Can rivalling truck companies collaborate? An Indonesian case study

Abstract

Trust is essential to maintaining secure collaboration in an uncertain competitive market environment in Indonesia. However, low levels of trust are proving to be a challenge for rival Indonesian truckload and less-than-truckload companies to establish long-term horizontal collaborations. This paper aims to analyze the role of key enablers in the behavioural aspect of trust development within horizontal collaborations characteristic of a significant section of freight trucking transportation. Authentic industrial data in the form of Indonesian case studies and simulations were utilized to establish whether a partnership can prove successful in a simulation context before the initiation of actual collaboration.

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Please
cite
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article
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press
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Sitadewi,
D.,
et
al.
Can
rivalling
truck
companies
collaborate?
An
Indonesian
case
study.
The
Asian
Journal
of
Shipping
and
Logistics
(2019),
https://doi.org/10.1016/j.ajsl.2019.12.002
ARTICLE IN PRESS
G Model
AJSL-223;
No.
of
Pages
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The
Asian
Journal
of
Shipping
and
Logistics
xxx
(2019)
xxx–xxx
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Original
Article
Can
rivalling
truck
companies
collaborate?
An
Indonesian
case
study
Dania
Sitadewi,
Liane
Okdinawati∗,
Desy
Anisya
Farmaciawaty
Institut
Teknologi
Bandung,
School
of
Business
Management,
Indonesia
a
r
t
i
c
l
e
i
n
f
o
Article
history:
Received
14
April
2019
Received
in
revised
form
11
November
2019
Accepted
3
December
2019
Keywords:
Collaboration
Transportation
Management
(CTM)
Horizontal
collaboration
Behavioural
approach
Agent-based
modelling
Freight
transportation
a
b
s
t
r
a
c
t
Trust
is
essential
to
maintaining
secure
collaboration
in
an
uncertain
competitive
market
environment
in
Indonesia.
However,
low
levels
of
trust
are
proving
to
be
a
challenge
for
rival
Indonesian
truckload
and
less-than-truckload
companies
to
establish
long-term
horizontal
collaborations.
This
paper
aims
to
analyze
the
role
of
key
enablers
in
the
behavioural
aspect
of
trust
development
within
horizontal
collab-
orations
characteristic
of
a
significant
section
of
freight
trucking
transportation.
Authentic
industrial
data
in
the
form
of
Indonesian
case
studies
and
simulations
were
utilized
to
establish
whether
a
partnership
can
prove
successful
in
a
simulation
context
before
the
initiation
of
actual
collaboration.
©
2019
The
Authors.
Production
and
hosting
by
Elsevier
B.V.
This
is
an
open
access
article
under
the
CC
BY-NC-ND
license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
1.
Introduction
The
contemporary
unpredictable
competitive
commercial
con-
text,
together
with
globalization,
has
induced
numerous
companies
active
in
various
industries
to
adapt
to
the
situation.
Truckload,
less-
than-truckload
and
other
transportation
companies
responded
and
readjusted
through
efficient
operation
and
shipment
delay
reduc-
tion
to
maintain
their
market
share.
Inefficiencies
on
the
part
of
truckload
and
less-than-truckload
companies
can
lead
to
both
delayed
delivery
times
and
extended
lead
times.
Shippers
are
compelled
to
utilize
multiple
freight
trucking
companies
to
avoid
shipment
delays,
thereby
potentially
enabling
them
to
achieve
the
flexibility
to
change
carriers
easily
in
the
short-term.
However,
transport
company
shipping
costs
could
increase
since
the
contract
rates
charged
by
secondary
carriers
may
not
prove
as
reasonable
as
those
of
primary
carriers
(Feng,
Yuan,
&
Lin,
2005).
Globalization
had
an
impact
on
Indonesia
through
the
dissolu-
tion
of
trade
barriers
and
the
growth
of
competition
from
outside
the
country’s
borders.
Truck
transport
in
Indonesia
accounts
for
approximately
70%
of
freight
distribution
(Herliana
&
Parsons,
2010).
Unfortunately,
most
domestic
freight
trucking
companies
rely
on
price-based
competition
due
to
a
lack
of
differentia-
tion
relating
to
shipping
services.
Low
entry
barriers
to
the
∗Corresponding
author.
E-mail
address:
aneu.okdinawati@sbm-itb.ac.id
(L.
Okdinawati).
Peer
review
under
responsibility
of
the
Korean
Association
of
Shipping
and
Logistics,
Inc.
freight
trucking
industry
exacerbate
the
existing
intensely
com-
petitive
situation.
Indonesia’s
significant
logistical
issues
include:
a
backhauling
(empty
truck)
problem,
traffic
congestion
and
poorly-
maintained
roads
(Sandee,
2016).
These
challenges
resulted
in
truck
operation-related
inefficiencies,
thereby
increasing
shipping
costs.
The
lack
of
available
trucks
resulting
in
an
inability
to
sat-
isfy
the
shipping
requirements
of
customers
represent
another
hurdle
confronting
Indonesian
freight
trucking
companies.
One
of
the
characteristics
of
a
transportation
company
is
its
inability
to
increase
its
supply
capacity
at
short
notice
and
the
challenges
its
faces
in
securing
additional
carrier
capacity
(Feng
et
al.,
2005).
Companies
may
seek
to
address
this
predicament
through
either
a
collaborative
or
competitive
strategy
(Jagoda,
2013),
each
of
which
has
its
respective
advantages
and
disadvantages.
The
char-
acteristics
of
the
competitive
strategy
include:
lacking
value,
being
short-lived
and
breeding
distrust
between
rival
companies.
Mean-
while,
the
adopting
of
a
collaborative
approach
can
result
in
long-term,
high
value
and
high
trust
relationships
(Jagoda,
2013).
According
to
Silva,
Novaes,
Scholz-Reiter,
Frazzon,
and
Coelho
(2010),
the
development
of
greater
levels
of
collaboration
between
companies
over
the
past
decade
has
been
increasing.
The
goal
of
commercial
enterprises
is
to
share
expertise
and
provide
enhanced
results
for
their
logistical
networks
instead
of
seeking
individual
ones.
In
the
specific
case
of
freight
trucking
companies,
one
means
of
achieving
efficiency
is
through
the
elimination
of
wastefulness
through
collaboration
with
trading
partners
and
other
companies
involved
in
transportation
management.
Collaborative
Transportation
Management
(CTM)
constitutes
an
integrated
process
unifying
all
collaborating
parties
in
achieving
https://doi.org/10.1016/j.ajsl.2019.12.002
2092-5212
©
2019
The
Authors.
Production
and
hosting
by
Elsevier
B.V.
This
is
an
open
access
article
under
the
CC
BY-NC-ND
license
(http://creativecommons.org/licenses/
by-nc-nd/4.0/).

Please
cite
this
article
in
press
as:
Sitadewi,
D.,
et
al.
Can
rivalling
truck
companies
collaborate?
An
Indonesian
case
study.
The
Asian
Journal
of
Shipping
and
Logistics
(2019),
https://doi.org/10.1016/j.ajsl.2019.12.002
ARTICLE IN PRESS
G Model
AJSL-223;
No.
of
Pages
11
2
D.
Sitadewi
et
al.
/
The
Asian
Journal
of
Shipping
and
Logistics
xxx
(2019)
xxx–xxx
the
goals
of
inefficiency
reduction
and
performance
improvement
in
transportation
planning
and
implementation
(CTM
White
Paper,
2004).
Collaboration
enables
each
participant
to
complement
its
partners,
thereby
introducing
flexibility
and
competitive
edge
to
the
entire
business
network
(Prakash
&
Deshmukh,
2010).
Coordi-
nation
and
planning
between
collaborating
companies
can
reduce
the
number
of
empty
truck
trips
and
backhauling
(transport-
ing
cargo
back
from
point
B
to
the
originating
point
A),
thereby
reducing
the
release
of
emissions
into
the
environment
(Schulte,
Lalla-Ruiz,
González-Ramírez,
&
Voß,
2017).
The
focus
of
previous
research
has
been
on
the
issue
of
cost
savings
through
horizontal
CTM
(Audy,
D’amours,
&
Ronnqvist,
2008;
Chabot,
Bouchard,
Legault-Michaud,
Renaud,
&
Coelho,
2018;
Nadarajah,
2008;
Taherian,
2013),
profit
sharing
(Frisk,
Gothe-
Lundgren,
Jornsten,
&
Roonqvist,
2010;
Liu,
Wu,
&
Xu,
2010)
and
increasing
capacity
utilization
(Peeta
&
Hernandez,
2011).
The
objective
of
such
investigations
is
to
improve
overall
collaboration
performance
through
the
use
of
resource
and
information
sharing
in
the
collaboration
mechanism.
