supply chain pedagogy 1

International Journal of Production Research,Vol. 46, No. 5, 1 March 2008, 1297–1313

Game theoretic enterprise management in industrial collaborative

networks with multi-agent systems

T. KAIHARA*y and S. FUJIIz

yFaculty of Engineering, Department of Computer and Systems Engineering,

Kobe University, Kobe, Japan

zFaculty of Science and Technology, Department of Mechanical Engineering,

Sophia University, Tokyo, Japan

(Revision received January 2007)

Nowadays, virtual enterprise (VE) is an important paradigm of businessmanagement in an agile environment. VE exists in several kinds of businessorganization through multi-layered product flows. It is obvious that amechanism, through which these different enterprises can be integrated together,is required for the better management of VE. In this paper, we focus on thenegotiation process in VE formulation as a basic research to clarify its effectivemanagement. Each enterprise in VE is defined as a software agent with multi-utilities, and three types of primitive business models are targeted, such as thevertically integrated business model, horizontally specialized business modeland hybrid business model. We develop a three-layered VE model for computersimulation so as to clarify VE formulation dynamism with the proposednegotiation mechanism.

Keywords: Virtual enterprise; Negotiation; Multi-agent system; Game theory;Collaborative network

1. Introduction

With the globalization of commerce, distribution and manufacturing, cooperationbetween enterprises of different sectors and cultures is significantly increasing.It is not only limited to sub-contracting and cooperation with suppliers andcustomers better known as ‘supply chain’ or ‘extended enterprise’, but alsoconcerned with virtual enterprise (VE). VE is an important concept of businessmanagement in an agile environment. VE is a temporary alliance of enterprises thatcome together to share skills or core competencies and resources in order to betterrespond to business opportunities in an agile environment and whose cooperationis supported by global computer networks (Camarinha-Matos et al. 1999), shownin figure 1.

VE is a relatively new concept and different from previous cooperative businessmodels (Putnik et al. 2005). Several kinds of organization are included in VE, andit is not easy to establish an appropriate collaboration amongst a large number

*Corresponding author. Email: [email protected]

International Journal of Production Research

ISSN 0020–7543 print/ISSN 1366–588X online � 2008 Taylor & Francis

http://www.tandf.co.uk/journals

DOI: 10.1080/00207540701224400

of enterprises, such as in supply chain management (SCM) (Goldratt 1983,Fisher 1994, Chang et al. 2004). They normally have different objectives and theseare often conflicting. Typical purchasing and manufacturing departments’ views,such as large product lot size, are completely against marketing or distribution views(Kovacs et al. 2001, Shen 2006). That might cause the separation of enterprises anddestroy VE relationships. A new mechanism is obviously required to integrate eachenterprise in VE so as to establish effective collaborative VE (Camarinha-Matoset al. 2006).

In this paper, we focus on the negotiation process in VE formulation as a basicresearch to clarify its effective and concurrent management. Each enterprise isdefined as an agent (Fox et al. 2000, Conen and Sandholm 2002), and a frameworkof multi-agent programming with marketing science (Katahira 1987) and gametheoretic approach (Von Neumann and Morgenstern 1947) is newly proposed asa negotiation algorithm among the agents. Concretely, each unit is defined as asoftware agent in our VE model, and their decision making is formulated asmarketing science models and N-person game theoretic methodology.

We first classify business models in VE into three types, such as the verticallyintegrated business model, horizontally specialized business model and hybridbusiness model. Then we propose a contract net protocol (CNP)-based negotiationprotocol amongst enterprises with marketing science models, such as thelexicographic model and maximum likelihood hierarchical (MLH) model, andN-person game theoretic approach (Smith 1980, Durfee et al. 1987, Katahira 1987,Sandholm 1993). CNP models transfer of control in a distributed system with themetaphor of negotiation among autonomous intelligent beings (Conen andSandholm 2002). CNP consists of a set of nodes that negotiate with one anotherthrough a set of messages (Kaihara and Fujii 2002, 2003). Nodes generally representthe distributed computing resources to be managed and correspond to ‘enterprises’ inthis paper. Marketing science-based negotiation is applied into the vertically inte-grated business model considering a realistic enterprise management strategy. Thehorizontally specialized business model includes N-person game theoretic negotia-tions to realize the coordination amongst enterprises in the same business segment.We develop a computer simulation model to form VE through multiple negotiations

Figure 1. VE and other co-operative enterprises.

1298 T. Kaihara and S. Fujii

amongst several potential members in the negotiation domain, and finally clarify theformation dynamism about three types of business model with the negotiationprocess.

The contribution of this paper is to facilitate comprehensive and rationalmanagement amongst all the collaborative enterprises not only for VE butalso SCM.

2. Business model in VE

2.1 Virtual enterprise model

A large number of diversified networked organizations of enterprises fall underthe general definition of VE. We assumed our VE model in the simplest possibledefinition as a basic research, as follows:

1. Duration: Single businessAn alliance of the enterprises is established towards a single businessopportunity, and is dissolved at the end of such process.

2. Topology: Fixed structureThere exist established supply chains with an almost fixed structure.

3. Participation: Single allianceAll the enterprises are participating int only a single alliance at the same time.

4. Coordination: Democratic allianceA different organization can be found in some supply chains withouta dominant company. All the enterprises cooperate on an equal basis,preserving their autonomy.

