Agent‐system co‐development in supply chain research: Propositions and demonstrative findings
| Published date | 01 May 2014 |
| Date | 01 May 2014 |
| DOI | http://doi.org/10.1016/j.jom.2014.03.002 |
Journal
of
Operations
Management
32
(2014)
154–174
Contents
lists
available
at
ScienceDirect
Journal
of
Operations
Management
jo
ur
nal
ho
me
pa
ge:
www.elsevier.com/locate/jom
Agent-system
co-development
in
supply
chain
research:
Propositions
and
demonstrative
findings
Chanchai
Tangponga,∗,
Kuo-Ting
Hungb,1,
Jin
Lia,2
aNorth
Dakota
State
University,
Department
of
Management
and
Marketing,
College
of
Business,
Richard
H.
Barry
Hall,
811
2nd
Avenue
N.,
Fargo,
ND
58108-6050,
USA
bSuffolk
University,
Information
Systems
and
Operations
Management
Department,
Sawyer
Business
School,
8
Ashburton
Place,
Boston,
MA
02108,
USA
a
r
t
i
c
l
e
i
n
f
o
Article
history:
Received
7
February
2013
Received
in
revised
form
23
February
2014
Accepted
3
March
2014
Available
online
19
March
2014
Keywords:
Behavioral
operations
management
Agent-system
co-development
Supply
chains
Adaptive
complex
systems
Vignette-based
experiment
Survey
research
a
b
s
t
r
a
c
t
In
this
study,
we
develop
an
agent-system
co-development
(ASC)
theoretical
framework
for
behavioral
research
in
supply
chains.
The
ASC
framework
aims
at
explaining
the
dynamic
agent-system
relationships
in
supply
chains
whereby
both
action-influencing
properties
of
human
agents
(e.g.,
beliefs,
personalities,
attitudes)
and
governance-influencing
properties
of
supply
chain
systems
(e.g.,
social
norms,
power-
dependence,
partnerial/adversarial
relationship
forms)
mutually
influence
each
other
over
time.
Two
empirical
studies
are
conducted
to
illustrate
how
ASC
can
be
a
useful
theoretical
framework
in
supply
chain
research
and
to
partially
validate
the
central
thesis
of
ASC
in
the
contexts
of
partnerial/adversarial
supply
chain
relationships
and
cooperative/competitive
attitudes
of
human
agents
in
supply
chains.
The
results
of
both
studies
support
the
central
thesis
of
ASC
regarding
the
dynamic
agent-system
relation-
ships.
From
two
replicated
experiments
in
Study
1,
the
results
suggest
that
agents’
cooperative
and
competitive
attitudes
in
business
relationships
are
altered
as
they
are
exposed
to
different
supply
chain
conditions
of
partnerial
and
adversarial
relationships.
In
addition,
from
the
multi-method
research
efforts
in
Study
2,
the
results
from
two
survey
studies
and
an
experiment
are
largely
consistent
with
one
another,
suggesting
that
personnel
turnovers
in
existing
supply
chain
systems
can
eventually
lead
to
changes
in
supply-chain-system
properties
including
the
degrees
of
long-term
commitment,
information
sharing,
and
joint
problem-solving
between
supply
chain
partners,
as
well
as
the
frequency
of
opportunism
occur-
rences
in
the
supply
chains.
Finally,
we
propound
that
the
dynamic
agent-system
relationships
proposed
in
the
ASC
framework
can
be
a
useful
analytical
lens
in
viewing
various
supply
chain
issues,
such
as
supply
chain
evolutions
and
changes,
supply
chain
designs
and
personnel
decisions,
and
self-reinforcing
feedback
loops
and
decision
tendencies
in
supply
chains.
©
2014
Elsevier
B.V.
All
rights
reserved.
1.
Introduction
Behavioral
operations
management
(BeOps)
has
emerged
as
a
major
domain
in
the
operations
and
supply
chain
literature.
