2021 China Automation Congress (CAC),
Год журнала:
2023,
Номер
unknown, С. 8569 - 8574
Опубликована: Ноя. 17, 2023
Understanding
the
spatiotemporal
patterns
of
electric
vehicle
(EV)
drivers'
charging
behavior
is
an
essential
component
both
demand
management
and
public
infrastructure
planning.
However,
most
existing
studies
rely
on
relatively
small
samples
EV
behavior,
potentially
missing
complexity
heterogeneity
inherent
in
these
patterns.
To
address
this
limitation,
our
study
proposes
a
two-step
framework
that
uses
trajectory
state-of-charge
data
from
over
200,000
battery
vehicles
(BEVs)
operating
Shanghai,
China
month.
This
comprehensive
set
represents
all
actively
used
BEVs
city.
The
initial
step
involves
using
density-based
clustering
algorithm
to
differentiate
between
mobility
service
BEV
(MBEV)
drivers
(traditional
taxi
ridesourcing
drivers)
private
(PBEV)
drivers.
bases
distinction
criteria
such
as
daily
travel
distance,
variance
locations,
frequency.
Then,
Latent
Dirichlet
Allocation
models
are
estimated
separately
for
MBEV
PBEV
These
identify
36
unique
each
type
driver,
encompassing
6
spatial
temporal
results
underscore
major
differences
drivers,
within
groups
themselves,
terms
their
station
choices.
likely
reflect
distinct
needs
preferences.
not
only
offers
analysis
megacity,
but
also
lays
groundwork
developing
more
driver-centered
strategies
Journal of Tourism and Services,
Год журнала:
2023,
Номер
14(27), С. 265 - 282
Опубликована: Дек. 18, 2023
COVID-19
has
crucially
changed
the
motivations,
attitudes,
and
behaviours
of
travellers.
This
study
explores
shifts
in
travel
attitudes
after
pandemic
how
these
changes
affect
intention
for
upcoming
travels.
It
investigates
moderating
role
traveller
personality
forming
relationships
between
attitude’s
antecedents
future
intention.
The
adopts
deductive
approach
employs
quantitative
method
to
achieve
its
aim.
compares
perceptions
collected
via
a
questionnaire
from
random
travellers
three
countries:
UAE,
Egypt,
Jordan.
PLS-SEM
is
used
data
analysis.
revealed
that
protection
motivation
intentions,
destination
selection
factors,
patterns/
arrangements
predict
post
pandemic.
Cautious
are
highly
concerned
with
intentions
post-epidemic
compared
normal
Findings
help
us
understand
Understating
influence
epidemic
on
tourists’
post-pandemic
strongly
needed
accelerate
tourism
recovery
ensure
safe
environment
tourists.
Theoretically,
responds
research
calls
examining
behaviours.
Practically,
profiles
based
their
(i.e.,
cautious
versus
travellers)
identifies
characteristics
each
category.
will
marketers
service
providers
adopt
relevant
strategies
meet
needs,
expectations
fears
new
normal.
Transportation Research Interdisciplinary Perspectives,
Год журнала:
2024,
Номер
25, С. 101085 - 101085
Опубликована: Май 1, 2024
There
is
a
research
gap
in
understanding
people's
perceived
risks
and
their
commute
mode
shifts
after
the
major
shift
anti-pandemic
policies.
Our
study
aims
to
reveal
relationship
between
commuters'
commuting
transfers
specific
context
of
canceling
We
conducted
an
online
sample
survey
residents
6
neighborhoods
one
month
lifting
policies
Kunming,
China.
Measured
risk
data
suggested
that
score
23
∼
30
accounted
for
62
%
respondents,
who
were
defined
as
high-perceived
group;
while
14
22
36
middle-perceived
only
2
respondents
with
14.
Commuting
transfer
statistics
showed
22.2
switched
from
other
modes
private
cars,
which
56.1
came
public
transportation.
Conversely,
out
81
car
commuters,
3
moved
modes.
used
nonparametric
tests
find
there
group
differences
shifts.
Specifically,
proportion
commuters
levels
shifted
travel
cars
was
11%
larger
than
levels.
Public
more
likely
switch
active
commuters.
The
test
results
also
single
variables
such
ownership,
distance,
age,
marital
status
significantly
correlated
distribution
shifting
mode.
