Thunderbird International Business Review,
Год журнала:
2024,
Номер
66(2), С. 211 - 219
Опубликована: Фев. 22, 2024
Abstract
Artificial
intelligence
is
a
dynamic
and
emerging
form
of
technological
innovation
that
has
numerous
ramifications
for
international
business
managers.
The
aim
this
article
to
obtain
commentary
from
researchers
about
the
role
artificial
will
play
in
global
arena.
This
includes
asking
questions
how
it
affect
internationalization
processes
whether
lead
more
collaboration.
Well‐known
provide
advice
on
what
managers
should
do
terms
staying
competitive
but
also
they
can
integrate
learning
into
their
operations.
Lastly,
suggestions
future
research
regarding
interplay
between
are
provided.
Journal of Business Logistics,
Год журнала:
2023,
Номер
44(4), С. 532 - 549
Опубликована: Сен. 29, 2023
Abstract
The
dawn
of
generative
artificial
intelligence
(AI)
has
the
potential
to
transform
logistics
and
supply
chain
management
radically.
However,
this
promising
innovation
is
met
with
a
scholarly
discourse
grappling
an
interplay
between
capabilities
drawbacks.
This
conversation
frequently
includes
dystopian
forecasts
mass
unemployment
detrimental
repercussions
concerning
academic
research
integrity.
Despite
current
hype,
existing
exploring
intersection
AI
(L&SCM)
sector
remains
limited.
Therefore,
editorial
seeks
fill
void,
synthesizing
applications
within
L&SCM
domain
alongside
analysis
implementation
challenges.
In
doing
so,
we
propose
robust
framework
as
primer
roadmap
for
future
research.
will
give
researchers
organizations
comprehensive
insights
strategies
navigate
complex
yet
landscape
integration
domain.
Technological Forecasting and Social Change,
Год журнала:
2023,
Номер
197, С. 122903 - 122903
Опубликована: Окт. 13, 2023
This
study
explores
the
potential
of
AI
to
enable
circular
business
model
innovation
(CBMI)
for
industrial
manufacturers
and
corresponding
capacities
dynamic
capabilities
required
their
commercialization.
Employing
an
analysis
six
leading
B2B
firms
engaged
in
digital
servitization,
we
conceptualize
perceptive,
predictive,
prescriptive
AI,
which
enhance
resource
efficiency
by
automating
augmenting
data-driven
decision
making.
We
further
identify
two
innovative
classes
AI-enabled
CBMs
–
augmentation
(e.g.,
optimization
solutions)
automation
autonomous
models
main
value
drivers.
Finally,
our
research
reveals
novel
underpinning
discovery,
realization,
make
economic
sustainable
values
come
life
collaborating
with
customers
ecosystem
partners.
represents
important
step
understanding
how
can
drive
circularity
servitization.
Overall,
contributes
practice
academic
literature
on
models,
servitization
highlighting
empower
underlying
processes
this
transformation.
Energy & Environment,
Год журнала:
2023,
Номер
unknown
Опубликована: Дек. 25, 2023
This
paper
investigates
the
intricate
relationship
between
artificial
intelligence
(AI)
and
green
innovation
within
context
of
sustainable
development
goals.
As
societies
strive
to
achieve
sustainability,
understanding
dynamics
technological
advancements
environmental
progress
becomes
paramount.
Drawing
from
panel
data
encompassing
51
countries
2000
2019,
this
study
employs
fixed-effects
models,
mediated
effects
spatial
Durbin
models
meticulously
examine
influence
AI
on
innovation.
The
empirical
findings
reveal
a
robust
significantly
positive
correlation
innovation,
highlighting
critical
role
in
fostering
Heterogeneity
analysis
across
developed
developing
economies
delineates
variations
impact
shedding
light
economic
levels
financial
structures.
Developed
nations
showcase
more
pronounced
AI-green
compared
their
counterparts,
complexities
technology
adoption
distinct
landscapes.
Moreover,
delves
into
transmission
mechanisms
underlying
nexus,
revealing
mediating
roles
industrial
structure
human
capital.
Industrial
upgrading
enhancement
capital
emerge
as
crucial
pathways
through
which
indirectly
stimulates
Spatial
analyses
reveals
relevance
globally,
emphasizing
AI's
substantial
not
only
domestic
spheres
but
also
neighboring
regions.