Scant
research
has
analyzed
the
relationship
and
interaction
between
partnership
elements
within
a
horizontal
collabora-
tive
transportation
management
context.
Pomponi,
Fratocchi,
and
Tafuri
(2015)
developed
a
theory-based
framework
for
horizontal
collaboration
relating
to
logistics
based
on
the
extent
of
coop-
eration
and
mutual
trust
between
cooperating
parties.
However,
previous
research
is
limited
in
addressing
the
issue
of
how
trust
develops
from
the
interactions
between
collaborative
agents.
The
absence
of
trust
between
parties
to
the
collaboration
is
one
of
the
behavioural
issues
that
can
negatively
affect
operational
success
(Bendoly,
Donohue,
&
Schultz,
2005).
Understanding
the
interaction
between
horizontal
collabora-
tive
agents
and
analyzing
the
trust
resulting
from
a
deepening
and
recurring
collaboration
from
the
operational
to
strategic
levels
con-
stitute
the
aims
of
this
study.
The
focus
on
behavioural
aspects
in
this
research
is
based
on
the
assumption
that
collaborating
parties
will
behave
adaptively
in
response
to
their
interactions
with
each
other.
Agent-based
modelling
(ABM)
simulation
is
also
utilized
to
obtain
empirical
evidence
of
trust
development
in
horizontal
CTM
mechanisms.
This
simulation
represents
a
modest
contribution
to
the
deepening
understanding
of
horizontal
collaboration
between
companies
in
Indonesia,
particularly
those
involved
in
the
freight
trucking
industry.
Moreover,
this
paper
constitutes
a
preliminary
investigation
into
horizontal
CTM
in
a
real-life
context.
2.
Literature
review
2.1.
Horizontal
collaborative
transportation
management
Collaborative
structures
in
transportation
manage-
ment
are
classified
as
one
of
three
forms:
horizontal
collaboration
(Carrier–Carrier),
vertical
collaboration
(Shipper–Carrier–Receiver)
and
lateral
collaboration
(a
com-
bination
of
horizontal
and
vertical
collaboration)
(Simatupang
and
Sridharan,
2002).
Asawasakulsorn
(2009)
defines
horizontal
collaboration
as
one
between
competing
carriers
within
the
same
supply
chain
level,
while
Sutherland
(2006)
identifies
CTM
as
coop-
eration
between
rival
trucking
companies.
Therefore,
horizontal
collaborative
transportation
management
is
defined
as
integrated
collaboration
between
competitors
operating
within
the
same
level
of
the
supply
chain
in
order
to
improve
performance
and
efficiency.
The
horizontal
collaboration
model
is
based
on
the
research
of
Taherian
(2013)
and
McKinsey
&
Co.
(2010),
the
latter
of
whom
classified
three
types
of
horizontal
collaboration
model
based
on
different
forms
of
leadership
approach:
convened
collaboration,
primus
inter-pares
collaboration
and
inter-pares
collaboration.
Meanwhile,
Taherian
(2013)
categorizes
horizontal
collabora-
tion
models
based
on
their
collaborative
processes,
i.e.,
manual
DIY
(Do-It-Yourself),
semi-automated
DIY
and
outsourced
to
3PL
(third-party
logistics).
Convened
collaboration
is
similar
in
character
to
the
outsourced
collaboration
coordination
proposed
by
Taherian
(2013),
where
a
neutral
or
third
party
logistics
provider
(3PL)
orchestrates
collab-
oration
between
several
parties
–
according
to
Taherian
(2013)
of
the
three
types
of
horizontal
partnership,
outsourced
to
3PL
encounters
the
fewest
problems
with
minimal
overheads
since
the
neutral
party
manages
the
entire
coordination
process.
Based
on
the
findings
of
his
study
of
the
UK
retail
industry,
Stephens
(2006)
suggests
that
the
presence
of
a
neutral
party
acting
in
the
role
of
‘honest
broker’
will
allow
more
initiative
for
horizontal
collab-
oration.
However,
such
collaboration
will
limit
opportunities
for
small-scale
shippers
to
influence
this
form
of
collaboration
and
reap
the
full
benefits
(Pomponi
et
al.,
2015).
Semi-automated
DIY
is
similar
to
primus
inter-pares
collaboration
in
that,
due
to
its
size
and
critical
mass,
one
partner
takes
the
lead
in
facilitating
the
partnership.
This
constitutes
a
form
of
collaboration,
poten-
tially
offering
more
substantial
profits.
Manual
DIY
is
similar
to
the
inter-pares
collaboration
proposed
by
McKinsey
&
Co.
(2010)
since
both
collaborating
parties
typically
have
a
similar-sized
operation.
This
type
of
collaboration
enables
them
to
consolidate
existing
activity
or
establish
new
joint
ventures.
Consequently,
it
requires
full
transparency
and
disclosure
of
confidential
information
such
as
routing,
pricing
and
knowledge
relating
to
consumers.
Unfor-
tunately,
there
is
a
higher
risk
of
opportunism
emerging
when
a
greater
degree
of
confidential
information
is
disclosed
(Pomponi
et
al.,
2015).
2.2.
Trust
development
in
horizontal
collaboration
Pomponi
et
al.
(2015)
have
proposed
a
theoretical
organiza-
tional
framework
for
horizontal
collaboration
incorporating
two
levels
of
classification,
namely;
the
extent
of
cooperation
and
trust.
This
trust
corresponds
with
the
scope
of
collaboration
due
to
the
belief
that
companies
rarely
choose
to
cooperate
across
all
decision-
making
levels
(Matopoulos,
Vlanchopoulou,
Manthou,
&
Manos,
2007).
Meanwhile,
Pomponi
et
al.
(2015)
further
argue
that
con-
tinuous
interaction
and
knowledge
sharing
cause
this
form
of
collaboration
to
evolve
over
time
from
mere
cooperation
at
the
operational
level
into
a
more
strategic
partnership.
This
research
finding
is
in
line
with
that
of
Lambert,
Emmelhainz,
and
Gardner
(1999).
Moreover,
at
every
level
of
cooperation
(operational,
tac-
tical,
and
strategic),
an
ongoing
trust
development
process
exists
(Lambert
et
al.,
1999).
Taherian
(2013)
suggests
that
trust
relates
to
the
commitment
of
the
various
parties
involved
in
the
collaborative
relationship.
This
paper
focuses
solely
on
the
trust
which
justifies
cur-
rent
collaboration
through
previous
experience
of
cooperation
and
trust,
which
constitutes
a
prerequisite
to
a
fruitful
and
sustainable
partnership.
As
Bendoly
et
al.
(2005)
argue,
the
trust
between
sup-
ply
chain
partners
can
significantly
influence
operational
success.
Those
arguments
also
supported
by
Fawcett,
Jones,
and
Fawcett
(2012)
research.
Fawcett
et
al.
(2012)
interview
238
leading
supply
chain
companies,
and
the
results
showed
that
companies
become
mature
and
sustained
through
a
virtuous
cycle
of
trust
in
their
col-
laborative
alliances.
Meanwhile,
the
existence
of
trust
is
essential
for
the
development
of
enduring
collaboration
when
all
mem-
bers
in
the
supply
chain
have
different
interests
and
expectations
is
proposed
by
Ramaswami
and
Simatupang
(2013).
The
extent
to
which
supply
chain
collaboration
is
associated
with
trust
also
examines
by
Talavera
(2014)
using
factor
analysis
of
57
Philip-
pine
companies.
Similar
results
also
showed
by
Al-Doori
(2019)

Please
cite
this
article
in
press
as:
Sitadewi,
D.,
et
al.
Can
rivalling
truck
companies
collaborate?
An
Indonesian
case
study.
The
Asian
Journal
of
Shipping
and
Logistics
(2019),
https://doi.org/10.1016/j.ajsl.2019.12.002
ARTICLE IN PRESS
G Model
AJSL-223;
No.
of
Pages
11
D.
Sitadewi
et
al.
/
The
Asian
Journal
of
Shipping
and
Logistics
xxx
(2019)
xxx–xxx
3
Fig.
1.
Trust
development
framework.
where
trust
is
one
of
the
critical
factors
for
effective
collaboration
initiatives.
Pomponi
et
al.
(2015)
classified
the
development
of
trust
within
horizontal
logistic
collaboration
into
three
types.
First,
agreement-
driven
trust
as
a
prerequisite
to
initiating
collaboration.
Second,
knowledge-driven
trust
or
trust
born
of
a
recurrent
virtuous
col-
laboration
cycle
where
the
requirements
of
each
partner
are
met
to
a
level
exceeding
their
expectations.
