Sustainable Development,
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 27, 2024
Abstract
This
study
investigates
the
impact
of
green
finance
(GF)
on
sustainable
development
and
supply
chains,
particularly
in
context
COVID‐19
pandemic.
It
explores
how
GF
influences
firms'
economic,
environmental,
social
sustainability,
with
a
focus
moderating
effects
modern
technologies
like
big
data
analytics
(BDA)
blockchain.
The
research
is
based
collected
from
562
managers
Egypt's
industrial
manufacturing
sectors
through
survey
conducted
between
November
18th,
2023,
January
12th,
2024.
survey,
which
used
five‐point
Likert
scale,
was
distributed
via
both
traditional
electronic
methods,
its
reliability
ensured
pilot
phase
involving
seven
academics
five
SC
practitioners.
analyzed
using
partial
least
squares
structural
equation
modeling,
chosen
for
effectiveness
non‐normal
distributions.
Bootstrapping
method
5000
iterations
employed
to
validate
model.
findings
reveal
that
significantly
enhances
chain
management
(GSCM),
when
moderated
by
BDA,
though
blockchain
technology
does
not
have
significant
effect.
Additionally,
GSCM
found
positively
influence
environmental
dimensions
development,
mediating
relationship
these
sustainability
outcomes.
provides
valuable
insights
practitioners
policymakers,
emphasizing
critical
role
BDA
fostering
especially
within
Egyptian
sectors.
Processes,
Год журнала:
2025,
Номер
13(2), С. 594 - 594
Опубликована: Фев. 19, 2025
Accurate
demand
forecasting
is
crucial
for
modern
supply
chain
management,
forming
the
foundation
inventory
optimization,
cost
control,
and
service
level
improvement.
However,
time
series
data
often
exhibit
high
volatility
diverse
patterns,
further
complicated
by
rapid
expansion
heterogeneity
of
sources.
These
challenges
can
result
in
significant
degradation
predictive
accuracy
when
traditional
models
are
applied
to
complex
datasets.
To
address
these
challenges,
this
study
proposes
an
end-to-end
framework
leveraging
Variational
Mode
Decomposition
(VMD)
attention
mechanisms.
The
first
employs
VMD
decompose
raw
into
multiple
modes
extract
hierarchical
features,
including
trends,
seasonal
short-term
variations.
Subsequently,
mechanism
introduced
dynamically
capture
integrate
sequences
alongside
contextual
information,
enhancing
focus
on
critical
features
improving
performance.
Experimental
results
demonstrate
that
proposed
method
achieves
superior
compared
conventional
approaches,
with
a
37%
reduction
Mean
Absolute
Error
(MAE)
relative
baseline
models.
This
substantial
improvement
provides
actionable
insights
decision-makers,
enabling
more
efficient
production
planning,
overall
optimization.
Sustainable Development,
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 27, 2024
Abstract
This
study
investigates
the
impact
of
green
finance
(GF)
on
sustainable
development
and
supply
chains,
particularly
in
context
COVID‐19
pandemic.
It
explores
how
GF
influences
firms'
economic,
environmental,
social
sustainability,
with
a
focus
moderating
effects
modern
technologies
like
big
data
analytics
(BDA)
blockchain.
The
research
is
based
collected
from
562
managers
Egypt's
industrial
manufacturing
sectors
through
survey
conducted
between
November
18th,
2023,
January
12th,
2024.
survey,
which
used
five‐point
Likert
scale,
was
distributed
via
both
traditional
electronic
methods,
its
reliability
ensured
pilot
phase
involving
seven
academics
five
SC
practitioners.
analyzed
using
partial
least
squares
structural
equation
modeling,
chosen
for
effectiveness
non‐normal
distributions.
Bootstrapping
method
5000
iterations
employed
to
validate
model.
findings
reveal
that
significantly
enhances
chain
management
(GSCM),
when
moderated
by
BDA,
though
blockchain
technology
does
not
have
significant
effect.
Additionally,
GSCM
found
positively
influence
environmental
dimensions
development,
mediating
relationship
these
sustainability
outcomes.
provides
valuable
insights
practitioners
policymakers,
emphasizing
critical
role
BDA
fostering
especially
within
Egyptian
sectors.
