A Novel Group Decision Making Model to Compare Online Shopping Platforms
Spectrum of Decision Making and Applications.,
Год журнала:
2024,
Номер
2(1), С. 1 - 27
Опубликована: Авг. 26, 2024
Over
the
years,
E-commerce
industry
has
been
witnessing
a
phenomenal
growth,
thanks
to
rapid
technological
advancement
in
Industry
4.0.
There
standout
surge
use
of
various
online
shopping
platforms
(OSP)
for
daily
use.
The
recent
pandemic
accelerated
growth
trajectory
and
made
transformational
change
digital
commerce
landscape.
As
result,
there
proliferation
OSPs
competitive
domain.
It
is
therefore
pertinent
address
questions:
How
do
customers
select
their
favorite
OSP?
To
what
extent
differ
based
on
consumers’
preferences?
present
work
addresses
these
questions
by
proposing
novel
group
decision
making
framework.
ongoing
study
provides
several
innovative
extensions
multi
criteria
models
like
Borda
count,
importance
assessment
(CIMAS),
modified
preference
selection
index
(MPSI),
root
method
(RAM).
In
this
paper,
researchers
provide
count
method,
integrated
with
CIMAS
determining
weights
utilizing
ranking
criteria.
Further,
extension
MPSI
RAM
multiple
normalizations.
authors
demonstrate
rare
combination
vector
non-linear
normalization
using
Heron
mean.
paper
derives
final
combining
multi-normalization
(MNMPSI)
Bayesian
logic.
are
selected
Uses
Gratification
theory
(UGT).
findings
reveal
that
interactive
app
interface
features
(C16),
user-friendly
search
(C13),
convenience
(C14),
product
availability
variety
(C12)
discounts
offers
(C8)
exert
significant
influence
selecting
OSP.
it
observed
Flipkart
(A2)
Amazon
(A1)
top
performers
eyes
users.
stability
reliability
proposed
methodology
examined
conducting
sensitivity
analysis
comparing
other
models.
robustness
practical
relevance
shall
notable
impetus
analysts
strategic
decision-makers.
Язык: Английский
Collaborative online shopping: customer satisfaction and the influence of product type, gender and involvement
Aslib Journal of Information Management,
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 12, 2024
Purpose
Online
shopping
has
recently
been
evolving
more
toward
the
subject
area
of
collaborative
online
(COS),
and
customer
satisfaction
is
one
key
determinants
for
success
COS.
In
this
study,
we
investigate
effect
product
type
gender
their
interaction
with
through
user
involvement
in
a
context.
Design/methodology/approach
We
developed
lab
experiment
mixed
two-by-two
factorial
design
to
test
proposed
research
model.
chose
(male
versus
female)
as
between-subjects
factor
(utilitarian
hedonic
product)
within-subjects
factor.
Findings
The
obtained
results
indicate
that
may
require
group
members
be
involved
than
utilitarian
product.
When
collaboratively
products,
male
groups
tend
show
higher
level
female
groups.
contrast,
when
products.
Furthermore,
our
greater
COS
lead
satisfaction.
Social
implications
Websites
sell
products
should
first
adopt
elements
support
Meanwhile,
sellers
aware
gap
still
exists
evolves
social
shopping.
addition,
websites
provide
(e.g.
co-browsing,
avatar
embodiment,
video
chat
voting
tools)
stimulate
involvement.
Originality/value
paper,
employ
theory
consumption
values,
which
decomposes
value
into
dimensions,
theoretical
foundation
together
well
interactions
findings
various
insights
empirical
evidence
improve
understanding
how
target
customers
across
different
types
Язык: Английский
Generative Adversarial Networks in Fashion Retailing and Customer Purchase Intention: An Extension of Theory of Consumption Value
Vision The Journal of Business Perspective,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 1, 2024
The
emergence
of
generative
adversarial
networks
(GANs)
in
marketing,
a
component
artificial
intelligence
(AI)
technology,
has
the
potential
to
influence
customer
behaviour
variety
ways.
In
various
contexts,
theory
consumption
value
(TCV)
elucidated
behaviour.
Few
studies
have
applied
TCV
GAN
particularly
fashion
retailing.
To
close
gap,
this
study
extends
GAN-fashion
A
mixed
research
approach
began
with
12-participant
explorative
focus
group
discussion
identify
factors
and
develop
questionnaire.
Second,
we
conducted
stratified
random
sampling-based
cross-sectional
survey
distributed
questionnaire
258
diverse
respondents.
Analytical
methods
included
structural
equation
modelling.
It
is
discovered
that
decision-intelligent
infrastructure
(representing
functional
value)
was
major
driver
purchase
intention
retailing
context.
This
also
found
contradictory
results
discussed
reasons
behind
them.
Overall,
contributed
both
theoretical
area,
by
extending
framework
retailing,
managerial
making
some
suggestions.
Also,
it
opened
up
many
new
avenues
for
future
Язык: Английский