Third,
collaboration-
driven
trust,
or
a
high-trust
relationship,
which
entails
continuous
open
communication
between
collaborating
partners
and
reduces
uncertainty.
These
various
forms
of
trust
development
are
shown
in
Fig.
1.
Pomponi
et
al.
(2015)
proposed
a
framework
within
which
companies
ultimately
collaborate
at
three
levels:
operational,
tac-
tical
and
strategic.
According
to
Okdinawati,
Simatupang,
and
Sunitiyoso
(2015),
the
operational
level
focuses
on
the
daily
pro-
cesses
involved
in
processing
customer
orders,
namely:
scheduling,
routing
and
order
processing.
The
operational
level
refers
to
the
initial
phase
of
collaboration
during
which
the
level
of
trust
is
an
agreement-driven
trust
(Pomponi
et
al.,
2015).
The
tactical
level
focuses
on
improving
efficiency
through
more
effective
and
efficient
transportation
within
the
logistic
process
through
the
application
of
freight
forecasting
and
order
assignment
which
helps
to
map
various
carriers
(Okdinawati
et
al.,
2015).
The
tac-
tical
level
corresponds
with
the
knowledge-driven
trust,
which
has
been
developed
over
time
through
the
accumulation
of
reciprocal
knowledge
resulting
from
interaction
(Pomponi
et
al.,
2015).
Finally,
at
the
foundation
of
the
supply
chain
collabora-
tion
process
lies
the
strategic
level
which
helps
to
identify
the
benefit,
risk,
commitment
sharing
and
limitations
of
the
strate-
gic
partnership
model
through
front-end
agreement
and
network
planning
to
establish
a
collaborative
relationship
(Okdinawati
et
al.,
2015).
The
strategic
level
corresponds
to
the
highest
level
of
trust,
which
is
a
collaboration-driven
trust
(Pomponi
et
al.,
2015).
The
research
gap
of
this
paper
relates
to
the
role
of
trust
in
horizontal
collaborative
transportation
management
in
ensuring
the
continuation
and
extent
of
the
horizontal
collaboration
pro-
cess
involved
in
truck
freight
transportation.
Although
previous
research
on
this
subject
is
limited
in
scope,
Lambert
et
al.
(1999)
revealed
ongoing
trust
development
at
every
level
of
cooperation
(operational,
tactical,
strategic).
Meanwhile,
a
study
by
Pomponi
et
al.
(2015)
proposed
that
the
evolution
of
collaboration
was
directly
related
to
the
prevailing
level
of
trust
from
limited
coop-
eration
to
a
strategic
partnership.
3.
Methodology
3.1.
Research
method
The
research
design
applied
in
this
paper
consists
of
seven
stages
adhering
to
the
principles
of
soft
system
methodology
(SSM),
as
shown
in
Fig.
2.
Soft
systems
methodology
(SSM)
focuses
on
the
means
of
achieving
a
desired
future
scenario
by
comparing
the
current
sit-
uation
with
an
ideal
one
(Checkland
&
Scholes,
1990).
Checkland
stated
that
when
a
researcher
is
faced
with
a
situation,
both
dynamic
and
unpredictable
in
character
or
when
goals
and
objec-
tives
defy
precise
quantification,
then
an
SSM
should
be
utilized.
According
to
Novani
and
Mayangsari
(2017),
when
a
problem
could
benefit
from
a
different
form
of
analysis,
SSM
can
be
applied.
How-
ever,
its
effective
application
requires
a
situation
within
which
sufficient
time
exists
for
participants
to
share
knowledge
and
expe-
riences,
thereby
learning
from
each
other.
This,
in
turn,
requires
the
existence
of
sufficiently
high
levels
of
trust
for
the
participants
to
feel
comfortable
in
openly
expressing
their
requirements
and
pref-
erences
(Novani
&
Mayangsari,
2017).
SSM
is
applied
through
seven
stages
(Checkland,
1981)
whose
implementation
does
not
need
to
adhere
to
a
particular
sequence,
namely:
(1)
unstructured
prob-
lem
situation,
(2)
structured
problem
situation,
(3)
root
definition
formulation,
(4)
conceptual
model
development,
(5)
comparison
of
models
with
“reality”,
(6)
defining
desirable
and
culturally
feasible
changes
and
(7)
implementation
of
ameliorative
action.
Agent-based
modelling
(ABM)
was
employed
in
this
research
as
a
computational
model
developed
to
analyze
and
understand
the
dynamic
interaction
between
the
environment
and
the
behaviour
of
agents
(Gilbert,
2008).
ABM
constitutes
a
method
of
studying
the
systems
thinking,
which
consists
of
the
interaction
between
both
agents
and
the
emergent
properties
arising
from
such
inter-
action
and
the
system
more
generally
(Axelrod,
1997).
ABM
is
able
to
demonstrate
the
comprehensive
effects
of
agent
diversity
with
regard
to
attributes
and
behaviour,
enabling
a
researcher
to
observe
the
model
as
it
gives
rise
to
the
behaviour
of
the
system
as
a
whole
(Macal
&
North,
2009).
The
three
elements
used
in
ABM
consist
of:
(1)
the
attributes
and
behaviours
of
agents;
(2)
the
rela-
tionships
and
means
of
interaction
between
agents;
and
(3)
the
environment
within
which
agents
interact
with
each
other.
ABM
constitutes
a
bottom-up
approach
that
relies
on
the
agents’
rela-
tionships
and
interaction
within
the
system
which
are
potentially
subject
to
change
over
time
and
considered
to
represent
a
process
or
systematic
behaviour
(Novani
&
Mayangsari,
2017).
3.2.
Case
description
In
order
to
understand
the
contemporary
state
of
the
trans-
portation
industry
in
Indonesia
and
to
develop
a
horizontal
CTM
model
of
freight
trucking
companies,
this
research
encompassed
two
case
studies.
The
adoption
of
a
case
study
approach
allows
for
a
detailed
description
of
agent
interactions
in
horizontal
CTM
and
the
development
of
trust
within
a
CTM
mechanism
to
be
devel-
oped.
The
selection
of
cases
was
based
on
the
recommendations
of
both
academics
and
practitioners
with
regard
to
the
prevalence
of
horizontal
collaboration
in
current
business
practice.
Both
case
studies
represent
real-life
conditions
and
are
employed
to
confirm
or
disprove
the
conclusions
drawn
from
the
ABM
simulation.
The
two
case
studies
used
for
this
research
comprise
Case
X,
three
freight
companies
in
Indonesia,
and
Case
Y,
the
Indone-
sian
Association
of
the
Freight
Trucking
Industry.
The
justification
for
selecting
these
cases
lies
in
both
having
experience
of
either
practicing
or
facilitating
horizontal
CTM
between
freight
trucking
companies.
The
collaboration
models
of
both
cases
studies
are
sim-
ilar
to
the
horizontal
collaboration
model
proposed
by
McKinsey

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Can
rivalling
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An
Indonesian
case
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Fig.
2.
Research
methodology.
&
Co.
(2010).
Case
X
is
identical
to
the
Inter-pares
collaboration
model,
while
Case
Y
is
similar
to
a
Convened
collaboration
model.
The
latter
is
one
in
which
a
neutral
party
helps
to
orchestrate
the
cooperation,
while
an
Inter-pares
model
constitutes
collaboration
between
companies
with
similar-sized
operations
(McKinsey
&
Co.,
2010).
Case
X
involved
the
examples
of
three
DKI
Jakarta
and
Bandung-based
transportation
companies
offering
freight
trucking
transportation
services,
while
Case
Y
featured
the
Indonesian
Asso-
ciation
of
the
Freight
Trucking
Industry.
This
body
aims
to
create
a
business-conducive
environment,
especially
relating
to
the
field
of
freight
trucking
transportation,
within
which
each
member
can
develop
its
competence
while,
simultaneously,
providing
a
strate-
gic
partnership
network.
Case
Y
was
established
in
August
2014
by
48
trucking
company
owners.
Based
on
the
data
elicited
dur-
ing
the
interviews
conducted,
the
number
of
unregistered
trucks
in
Indonesia
trucking
association
within
Indonesia
remains
persis-
tently
high.
The
Indonesian
National
Police
(POLRI)
confirmed
the
presence
of
5.2
million
registered
trucks
on
the
country’s
roads,
while
only
approximately
0.8%
of
this
number
had
joined
the
asso-
ciation
(Case
Y,
2018).
For
the
purposes
of
data
collection,
two
informants
constituting
representatives
of
each
case
study
were
interviewed
for
2–3
hours
during
four
separate
sessions.
All
informants
were
senior
execu-
tives
of
their
respective
organizations
with
more
than
fifteen
years’
experience
of
the
freight
trucking
transportation
industry.
