Journal of Engineering Design and Technology,
Год журнала:
2024,
Номер
unknown
Опубликована: Март 19, 2024
Purpose
The
circular
economy
business
models
(CEBMs)
provide
ways
for
firms
operating
in
the
construction
industry
to
move
from
a
linear
approach.
Thus,
this
study
aims
explore
CEBM
research
within
sector
show
focus
area
of
studies,
highlighting
new
areas
that
require
attention.
Design/methodology/approach
This
adopted
bibliometric
approach,
using
Scopus
database
as
data
source.
keywords
used
paper
extraction
were
“circular
business”
OR
AND
“model”
“models”
“construction
industry”
“building
industry”.
VOSviewer
software
was
then
prepare
co-occurrence
and
co-authorship
map
based
on
bibliographic
gathered.
Findings
study’s
findings
reveal
five
clusters
industry.
These
include
intelligence,
modular
modelling,
eco-construction,
sustainable
economics
smart
energy-efficient
buildings.
two
most
cited
scholars
had
publications
each,
while
top
journals
are
Journal
Cleaner
Production
Sustainable
Consumption
.
concludes
there
is
need
CEBMs’
archetypes
frameworks.
will
enable
smooth
transition
sector.
Research
limitations/implications
information
gathered
single
database,
Scopus;
hence,
other
databases,
including
Web
Science,
Google
Scholar
Dimensions,
might
produce
more
articles
examination
and,
consequently,
different
subject
under
investigation.
Practical
implications
would
assist
researchers
considering
mentioned,
which
yet
receive
attention,
by
extension,
enhance
economic
development
maintaining
environmental
sustainability.
Originality/value
made
significant
contribution
body
knowledge
identifying
platforms
have
been
instrumental
advancing
attention
Developments in the Built Environment,
Год журнала:
2023,
Номер
17, С. 100300 - 100300
Опубликована: Дек. 12, 2023
Large
Language
Models
(LLMs)
trained
on
large
data
sets
came
into
prominence
in
2018
after
Google
introduced
BERT.
Subsequently,
different
LLMs
such
as
GPT
models
from
OpenAI
have
been
released.
These
perform
well
diverse
tasks
and
gaining
widespread
applications
fields
business
education.
However,
little
is
known
about
the
opportunities
challenges
of
using
construction
industry.
Thus,
this
study
aims
to
assess
A
critical
review,
expert
discussion
case
validation
are
employed
achieve
study's
objectives.
The
findings
revealed
for
throughout
project
lifecycle.
leveraging
highlighted
a
use
prototype
developed
materials
selection
optimization.
would
be
benefit
researchers,
practitioners
stakeholders,
it
presents
research
vistas
Smart and Sustainable Built Environment,
Год журнала:
2023,
Номер
13(1), С. 85 - 116
Опубликована: Июль 26, 2023
Purpose
This
study
aims
to
investigate
the
literature
related
use
of
digital
technologies
for
promoting
circular
economy
(CE)
in
construction
industry.
Design/methodology/approach
A
comprehensive
approach
was
adopted,
involving
bibliometric
analysis,
text-mining
analysis
and
content
meet
three
objectives
(1)
unveil
evolutionary
progress
field,
(2)
identify
key
research
themes
field
(3)
challenges
hindering
implementation
CE.
Findings
total
365
publications
analysed.
The
results
revealed
eight
categorised
into
two
main
clusters
including
“digitalisation
advanced
technologies”
“sustainable
technologies”.
former
involved
technologies,
namely
machine
learning,
artificial
intelligence,
deep
big
data
analytics
object
detection
computer
vision
that
were
used
forecasting
demolition
(C&D)
waste
generation,
identification
classification
management.
latter
included
such
as
Internet
Things
(IoT),
blockchain
building
information
modelling
(BIM)
help
optimise
resource
use,
enhance
transparency
sustainability
practices
Overall,
these
show
great
potential
improving
management
enabling
CE
construction.
Originality/value
employs
a
holistic
provide
status-quo
understanding
can
be
utilised
support
Further,
this
underlines
associated
with
adopting
whilst
also
offering
opportunities
future
improvement
field.
Buildings,
Год журнала:
2023,
Номер
13(5), С. 1164 - 1164
Опубликована: Апрель 28, 2023
A
building
faces
several
challenges
across
its
lifecycle
stages.
