Moderating effects of energy poverty for sustainable tourism, policy, innovation, and environmental resilience: evidence from SEM-ANN approaches
Discover Sustainability,
Год журнала:
2025,
Номер
6(1)
Опубликована: Фев. 16, 2025
Язык: Английский
Nexus of digital financial service adoption, decent work and environmental sustainability: results from SEM-NCA approaches
Discover Sustainability,
Год журнала:
2025,
Номер
6(1)
Опубликована: Март 13, 2025
Abstract
With
growing
global
attention
on
sustainability,
financial
inclusion,
and
decent
work,
there
remains
a
gap
in
understanding
how
literacy,
access
to
capital,
digital
payment
usage
impact
both
work
environmental
particularly
the
context
of
developing
economies.
Existing
research
also
overlooks
mediating
role
bridging
these
factors
with
sustainability.
A
sample
384
valid
responses
was
collected
using
convenience
sampling
from
service
users
providers.
The
data
were
analyzed
PLS-SEM
examine
direct
indirect
relationships
between
variables,
NCA
employed
assess
robustness
necessity
achieving
results
show
that
positively
affect
Moreover,
mediates
relationship
inclusion
demonstrating
its
crucial
sustainable
outcomes.
study
contributes
theoretical
literature
by
integrating
Capability
Approach,
Institutional
Theory,
Stakeholder
Theory
explain
contribute
This
multi-theory
framework
enhances
mechanisms
through
which
influences
development.
adds
value
extending
introducing
relationships.
findings
this
provide
valuable
insights
for
policymakers
design
inclusive
strategies
promote
foster
contributing
broader
development
goals.
Язык: Английский
Factors Affecting Digital Financial Service Adoption in Bangladesh: Evidence from SEM-ANN Approaches
Journal of risk analysis and crisis response,
Год журнала:
2024,
Номер
14(4)
Опубликована: Дек. 31, 2024
The
rapid
growth
of
Digital
Financial
Services
(DFS)
has
revolutionized
the
financial
landscape
in
developing
countries,
including
Bangladesh.
Despite
its
growing
importance,
understanding
factors
influencing
DFS
adoption
remains
limited,
particularly
when
leveraging
advanced
analytical
frameworks.
This
study
investigates
key
drivers
affecting
Bangladesh
by
employing
Structural
Equation
Modeling
(SEM)
and
Artificial
Neural
Network
(ANN)
approaches.
Using
survey
data
collected
from
340
users,
SEM
analysis
validates
proposed
relationships,
identifying
literacy,
trust,
access
to
capital,
digital
payment
usage,
inclusion
as
significant
driving
adoption.
ANN
modeling
further
highlights
relative
importance
these
predictors,
revealing
literacy
most
influential
factor,
closely
followed
inclusion,
trust
services,
capital
usage.
dual-method
provides
nuanced
insights
for
policymakers,
institutions,
technology
providers,
aiming
enhance
promote
Язык: Английский