Geomatics and Environmental Engineering,
Год журнала:
2021,
Номер
15(4), С. 59 - 80
Опубликована: Сен. 17, 2021
The
COVID-19
pandemic
represents
a
combined
supply
and
demand
shock
to
the
financial
housing
market
but
also
an
unusual
negative
in
terms
of
health
society
(households)
national
economy.
fall
was
initially
assumed
together
with
price
decreases
as
consequence
uncertainty
society,
significant
falls
stock
markets
corporate
solvency.
However,
results
research
selected
Polish
cities
do
not
indicate
such
recession.
This
article
examines
dynamics
forecasting
during
pandemic.
TRAMO/SEATS
ARIMA
models
were
used
for
decomposition
dwelling
time
series.
market,
represented
by
local
markets,
still
shows
growing
trend
despite
throughout
2020.
may
slow
down
2021,
strong
forecasted
growth
trends
Warszawa
Poznań
suggest
that
there
will
be
no
decline
Poland
near
future.
Land,
Год журнала:
2022,
Номер
11(11), С. 2100 - 2100
Опубликована: Ноя. 21, 2022
Machine
learning
algorithms
are
being
used
for
multiple
real-life
applications
and
in
research.
As
a
consequence
of
digital
technology,
large
structured
georeferenced
datasets
now
more
widely
available,
facilitating
the
use
these
to
analyze
identify
patterns,
as
well
make
predictions
that
help
users
decision
making.
This
research
aims
best
machine
predict
house
prices,
quantify
impact
COVID-19
pandemic
on
prices
Spanish
city.
The
methodology
addresses
phases
data
preparation,
feature
engineering,
hyperparameter
training
optimization,
model
evaluation
selection,
finally
interpretation.
Ensemble
based
boosting
(Gradient
Boosting
Regressor,
Extreme
Gradient
Boosting,
Light
Machine)
bagging
(random
forest
extra-trees
regressor)
compared
with
linear
regression
model.
A
case
study
is
developed
microdata
real
estate
market
Alicante
(Spain),
before
after
declaration
derived
from
COVID-19,
together
information
other
complementary
sources
such
cadastre,
socio-demographic
economic
indicators,
satellite
images.
results
show
perform
better
than
traditional
models
because
they
adapted
nonlinearities
complex
data.
Algorithms
overfitting
problems
those
have
performance
lower
overfitting.
contributes
literature
by
one
first
studies
explore
incidence
prices.
Sustainability,
Год журнала:
2021,
Номер
13(21), С. 12277 - 12277
Опубликована: Ноя. 7, 2021
While
it
is
well-known
that
housing
prices
generally
increased
in
the
United
States
(U.S.)
during
COVID-19
pandemic
crisis,
to
best
of
our
knowledge,
there
has
been
no
research
conducted
understand
spatial
patterns
and
heterogeneity
price
changes
U.S.
real
estate
market
crisis.
There
less
attention
on
consequences
this
pandemic,
terms
distribution
The
objective
study
was
explore
heterogeneous
change
rates
across
different
areas
pandemic.
We
calculated
global
Moran’s
I,
Anselin’s
local
Getis-Ord’s
Gi∗
statistics
2856
counties.
following
two
major
findings
were
obtained:
(1)
influence
crisis
varied
space
not
only
differed
from
metropolitan
rural
areas,
but
also
one
area
another.
(2)
It
seems
made
Americans
more
cautious
about
buying
property
densely
populated
urban
downtowns
had
higher
levels
virus
infection;
therefore,
found
year
2020–2021,
hot
spots
typically
located
affordable
suburbs,
smaller
cities,
away
high-cost,
high-density
downtowns.
This
may
be
helpful
for
understanding
relationship
between
market,
as
well
human
behaviors
response
Sustainability,
Год журнала:
2021,
Номер
13(13), С. 7420 - 7420
Опубликована: Июль 2, 2021
Aspects
of
sustainable
construction
investment
and
real
estate
development
(CIRED)
their
interrelations
during
the
period
pre-,
intra-,
post-COVID-19,
are
presented
in
research.
Applications
topic
model,
environmental
psychology
theory,
building
life
cycle
method,
certain
elements
bibliometrics,
webometrics,
article
level
metrics,
altmetrics,
scientometrics
make
it
possible
to
perform
a
quantitative
analysis
on
CIRED.
The
CIRED
model
was
developed
seven
steps.
This
paper
aims
present
literature
review
throughout
pandemic
look
at
responses
from
sector.
sector
is
field
that
appears
be
rapidly
expanding,
judging
volume
current
research
papers.
focuses
last
year’s
leading
peer-reviewed
journals.