The
con-
duct
of
the
interview
aimed
to
define
the
nature
of
the
current
problems
besetting
this
economic
sector.
This
investigation
adopted
a
subjective
approach
of
face
val-
idation
to
evaluate
the
model,
its
behaviour
and
underlying
assumptions,
together
with
the
ABM
simulation
results.
During
face
validation,
the
experts
and
the
representatives
of
both
case
studies
were
asked
to
evaluate
whether
the
model,
the
interactions
and
ABM
simulation
results
represented
the
real
system,
is
justifiable
and
within
reason
(Sargent,
1986).
3.3.
Conceptual
framework
The
Case
X
study
resembles
the
Inter-pares
collaboration
model
since
Case
X
usually
provides
shipping
services
for
FMCG
(fast-
moving
consumer
goods)
through
its
existing
fleet
of
trucks.
Customer
shipment
requests
frequently
relate
to
the
delivery
of
a
full
truckload
of
FMCGs
from
Banten
to
East
Java.
Having
provided
an
excellent
delivery
service,
the
empty
trucks
belonging
to
Case
X
must
return
to
Banten,
a
requirement
which,
from
an
economic
perspective,
constitutes
inefficiency
since
the
return
journey
will
incur
operating
expenses
such
as
fuel,
road
tolls
and
the
driver’s
salary.
Therefore,
Case
X
will
contact
competing
trucking
compa-
nies
in
an
effort
to
collaborate
in
combining
their
respective
cargos
for
the
return
trip
to
Banten.
Such
horizontal
collaboration
in
the
area
of
backhauling
has
significantly
addressed
the
issue
of
empty
truck
capacity
for
Case
X
by
consolidating
cooperating
partners’
deliveries
for
a
return
trip.
In
this
case
study,
since
both
collaborating
partners
were
carri-
ers
constituting
either
rival
or
unrelated
freight
trucking
companies
whose
decision
to
collaborate
was
driven
by
necessity,
they
exhib-
ited
little
or
no
mutual
trust.
This
state
of
affairs
was
evidenced
by
the
reluctance
of
each
company
to
disclose
confidential
informa-
tion
such
as
their
internal
operation
procedures,
customer
details
or
pricing
to
competitors
–
a
fact
confirmed
by
the
interviews
conducted.
Interviewees
expressed
the
fear
that
any
information
disclosed
would
be
used
by
competitors
to
steal
market
share
by
offering
lower
pricing
and
providing
more
rapid
shipping
services
to
potential
customers.
Due
to
a
lack
of
mutual
trust,
the
current
collaboration
between
Case
X
and
its
partners
is
limited
to
the
operational
level,
focusing
largely
on
daily
operations
which
involve
customer
order
deliv-
ery.
Consequently,
less
risk,
particularly
that
resulting
from
sharing
sensitive
information
with
collaborating
partners,
is
involved.
No
truck
freight
company
possesses
an
inherent
ability
to
orchestrate
collaboration
as
the
Case
Y
study
serves
to
illustrate.
Therefore,
a
neutral
party
acting
as
a
mediator
is
required
to
help
coordinate
the
cooperation
process
between
freight
trucking
companies.
Based
on
information
elicited
by
the
interviews
conducted,
the
presence
of
Case
Y
as
a
neutral
party
has
induced
greater
initiative
for
horizontal
collaboration.
Therefore,
Case
Y
study
bears
a
certain
resemblance
to
the
Convened
collaboration
model.
Within
this
context,
Case
Y
acts
as
the
neutral
party,
while
the
freight
trucking
service
compa-
nies
are
referred
to
as
the
carriers.
Recommendations
by
Case
Y
regarding
membership
and
col-
laboration
include:
generating
trust,
lending
credibility,
and
maintaining
a
good
relationship
between
collaborating
carriers.
Any
freight
trucking
company
can
request
Case
Y
via
the
support
of
the
association’s
communication
channel
in
identifying
fellow
freight
trucking
companies
interested
in
collaboration.
Since
the
freight
trucking
company
is
a
member
of
Case
Y,
other
similar
companies
are
likely
to
demonstrate
greater
trust
in
any
partner-
ship.
In
return
for
facilitating
collaboration,
the
association
levies
a
fee
amounting
to
2.5%
of
the
value
of
the
total
freight
trucking
service
provided,
while
the
truck
owner
receives
2.5%
and
the
com-
pany
which
handles
customer
orders
payment
equivalent
to
5%
of
the
value
of
the
service.
A
potential
framework
for
horizontal
CTM
based
on
the
contexts
of
the
foregoing
case
studies
is
con-
tained
in
Fig.
3.
This
model
should
promote
understanding
of
trust
development
at
each
level
of
horizontal
CTM.
The
content
of
Fig.
3
represents
the
ideal
situation
regarding
the
structure
of
horizontal
CTM
that
involves
various
collaborat-
ing
agents.
The
three
agents
in
the
conceptual
framework
consist

Please
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article
in
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Sitadewi,
D.,
et
al.
Can
rivalling
truck
companies
collaborate?
An
Indonesian
case
study.
The
Asian
Journal
of
Shipping
and
Logistics
(2019),
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ARTICLE IN PRESS
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5
Fig.
3.
The
framework
for
horizontal
CTM.
of
Carrier
A,
Carrier
B
and
a
neutral
party.
To
simplify
simula-
tion,
one
agent
represents
both
the
truck
operator
and
the
cargo
owner.
It
is
important
to
note
that
the
roles
of
Carrier
A
and
Car-
rier
B
are
interchangeable.
For
example,
Carrier
A
might
be
the
truck
owner
who
transports
cargo
to
satisfy
customer
require-
ments.
Carrier
B
might
collaborate
by
using
Carrier
A’s
truck
to
avoid
backhauling
or
reduce
transportation
costs.
A
carrier’s
goals
are
to
satisfy
customer
requirements,
expand
market
share
and
maximize
their
profits
by
either
increasing
freight
trucking
rates
or
reducing
shipment
costs
(Okdinawati
et
al.,
2015).
Since
both
agents
are
carriers,
each
has
similar
clearly
defined
roles
and
activ-
ities.
However,
each
agent
offers
a
different
capacity
and
resources
to
potential
customers.
Carriers
may
decide
to
collaborate
in
order
to
satisfy
demand
depending
on
the
number
of
customers
and
the
nature
of
their
demands.
The
inclusion
of
both
Carrier
A
and
Car-
rier
B
represents
a
prerequisite
for
horizontal
CTM,
while
that
of
a
neutral
party
is
optional
and
depends
on
the
need
for
collaborative
partners.
The
neutral
party
can
facilitate
collaboration
even
when
the
carriers
are
unable
to
cooperate
due
to
the
necessary
skill
set
being
outside
their
core
capability
or,
alternatively,
because
of
a
lack
of
trust
on
their
part.
The
agents
will
seek
a
collaborative
partner
by
enhancing
their
attractiveness
to
collaborate
at
the
formation
stage
(Okdinawati,
Simatupang,
&
Sunitiyoso,
2017).
Both
agents
will
indicate
the
hard
constraints
they
face
and
the
key
enablers
as
behavioural
aspects
of
CTM.
Collaboration
partner
selection
against
a
background
of
hard
constraints
is
conducted
to
ease
collaborative
compatibilities
across
various
factors,
including:
product,
type
of
truck
employed,
geography
and
product
handling
(Taherian,
2013).
If
agents
choose
to
collaborate,
the
subsequent
step
is
to
align
the
key
enablers
of
CTM
with
each
agent
to
ensure
successful
cooperation.
Key
enablers
of
collaboration
represent
a
concept
focusing
on
the
behavioural
aspect
of
CTM,
namely;
how
effectively
individu-
als
work
together
both
internally
and
with
cooperating
partners
(Sutherland,
2006).
The
key
enablers
of
CTM
consist
of
common
interest,
openness,
prioritization,
clear
expectations,
leadership,
cooperation
and
trust
(Sutherland,
2006).
The
term
“Common
interest”
signifies,
ensuring
that
all
collaborating
parties
share
an
ongoing
interest
in
and
commitment
to
the
outcome
of
the
collab-
oration.
“Transparency”
or
“Openness”
means
the
behaviour
of
all
collaborating
parties
in
openly
sharing
their
practice,
resources
and
proprietary
information.
“Recognizing
who
and
what
is
essential”
or
“prioritisation”
means
an
agent
should
be
mindful
of
what
is
essential
and
prioritize
common
goals.
“Clear
expectation”
means
all
collaborating
partners
should
have
a
firm
understanding
of
the
expected
contribution
and
goals
within
the
collaborative
relation-
ship.