Furthermore,
we
employed
binary
logistic
regression
model
higher
levels,
longer
distances,
or
ownership
conclusion
this
COVID-19
pandemic
prevention
control
increases
level
pushes
them
commuting.
It
necessary
pre-estimating
level,
pre-judging
changes
daily
behaviors
before
deciding
cancel
Ridehailing
services
are
changing
the
way
we
travel.
Research
has
examined
impact
of
this
mode
on
different
dimensions,
such
as
shift
in
choice,
induced
travel,
trip
frequency,
vehicle
miles
traveled
(VMT),
etc.
focused
mostly
mobility
metrics.
However,
ridehailing
extends
beyond
changes
to
increased
accessibility
destinations
thereby
activity
space
its
users,
hitherto
unavailable
due
lack
transport,
safety
concerns,
or
undesirable
because
parking
costs
driving
stress.
Understanding
change
is
essential
for
congestion
management,
short-
and
long-range
transportation
plans,
demand
estimation,
land
use
planning.
Hence,
examine
average
distance
household
ownership
ride-hailing
users
were
introduced
gained
popularity
Chicago
Metropolitan
Region
using
linear
Difference-in-Difference
(DiD)
regression.
Taking
a
quasi-experimental
causal
approach
repeated
cross-sectional
travel
survey
datasets
from
2008
2018
our
analysis,
match
treatment
control
group
two
two-dimensional
Propensity
Score
Matching
(PSM).
The
matching
based
set
demographics,
socioeconomic,
residential
built
environment
variables.
It
helps
address
challenges
longitudinal
incomparability
groups,
which
improve
results
DiD
Using
PSM
identify
potential
user
(pre-treatment),
non-ride-hailing
(post-control),
(pre-control)
known
(post-treatment).
same
also
decreased
by
2.024
with
app-based
presence
between
2018,
could
be
increase
their
multi-modal
Research Square (Research Square),
Год журнала:
2023,
Номер
unknown
Опубликована: Авг. 14, 2023
Abstract
Amid
the
increased
utilization
of
ride-sourcing,
relationship
between
these
services
and
public
transit
received
significant
attention
from
policymakers
researchers.
Prior
studies
have
found
that
ride-sourcing
has
mixed
impacts
on
ridership
use
tends
to
be
positively
associated
with
use.
However,
primarily
treated
pass
ownership
as
explanatory
variables.
Given
potential
for
influence
use,
further
work
is
needed
understand
services.
To
explore
whether
a
source
heterogeneity
among
users,
this
study
uses
an
econometric
model
determinants
in
Metro
Vancouver.
Using
data
web-based
survey,
two-stage
used
jointly
ownership,
adoption,
frequency.
The
results
demonstrate
users.
Specifically,
factors
influencing
(and
elasticity
factors)
were
differ
based
ownership.
Additionally,
suggest
attitudes
perceptions
toward
can
These
findings
help
inform
targeted
approaches
limiting
negative
2021 China Automation Congress (CAC),
Год журнала:
2023,
Номер
unknown, С. 8569 - 8574
Опубликована: Ноя. 17, 2023
Understanding
the
spatiotemporal
patterns
of
electric
vehicle
(EV)
drivers'
charging
behavior
is
an
essential
component
both
demand
management
and
public
infrastructure
planning.
However,
most
existing
studies
rely
on
relatively
small
samples
EV
behavior,
potentially
missing
complexity
heterogeneity
inherent
in
these
patterns.
To
address
this
limitation,
our
study
proposes
a
two-step
framework
that
uses
trajectory
state-of-charge
data
from
over
200,000
battery
vehicles
(BEVs)
operating
Shanghai,
China
month.
This
comprehensive
set
represents
all
actively
used
BEVs
city.
The
initial
step
involves
using
density-based
clustering
algorithm
to
differentiate
between
mobility
service
BEV
(MBEV)
drivers
(traditional
taxi
ridesourcing
drivers)
private
(PBEV)
drivers.
bases
distinction
criteria
such
as
daily
travel
distance,
variance
locations,
frequency.
Then,
Latent
Dirichlet
Allocation
models
are
estimated
separately
for
MBEV
PBEV
These
identify
36
unique
each
type
driver,
encompassing
6
spatial
temporal
results
underscore
major
differences
drivers,
within
groups
themselves,
terms
their
station
choices.
likely
reflect
distinct
needs
preferences.
not
only
offers
analysis
megacity,
but
also
lays
groundwork
developing
more
driver-centered
strategies