There
are
significant
direct,
indirect,
total
its
spillover
characteristics
catalytic
it
plays
driving
collaborative
global
scale.
research
contributes
nuanced
insights
interplay
providing
foundation
for
policymakers,
businesses,
researchers
comprehend
multifaceted
dimensions
interventions
emphasize
imperative
efforts
utilizing
potential
propel
thereby
advancing
sustainability
agendas.
Technological Forecasting and Social Change,
Год журнала:
2023,
Номер
199, С. 123076 - 123076
Опубликована: Дек. 14, 2023
With
the
continuous
intervention
of
AI
tools
in
education
sector,
new
research
is
required
to
evaluate
viability
and
feasibility
extant
platforms
inform
various
pedagogical
methods
instruction.
The
current
manuscript
explores
cumulative
published
literature
date
order
key
challenges
that
influence
implications
adopting
models
Education
Sector.
researchers'
present
works
both
favour
against
AI-based
applications
within
Academic
milieu.
A
total
69
articles
from
a
618-article
population
was
selected
diverse
academic
journals
between
2018
2023.
After
careful
review
articles,
presents
classification
structure
based
on
five
distinct
dimensions:
user,
operational,
environmental,
technological,
ethical
challenges.
recommends
use
ChatGPT
as
complementary
teaching-learning
aid
including
need
afford
customized
optimized
versions
tool
for
teaching
fraternity.
study
addresses
an
important
knowledge
gap
how
enhance
educational
settings.
For
instance,
discusses
interalia
range
AI-related
effects
learning
creative
prompts,
training
datasets
genres,
incorporation
human
input
data
confidentiality
elimination
bias.
concludes
by
recommending
strategic
solutions
emerging
identified
while
summarizing
ways
encourage
wider
adoption
other
sector.
insights
presented
this
can
act
reference
policymakers,
teachers,
technology
experts
stakeholders,
facilitate
means
sector
more
generally.
Moreover,
provides
foundation
future
research.
European Journal of Innovation Management,
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 1, 2024
Purpose
This
study
examines
the
existing
literature
on
generative
artificial
intelligence
(Gen
AI)
and
its
impact
across
many
sectors.
analysis
explores
potential,
applications,
challenges
of
Gen
AI
in
driving
innovation
creativity
generating
ideas.
Design/methodology/approach
The
adopts
a
comprehensive
review
approach,
carefully
assessing
current
scientific
articles
published
from
2022
to
2024.
trends
insights
derived
research.
Findings
indicates
that
has
significant
potential
augment
human
processes
as
collaborative
partner.
However,
it
is
imperative
prioritize
responsible
development
ethical
frameworks
order
effectively
tackle
biases,
privacy
concerns,
other
challenges.
significantly
transforming
business
models,
processes,
value
propositions
several
industries,
but
with
varying
degrees
effect.
indicate
also
despite
theory-driven
approach
investigating
AI's
creative
innovative
cutting-edge
applications
research
prioritizes
examining
possibilities
models.
Research
limitations/implications
Although
this
offers
picture
great
possibilities,
concurrently
underlines
necessity
for
deep
knowledge
nuances
fully
harness
capabilities.
findings
continuous
exploration
efforts
are
required
address
assure
implementation.
Therefore,
more
needed
enhancing
human-AI
collaboration
defining
norms
varied
circumstances.
Originality/value
presents
relevant
transformational
an
catalyst.
It
emphasizes
major
issues
integration.
Technological Forecasting and Social Change,
Год журнала:
2024,
Номер
208, С. 123653 - 123653
Опубликована: Авг. 24, 2024
In
today's
data-driven
era,
ubiquitous
concern
about
environmental
issues
pushes
more
startups
to
engage
in
business
model
innovation
that
promotes
environmentally
friendly
technologies.
The
goal
of
these
is
create
technology-based
products
and
services
enhance
sustainability.
this
context,
artificial
intelligence
promises
be
a
key
instrument
create,
capture,
deliver
value.
However,
the
existing
literature
lacks
deep
understanding
how
using
AI
innovate
their
models
achieve
positive
impact.
Therefore,
paper
investigates
green
technology
utilize
from
perspective
for
We
conduct
qualitative,
exploratory
multiple-case
study
Eisenhardt
methodology,
based
on
interview
data
analyzed
qualitative
content
analysis.
derive
five
predominant
manifestations
AI-driven
identify
archetypical
connections
between
dimensions.
Further,
we
establish
three
overarching
associations
among
cases.
doing
so,
contribute
theory
practice
by
providing
deeper
account
attempt
maximize
impact
through
AI.
results
also
highlight
driven
can
support
society
securing
sustainable
future.
