Human development welfare of renewable energy technology innovation under carbon reduction targets
Technology Analysis and Strategic Management,
Год журнала:
2025,
Номер
unknown, С. 1 - 17
Опубликована: Фев. 3, 2025
Язык: Английский
Exploring the enablers for building resilience in solar photovoltaic Energy supply chains
Operations Management Research,
Год журнала:
2024,
Номер
unknown
Опубликована: Май 21, 2024
Abstract
A
solar
photovoltaic
energy
supply
chain
(SPvESC)
is
a
global
network
with
several
linkages,
including
mineral
and
metal
mining,
material
processing,
module
panel
manufacturing.
Due
to
the
wide
range
of
uncertainties
unfavorable
environmental
effects
associated
current
linear
business
models,
this
vulnerable
disruptions.
Strengthening
resilience
SPvESCs
crucial
for
addressing
any
disturbances.
This
requires
identifying
key
enablers
in
SPvESCs,
an
area
that
has
been
understudied
existing
literature.
An
enabler
aspect
facilitates
achievement
goal
by
another
aspect.
research
contributes
literature
systematically
investigating
achieve
resilience.
Thus,
objective
analysis
identify
have
potential
enhance
Türkiye.
was
done
applying
Nominal
Group
Technique
(NGT)
conjunction
review
Neutrosophic
(N)-DEMATEL
then
utilized
determine
relationships
between
identified
enablers.
Finally,
results
were
validated
using
N-DELPHI.
The
revealed
sensing
seizing
new
adaptability
changes
novel
generation
information
technologies,
contingency
plans
natural
man-made
disasters
most
influential
findings
provide
implications
practitioners,
policymakers,
researchers
help
ensure
improved
SPvESCs.
Язык: Английский
Forecasting Green Technology Diffusion in OECD Economies Through Machine Learning Analysis
Ekonomi Politika ve Finans Arastirmalari Dergisi,
Год журнала:
2024,
Номер
9(3), С. 484 - 502
Опубликована: Сен. 30, 2024
An
accelerating
global
shift
towards
sustainable
development
has
made
the
diffusion
of
green
technologies
a
critical
area
focus,
particularly
within
OECD
economies.
This
study
aims
to
use
machine-learning
approach
explore
future
technology
across
countries.
It
provides
detailed
forecasts
from
2023
2037,
highlighting
varying
rates
(GTD)
among
different
nations.
To
achieve
this,
Autoregressive
Integrated
Moving
Average
(ARIMA)
model
is
employed
offer
new
evidence
on
how
progress
can
be
predicted.
Based
empirical
data,
categorizes
countries
into
high,
moderate,
and
low
GTD
growth.
The
findings
suggest
that
Japan,
Germany,
USA
will
experience
significant
growth
in
GTD,
while
like
Australia,
Canada,
Mexico
see
moderate
increases.
Conversely,
some
nations,
including
Ireland
Iceland,
face
challenges
with
or
negative
values.
concludes
applying
this
valuable
insights
predictions
for
policymakers
aiming
enhance
adoption
their
respective
Язык: Английский
Identifying the Key Drivers in Energy Technology Fields: The Role of Spillovers and Public Policies
Sustainability,
Год журнала:
2024,
Номер
16(20), С. 8875 - 8875
Опубликована: Окт. 14, 2024
This
study
investigates
the
salient
roles
of
knowledge
spillover
and
environmental
policies
on
clean
technology
innovation.
Employing
a
panel
vector
autoregressive
model
(PVAR)
connectedness
network
analysis
with
comprehensive
longitudinal
dataset
comprising
100
million
patent
documents
across
26
countries,
identifies
fields
that
are
most
efficient
in
driving
innovation
subsequently
quantifies
effects
for
each
field.
The
impact
public
regulations
technological
innovations
is
also
examined
depth.
results
reveal
complex
nuanced
system,
significant
spillovers
occurring
within
energy
non-energy-related
fields.
show
significantly
influence
innovation,
support
adoption
having
substantial
impact.
Furthermore,
market-based
weaker
than
non-market-based
policies,
which
an
important
consideration
policymakers.
findings
hold
significance
policymakers
addressing
sustainability
goals
their
implications.
Язык: Английский