The
extant
body
of
BeOps
research
has
been
quite
diverse,
covering
a
broad
range
of
inquires
such
as
human
biases,
cognitions,
percep-
tions,
individual/group
decisions,
and
negotiations
in
operations
and
supply
chain
systems
(e.g.,
Bendoly
et
al.,
2010;
Croson
et
al.,
2013;
Gino
and
Pisano,
2008).
BeOps
studies,
while
diverse,
share
a
central
thrust
in
highlighting
the
importance
of
behavioral
issues
∗Corresponding
author.
Tel.:
+1
701
231
9445;
fax:
+1
701
231
7508.
E-mail
addresses:
Charnchai.Tangpong@ndsu.edu
(C.
Tangpong),
khung@suffolk.edu
(K.-T.
Hung),
Jin.Li@ndsu.edu
(J.
Li).
1Tel.:
+1
617
573
8395;
fax:
+1
617
994
4228.
2Tel.:
+1
701
231
8129;
fax:
+1
701
231
7508.
in
operations
and
supply
chain
management,
as
the
successes
of
the
implementation
of
various
operations
and
supply
chain
tools,
techniques,
and
policies
depend
largely
on
the
understanding
of
human
behaviors
(e.g.,
Bendoly
et
al.,
2006;
Bendoly
and
Speier,
2008;
Gino
and
Pisano,
2008).
In
essence,
BeOps
has
brought
the
human
element
back
to
the
focus
of
operations
and
supply
chain
studies.
Supply
chain
research
has
extensively
leveraged
the
BeOps
per-
spective
in
examining
supply
chain
phenomena
such
as
bullwhip
effect
(e.g.,
Croson
and
Donohue,
2006;
Nienhaus
et
al.,
2006),
newsvendor
problem
(e.g.,
Bostian
et
al.,
2008;
Cui
et
al.,
2012),
and
buyer–supplier
multiple-block
contract
(Lim
and
Ho,
2007).
This
research
stream
broadly
examines
the
effects
of
human
factors
on
performance
outcomes
of
supply
chain
systems,
and
has
sig-
nificantly
contributed
to
the
supply
chain
management
literature,
which
traditionally
has
been
focused
largely
on
rational
deci-
sions,
optimization,
and
performance
effects
of
supply
chain
system
http://dx.doi.org/10.1016/j.jom.2014.03.002
0272-6963/©
2014
Elsevier
B.V.
All
rights
reserved.
C.
Tangpong
et
al.
/
Journal
of
Operations
Management
32
(2014)
154–174
155
properties
(e.g.,
Donohue
and
Siemsen,
2010;
Gino
and
Pisano,
2008).
In
other
words,
the
introduction
of
BeOps
to
supply
chain
research
has
broadened
the
domain
of
supply
chain
studies
to
cover
not
only
the
properties
of
supply
chain
systems
(e.g.,
structure,
design,
social
norms,
etc.)
but
also
the
properties
of
human
agents
(e.g.,
biases,
cognitions,
personalities,
attitudes,
etc.)
who
operate
in
the
systems.
Recent
supply
chain
research
has
also
revealed
that
these
two
sets
of
properties
can
jointly
affect
various
supply
chain
outcomes
such
as
conflict
resolution,
innovation,
and
opportunism
(e.g.,
Brown
et
al.,
2000;
Carson
et
al.,
2006;
Jap
and
Anderson,
2003;
Lumineau
and
Henderson,
2012;
Mooi
and
Frambach,
2012;
Poppo
and
Zenger,
2002;
Tangpong
et
al.,
2010).
Supply
chain
management
literature
thus
far
seems
to
regard
supply
chain
system
properties
and
human
agent
properties
as
two
separate
sets
that
can
independently
or
jointly
affect
supply
chain
outcomes.
As
such,
the
dynamic
relationships
between
these
two
sets
of
properties
have
been
overlooked
and
not
been
ade-
quately
studied.
The
understanding
of
the
dynamic
agent-system
relationships
in
supply
chains
can
potentially
give
us
substantive
insights
into
the
evolution
and
mutation
of
supply
chains,
and
can
help
us
address
the
challenges
faced
by
supply
chain
managers
and
senior
executives
who
are
tasked
with
the
responsibility
of
re-designing
or
re-structuring
supply
chains
and
buyer–supplier
relationships
in
the
supply
chain
networks.
