From familiarity to acceptance: The impact of Generative Artificial Intelligence on consumer adoption of retail chatbots
Journal of Retailing and Consumer Services,
Год журнала:
2025,
Номер
84, С. 104234 - 104234
Опубликована: Янв. 17, 2025
Язык: Английский
Enhancing Institutional Sustainability Through Process Optimization: A Hybrid Approach Using FMEA and Machine Learning
Sustainability,
Год журнала:
2025,
Номер
17(4), С. 1357 - 1357
Опубликована: Фев. 7, 2025
Administrative
processes
in
higher
education
institutions
often
encounter
inefficiencies,
duplication
of
efforts,
and
a
lack
clarity,
which
undermine
institutional
sustainability
user
satisfaction.
This
study
introduces
hybrid
optimization
framework
that
integrates
Failure
Mode
Effects
Analysis
(FMEA)
with
machine
learning
(ML)
to
enhance
the
reliability
efficiency
renowned
university
Ecuador.
Due
variability
data,
tailored
model
was
developed
for
each
ten
critical
analyzed.
Two
models
were
employed
process:
one
focused
on
predicting
high
RPN
values
(current
state)
another
evaluating
proposed
improvements
leading
low
(optimized
state).
Significant
reductions
observed
metrics
such
as
Root
Mean
Square
Error
(RMSE)
Absolute
(MAE).
For
instance,
RMSE
decreased
from
maximum
9.07
4.24
model,
while
MAE
improved
2.86
3.25
across
processes.
Key
included
addressing
failure
modes
errors
requirements,
unclear
steps,
incomplete
documentation.
These
findings
underscore
effectiveness
combining
FMEA
ML
optimize
processes,
align
practices
Sustainable
Development
Goals
(SDGs),
establish
replicable
promoting
resilience,
transparency,
administrative
management.
Язык: Английский
Generative AI vs. Traditional Databases: Insights from Industrial Engineering Applications
Publications,
Год журнала:
2025,
Номер
13(2), С. 14 - 14
Опубликована: Март 25, 2025
This
study
evaluates
the
efficiency
and
accuracy
of
Generative
AI
(GAI)
tools,
specifically
ChatGPT
Gemini,
in
comparison
with
traditional
academic
databases
for
industrial
engineering
research.
It
was
conducted
two
phases.
First,
a
survey
administered
to
101
students
assess
their
familiarity
GAIs
most
commonly
used
tools
field.
Second,
an
assessment
quality
information
provided
by
carried
out,
which
11
professors
participated
as
evaluators.
The
focuses
on
query
process,
response
times,
accuracy,
using
structured
methodology
that
includes
predefined
prompts,
expert
validation,
statistical
analysis.
A
comparative
through
standardized
search
workflows
developed
Bizagi
tool,
ensuring
consistency
evaluation
both
approaches.
Results
demonstrate
significantly
reduce
times
compared
conventional
databases,
although
completeness
responses
require
careful
validation.
Chi-Square
analysis
performed
statistically
differences,
revealing
no
significant
disparities
between
tools.
While
offer
advantages,
remain
essential
in-depth
literature
searches
requiring
high
levels
precision.
These
findings
highlight
potential
limitations
research,
providing
insights
into
optimal
application
education.
Язык: Английский
Students' mindset to adopt AI chatbots for effectiveness of online learning in higher education
Future Business Journal,
Год журнала:
2025,
Номер
11(1)
Опубликована: Март 10, 2025
Abstract
The
rapid
incorporation
of
Artificial
Intelligence
(AI)
technologies
into
higher
education
is
shifting
the
focus
toward
understanding
students’
perspectives
and
factors
affecting
adoption
AI
chatbots
to
maximize
their
use
in
online
virtual
educational
environments.
This
study
fills
an
important
gap
literature
by
examining
direct
mediated
relationships
key
constructs
such
as
perceived
usefulness,
ease
use,
technical
competency
chatbot
usage.
aims
investigate
mindsets
regarding
adopting
for
effectiveness
learning
education.
Data
were
collected
from
429
university
students
analyzed
using
partial
least
squares-based
structural
equation
modeling
(PLS-SEM)
technique.
results
revealed
that
usefulness
(PU),
(PEU),
tech
(TC)
have
a
significant
impact
on
capability.
Subjective
norm
(SN)
has
no
capability
significantly
influences
effectiveness.
findings
indicated
mediates
effect
PU,
PEU,
TC
chatbots;
however,
there
mediating
relationship
between
SN
Facilitating
conditions
moderate
PU
research
addresses
new
insight
within
context
education,
particularly
demonstrating
moderating
function
tech-competent
concepts.
Язык: Английский
Addressing Rights on Responsible AI in Digital Companies
Advances in computational intelligence and robotics book series,
Год журнала:
2025,
Номер
unknown, С. 109 - 138
Опубликована: Март 7, 2025
This
study
examined
the
top
five
reference
companies
for
Generation
Z,
in
relation
to
bias
and
responsible
Artificial
Intelligence
(AI).
Through
a
literature
analysis
on
of
Law
15/2022,
July
12
(15917/2022),
comprehensive
equal
treatment
non-discrimination,
key
factors
are
detected
determine
whether
or
not
comply
from
an
ethical
point
view.
The
findings
confirmed
that
all
items
analyzed
complied
with
except
seals
algorithms
officially.
These
results
essential
guide
market
towards
more
transparent
business
models,
which
helps
increase
trust
they
transmit
society.
offers
implications,
limitations
future
lines
research,
focus
algorithmic
literacy.
Язык: Английский