“Leadership”
means
nothing
significant
will
be
accomplished
without
a
dominant
party
to
drive
the
collaboration
forward.
“Cooperation
and
benefit-sharing”
refers
to
distributing
both
profit
and
expenses
among
collaborating
partners.
On
the
basis
of
each
of
these
key
enablers,
the
CTM
can
decide
whether
the
agent
will
have
the
capacity
to
conduct
various
functions
at
the
operational,
tactical
and
strategic
levels.
The
next
stage
is
the
degree
of
involvement
in
the
collabora-
tion
at
the
three-levels
of
decision-making
–
the
framework
for
the
CTM
planning
stage
adopted
from
the
research
of
Okdinawati
et
al.
(2015).
In
the
opinion
of
these
authors,
the
collaboration
stage
starts
with
the
strategic
stage,
moving
to
the
tactical
stage

Please
cite
this
article
in
press
as:
Sitadewi,
D.,
et
al.
Can
rivalling
truck
companies
collaborate?
An
Indonesian
case
study.
The
Asian
Journal
of
Shipping
and
Logistics
(2019),
https://doi.org/10.1016/j.ajsl.2019.12.002
ARTICLE IN PRESS
G Model
AJSL-223;
No.
of
Pages
11
6
D.
Sitadewi
et
al.
/
The
Asian
Journal
of
Shipping
and
Logistics
xxx
(2019)
xxx–xxx
and
culminating
in
the
operational
stage.
The
rationale
underpin-
ning
these
three
stages
is
that
horizontal
collaboration
is
divided
on
the
basis
of
their
respective
time
horizons.
Initially,
strategic
level
collaboration
serves
as
the
foundation
of
the
entire
long-
term
collaborative
planning
process
in
identifying
benefits,
risks,
commitments
and
limitations
inherent
to
the
strategic
partner-
ship
model
(Okdinawati
et
al.,
2015).
Collaboration
moves
from
the
strategic
level
to
the
tactical
level
whose
aim
is
to
improve
trans-
port
utilization
and
increase
efficiency
on
a
weekly
and
monthly
basis.
Finally,
collaboration
moves
from
the
strategic
and
tactical
level
to
the
operational
level
where
the
strategic
and
tactical
plans
translate
into
daily
operational
process
flows
which
process
the
orders
placed
by
customers
(Okdinawati
et
al.,
2015).
Based
on
the
case
studies
conducted
in
the
course
of
the
research
reported
here,
the
majority
of
the
collaboration
in
Indonesia
starts
at
the
operational
rather
than
the
strategic
level.
Both
collaborat-
ing
partners
are
carriers
who
are
either
rival
or
unrelated
freight
trucking
companies
(Asawasakulsorn,
2009;
Sutherland,
2006).
The
rival
carriers
decide
to
collaborate
out
of
necessity
with
little
or
no
trust
evident
in
the
resulting
relationship.
Collaboration
at
the
operational
level
mainly
focuses
on
daily
operations
for
customer
order
fulfilment
and
its
initiating
demands
only
a
minimal
amount
of
trust.
Therefore,
in
real
life,
it
is
easier
to
initiate
horizontal
collaboration
at
the
operational
level.
Reflecting
on
both
case
stud-
ies,
the
collaboration
stages
discussed
start
at
this
level,
before
moving
to
the
tactical
level
and
finally
to
the
strategic
level.
The
expectation
of
collaboration
evolved
as
trust
in
the
relationship
developed.
This
research
adopted
the
framework
contained
in
Fig.
1,
relat-
ing
to
the
extent
of
trust-based
collaboration
from
the
work
of
Pomponi
et
al.
(2015).
Within
every
level
of
collaboration
(oper-
ational,
tactical
and
strategic
level),
a
process
of
trust
development
is
ongoing
(Lambert
et
al.,
1999;
Pomponi
et
al.,
2015).
The
result
of
successful
collaboration
may
increase
the
trust
between
participating
partners.
As
the
companies
develop
a
more
compre-
hensive
mutual
understanding,
they
gain
more
insight
into
and,
subsequently,
satisfy
their
respective
performance
expectations
within
the
relationship.
Meanwhile,
unsuccessful
collaboration
may
decrease
the
mutual
trust
between
partners
as
companies
fail
to
deliver
satisfactory
results
at
the
operational,
tactical
or
strategic
level.
Trust
is
vital
to
ensuring
that
the
collaboration
works
and
allows
its
participants
to
reap
full
benefit
against
the
background
of
an
uncertain
competitive
market
environment
and
market
demand.
Carriers
will
decide
whether
to
continue
collab-
oration
or
dissolve
the
partnership
based
on
the
results
of
the
development
of
trust.
If
carriers
choose
to
maintain
collaboration
with
existing
partners,
they
will
return
to
the
formation
stage
and
repeat
the
decision-making
sequences.
Even
though
the
case
study
takes
place
within
Indonesia
as
an
emerging
country,
the
results
of
the
analysis
of
the
conceptual
model
can
be
replicated
within
any
context
since
they
relate
to
the
development
of
trust
grounded
in
successful
collaboration.
Therefore,
the
application
of
the
model
is
not
restricted
to
the
conditions
prevailing
within
a
specific
country,
in
this
case,
Indonesia.
3.4.
Agent-based
modelling
simulation
During
the
ABM
simulation,
every
agent
operates
within
con-
ditions
that
consist
of
the
hard
constraints
and
key
enablers
as
the
behavioural
aspect
of
horizontal
CTM.
Agent
roles,
rules
and
attributes,
shown
in
Table
1,
can
affect
their
willingness
to
collabo-
rate,
ability
to
work
and
the
trust
between
collaborating
parties.
The
research
involving
this
simulation
assumes
that
customer
demands
are
constant
and
at
a
level
where
carriers
must
collaborate
in
order
to
fulfil
customer
orders.
Two
scenarios
run
simultaneously
in
the
NetLogo
program.
Indeed,
in
this
simulation,
both
Scenario
1
and
Scenario
2
ran
concurrently
using
the
same
agents
with
the
result
shown
in
the
plot
monitor.
The
simulation
was
con-
ducted
100
times,
with
each
simulation
run
continued
until
both
agents
achieved
the
highest
level
of
trust:
Collaboration-driven
trust.
Moreover,
a
single
iteration
represented
one
cycle
of
the
collaboration
completed
in
the
course
of
a
month.
This
research
refers
to
the
freight
trucking
companies
as
the
Car-
riers,
two
of
which,
Carrier
A
and
Carrier
B,
were
employed.
Two
simulations
were
conducted
to
provide
evidence
of
trust
devel-
opment
in
horizontal
collaboration
mechanisms.
Two
scenarios
were
included
in
the
simulation.
Scenario
1
was
a
reflection
of
the
study
of
Case
X,
where
the
horizontal
collaboration
involved
two
carriers
with
similar-sized
operations.
Within
this
research,
Scenario
1
is
referred
to
as
the
model
of
the
ideal
situation
since
both
agents
demonstrated
zero
mutual
trust
prior
to
their
collabo-
ration.
Scenario
2
parallels
the
study
of
Case
Y,
in
which
a
neutral
party
facilitated
the
horizontal
collaboration
between
two
carriers.
In
Scenario
2,
Carrier
A
and
Carrier
B,
both
of
whom
are
members
of
the
trucking
association,
requested
Case
Y
to
provide
a
communi-
cation
platform
enabling
them
to
meet
and
propose
their
intention
to
seek
a
collaborative
partner.
Case
Y,
as
the
trucking
association,
lent
credibility
to
and
enhanced
the
reputation
of
the
freight
truck-
ing
companies,
thereby
facilitating
collaboration
and
adding
a
trust
score
of
5
(Tn
+
5)
to
each
agent.
Matopoulos
et
al.
(2007)
believe
that
it
is
rare
for
companies
to
collaborate
in
a
straightforward
manner
at
all
decision-making
lev-
els.
Meanwhile,
Pomponi
et
al.
(2015)
state
that
a
minimum
degree
of
mutual
trust
constitutes
a
prerequisite
to
continuing
the
col-
laboration
to
the
next
level.
Therefore,
within
this
simulation,
the
collaboration
stages
also
developed
on
the
basis
of
a
hierarchical
decision-making
structure
commencing
with
the
operational
level,
moving
to
the
tactical
level
and
ending
with
the
strategic
level.
Dif-
ferent
activities
are
conducted
on
each
level
from
the
operational
level
until
the
strategic
level.
When
collaboration
resulted
in
the
completion
of
one
of
the
activities
at
each
level,
the
trust
score
increased
(Tn
+
1),
while
failure
by
agents
to
complete
the
activity
caused
them
to
lose
one
Trust
(Tn
−
1)
score,
then
trust
score
will
add
up
in
each
level.
