Evaluating consumer shopping, delivery demands, and last-mile preferences: An integrated MDCEV-HCM approach
Transportation Research Part E Logistics and Transportation Review,
Journal Year:
2025,
Volume and Issue:
197, P. 104067 - 104067
Published: March 16, 2025
Language: Английский
Resident Preferences for Urban Green Spaces in Response to Pandemic Public Health Emergency: A Case Study of Shanghai
Yonggeng Xiong,
No information about this author
Min Xu,
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Yan Zhao
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et al.
Sustainability,
Journal Year:
2024,
Volume and Issue:
16(9), P. 3738 - 3738
Published: April 29, 2024
The
COVID-19
pandemic
represents
a
quintessential
public
health
crisis,
profoundly
impacting
the
utilization
patterns
of
urban
green
spaces
through
stringent
quarantine
and
lockdown
measures.
However,
existing
research
inadequately
addresses
specific
concerns
regarding
future
tends
to
oversimplify
population
divisions.
This
study
delves
into
needs
preferences
Shanghai
residents
affected
by
measures,
focusing
on
various
aspects
such
as
types
spaces,
facilities,
landscape
elements,
spatial
types.
Multifactorial
clustering
was
also
performed.
delineates
following
conclusions:
(1)
It
is
imperative
afford
access
at
least
once
week,
even
during
periods.
(2)
Residents
exhibited
preference
for
accessible
equipped
with
essential
amenities,
favoring
unobstructed
vistas
plant-centric
ecological
landscapes
pandemic.
Additionally,
there
notable
private
among
residents.
(3)
Post-pandemic,
“affluent”
group
displays
heightened
overall
demand
“middle-class”
shows
conspicuous
inclination
towards
space
while
“low-income”
consistently
exhibits
low
after
underscores
necessity
developing
human-centric
promote
equity
resilience
in
face
emergencies,
rooted
residents’
amidst
crises.
Language: Английский
Temporal Stability of Factors Affecting Residents’ Non-Commuting Travel Behavior across Different Stages of a Sudden and Localized Outbreak of COVID-19
Xinwei Ma,
No information about this author
Ying Shen,
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Zhenhao Liu
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et al.
Transportation Research Record Journal of the Transportation Research Board,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 27, 2025
People’s
attitudinal
shifts
toward
an
epidemic
at
different
stages
of
the
affect
their
travel
behavior.
Non-commuting
behavior
is
more
variable
than
commuting,
as
non-commuters
have
options.
However,
few
studies
explored
changes
in
non-commuting
and
its
influencing
factors
across
sudden
localized
COVID-19
outbreaks.
Using
survey
data
collected
Nanjing,
China,
where
there
was
a
outbreak
COVID-19,
this
research
adopted
random
parameter
ordered
logit
model
with
heterogeneity
means
variances
(HMV)
to
explore
early,
middle,
late
stages.
The
results
revealed
that
considering
HMV
would
improve
fitness.
In
addition,
temporal
stability
investigated
via
likelihood
ratio
test,
which
confirms
traveler
behavioral
differences
showed
“e-bike
ownership”
“the
number
PCR
(polymerase
chain
reaction)
tests”
positively
correlated
trips
over
three
variables
“people
who
live
together
red
health
code,”“mask
replacement
frequency,”
“risk-free
areas”
are
significant
early-stage
middle-stage
models.
green
code
all
time”
only
become
late-stage
model.
Research
findings
contribute
understanding
behaviors
targeted
management
needs
during
local
outbreaks,
can
help
government
address
issues
under
future
major
events.
Language: Английский
The battery-swapping revolution: Exploring user preferences in electric micro-mobility sector
Fan Zhang,
No information about this author
Huitao Lv,
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Chenchen Kuai
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et al.
Transportation Research Part A Policy and Practice,
Journal Year:
2025,
Volume and Issue:
194, P. 104416 - 104416
Published: Feb. 17, 2025
Language: Английский
How does Bike Absence Influence Mode Shifts Among Dockless Bike-Sharing Users? Evidence From Nanjing, China
Hongjun Cui,
No information about this author
Zhixiao Ren,
No information about this author
Xinwei Ma
No information about this author
et al.
Transportation Research Record Journal of the Transportation Research Board,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 24, 2025
Dockless
bike-sharing
users
often
encounter
difficulties
in
finding
available
bikes
at
their
preferred
times
and
locations.
This
study
examines
the
determinants
of
users’
mode
shifts
context
bike
absence,
using
survey
data
from
Nanjing,
China.
An
integrated
choice
latent
variable
model
based
on
multinomial
logit
was
employed
to
investigate
impact
socio-demographic
characteristics,
trip
attributes,
psychological
factors
travel
choices.
Mode
models
were
estimated
with
seven
alternatives,
including
bike-sharing-related
choices
(i.e.,
waiting
place,
picking
up
way,
a
detour),
bus,
taxi,
riding
hailing,
walking.
The
findings
showed
that
under
shared-bike
unavailability,
pick
way
rather
than
take
detours,
buses
walking
as
favored
alternatives
shared
bikes.
