
Of
29
systems/tools,
8
developed
specific
diseases,
16
assessing
all
fields
health
another
not
restricted
grouped
14
namely
“information
transparency”,
“validity
(added)
value”,
“(medical)
safety”,
“interoperability
compatibility”,
“actuality”,
“engagement”,
“data
security”,
“usability
design”,
“technology”,
“organizational
aspects”,
“social
“legal
“equity
equality”,
“cost(-effectiveness)”.
Discussion
This
provides
broad
overview
existing
systems.
Many
cover
only
few
dimensions
therefore
do
allow
comprehensive
assurance.
Our
findings
can
contribute
development
Systematic
Review
Registration
https://www.researchprotocols.org/2022/7/e36974/
,
International
Registered
Report
Identifier,
IRRID
(DERR1-10.2196/36974).
Heliyon,
Год журнала:
2023,
Номер
9(6), С. e16766 - e16766
Опубликована: Май 27, 2023
Due
to
technological
advancements
and
consumer
demands,
online
shopping
creates
new
features
adapts
standards.
A
robust
customer
satisfaction
prediction
model
concerning
trust
privacy
platforms
can
encourage
an
organization
make
better
decisions
about
its
service
quality.
This
study
presented
approach
predict
using
the
blockchain-based
framework
combining
Multi-Dimensional
Naive
Bayes-K
Nearest
Neighbor
(MDNB-KNN)
Multi-Objective
Logistic
Particle
Swarm
Optimization
Algorithm
(MOL-PSOA).
regression
is
employed
quantify
impact
of
various
production
factors
on
satisfaction.
The
proposed
method
yields
levels
measurement
for
(98%),
accuracy
(95%),
necessary
time
(60%),
precision
recall
(95%)
compared
existing
studies.
Measuring
with
a
trustworthy
platform
facilitates
development
conceptual
practical
distinctions
influencing
customers'
purchasing
decisions.
International Journal of Human-Computer Interaction,
Год журнала:
2024,
Номер
unknown, С. 1 - 14
Опубликована: Фев. 18, 2024
The
increase
of
digital
health
solutions
to
mitigate
work-related
mental
issues
has
been
marked,
and
the
COVID-19
pandemic
further
reinforced
this
trend.
This
paper
evaluates
usability
acceptability
a
platform
developed
provide
tools
resources
support
key
organizational
stakeholders.
Through
semi-structured
interviews
with
think-aloud
cognitive
walkthrough
techniques,
31
potential
end-users
identified
critical
factors
influencing
platform.
Key
themes
included
perceived
intuitiveness
system,
clarity
information,
users'
emotional
response
tools,
namely
enjoyment.
Acceptability
performance
expectancy,
trust,
facilitating
conditions.
findings
insights
for
both
research
practice,
enriching
understanding
platforms
from
perspectives
different
knowledge
can
also
guide
designers
developers
eHealth
applications
in
workplace.