Assume
that
If
the
agreement-driven
trust
level
were
not
reached,
the
collaboration
would
persist
at
the
operational
level.
Only
when
the
level
of
trust
achieves
the
trust
milestones
can
the
degree
of
participation
within
the
collaboration
extend
from
the
operational
level
to
the
tactical
level.
The
justification
for
the
trust
threshold
adopted
for
the
purposes
of
this
simulation
is
that
this
research
assumed
that
trust
score
(Tn)
values
range
from
0
to
100.
It
is
assumed
that,
at
the
operational
stage,
agreement-driven
trust
is
achieved
if
the
trust
score
is
equal
to
or
higher
than
twenty-five
(Tn
≥
25).
Should
the
trust
score
exceed
seventy-five
(Tn
≥
75),
the
“Knowledge-driven
trust”
level
can
be
said
to
have
been
reached.
Meanwhile,
when
the
trust
score
surpasses
ninety
(Tn
≥
100),
trust
stands
at
the
“Collaboration-driven
trust”
level.
Initially,
the
system
will
generate
hard
constraints,
and
key
enablers
score
randomly
using
a
binomial
value
scale
of
zero
and
one.
A
generated
score
of
one
(1)
indicates
“yes”
and
that
the
agent
owns
the
factor.
If
the
score
is
zero
(0),
this
means
that
the
agent
does
not
own
the
factor.
The
total
of
the
hard
constraints
for
both
agents
constitutes
consideration
for
collaborative
partner
selection.
At
this
stage,
potential
collaboration
requires
the
minimum
value
of
four
(4)
hard
constraints
experienced
by
both
agents.
For
this
study,
C
represents
the
total
of
hard
constraints
experienced
by
agents,
along
the
following
lines:
If
C
>
4,
the
carriers
will
collaborate.
If
C
<
4,
the
carriers
will
not
collaborate.

Please
cite
this
article
in
press
as:
Sitadewi,
D.,
et
al.
Can
rivalling
truck
companies
collaborate?
An
Indonesian
case
study.
The
Asian
Journal
of
Shipping
and
Logistics
(2019),
https://doi.org/10.1016/j.ajsl.2019.12.002
ARTICLE IN PRESS
G Model
AJSL-223;
No.
of
Pages
11
D.
Sitadewi
et
al.
/
The
Asian
Journal
of
Shipping
and
Logistics
xxx
(2019)
xxx–xxx
7
Table
1
Roles,
rules
and
attributes
relating
to
agents.
Collaboration
stage
Carrier
A
Carrier
B
Neutral
party
Information
shared
Formation
stage Roles
Participate
in
the
tender
process
Facilitates
collaboration
between
carriers
Hard
constraints:
-
Type
of
cargo/products
-
Product
handling
procedure
-
Geography
Rules Disclose
relevant
information
to
enhance
the
incentive
to
collaborate
Lending
credibility
and
reputation
to
the
truck
companies
Key
enablers:
-
Transparency,
-
Clear
expectation
-
Benefit-sharing
-
Leadership
-
Prioritizations
-
Common
interest
-
Cooperation
Positioning
based
on
hard
constraints
and
information
provided
by
all
agents.
Operational
stage Roles
Focus
on
daily
operational
process
flow
to
fulfil
customer
orders.
–
Progress
towards
completion
of
operational
stage
functions:
order
processing,
routing
and
scheduling.
Rules Align
order
processing –
Draft
delivery
schedule
Coordinate
route
planning
Tactical
stage Roles
Achieve
enhanced
resource
management
to
improve
transportation
utilization.
–
Progress
towards
completion
of
tactical
stage
functions:
forecasting
and
order
assignment.
Rules Forecast
future
shipment –
Arrange
carrier/shipment
assignment
Strategic
stage Roles
Aim
to
achieve
growth
and
long-term
commitment
sharing
through
a
strategic
partnership
–
Progress
towards
completion
of
strategic
stage
functions:
front-end
agreement
and
network
planning.
Rules Mutual
acceptance
of
front-end
agreement
–
Assemble
network
planning
Table
2
Key
enablers
and
activities
at
the
various
stages
of
collaboration.
Collaboration
stages
Activities
Description
Operational
level
Order
processing “Order
processing”
requires
both
agents
to
own
either
“clear
expectations”
or
“transparency”
as
enablers
of
the
human
aspect
of
CTM.
Routing
“Routing”
requires
both
agents
to
own
either
“cooperation”
or
“transparency”
as
enablers
of
the
human
aspect
of
CTM.
Scheduling
“Scheduling”
requires
both
agents
to
own
either
“prioritization”
or
“transparency”
as
enablers
of
the
human
aspect
of
CTM.
Tactical
level
Shipment
forecasting “Shipment
forecasting”
requires
both
agents
to
own
either
“benefit
sharing”
or
“transparency”
as
enablers
of
the
human
aspect
of
CTM.
Order
assignment
“Order
assignment”
requires
both
agents
to
own
either
“cooperation”
or
“transparency”
as
enablers
of
the
human
aspect
of
CTM.
Strategic
level
Front-end
agreement
“Front-end
agreement”
requires
both
agents
to
own
either
“leadership”
or
“common
interest”
as
enablers
of
the
human
aspect
of
CTM.
Network
planning
“Network
planning”
requires
both
agents
to
own
either
“clear
expectation”
or
“transparency”
as
enablers
of
the
human
aspect
of
CTM.
Table
3
Summary
of
simulation
one
and
simulation
two
scenarios.
Simulation
Scenario
1
Simulation
Scenario
2
Description
All
agents
independently
used
the
key
enablers
of
the
human
aspect
of
CTM
to
conduct
horizontal
collaboration
and
develop
trust.
All
agents,
with
the
help
of
a
neutral
party,
developed
trust
using
key
enablers
of
the
human
aspect
of
CTM
to
promote
horizontal
collaboration.
Agents
Carrier:
Company
Y
Carrier:
Company
Z
Neutral
party:
APTRINDO
Carrier:
Company
X
Carrier:
Company
Y
Decision
variables
Formation
stage
Hard
constraints
score
≥
4
to
join
collaboration.
Operational
stage
Choose
to
conduct
scheduling,
routing
and
order
processing
based
on
the
availability
of
key
enablers
of
the
human
aspect
of
CTM.
Agreement-driven
trust
reached
when
trust
≥
25.
Tactical
stage
Choose
to
conduct
forecasting
and
order
assignments
based
on
the
availability
of
key
enablers
of
the
human
aspect
of
CTM.
Knowledge-driven
trust
reached
when
trust
≥
75.
Strategic
stage
Choose
to
conduct
front-end
agreement
and
network
planning
based
on
the
availability
of
key
enablers
of
the
human
aspect
of
CTM.
Collaboration-driven
trust
reached
when
trust
≥
100.

Please
cite
this
article
in
press
as:
Sitadewi,
D.,
et
al.
Can
rivalling
truck
companies
collaborate?
An
Indonesian
case
study.
The
Asian
Journal
of
Shipping
and
Logistics
(2019),
https://doi.org/10.1016/j.ajsl.2019.12.002
ARTICLE IN PRESS
G Model
AJSL-223;
No.
of
Pages
11
8
D.
Sitadewi
et
al.
/
The
Asian
Journal
of
Shipping
and
Logistics
xxx
(2019)
xxx–xxx
In
this
study,
H
represents
the
total
of
key
enablers
of
behavioural
aspects
of
CTM
owned
by
the
agents.
For
this
simu-
lation
featuring
two
agents,
the
maximum
value
of
key
enablers
is
fourteen
(14)
since
each
agent
owned
a
total
of
seven
(7)
(common
interest,
transparency,
prioritization,
clear
expectations,
leadership,
cooperation
and
benefit-sharing).
Each
of
these
key
enablers
of
CTM
influences
the
ability
of
the
agent
to
conduct
various
activities
at
the
operational,
tactical
and
strategic
lev-
els.
The
key
enablers,
as
the
behavioural
aspects
of
CTM
at
each
collaboration
stage,
are
shown
in
Table
2.
Meanwhile,
Table
3
con-
tains
a
summary
of
the
simulation
description
and
the
parameters
employed.
4.
Results
and
discussion
In
both
Scenario
1
and
Scenario
2,
the
agents
can
cooperate
only
at
the
operational
level
at
the
start
of
the
collaboration.
Scenario
1
starts
the
collaboration
with
zero
trust.
Scenario
2
starts
with
a
trust
score
of
ten
due
to
the
presence
of
a
neutral
party,
which
adds
a
trust
score
of
five
(Tn
+
5)
for
each
agent
at
the
beginning
of
the
collaboration.