The
importance
of
the
dynamic
agent-system
relationships
to
supply
chain
manage-
ment
practices
is
simply
illustrated
by
the
ill
efforts
of
the
U.S.
automakers
to
form
partnerial
relationships
with
their
part
sup-
pliers
in
the
1980s
when
aggressive
bargaining
and
opportunistic
behaviors
among
their
purchasing
agents
indeed
determined
the
eventual,
adversarial
form
of
their
buyer–supplier
relationships
(Kanter,
1989;
Lyons
et
al.,
1990).
Such
adversarial
relationships
between
the
U.S.
automakers
and
their
suppliers
persisted
in
the
1990s
(Mudambi
and
Helper,
1998)
and
still
remain
today
(Höhn,
2010;
Ro
et
al.,
2008).
The
importance
of
such
dynamic
agent-system
relationships
has
motivated
us
to
shift
the
research
inquiry
toward
the
mutual
influ-
ences
between
human
agent
properties
and
supply
chain
system
properties.
The
first
research
objective
of
this
study
is
therefore
to
propose
an
Agent-System
Co-development
(ASC)
framework,
which
is
rooted
in
dynamic
person-situation
psychology,
com-
plex
systems
and
teleological
perspectives,
as
a
theoretical
lens
in
examining
how
human
agent
properties
and
supply
chain
sys-
tem
properties
mutually
influence
each
other
over
time.
The
other
objective
of
this
study
is
to
partially
validate
the
ASC
frame-
work,
using
vignette-based
experiments
(e.g.,
Rungtusanatham
et
al.,
2011)
along
with
conventional
surveys
(Flynn
et
al.,
1990).
On
the
whole,
this
study
aims
to
postulate
theoretical
proposi-
tions
regarding
the
mutual
relationships
between
human
agent
properties
and
supply
chain
system
properties
and
to
provide
demonstrative
empirical
findings
for
such
relationships.
In
the
next
section,
we
provide
the
background
of
this
study,
which
briefly
reviews
the
literature
regarding
the
application
of
BeOps
in
supply
chain
research.
We
then
provide
the
theoretical
development
and
the
central
propositions
of
ASC
in
the
third
sec-
tion,
and
detail
the
empirical
efforts
to
test
the
propositions
in
the
fourth
and
fifth
sections.
Finally,
we
end
the
paper
with
the
discussion
and
conclusion.
2.
Literature
background
Recent
supply
chain
management
research
has
applied
the
BeOps
perspective
as
a
behavioral
analytical
lens
in
explaining
various
phenomena
in
supply
chains
that
might
have
been
consid-
ered
anomalies
if
viewed
through
the
conventional
supply
chain
rational
decision
and
optimization
lenses
(Donohue
and
Siemsen,
2010).
For
example,
in
the
context
of
inventory
management,
decision-makers’
risk
preference
and
biases,
such
as
anchoring,
recency,
and
reinforcement
biases
(Bostian
et
al.,
2008;
Cui
et
al.,
2012;
Schweitzer
and
Cachon,
2000),
have
been
used
to
explain
systematic
deviations
of
decision-makers’
actual
order
quantities
from
optimal
order
quantity
for
the
single-period
ordering
decision
under
uncertain
demands,
i.e.,
the
newsvendor
problem.
Bostian
et
al.
(2008)
found
that
the
most
recent
demand
observation
is
more
likely
to
be
greater
than
the
optimal
order
quantity
if
the
optimal
order
quantity
is
low.
Thus,
a
manager’s
recency
bias
tends
to
result
in
an
order
quantity
larger
than
the
optimal
order
quan-
tity.
Similarly,
when
the
optimal
order
quantity
is
high,
a
manager’s
recency
bias
tends
to
result
in
an
order
quantity
lower
than
the
opti-
mal
order
quantity.