A
combination
various
keywords
applied
for
criteria
selections
included
investment,
development,
civil
engineering,
COVID-19,
sustainability,
as
well
residential,
industrial,
commercial,
land,
special
purpose
estate,
along
with
risks,
strategies,
trends.
articles
reviewed
this
paper,
which
analyzes
three
hypotheses,
post-pandemic
hypotheses
were
validated
by
analyzing
scientific
publications
around
world.
Two
innovative
study
stand
out
among
most
advanced
first
two
innovations
integrated
COVID-19
pandemic,
COVID-19-related
national
policies,
business
strategies
relevant
interests
investors
impact
policy
spread
COVID-19.
In
addition,
demonstrates
marked
increase
effectiveness
analysis,
when
CIRED,
involved
stakeholders
own
individual
interests,
situation,
external
micro-,
meso-,
macro-environments
covered
comprehensively
single
entity.
Environment and Planning B Urban Analytics and City Science,
Год журнала:
2022,
Номер
49(6), С. 1646 - 1662
Опубликована: Янв. 4, 2022
How
the
COVID-19
pandemic
has
altered
segmentation
of
residential
rental
markets
is
largely
unknown.
We
therefore
assessed
housing
submarkets
before
and
during
in
Cracow,
Poland.
used
geographically
temporally
weighted
regression
to
investigate
marginal
prices
attributes
over
space–time.
The
were
further
reduced
a
few
principal
components
per
time
period
spatially
clustered
identify
submarkets.
Finally,
we
applied
adjusted
Rand
index
evaluate
spatiotemporal
stability
results
revealed
that
outbreak
significantly
lowered
rents
modified
relevance
some
characteristics
for
prices.
Proximity
university
was
no
longer
among
amenities
pandemic.
Similarly,
virus
diminished
effect
unit’s
proximity
city
center.
market
partitioning
showed
number
Cracow’s
increased
as
result
pandemic,
it
enhanced
spatial
variation
covariates.
Our
findings
suggest
emergence
coronavirus
reshaped
three
ways:
Rents
decreased,
underlying
price-determining
factors
changed,
submarket
structure
altered.
Land Use Policy,
Год журнала:
2022,
Номер
119, С. 106191 - 106191
Опубликована: Май 27, 2022
The
ongoing
pandemic
has
led
to
substantial
volatility
in
residential
housing
markets.
However,
relatively
little
is
known
about
whether
the
dominated
by
demand
or
supply,
and
how
different
priced
markets
contribute
volatility.
This
article
first
examines
temporal
effect
of
COVID-19
on
house
prices,
demand,
supply
Los
Angeles,
second
explores
heterogeneity
luxury
low-end
within
city.
For
identification,
employs
a
revised
difference-in-differences
(DID)
method
that
controls
more
rigorously
for
unobservables
improves
traditional
DID
with
smaller
prior
trends.
Using
individual
level
data,
result
shows
that,
response
outbreak,
all
decreased
March
May
2020
increased
July
August
2020,
dominating
process.
Second,
exploration
identifies
diverging
impacts
higher-
lower-
Particularly,
decline
overall
price
before
June
originates
mainly
from
lower-priced
market
while
higher-priced
one
experienced
limited
changes
demand.
After
July,
market's
surge
price,
whereas
not
fully
recovered
decreases
prices
Finally,
larger
found
be
associated
higher
service
shares
lower
homeownership
rates.
results
only
facilitate
participants
their
decision
making
but
also
aid
local
governments
formulating
policies
allocating
subsidies
mitigate
effects
outbreak.
Journal of Urban Management,
Год журнала:
2023,
Номер
12(3), С. 268 - 283
Опубликована: Июль 5, 2023
The
COVID-19
pandemic
has
affected
various
aspects
of
people's
lives,
including
housing.
Research
argued
that
the
economic
impact
includes
stagnancy
in
real
estate
markets.
Similarly,
Indonesian
real-estate
market
players
have
reported
declining
demand
for
high-rise
and
dense
multi-unit
residential
buildings
favor
landed
houses
during
pandemic.
However,
it
not
yet
included
customers'
perspective
analysis,
which
raises
a
question
whether
there
been
change
preferences
types
housing
caused
by
This
paper
aims
to
provide
scientific
discourse
on
topic
using
explanatory
quantitative
method.
research
sampled
over
380
respondents
from
customers
2020.
data
were
analyzed
binary
logistic
regression
calculations.
result
suggests
increases
need
control
living
space
affect
respondents'
preferences.
Factors
this
phenomenon
include
fear
meeting
people
recessions;
are
direct
impacts