The
simulation
randomly
generated
the
hard
constraints
and
key
enablers
as
behavioural
aspects
of
CTM.
During
the
initiation
of
collaboration,
both
Carrier
A
and
Carrier
B
will
align
the
hard
constraint
factors
and
decide
to
join
the
collaboration.
The
simulation
indicated
that
both
carriers
encountered
the
following
hard
constraints:
truck
compatibility,
product
compatibility,
prod-
uct
handling
and
geography.
Table
4
contains
a
summary
of
the
key
enablers
generated
by
the
simulation
for
each
carrier
agent.
Owning
one
of
the
key
enablers
will
influence
the
ultimate
out-
come
of
the
collaboration.
For
example,
when
no
carrier
owned
the
“leadership”,
this
resulted
in
none
driving
the
partnership
for-
ward.
4.1.
Simulation
results
with
fourteen
key
enablers
In
the
ideal
situation
where
all
fourteen
key
enablers
are
present
within
both
carriers,
trust
can
develop
much
faster,
allowing
both
agents
to
collaborate
across
all
functions
at
every
level
of
collaboration
(operational–tactical–strategic).
Trust
can
develop
incrementally
from
the
agreement-driven
trust
at
the
ini-
tiation
of
the
collaboration
to
the
highest
level
of
trust,
namely;
collaboration-driven
trust.
Scenario
2
developed
trust
at
a
much
faster
rate
compared
to
Scenario
1
due
to
the
presence
of
a
neu-
tral
party
which
instilled
additional
trust
at
the
outset
of
the
collaboration.
Since
both
Carrier
A
and
Carrier
B
were
capable
of
collaborating
in
all
functions
of
the
operational
stage
(scheduling,
routing
and
order
processing),
agreement-driven
trust
(Tn
≥
25)
was
achieved
during
the
fifth
iteration
of
Scenario
1
with
a
trust
score
of
32
(Tn
=
32)
and
the
third
iteration
of
Scenario
2
with
a
trust
score
of
28
(Tn
=
28).
As
the
extent
of
the
collab-
oration
of
both
agents
deepens
at
the
tactical
stage,
shipment
forecasting
and
conducting
carrier
assignment
can
be
mutually
undertaken.
At
the
tactical
level,
both
agents
enhanced
knowl-
edge
and
understanding
of
their
partner’s
requirements
and
methods
of
working.
Therefore,
both
carriers
will
deliver
better
collaboration
results
vis-a-vis
their
respective
partner’s
expec-
tations,
which,
in
turn,
increases
trust.
Knowledge-driven
trust
(Tn
≥
75)
in
Scenario
1
was
achieved
after
the
ninth
interaction
with
trust
score
s
78
(Tn
=
78)
and
the
eighth
iteration
of
trust
score
82
(Tn
=
82).
As
the
trust
develops
into
knowledge-driven
trust,
both
agents
understand
each
other
sufficiently
well
for
them
to
extend
the
collaboration
to
the
strategic
level.
In
the
eleventh
iteration
of
Scenario
1
with
a
trust
score
(Tn
=
106)
and
the
ninth
iteration
of
Scenario
2
with
a
trust
score
(Tn
=
100),
both
agents
achieved
the
highest
form
of
trust
development,
a
collaboration-driven
trust
(Tn
≥
100).
At
the
highest
level
of
trust,
collaborating
agents
were
comfortable
with
open
com-
munication
which
manifested
itself
as
a
greater
commitment
to
information-sharing
of
knowledge
and
internal
procedures
which
promoted
transparency
and
reduced
uncertainty
(Kwon
and
Suh,
2005).
Low
levels
of
uncertainty,
high
levels
of
trust
and
transparency
between
collaborating
agents
allow
for
long-term
collaboration.
4.2.
Simulation
results
of
six
key
enablers
In
the
simulation
featuring
a
total
of
six
key
enablers
owned
by
both
carriers
throughout
every
level
of
collaboration
(operational–tactical–strategic),
both
Carrier
A
and
Carrier
B
either
successfully
conducted
or
failed
to
conduct
each
equitable
share
of
the
partnership.
At
the
operational
level,
both
carriers
jointly
collaborated
only
during
the
routing
phase,
while
only
Carrier
A
conducted
scheduling
and
Carrier
B
alone
conducted
order
pro-
cessing.
Due
to
the
presence
of
a
neutral
party
which
engendered
additional
trust
at
the
initiation
of
the
collaboration,
Scenario
2
had
the
advantage
of
a
head-start
in
developing
trust
compared
to
Scenario
1.
Both
agents
achieved
agreement-driven
trust
only
after
the
trust
score
exceeded
or
equalled
twenty-five
(Tn
≥
25)
in
the
thirteenth
iteration
of
Scenario
1
with
a
trust
score
of
26
(Tn
=
26)
and
in
the
eighth
iteration
in
Scenario
2
with
a
trust
score
of
26
(Tn
=
26).
At
the
tactical
level,
both
carriers
jointly
collab-
orated
only
on
shipment
forecasting
and
failed
to
cooperate
on
carrier
assignment.
Neither
was
willing
to
disclose
internal
infor-
mation.
Thus,
both
carriers
were
relatively
slower
at
gaining
more
knowledge
about
their
partners’
requirements
and
understanding
how
their
partners
worked.
A
paucity
of
“transparency”
under-
pinned
the
reluctance
of
each
carrier
to
share
information
about
its
internal
organizational
processes.
However,
both
carriers
owned
“cooperation”,
thus
ensuring
that
each
would
attempt
to
solve
problems
jointly,
rather
than
taking
punitive
action.
Knowledge-
driven
trust
(Tn
≥
75)
was
achieved
in
the
thirty-eighth
iteration
in
Scenario
1
with
a
trust
score
of
76
(Tn
=
76)
and
in
the
thirty-
third
iteration
in
Scenario
2
with
a
trust
score
of
76
(Tn
=
76).
Only
Carrier
A
owned
“leadership”
with
the
result
that
it
represented
the
dominant
party
that
led
collaboration
at
the
strategic
level.
Both
Carrier
A
and
Carrier
B
accumulated
trust
score
s
in
every
iteration
of
the
strategic
stage.
When
the
trust
reached
a
trust
score
of
one
hundred
(Tn
=
100),
it
developed
into
collaboration-
driven
trust,
the
highest
level
of
trust
in
the
horizontal
collaboration
trust
model.
Collaboration-driven
trust
(Tn
≥
100)
was
achieved
in
the
fiftieth
iteration
in
Scenario
1
with
a
trust
score
of
100
(Tn
=
100)
and
at
the
forty-fifth
iteration
of
Scenario
2
with
a
trust
score
of
100
(Tn
=
100).
Despite
achieving
the
highest
level
of
trust,
collaborating
agents
remained
uncomfortable
with
open
commu-
nication.
This
translated
into
a
reduced
willingness
for
information
sharing
relating
to
knowledge
and
internal
procedures
for
fear
of
opportunist
behaviour
by
competitors.
This
situation
hindered
transparency
and
allowed
uncertainty
to
persist,
thereby
inhibiting
both
carriers’
meaningful
long-term
collaboration
at
the
strategic
stage.
This
situation
was
similar
to
the
findings
of
the
case
studies,
which
suggested
that
the
development
of
trust
between
rival
or
unrelated
freight
trucking
companies
requires
a
greater
length
of
time.
4.3.
Simulation
result
with
four
key
enablers
The
simulation
featuring
a
total
of
only
four
key
enablers
restricted
the
ability
of
both
Carrier
A
and
Carrier
B
to
collaborate
seamlessly,
mainly
due
to
the
lack
of
established
common
interest
and
a
clear
expectation
of
the
collaboration
outcome.
It
should
be
noted
that
in
a
horizontal
collaboration
involving
rival
companies,

Please
cite
this
article
in
press
as:
Sitadewi,
D.,
et
al.
Can
rivalling
truck
companies
collaborate?
An
Indonesian
case
study.
The
Asian
Journal
of
Shipping
and
Logistics
(2019),
https://doi.org/10.1016/j.ajsl.2019.12.002
ARTICLE IN PRESS
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AJSL-223;
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Pages
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D.
Sitadewi
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/
The
Asian
Journal
of
Shipping
and
Logistics
xxx
(2019)
xxx–xxx
9
Table
4
Key
enablers
to
the
CTM
generated
in
the
simulation.