These
biases
drive
managerial
behaviors
and
explain
the
“pull-to-center”
effect
(i.e.,
the
average
order
quanti-
ties
are
too
low
when
they
should
be
high
and
vice
versa)
that
is
observed
in
actual
managerial
decisions
in
newsvendor
problems.
Cui
et
al.
(2012)
found
that,
while
making
newsvendor
decisions,
Chinese
and
American
managers
demonstrated
significantly
dif-
ferent
decision
process
biases,
which
led
to
different
decisions
and
performance
outcomes.
In
the
context
of
buyer–supplier
dyadic
operations,
Lim
and
Ho
(2007)
experimentally
examined
the
effect
of
decision-makers’
beliefs
on
the
design
of
multiple-block
contract
between
a
manufacturer–retailer
dyad
under
a
deterministic
downstream
demand.
A
contract
may
price
each
unit
the
same
(that
is,
one-
block)
or
price
incremental
block
of
units
with
declining
marginal
prices
(that
is,
multiple-blocks).
Theoretical
marketing
models
pre-
dict
that,
when
the
number
of
blocks
is
increased
from
one
to
two,
the
manufacturer’s
profits
improve
significantly
because
both
channel
efficiency
and
its
share
of
channel
profits
increase.
Increas-
ing
the
number
of
blocks
to
three
and
beyond
yields
no
incremental
profits.
Thus,
the
manufacturer
should
prefer
a
two-block
con-
tract
to
a
one-block
price
contract.
Lim
and
Ho
(2007),
however,
found
that
the
experimental
outcome
deviated
from
these
theoret-
ical
predictions
and
the
manufacturer
would
benefit
from
having
more
blocks
(i.e.,
beyond
two)
in
the
price
contracts.
Their
results
suggest
that
the
retailer
was
averse
toward
losing
the
counterfac-
tual
profits
it
would
have
earned
if
the
lower
marginal
prices
were
actually
applied.
The
manufacturer
then
accounted
for
such
influ-
ence
on
the
retailer
in
its
contract
design
decisions,
price
setting,
and
the
number
of
blocks,
and
derived
higher
channel
efficiency
and
its
share
of
channel
profit
from
the
dyadic
relationship.
Sim-
ilarly,
Wu
(2013)
investigated
the
performance
of
supply
chain
contracts
in
a
laboratory
setting
and
revealed
that
in
the
repeated
interactions,
individuals’
behavior
deviated
from
the
economic
self-
interest
assumption
and
had
social
preference
for
fairness,
which
in
turn
enhanced
the
supply
chain
performance.
Studies
from
behavioral
operations
have
also
examined
the
behavioral
causes
of
the
bullwhip
effect,
the
phenomenon
of
increasing
demand
variability
in
the
supply
chain
from
down-
stream
(retail)
to
upstream
(manufacturer)
(Cachon
et
al.,
2007).
Croson
and
Donohue
(2002,
2006)
found
experimentally
that
bull-
whip
effect
is
explained,
at
least
to
some
extent,
by
managers’
misperception
and
cognitive
limitations
where
they
underesti-
mate
existing
supply
line
inventory.
Behavioral
research
on
supply
chain
inventory
management
and
bullwhip
effect
has
also
been
augmented
by
the
inclusion
of
system
dynamics,
highlighting
the
importance
of
“complexity
in
dynamic
contexts
consists
of
feed-
back
processes,
time
delays,
stocks
and
flows,
and
nonlinearities”
(Bendoly
et
al.,
2010,
p.
446).
Scholars
have
found
that
the
per-
ception
and
recognition
of
the
feedback
of
inventory
availability
on
customer
demand
resulted
in
higher
inventory
level/safety
stock
and
order
variability
(Dana
and
Petruzzi,
2001;
Gonc¸
alves
et
al.,
2005).
Likewise,
Ancarani
et
al.
(2012)
experimentally
illus-
trated
that
order
variability
and
bullwhip
effect
became
amplified
under
supply
chain
uncertainty
(i.e.,
stochastic
lead
times)
whereas
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