Determinants of Generative AI in Promoting Green Purchasing Behavior: A Hybrid Partial Least Squares–Artificial Neural Network Approach
Business Strategy and the Environment,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 11, 2025
ABSTRACT
In
the
era
of
rapid
technological
advancement,
generative
artificial
intelligence
(AI)
has
emerged
as
a
transformative
force
in
various
sectors,
including
environmental
sustainability.
This
research
investigates
factors
and
consequences
using
AI
to
access
information
influence
green
purchasing
behavior.
It
integrates
theories
such
adoption
model,
value–belief–norm
theory,
elaboration
likelihood
cognitive
dissonance
theory
pinpoint
prioritize
determinants
usage
for
Data
from
467
participants
were
analyzed
hybrid
methodology
that
blends
partial
least
squares
(PLS)
with
neural
networks
(ANN).
The
PLS
outcomes
indicate
interactivity,
responsiveness,
knowledge
acquisition
application,
concern,
ascription
responsibility
are
key
predictors
use
information.
Furthermore,
concerns,
values,
personal
norms,
responsibility,
individual
impact,
emerge
ANN
analysis
offers
unique
perspective
discloses
variations
hierarchy
these
predictors.
provides
valuable
insights
stakeholders
on
harnessing
promote
sustainable
consumer
behaviors
Язык: Английский
Necessary Configuration Analysis (NConfA): a new multivariate approach
Service Industries Journal,
Год журнала:
2025,
Номер
unknown, С. 1 - 10
Опубликована: Янв. 29, 2025
Язык: Английский
Examining generative AI user continuance intention based on the SOR model
Aslib Journal of Information Management,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 5, 2025
Purpose
The
purpose
of
this
research
is
to
examine
generative
artificial
intelligence
(AI)
user
continuance
intention
based
on
the
stimulus-organism-response
model.
Design/methodology/approach
We
adopted
a
mixed
method
structural
equation
modeling
and
fuzzy-set
qualitative
comparative
analysis
conduct
data
analysis.
Findings
results
found
that
AI
content
quality
(perceived
personalization,
perceived
accuracy
credibility)
system
interactivity,
anthropomorphism
intelligence)
affect
sense
empowerment
satisfaction,
both
which
further
determine
intention.
Originality/value
Extant
has
identified
effect
flow,
trust
parasocial
interaction
continuance,
but
it
seldom
disclosed
internal
decisional
process
This
tries
fill
gap,
enrich
extant
continuance.
Язык: Английский
Recipes for consumer loyalty intentions toward AI speakers: A complexity theory approach
Service Business,
Год журнала:
2025,
Номер
19(2)
Опубликована: Март 20, 2025
Язык: Английский
Sustained use of generative AI for shopping: a PLS-ANN analysis
Service Industries Journal,
Год журнала:
2025,
Номер
unknown, С. 1 - 34
Опубликована: Апрель 3, 2025
Язык: Английский
Unveiling Psychosocial Factors Influencing Metaverse-Associated App Adoption: Acumens from fsQCA Approach
International Journal of Human-Computer Interaction,
Год журнала:
2025,
Номер
unknown, С. 1 - 15
Опубликована: Апрель 3, 2025
Язык: Английский
Do Ethical Issues Influence the Interest of Young People in Using Artificial Intelligence? An Integrated Application of Qualitative Comparative Analysis
Sustainable Technology and Entrepreneurship,
Год журнала:
2025,
Номер
unknown, С. 100108 - 100108
Опубликована: Март 1, 2025
Язык: Английский
Determinants of ChatGPT adoption among students in higher education: the moderating effect of trust
The Electronic Library,
Год журнала:
2024,
Номер
unknown
Опубликована: Окт. 11, 2024
Purpose
ChatGPT
is
a
cutting-edge
chatbot
powered
by
artificial
intelligence
that
could
revolutionise
and
advance
the
teaching
learning
process.
Drawing
on
technology
acceptance
model
(TAM)
information
system
(IS)
success
model,
this
study
aims
to
investigate
determinants
of
students’
intention
use
for
education
purposes.
Design/methodology/approach
The
partial
least
squares
technique
was
used
analyse
406
usable
data
collected
from
university
students
in
Malaysia.
Findings
results
confirmed
relationships
between
perceived
usefulness
(PU),
ease
(PEU),
attitude
proposed
TAM.
PU
PEU
are
influenced
quality.
Surprisingly,
trust
moderates
negatively
influences
attitude.
Practical
implications
findings
provide
insight
higher
institutions,
unit
instructors
developers
what
may
promote
education.
Originality/value
contributes
literature
exploring
adoption,
extending
TAM
incorporating
IS
factors
assessing
moderating
effect
information.
Язык: Английский
The impact of ChatGPT’s competencies on users’ intention to use
Service Industries Journal,
Год журнала:
2024,
Номер
unknown, С. 1 - 30
Опубликована: Окт. 16, 2024
Driven
by
ChatGPT's
popularity,
generative
conversational
artificial
intelligence
(GCAI)
has
captured
global
interest.
Despite
its
widespread
adoption,
the
competencies
of
GCAI
and
their
influence
on
users'
intention
to
use
it
remain
underexplored.
This
study
examines
effect
GCAI.
Using
a
mixed-methods
approach,
we
analyze
social
media
comments
identify
four
key
competencies.
Based
naturalness
theory,
trust
literature,
stimulus-organism-response
model,
propose
test
research
model
via
survey.
Our
results
show
that
accuracy
response,
self-learning,
natural
language
interaction
enhance
in
it,
while
human-like
empathy
influences
but
not
intention.
Trust
fully
mediates
relationship
between
intention,
partially
other
three
fills
gap
understanding
GCAI's
appeal
offers
guidance
for
developers
marketers.
Язык: Английский
Factors Affecting the Use of ChatGPT for Obtaining Shopping Information
International Journal of Consumer Studies,
Год журнала:
2024,
Номер
49(1)
Опубликована: Дек. 13, 2024
ABSTRACT
ChatGPT
transforms
the
shopping
experience
by
providing
responses
in
human‐like
language
about
products,
services,
and
brands
to
customers.
This
study
investigated
influential
drivers
of
intention
use
obtain
information.
We
extended
“extended
unified
theory
acceptance
technology”
UTAUT2
incorporating
direct
moderating
effects
trust
technology
anxiety.
To
test
model
on
data
from
412
respondents,
a
hybrid
Partial
Least
Squares—Artificial
Neural
Network
(PLS‐ANN)
approach
was
employed.
combines
strengths
PLS
for
modeling
complex
variable
relationships
ANN
capturing
nonlinear
dependencies
interactions.
analysis
identified
performance
expectancy,
effort
facilitating
conditions,
hedonic
motivation,
as
significant
usage.
The
associations
between
its
predictors
are
negatively
moderated
revealed
that
has
highest
effect
choice
ChatGPT,
followed
expectancy.
By
extending
framework
applying
PLS‐ANN
method,
this
advances
theoretical
understanding
adoption
provides
practical
insights
marketers
developers
AI‐driven
text
generators.
It
emphasizes
importance
building
alleviating
anxiety
promote
wider
ChatGPT.
broader
significance
research
lies
contribution
shaping
future
retail
e‐commerce
strategies
encouraging
more
informed
user‐centric
development
AI
technologies
domain.
Язык: Английский