Total
of
four
key
enablers
Total
of
six
key
enablers
Total
of
fourteen
key
enablers
Carrier
A “Prioritization”
“Common
interest”
“Prioritization”
“Leadership”
“Cooperation”
“Prioritization”
“Transparency”
“Common
interest”
“Cooperation”
“Leadership”
“Clear
expectation”
“Benefit
sharing”
Carrier
B
“Transparency”
“Prioritization”
“Benefit
sharing”
“Clear
expectation”
“Cooperation”
“Prioritization”
“Transparency”
“Common
interest”
“Cooperation”
“Leadership”
“Clear
expectation”
“Benefit
sharing”
Table
5
Summary
of
trust
values
generated
from
the
simulations.
both
should
harbour
the
common
goal
of
developing
a
shared
col-
laborative
perspective
(Pomponi
et
al.,
2015).
This
condition
limits
the
development
of
trust,
as
seen
in
Table
5,
where
collaboration
stagnated
at
the
tactical
stage.
In
this
simulation,
agreement-driven
trust
was
achieved
when
the
trust
score
exceeded
or
was
equal
to
twenty-five
(Tn
≥
25).
Only
after
the
trust
score
had
reached
26
(Tn
=
26)
in
the
thirteenth
iteration
of
Scenario
1
and
the
eighth
iteration
of
Scenario
2,
did
the
trust
resulting
from
the
collabo-
ration
develop
into
agreement-driven
trust,
thereby
enabling
the
partnership
to
move
to
the
tactical
stage.
As
both
agents
in
these
scenarios
entered
the
tactical
stage,
the
key
enablers
owned
by
each
influenced
their
respective
ability
to
conduct
activities
at
the
tactical
level.
In
the
simulation,
Carrier
B
performed
the
major-
ity
of
the
collaboration
stage
activities
unilaterally,
while
willingly
sharing
this
knowledge
with
Carrier
A
during
the
tactical
stage.
However,
Carrier
A
did
not
reciprocate
this
gesture
since
it
did
not
own
the
necessary
key
enablers.
The
longer
the
collaboration
per-
sisted,
the
more
evident
it
became
that
the
behaviour
of
Carrier
A
did
not
inspire
trust,
as
it
contributed
little
to
the
partnership.
Rather,
a
higher
risk
of
opportunism
existed
since
Carrier
B
con-
sistently
disclosed
its
internal
process,
customer
information
and
other
confidential
data
to
Carrier
A.
This
situation
hindered
trans-
parency
and
allowed
uncertainty
to
persist
between
collaborating
agents
which
restricted
the
development
of
trust.
The
collabora-
tion
no
longer
developed
trust
during
the
thirty-third
iteration
of
Scenario
1,
when
the
trust
score
was
64
(Tn
=
64).
Meanwhile,
Sce-
nario
2
required
thirty
iterations
before
trust
ceased
developing
when
the
trust
score
was
64
(Tn
=
64).
Trust
was
unable
to
develop
to
the
next
level,
the
knowledge-driven
trust
level,
and
the
extent
of
collaboration
was
restricted
to
the
operational
stage
and
tactical
stages.
The
simulation
result
was
almost
identical
to
the
situation
in
the
case
study
in
which
rival
carriers
tended
to
restrict
collab-
oration
to
the
operational
level
since
it
focused
primarily
on
daily
operations
relating
to
customer
order
fulfilment
and
minimizing
the
risk
of
opportunistic
behaviour.
According
to
the
simulation
results,
in
order
to
achieve
more
rapid
trust
development
in
a
shorter
time
period
into
the
highest
level
of
trust,
all
collaborating
agents
must
own
all
key
enablers
as
behavioural
aspects
of
CTM.
In
contrast,
trust
stops
developing
when
neither
agent
holds
the
majority
of
the
essential
key
enablers.
Therefore,
key
enablers
of
behavioural
aspects
of
CTM
are
crucial
to
determining
the
success
of
collaboration
both
in
terms
of
how
well
individuals
cooperate
both
internally
and
externally
with
a
collab-
oration
partner.
The
result
of
the
simulation
proves
the
validity
of
the
theory
propounded
by
Gino
and
Pisano
(2008).
The
company’s
behaviours
are
critical
in
influencing
both
the
manner
in
which
the
vast
majority
of
the
operating
systems
function
and
the
quality
of
their
performance.
5.
Conclusion
This
paper
presents
an
understanding
of
how
the
behaviour
and
actions
of
a
company
are
critical
in
influencing
horizontal
col-
laboration
and
subsequent
development
of
trust.
Among
the
key

Please
cite
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article
in
press
as:
Sitadewi,
D.,
et
al.
Can
rivalling
truck
companies
collaborate?
An
Indonesian
case
study.
The
Asian
Journal
of
Shipping
and
Logistics
(2019),
https://doi.org/10.1016/j.ajsl.2019.12.002
ARTICLE IN PRESS
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AJSL-223;
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Pages
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10
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Sitadewi
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/
The
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of
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and
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xxx
(2019)
xxx–xxx
enablers
within
the
behavioural
aspects
of
CTM,
“transparency”
is
the
most
crucial
since
it
relates
to
information
sharing
regard-
ing
internal
operation
processes
with
collaboration
partners.
The
simulation
results
showed
that
“transparency”
is
beneficial
since
it
reduces
the
vulnerability
of
collaborating
companies
to
opportunis-
tic
behaviour.
Moreover,
“common
interest”,
“clear
expectation”,
“cooperation”
and
“benefit
sharing”
are
also
essential
to
horizon-
tal
CTM.
The
simulation
results
indicated
that
where
collaborating
agents
co-own
“clear
expectations”,
“cooperation”,
and
“benefit
sharing”,
this
enables
both
companies
to
lay
the
groundwork
for
a
long-term
strategic
horizontal
collaboration
agreement.
This
con-
dition
facilitates
the
development
of
trust
on
the
part
of
both
companies
in
achieving
the
full
potential
and
benefits
of
the
col-
laboration.
The
simulation
results
of
this
research
also
made
the
following
discovery.
First,
the
presence
of
a
neutral
party
facilitating
col-
laboration
is
not
crucial
to
accelerating
the
development
of
trust
during
the
horizontal
collaboration
between
truck
freight
compa-
nies.
There
exists
the
possibility
that
employing
the
services
of
a
neutral
party
can
be
avoided
provided
that
both
collaborating
agents
control
all
necessary
key
enablers
as
behavioural
aspects
of
CTM.
However,
the
presence
of
a
neutral
party
is
crucial
to
inspir-
ing
trust
and
a
good
reputation,
especially
between
carriers
with
no
previous
knowledge
of
each
other.
The
Case
X
study
is
only
appli-
cable
to
collaborating
carriers
with
a
higher
level
of
expertise
and
resources
to
manage
the
collaboration.
Unfortunately,
not
all
truck-
load
companies
in
Indonesia
have
either
the
knowledge
or
capacity
to
manage
horizontal
collaboration.
Matopoulos
et
al.
(2007)
reported
that
some
authors
regard
power
as
one
of
the
elements
that
can
significantly
hinder
the
development
of
trust
during
collaboration.
Since
the
research
reported
here
does
not
analyze
power
play,
bargaining
strategies
or
the
risks
inherent
to
horizontal
collaboration,
these
factors
will
be
the
focus
of
a
future
investigation.
The
focus
of
this
study
was
limited
to
the
difference
in
trust
score
based
on
a
company’s
“will-
ingness
to
collaborate”.
However,
the
research
did
not
include
the
difference
in
trust
score
based
on
management
performance
in
such
areas
as
sales
and
revenue,
which
also
represent
an
area
for
research.
This
paper
contributes
to
learning
points
contained
both
in
the
relevant
literature
and
practical
contributions
of
the
final
stage
within
SSM,
namely;
“implementation
of
ameliorative
action”.
Since
it
is
difficult
to
conduct
field
experimentation,
thus,
this
research
uses
computational
simulation
using
ABM
to
demonstrate
the
initiation
and
continuation
of
horizontal
collaboration
based
on
trust
development.
The
simulation
result
based
on
both
the
current
and
ideal
situation
showed
the
collaboration
can
be
developed
and
sustained
through
three
stages
of
trust
development
(agreement-
driven
trust,
knowledge-driven
trust,
and
collaboration-driven
trust)
that
are
influenced
by
the
presence
of
key
enablers
in
the
behavioural
aspect
(transparency,
common
interest,
cooperation,
leadership,
clear
expectation,
prioritization,
and
benefit-sharing)
in
each
collaboration
party.
Thereby,
the
practical
contribution
of
this
paper
is
to
demonstrate
that
in
the
real
system
truck
freight
transportation
companies
can
collaborate
and
continuously
main-
tained
its
collaboration
with
the
identified
behavioural
enablers.
Incomplete
key
enablers
in
the
behavioural
aspect
may
hinder
the
continuation
and
extension
of
horizontal
collaboration
among
truck
freight
transportations.
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