Lower-educated
tended
wait
showing
greater
concern
for
time
compared
time.
Lower-income
users,
commuters,
females
whereas
noncommuters
males
opted
detours.
insights
gained
this
could
provide
ideas
solving
problems
demand
estimation,
parking
area
siting,
developing
multimodal
synergies
sharing
enhance
utilization
user
satisfaction.
Language: Английский
Modeling Real Demand in Dockless Bike-Sharing Systems: Integrating User Preferences and Behavioral Insights
Zhixiao Ren,
No information about this author
Hongjun Cui,
No information about this author
Xinwei Ma
No information about this author
et al.
Journal of Transportation Engineering Part A Systems,
Journal Year:
2025,
Volume and Issue:
151(7)
Published: April 29, 2025
Language: Английский
Incorporating mobile phone data-based travel mobility analysis of metro ridership in aboveground and underground layers
Jiping Xing,
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Xiaohong Jiang,
No information about this author
Yu Yuan
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et al.
Electronic Research Archive,
Journal Year:
2024,
Volume and Issue:
32(7), P. 4472 - 4494
Published: Jan. 1, 2024
<p>Metro
transit
is
the
core
of
urban
transportation,
and
mobility
analysis
metro
ridership
can
contribute
to
enhance
overall
service
level
transit.
Researchers
studying
are
focused
on
spatiotemporal
distribution
characteristics
in
underground
system
station
by
smart
card
data.
However,
limited
lack
travel
chain
integrity,
their
activity
patterns
cannot
be
used
identify
heterogeneity
ridership's
origin
transfer
mode.
In
our
research,
we
applied
full
coverage
mobile
phone
data
complete
perspective
ground
First,
boarding
alighting
stations
was
extracted
order
then
extracted.
Second,
relying
flow
identification
method,
aboveground
destination
outside
were
extracted,
transferred
traffic
mode
identified.
The
empirical
results
have
shown
that
proposed
framework
accurately
analyze
an
area
station.</p>
Language: Английский
The Effects of the COVID-19 Pandemic on the Modal Shifting Utilising a Latent Class Choice Model with Covariates
PROMET - Traffic&Transportation,
Journal Year:
2024,
Volume and Issue:
36(3), P. 399 - 414
Published: June 20, 2024
The
COVID-19
pandemic
has
posed
significant
challenges
to
global
public
health
organisations
and
governments,
leading
countermeasures
like
hand
sanitizer
availability,
social
distancing,
mandatory
face
mask
wearing,
which
have
disrupted
the
transportation
sector
impacted
virus
spread.
Anticipating
effects
of
circumstances
a
on
mobility
is
essential
for
operators
managers
systems
effectively
safely
manage
system.
In
this
study,
measures
taken
during
pandemic,
such
as
those
mentioned
above,
were
considered
indicators
in
latent
class
model
(LCM)
modal
shifting.
incorporates
sociodemographic
variables
covariates
understand
their
impact
shifting
from
transport
private
cars.
An
online
survey
with
53,973
valid
responses
was
conducted
Istanbul,
Turkiye.
As
result
LCM
covariates,
two-latent-class
model,
best
fit
among
models
ranging
two
six
classes,
emerged.
Class-1
participants
show
increased
sensitivity
mode,
while
Class-2
are
less
concerned
tend
maintain
existing
mode.
suggests
using
estimate
shift
cars
any
given
situation.
Language: Английский
Commuting Behavior Changes at Different Stages of Localized COVID-19 Outbreak: Evidence from Nanjing, China
Pei‐Yu Chen,
No information about this author
Tom Wu,
No information about this author
Yurui Yin
No information about this author
et al.
Systems,
Journal Year:
2024,
Volume and Issue:
12(8), P. 271 - 271
Published: July 28, 2024
Commuting
behaviors
have
been
changed
by
the
COVID-19
pandemic.
To
investigate
impacts
at
different
stages
of
sudden
and
localized
outbreak,
this
paper
carries
out
an
online
survey
to
obtain
data,
targeting
residents
in
Nanjing
China,
where
there
had
outbreaks
proposes
a
sequential
analysis
method
calculate
complexity
commuting
behavior
changes.
The
Tobit
model
is
used
explore
factors
that
influence
Results
show
commuters
using
public
transportation
drop
significantly
when
occur,
with
43.5%
them
switching
private
cars
or
working
from
home.
number
home
increases
14
times.
While
outbreak
gradually
subsides,
modes
tend
recover,
but
does
not
immediately
return
state
before
outbreak.
Regression
results
indicate
aged
40–60
maintain
their
habits,
while
younger
workers
are
more
flexible
on
options.
Middle-income
commuters,
those
living
low-risk
areas
near
subway
within
800
m
prefer
change
modes,
opting
for
what
they
perceive
be
safer
ways
commute.
For
medium-
high-risk
who
people
non-green
health
codes,
adjust
real
time
based
color
codes
risk
level
live.
research
findings
contribute
our
understanding
targeted
management
needs
during
local
outbreaks,
can
help
government
formulate
comprehensive
effective
pandemic
prevention
policy.
Language: Английский