Total Quality Management & Business Excellence,
Год журнала:
2024,
Номер
unknown, С. 1 - 33
Опубликована: Дек. 23, 2024
Purpose:
This
study
investigated
the
potential
for
optimising
environmental,
social,
and
governance
(ESG)-enhanced
organisational
performance
through
integration
of
Lean,
Six
Sigma,
Kaizen,
operational
excellence
(OpEx),
most
used
continuous
improvement
methodologies.
identified
common
themes
within
these
methodologies,
focusing
on
their
collective
impact
ESG
performance,
pinpointed
gaps
in
existing
literature,
outlined
a
comprehensive
agenda
future
research
holistic
effectiveness
methodologies
maximising
outcomes.
Business Strategy and the Environment,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 7, 2024
Abstract
The
present
study
evaluates
how
the
joint
implementation
of
circular
economy
(CE)
and
operational
excellence
(OE)
practices
supported
by
adoption
industry
4.0
technologies
(Internet
Things
Big
Data
Analytics)
influence
manufacturing
firms'
performance
environmental
sustainability.
Drawing
from
paradox
theory,
it
also
investigates
moderating
role
managing
paradoxical
tensions
arising
these
implementations.
To
test
hypothesized
relationships,
survey
data
are
collected
147
Indian
firms
implementing
CE,
OE
practices,
internet
things
(IoT)
big
analytics
(BDA)‐enabled
digital
systems.
analyzed
using
structural
equation
modeling
moderated
mediation
analysis.
Results
indicate
a
direct
significant
effect
IoT
BDA‐enabled
systems
on
sustainability,
partial
CE
implementations,
respectively.
There
is
strong
moderation
impact
implementations
performance.
Additionally,
conditional
indirect
sustainability
outcomes
BDA
increases
with
greater
effort
in
tensions.
answers
call
for
empirical
research
organizational
that
surface
due
to
conflicting
demands
initiatives
related
efficiency
Research Square (Research Square),
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 10, 2025
Abstract
Manufacturing
industries
across
the
globe
are
undergoing
a
digital
transformation
that
demands
both
efficiency
and
sustainability.
Industry
4.0
(I4.0)
Lean
(L4.0)
methodologies
have
become
focal
points
in
these
efforts.
Despite
widespread
recognition
of
benefits
integrating
L4.0
I4.0,
more
studies
need
to
address
practical
challenges
this
integration,
especially
key
factors
influence
its
successful
implementation.
Small
medium-sized
enterprises
(SMEs)
emerging
economies
often
face
significant
practices
due
resource
limitations
complex
operational
challenges.
This
study
bridges
critical
research
gap
by
proposing
an
integrated
framework
combines
Artificial
Neural
Networks
(ANN)
with
fuzzy
Interpretive
Structural
Modeling
(FISM)
identify
prioritise
success
(CSFs)
for
adoption.
A
survey
216
manufacturing
SMEs
was
used
validate
CSFs
through
Exploratory
Factor
Analysis
(EFA).
The
ANN
analysis
revealed
Process
Factors
highest
normalised
importance
(NI)
100%,
followed
Organizational
(NI
=
60.46%),
Human
58.93%),
Technological
43.21%),
External
42.13%),
Environmental
39.63%).
Complementary
FISM
Cross-Impact
Matrix
Multiplication
Applied
Classification
(MICMAC)
analyses
further
structured
relationships,
underscoring
roles
Change
Management,
Culture,
Waste
Reduction,
Regulatory
Compliance.
These
findings
offer
theoretical
advancement
understanding
CSF
interactions
guidance
striving
achieve
sustainable
practices.
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Май 18, 2025
Manufacturing
industries
across
the
globe
are
undergoing
a
digital
transformation
that
demands
both
efficiency
and
sustainability.
Industry
4.0
(I4.0)
Lean
(L4.0)
methodologies
have
become
focal
points
in
these
efforts.
Despite
widespread
recognition
of
benefits
integrating
L4.0
I4.0,
more
studies
need
to
address
practical
challenges
this
integration,
especially
key
factors
influence
its
successful
implementation.
Small
medium-sized
enterprises
(SMEs)
emerging
economies
often
face
significant
practices
due
resource
limitations
complex
operational
challenges.
This
study
bridges
critical
research
gap
by
proposing
an
integrated
framework
combines
Artificial
Neural
Networks
(ANN)
with
fuzzy
Interpretive
Structural
Modeling
(FISM)
identify
prioritise
success
(CSFs)
for
adoption.
A
survey
216
manufacturing
SMEs
was
used
validate
CSFs
through
Exploratory
Factor
Analysis
(EFA).
