International Transactions in Operational Research,
Год журнала:
2024,
Номер
unknown
Опубликована: Июль 31, 2024
Abstract
Artificial
intelligence
(AI)
as
a
disruptive
technology
is
not
new.
However,
its
recent
evolution,
engineered
by
technological
transformation,
big
data
analytics,
and
quantum
computing,
produces
conversational
generative
AI
(CGAI/GenAI)
human‐like
chatbots
that
disrupt
conventional
operations
methods
in
different
fields.
This
study
investigates
the
scientific
landscape
of
CGAI
human–chatbot
interaction/collaboration
evaluates
use
cases,
benefits,
challenges,
policy
implications
for
multidisciplinary
education
allied
industry
operations.
The
publications
trend
showed
just
4%
(
n
=
75)
occurred
during
2006–2018,
while
2019–2023
experienced
astronomical
growth
1763
or
96%).
prominent
cases
(e.g.,
ChatGPT)
teaching,
learning,
research
activities
computer
science
(multidisciplinary
AI;
32%),
medical/healthcare
(17%),
engineering
(7%),
business
fields
(6%).
intellectual
structure
shows
strong
collaboration
among
eminent
sources
business,
information
systems,
other
areas.
thematic
highlights
including
improved
user
experience
human–computer
interaction,
programs/code
generation,
systems
creation.
Widespread
usefulness
teachers,
researchers,
learners
includes
syllabi/course
content
testing
aids,
academic
writing.
concerns
about
abuse
misuse
(plagiarism,
integrity,
privacy
violations)
issues
misinformation,
danger
self‐diagnoses,
patient
applications
are
prominent.
Formulating
strategies
policies
to
address
potential
challenges
teaching/learning
practice
priorities.
Developing
discipline‐based
automatic
detection
GenAI
contents
check
proposed.
In
operational/operations
areas,
proper
CGAI/GenAI
integration
with
modeling
decision
support
requires
further
studies.
Computers and Education Artificial Intelligence,
Год журнала:
2021,
Номер
2, С. 100033 - 100033
Опубликована: Янв. 1, 2021
The
introduction
of
Artificial
Intelligence
technology
enables
the
integration
Chatbot
systems
into
various
aspects
education.
This
is
increasingly
being
used
for
educational
purposes.
has
potential
to
provide
quick
and
personalised
services
everyone
in
sector,
including
institutional
employees
students.
paper
presents
a
systematic
review
previous
studies
on
use
Chatbots
A
approach
was
analyse
53
articles
from
recognised
digital
databases.
results
comprehensive
understanding
prior
research
related
education,
information
existing
studies,
benefits,
challenges,
as
well
future
areas
implementation
field
implications
findings
were
discussed,
suggestions
made.
Contemporary Educational Technology,
Год журнала:
2023,
Номер
15(3), С. ep429 - ep429
Опубликована: Апрель 3, 2023
Artificial
intelligence
(AI)
introduces
new
tools
to
the
educational
environment
with
potential
transform
conventional
teaching
and
learning
processes.
This
study
offers
a
comprehensive
overview
of
AI
technologies,
their
applications
in
education,
difficulties
involved.
Chatbots
related
algorithms
that
can
simulate
human
interactions
generate
human-like
text
based
on
input
from
natural
language
are
discussed.
In
addition
advantages
cutting-edge
chatbots
like
ChatGPT,
use
education
raises
important
ethical
practical
challenges.
The
authors
aim
provide
insightful
information
how
may
be
successfully
incorporated
into
setting
benefit
teachers
students,
while
promoting
responsible
use.
Technological Forecasting and Social Change,
Год журнала:
2021,
Номер
175, С. 121390 - 121390
Опубликована: Дек. 13, 2021
With
the
continuing
application
of
artificial
intelligence
(AI)
technologies
in
decision-making,
algorithmic
decision-making
is
becoming
more
efficient,
often
even
outperforming
humans.
Despite
this
superior
performance,
people
consciously
or
unconsciously
display
reluctance
to
rely
on
algorithms,
a
phenomenon
known
as
algorithm
aversion.
Viewed
behavioral
anomaly,
aversion
has
recently
attracted
much
scholarly
attention.
view
synthesize
findings
existing
literature,
we
systematically
review
80
empirical
studies
identified
through
searching
seven
academic
databases
and
using
snowballing
technique.
We
inductively
categorize
influencing
factors
under
four
main
themes:
algorithm,
individual,
task,
high-level.
Our
analysis
reveals
that
although
individual
have
been
investigated
extensively,
very
little
attention
given
exploring
task
high-level
factors.
contribute
literature
by
proposing
comprehensive
framework,
highlighting
open
issues
studies,
outlining
several
research
avenues
could
be
handled
future
research.
model
guide
developers
designing
developing
managers
implementing
decision.
