Journal of Global Information Management,
Год журнала:
2024,
Номер
32(1), С. 1 - 32
Опубликована: Дек. 28, 2024
Despite
the
risks
associated
with
generative
AI
(GenAI)
chatbots,
people
increasingly
use
these
technologies,
which
may
seem
contradictory.
This
study
identified
and
explored
factors
related
to
trust,
perceived
values,
satisfaction,
sustainable
of
GenAI
chatbots.
Relying
on
IS
theories
build
a
stimulus-organism-response
model,
authors
tested
model
using
PLS-SEM
data
from
393
ChatGPT
users.
The
results
show
that
user
competence
autonomy
dramatically
increase
user's
trust
in
ChatGPT,
improves
hedonic
value
(HV),
utilitarian
(UV),
value-in-use,
task-technology
fit
(TTF),
information
accuracy,
knowledge
acquisition,
informativeness,
satisfaction.
In
addition
satisfaction
depends
HV,
UV,
TTF.
sustainability
HV
However,
privacy
concerns,
risks,
awareness
do
not
affect
consumer
trust.
There
is
complete
mediation
between
sustainability,
as
well
sustainability.
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.
European Journal of Innovation Management,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 27, 2025
Purpose
This
paper
aims
to
contribute
the
discussion
on
integrating
humans
and
technology
in
customer
service
within
framework
of
Society
5.0,
which
emphasizes
growing
role
artificial
intelligence
(AI).
It
examines
how
effectively
new
generative
AI-based
chatbots
can
handle
emotions
explores
their
impact
determining
point
at
a
customer–machine
interaction
should
be
transferred
human
agent
prevent
disengagement,
referred
as
Switch
Point
(SP).
Design/methodology/approach
To
evaluate
capabilities
managing
emotions,
ChatGPT-3.5,
Gemini
Copilot
are
tested
using
Trait
Emotional
Intelligence
Questionnaire
Short-Form
(TEIQue-SF).
A
reference
is
developed
illustrate
shift
Findings
Using
four-intelligence
(mechanical,
analytical,
intuitive
empathetic),
this
study
demonstrates
that,
despite
advancements
AI’s
ability
address
service,
even
most
advanced
chatbots—such
ChatGPT,
Copilot—still
fall
short
replicating
empathetic
(HI).
The
concept
emotional
awareness
(AEA)
introduced
characterize
AI
understanding
triggering
SP.
complementary
rather
than
replacement
perspective
HI
proposed,
highlighting
Research
limitations/implications
exploratory
nature
requires
further
theoretical
development
empirical
validation.
Practical
implications
has
only
an
character
with
respect
possible
real
introduction
collaborative
approaches
integration
5.0.
Originality/value
Customer
Relationship
Management
managers
use
proposed
guide
adopt
dynamic
approach
HI–AI
collaboration
AI-driven
service.
Electronics,
Год журнала:
2025,
Номер
14(3), С. 530 - 530
Опубликована: Янв. 28, 2025
This
study
investigates
the
factors
influencing
users’
intention
to
use
generative
AI
by
employing
a
Bayesian
network-based
probabilistic
structural
equation
model
approach.
Recognizing
limitations
of
traditional
models
like
technology
acceptance
and
unified
theory
technology,
this
research
incorporates
novel
constructs
such
as
perceived
anthropomorphism
animacy
capture
unique
human-like
qualities
AI.
Data
were
collected
from
803
participants
with
prior
experience
using
applications.
The
analysis
reveals
that
social
influence
(standardized
total
effect
=
0.550)
is
most
significant
predictor
intention,
followed
effort
expectancy
(0.480)
usefulness
(0.454).
Perceived
(0.149)
(0.145)
also
but
lower
relative
impact.
By
utilizing
model,
overcomes
linear
models,
allowing
for
exploration
nonlinear
relationships
conditional
dependencies.
These
findings
provide
actionable
insights
improving
design,
user
engagement,
adoption
strategies.
INTERNATIONAL JOURNAL OF INNOVATIONS & RESEARCH ANALYSIS,
Год журнала:
2025,
Номер
04(04(I)), С. 209 - 212
Опубликована: Янв. 9, 2025
Managers
and
leadership
activities
are
at
the
core
of
any
organization's
operation
control
is
mechanism
she/he
offers.
Retaining
talented
employees
crucial
for
an
organization’s
sustainable
development,
ineffective
often
leads
to
employee
disengagement.
Blue
Ocean
Leadership
tries
bring
one
significant
reform
fundamental
level
leadership,
which
has
impact
on
organisations
where
disengaged
work
force
standard.
The
paper
only
identifies
by
employing
secondary
data
contrast
it
with
traditional
models,
defines
"concept"
Leadership,
then
performs
a
thorough
analysis.
Abant Sosyal Bilimler Dergisi,
Год журнала:
2025,
Номер
25(1), С. 365 - 389
Опубликована: Март 24, 2025
The
use
of
artificial
intelligence
(AI)
in
the
retail
sector
is
steadily
increasing.
This
study
aims
to
reveal
usage
AI
retailing
over
years.
For
thisKoh
purpose,
137
studies
published
Journal
Retailing
and
Consumer
Services
were
analyzed
according
SPAR-4-SLR
protocol.
reviewed
across
four
domains:
publication
year,
consumer
approach,
technology
applied,
theoretical
framework.
Findings
indicate
that
most
2024,
primarily
focusing
on
purchasing
behavior,
extensive
chatbots,
frequent
application
Technology
Acceptance
Model
(TAM)
grounding.
research
distinguishes
itself
by
examining
retailer-consumer
behavior
relationship,
mainly
contributing
current
knowledge
this
area.
Keywords:
AI,
ıntelligence,
retailing,
behaviour