Challenges
such
as
production
inefficiency
and
inadequate
waste
management
hinder
advancement
in
the
construction
industry.
Furthermore,
sector
has
emerged
one
of
largest
producers
world,
which
can
lead
to
detrimental
impacts
on
economy
environment.
Conventional
approaches
are
insufficient
eradicate
these
concerns.
Thus,
practitioners
have
sought
implement
novel
methods
ameliorate
process.
In
this
regard,
design
for
manufacturing
assembly
(DfMA)
deconstruction
(DfD)
gained
prominence,
studies
elucidated
methods’
unprecedented
potential
wholly
transform
process
mitigate
unwanted
brought
about
by
This
study
identified
applications
benefits
DfMA
DfD
construction,
well
recent
developments
research
gaps,
through
a
literature
review,
using
Scopus
primary
database
MATLAB
conducting
data
text
analytics.
The
current
body
knowledge
necessitates
further
assessment
following
gaps:
(1)
development
standard
construction-oriented
guidelines;
(2)
corroboration
developed
tools
practical
application;
(3)
integration
holistic
with
emerging
technologies,
additive
digital
fabrication;
(4)
comparison
structures
constructed
built
conventional
approaches;
(5)
comprehensive
application
guidelines
structural
systems;
(6)
DfD;
(7)
execution
sustainability
evaluate
impact
(8)
identification
solutions
barriers
uptake
construction.
Journal of Environmental Management,
Год журнала:
2024,
Номер
351, С. 119908 - 119908
Опубликована: Янв. 1, 2024
The
construction
industry
generates
a
substantial
volume
of
solid
waste,
often
destinated
for
landfills,
causing
significant
environmental
pollution.
Waste
recycling
is
decisive
in
managing
waste
yet
challenging
due
to
labor-intensive
sorting
processes
and
the
diverse
forms
waste.
Deep
learning
(DL)
models
have
made
remarkable
strides
automating
domestic
recognition
sorting.
However,
application
DL
recognize
derived
from
construction,
renovation,
demolition
(CRD)
activities
remains
limited
context-specific
studies
conducted
previous
research.
This
paper
aims
realistically
capture
complexity
streams
CRD
context.
study
encompasses
collecting
annotating
images
real-world,
uncontrolled
environments.
It
then
evaluates
performance
state-of-the-art
automatically
recognizing
in-the-wild.
Several
pre-trained
networks
are
utilized
perform
effectual
feature
extraction
transfer
during
model
training.
results
demonstrated
that
models,
whether
integrated
with
larger
or
lightweight
backbone
can
composition
in-the-wild
which
useful
automated
outcome
emphasized
applicability
across
various
industrial
domains,
thereby
contributing
resource
recovery
encouraging
management
efforts.
Buildings,
Год журнала:
2024,
Номер
14(1), С. 281 - 281
Опубликована: Янв. 19, 2024
Building
construction
accounts
for
a
significant
proportion
of
global
greenhouse
gas
emissions,
raw
material
extraction,
and
waste
production.
Applying
circular
economy
(CE)
principles
in
the
building
industry
would
considerably
reduce
these
values.
However,
uptake
by
is
relatively
slow,
which
largely
attributed
to
sectoral
barriers,
including
limitations
knowledge
experience.
This
review
paper
aims
assess
contribute
diminishing
obstacles
offering
comprehensive
usage
strategies
within
sector.
Opportunities
facilitators
change
are
also
presented,
innovations
emerging
technologies
recycling,
digitization,
robotic
systems,
novel
materials,
processing.
Finally,
four
case
studies
demonstrate
application
theory
via
block
system,
recycled
aggregate,
modular
kitchen
reuse,
an
energy
efficiency
retrofit.
The
conclusions
show
that
future
efforts
should
prioritize
development
strong
regulatory
frameworks,
awareness
initiatives,
international
cooperation.
In
this
regard,
integration
technological
advancements,
such
as
AI,
robotics,
blockchain,
essential
optimizing
management
efficiency.
Furthermore,
education
on
practices
plays
critical
role.
Through
collaboration,
standardizing
approaches
can
promote
more
sustainable
resilient
industry.