International Journal of Human-Computer Interaction,
Год журнала:
2022,
Номер
40(2), С. 441 - 456
Опубликована: Сен. 14, 2022
This
study
investigates
the
effect
of
chatbot
humanization
on
perception
eeriness,
trust,
and
users’
behavioral
intention.
Specifically,
this
employed
a
2
(humanization
agent
avatar:
hyperrealistic-animated
vs.
cartoonish-still)
×
(avatar
familiarity:
celebrity
avatar
non-celebrity
avatar)
between-subjects
experiment
(N
=
185),
in
which
participants
were
asked
to
purchase
laptop
from
an
e-commerce
vendor
by
interacting
with
agent.
Based
predictions
uncanny
valley
hypothesis
(UVE),
enhancing
human
likeness
through
visual
realism
animacy
was
predicted
negatively
influence
trust
intention
as
consequence
activation
negative
affective
state
(i.e.,
feeling
eeriness).
Consistent
our
predictions,
results
PLS-SEM
showed
that
(a)
significantly
increased
(b)
eeriness
influenced
agent,
c)
determined
affected
willingness
reuse
chatbot,
d)
relationship
between
moderated
familiarity
avatar.
We
discuss
theoretical
implications
current
UVE
well
its
practical
for
implementation
anthropomorphized
agents
context.
Journal of Retailing and Consumer Services,
Год журнала:
2023,
Номер
75, С. 103440 - 103440
Опубликована: Июнь 16, 2023
Artificial
Intelligence
(AI)-powered
conversational
agents
have
become
ubiquitous
tools
in
the
digital
transformation
of
conventional
customer-company
interactions.
Despite
widespread
implementation
agents,
there
is
still
a
limited
understanding
how
customers
use
and
resist
these
technologies
for
shopping.
To
address
this
gap,
study
investigates
factors
that
influence
usage
resistance
AI-based
shopping
using
extended
behavioral
reasoning
theory
(BRT)
partial
least
squares-based
structural
equation
modeling
(PLS-SEM).
test
proposed
framework,
conducted
two
empirical
studies
South
Korea.
Study
1
focused
on
text-based
chatbots
with
sample
232
participants,
while
2
examined
voice-based
234
participants.
The
results
both
mainly
supported
hypotheses
driven
by
BRT.
Theoretically,
contributes
offering
comprehensive
customer
motivation,
attitudes,
intentions
toward
AI-powered
Managerially,
provides
important
insights
retail
managers
developers
By
drive
resistance,
managers,
can
better
design
deploy
innovative
to
enhance
experience
improve
business
outcomes.
Computers in Human Behavior,
Год журнала:
2022,
Номер
135, С. 107343 - 107343
Опубликована: Июнь 2, 2022
In
this
study,
we
delve
into
the
perceived
quality
of
recommendations
provided
by
AI-based
virtual
service
assistants
(VSAs).
Specifically,
role
social
presence
VSAs
in
influencing
recommendation
perceptions
is
investigated.
We
also
explore
how
a
VSA
formed
and
anthropomorphism
plays
vital
shaping
eventually
instilling
trust
among
consumers.
These
relationships
are
examined
context
online
government
services.
The
results
indicate
that
consumer
interaction
with
-
manifesting
via
anthropomorphism,
presence,
dialog
length,
attitudes
improves
perceptions,
which
further
instills
VSA-based
recommendations.
Perceived
was
found
to
strongly
influence
formation
whereas
outcomes
were
be
partially
conditional
on
length
degree
positive
toward
VSAs.
findings
additionally
suggest
can
considered
actor
possesses
capability
bring
"human
touch"
services,
therefore
improving
overall
experience.
Procedia Computer Science,
Год журнала:
2022,
Номер
201, С. 421 - 428
Опубликована: Янв. 1, 2022
Chatbots
are
increasingly
finding
their
way
into
e-commerce
and
e-services,
as
implementation
opens
up
promising
opportunities
to
improve
customer
service.
The
present
paper
examines
chatbots
in
this
context,
elaborating
on
functional
aspects
that
rapidly
leading
significant
improvements
service
quality.
First,
based
a
literature
review
of
recent
publications
field,
an
overview
key
features
functionalities
underlining
the
relevance
for
is
provided.
Second,
further
contribution
made
by
introducing
two
categories
chatbots'
objectives
dedication,
i.e.
"improvement
performance"
"fulfillment
customer's
expectations".
considered
customer-related
functions
interaction,
entertainment,
problem-solving,
trendiness,
customization.
chatbot
discussed
detail.
Their
positive
influence
quality,
constituting
goal,
well
potential
pointed
out.
