International Journal of Production Economics,
Год журнала:
2024,
Номер
274, С. 109324 - 109324
Опубликована: Июнь 25, 2024
This
study
investigates
digital
transformation
and
the
usability
of
emerging
technologies
in
policymaking.
Prior
studies
categorised
into
three
distinct
phases
digitisation,
digitalisation,
transformation.
They
mainly
focus
on
operational
or
functional
levels,
however,
this
considers
at
strategic
level.
Previous
confirmed
that
using
new
AI-based
will
enable
organisations
to
use
achieve
higher
efficiency.
A
novel
methodological
approach
for
policymaking
was
constructed
through
lens
organisational
learning
theory.
The
proposed
framework
validated
a
case
transportation
industry
small
municipality.
In
selected
study,
confirmatory
model
developed
tested
utilising
Structural
Equation
Modelling
with
data
collected
from
survey
494
local
stakeholders.
Artificial
Neural
Network
utilised
predict
then
identify
most
appropriate
policy
according
cost,
feasibility,
impact
criteria
amongst
six
policies
extracted
literature.
results
research
confirm
utilisation
decision-making
generative
AI
platform
level
outperforms
human
terms
applicability,
efficiency,
accuracy.
Sustainability,
Год журнала:
2025,
Номер
17(10), С. 4453 - 4453
Опубликована: Май 14, 2025
The
integration
of
Industry
4.0
and
Artificial
Intelligence
(AI)
technologies
has
redefined
global
supply
chain
operations,
with
increasing
emphasis
on
sustainability
as
a
strategic
priority.
Despite
this
evolution,
there
remains
significant
gap
in
the
literature
regarding
structured
prioritization
sustainability-related
indicators
influenced
by
digital
transformation.
This
study
addresses
that
identifying
ranking
key
enablers
across
environmental,
operational,
strategic,
social
dimensions
using
Best–Worst
Method
(BWM),
robust
multi-criteria
decision-making
(MCDM)
technique.
Based
expert
input
from
37
professionals
fields
management,
sustainability,
technologies,
twenty
were
evaluated
within
four
separate
thematic
groups.
Results
reveal
Emissions
Monitoring
Reduction
Energy
Efficiency
are
most
critical
environmental
dimension,
while
Supply
Chain
Traceability
Smart
Inventory
Management
dominate
operational
category.
Resilience
is
identified
top
factor,
Ethical
Sourcing
deemed
vital
standpoint.
These
findings
provide
actionable
insights
for
policymakers
practitioners,
supporting
data-driven
alignment
investments
goals.
research
contributes
to
both
academic
discourse
practical
frameworks
offering
replicable
approach
prioritizing
context
also
identifies
limitations
proposes
future
directions
enhance
sustainable
development
chains.
Journal of Organizational Change Management,
Год журнала:
2024,
Номер
37(5), С. 945 - 964
Опубликована: Апрель 27, 2024
Purpose
It
becomes
a
strategic
option
for
enterprises
to
upgrade
and
improve
supply
chain
efficiency
(SCE)
by
promoting
the
digital
transformation
(DT).
This
study
formulated
parallel
mediation
model
analyze
relationships
among
DT,
transparency
(SCT),
agility
(SCA)
SCE
reveal
how
DT
affects
through
of
SCT
SCA.
Design/methodology/approach
Three
paradigms,
i.e.
resource-based
view
(RBV),
dynamic
capability
(DCV)
structure-conduct-performance
(SCP)
were
employed
address
effects.
A
total
392
questionnaires
(samples)
from
port-hinterland
in
pilot
project
New
Land-Sea
Corridor
western
China
collected,
which
was
then
applied
formulate
structural
equation
(SEM)
verify
proposed
hypotheses.
Findings
The
results
confirmed
existences
mediating
effects
SCA
between
SCE.
On
one
hand,
direct
effect
on
is
not
significant
when
plays
jointly
impacts
other
play
positive
full
Research
limitations/implications
contributed
literature
changing
activities
processes.
Specifically,
it
highlighted
leads
via
activities.
In
addition,
this
specified
conditions
that
insignificant
has
reflects
SCE,
time
are
acting
Originality/value
By
integrating
insights
RBV,
DCV
SCP
clarified
mechanisms
provided
insight
role
relationship
novelty
extend
existing
provide
implications
future
research.
International Journal of Production Economics,
Год журнала:
2024,
Номер
274, С. 109324 - 109324
Опубликована: Июнь 25, 2024
This
study
investigates
digital
transformation
and
the
usability
of
emerging
technologies
in
policymaking.
Prior
studies
categorised
into
three
distinct
phases
digitisation,
digitalisation,
transformation.
They
mainly
focus
on
operational
or
functional
levels,
however,
this
considers
at
strategic
level.
Previous
confirmed
that
using
new
AI-based
will
enable
organisations
to
use
achieve
higher
efficiency.
A
novel
methodological
approach
for
policymaking
was
constructed
through
lens
organisational
learning
theory.
The
proposed
framework
validated
a
case
transportation
industry
small
municipality.
In
selected
study,
confirmatory
model
developed
tested
utilising
Structural
Equation
Modelling
with
data
collected
from
survey
494
local
stakeholders.
Artificial
Neural
Network
utilised
predict
then
identify
most
appropriate
policy
according
cost,
feasibility,
impact
criteria
amongst
six
policies
extracted
literature.
results
research
confirm
utilisation
decision-making
generative
AI
platform
level
outperforms
human
terms
applicability,
efficiency,
accuracy.