The
ANN
analysis
revealed
Process
Factors
highest
normalised
importance
(NI)
100%,
followed
Organizational
(NI
=
60.46%),
Human
58.93%),
Technological
43.21%),
External
42.13%),
Environmental
39.63%).
Complementary
FISM
Cross-Impact
Matrix
Multiplication
Applied
Classification
(MICMAC)
analyses
further
structured
relationships,
underscoring
roles
Change
Management,
Culture,
Waste
Reduction,
Regulatory
Compliance.
These
findings
offer
theoretical
advancement
understanding
CSF
interactions
guidance
striving
achieve
sustainable
practices.
Business Strategy and the Environment,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 19, 2025
ABSTRACT
The
study
examines
the
link
among
Industry
4.0
(I4.0)
technologies,
environmental
orientation,
organizational
flexibility,
and
circular
economy
(
CE
)
to
drive
sustainability.
To
ascertain
these
links,
we
analyze
responses
of
managers
working
in
manufacturing
sector
India
using
PLS‐SEM.
Relying
on
resource‐based
view
(RBV),
our
findings
confirmed
that
I4.0
complement
each
other
achieve
Further,
orientation
mediate
between
sustainable
performance.
Additionally,
sequential
mediation
indicates
(i)
flexibility
(ii)
sequentially
This
sheds
light
interrelation
identified
factors
provides
actionable
insights
for
firms
seeking
improve
sustainability
suggest
integration
technologies
practices,
supported
by
can
significant
improvements.
offers
pivotal
managerial
implications
strategically
aligning
digital
transformation
initiatives.
Business Strategy and the Environment,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 24, 2024
ABSTRACT
Regulatory
authorities
are
putting
a
lot
of
pressure
on
manufacturers
to
devise
strategies
boost
their
contribution
the
circular
economy.
The
limited
comprehension
surrounding
complex
interplay
that
exists
between
deployment
Industry
4.0
(I4.0)
strategies,
capability
acquire
information,
and
ability
balance
exploration
exploitation
activities
within
an
organization
acts
as
barrier
for
attain
optimal
levels
organizational
performance.
As
result,
purpose
current
investigation
is
investigate
strategic
execution
I4.0
manufacturers'
information
acquisition
in
order
foster
ambidexterity
required
flourish
innovation‐driven
high‐performance
ecosystem
attaining
economy
In
this
study,
data
from
cross‐sectional
survey
included
responses
sample
238
Indian
were
assessed
using
structural
equation
modeling.
According
results,
technologies
assist
organizations
strengthening
exploitative
explorative
capabilities,
allowing
them
achieve
success
innovation,
which
directly
related
performance
activities.
Unexpectedly,
association
organization's
its
innovation
not
substantial,
but
it
completely
mediated
by
both
characterized
ambidexterity.
Quality Management Journal,
Год журнала:
2024,
Номер
unknown, С. 1 - 13
Опубликована: Дек. 20, 2024
The
value
of
Industry
4.0
(I4.0)
production
is
often
assessed
without
considering
sustainability,
leading
to
incomplete
evaluations.
disconnect
between
quality
management
and
circular
economy
principles
hinders
efforts
enhance
resource
efficiency.
Additionally,
the
absence
holistic
methodologies
constrains
exploration
complex
connections
elements
sustainability
factors.
This
research
proposes
an
integrated
approach
measure
I4.0
production,
emphasizing
sustainability.
It
integrates
into
boost
efficiency
reduce
waste.
study
uses
Lean
Six
Sigma
Delphi
technique
identify
refine
elements,
which
are
then
mapped
alongside
factors
indices
using
adapted
interpretive
structural
modeling
(AISM).
provides
cluster
managers
with
insights
quality,
efficiency,
waste
reduction,
sustainable
practices,
fostering
a
paradigm
shift
toward
in
manufacturing
ecosystems.
International Journal of Innovative Science and Research Technology (IJISRT),
Год журнала:
2024,
Номер
unknown, С. 611 - 619
Опубликована: Сен. 21, 2024
This
literature
review
examines
the
relationship
between
Lean
manufacturing
practices
and
organizational
performance
across
various
industries.
By
analyzing
recent
research
from
2020
to
2024,
this
study
synthesizes
findings
on
key
practices,
their
implementation
challenges,
impact
different
aspects
of
performance.
The
highlights
evolving
nature
in
context
Industry
4.0
sustainable
manufacturing.
It
also
identifies
gaps
current
suggests
directions
for
future
studies.
indicate
that
while
generally
positively
influence
performance,
effectiveness
depends
factors
including
culture,
technological
turbulence,
integration
with
other
management
approaches.