5. Visibility scope: Single levelAll the enterprises in VE communicate only to their direct neighbours in theirarchitecture (figure 2). That is the case observed in most supply chains.

Needless to say, it is a very important and difficult activity when forminga virtual enterprise to select appropriate business partners, i.e. partnering, because

Figure 2. VE model.

Game theoretic enterprise management in industrial collaborative networks 1299

each enterprise must consider not only the pursuit of profit but also sharing the riskto join the virtual enterprise. The partnering is described as coordination activityamongst the enterprises, and some sophisticated coordination mechanism is requiredto realize efficient interactions.

The development of a coordination mechanism in computer-science can be foundin the area of workflow management system, computer-supported cooperative work(CSCW), and multi-agent systems. The area of multi-agent systems, especially wheninvolving intelligent autonomous agents, has been the discussion of coordinationissues and supporting mechanism (Kaihara and Fujii 2002, 2003). The interactioncapability, both amongst agents and between agents and their environment, is oneof the basic characteristics of an agent (Fox 2000). In this paper we focus on thecontract net protocol (CNP), which is one of the mechanisms coming from earlywork on multi-agent systems (Smith 1980), as the coordination and negotiationmechanism amongst business units in VE. Figure 2 shows the assumed VE modelin this paper. We call an enterprise as unit, and there exist m layers, which have mn

units in the model. The lowest level corresponds to consumers who create originaltask requests to the VE.

At first, the customer dispatches new orders to all the units in layer m, and thenseveral units, which are satisfied with the order, respond and circulate the ordertoward upper units in the VE model. Finally a VE with single supply chain will beestablished as a temporary alliance for the order as a consequence of theirnegotiations through all the layers.

2.2 Business model in VE environment

As described in the previous section, there exist many business models in VEenvironment. We classify three types of business model in this study: the verticallyintegrated business model, the horizontally specialized business model and thehybrid business model as basic study. VE is regarded as an aggregation or acombination of these three business models, no matter how messy and complicatedtheir structure is in reality. We try to simplify the VE structure from the systemsengineering viewpoint, and analyze the formation dynamism in VE with thenegotiation mechanism in this paper.

Figure 1 shows the hypothetical VE model in this paper. We call an enterprisea unit, and there exist n layers, which have mn units in the VE model. The rightend corresponds to consumers who can create original task requests to the VE.As the layer number increases, we describe it lower based on the product flow orderin this paper.

Generally we can observe vertical business models in traditional industries.In this business model the manufacturing business processes top-down as well asbottom-up from the process requirements, resulting in an integrated approach tooverall business requirements. We will call this business model, which is based onend-to-end proprietary solutions that lock a customer to a manufacturer, a ‘verticallyintegrated business model’. Each unit at the same layer in figure 2 never tries tocooperate in our vertically integrated business model, because each unit is keento find its appropriate partner just in vertical directions. For example, Unitij triesto find an alliance unit at each neighbouring layer: layer (i� 1) and (iþ 1) in figure 2.Consequently only one SC can be formed in this business model. We introduce the


consumer’s behaviour in marketing science into unit behaviour, and that makesour VE model more practical.

On the other hand, enterprise relationships may represent a forerunning patternof the learning alliance, whereby ongoing close interaction of horizontal alliancepartners at single level or multiple hierarchical levels can be used to facilitatethe mutual accumulation of superior organizational capabilities within the alliancefirms. We will call this business model a ‘horizontally specialized business model’. Allthe units at the same layer try to cooperate to maximise their profit in total in ourhorizontally specialized business model. They behave as if they are under jointmanagement, and we can see a kind of this style of management in industrial clustersin Japan (Kansai Bureau of Economy, Trade and Industry, available online). Weapply N-persons game theory to formulate their behaviour in cooperation, because itdescribes a decision-making process to find their equilibrium solution in a socialmanner.

Finally, a hybrid business model combines the above-mentioned two businessmodels. There exists a parent–child relationship amongst units in VE, and the parentcompany has the advantage in their contract. Units in the child companies tryto keep harmony as a group by sharing a common destiny in their management.We can see this type of business model sometimes in the Japanese automobileindustry, such as Toyota or Mazda. We propose an alliance strategy based oncooperative game theory in this business model.

Detailed architecture of the three business models is described in section 4.

3. Enterprise agent

3.1 Unit structure

Each unit (enterprise) is defined as agent in our VE model, and its structure isdescribed in figure 2. We adopt CNP as the coordination and negotiationmechanism amongst the units. CNP models transfer control in a distributedsystem with the metaphor of negotiation between autonomous intelligent beings.CNP consists in three interaction phases, involving two roles (manager andcontractor). A manager announces a task to a set of contractors, each contractorbids for the task, and the manager awards the task (i.e. reward) to the contractorwith the best bid. Any agent can start such a protocol by endorsing the adequaterole. Nodes generally represent the distributed computing resources to be managed,corresponding to ‘units’ in this paper. The unit structure proposed in this paper isdescribed in figure 3.

An agent (¼unit) can act both as a manager and a contractor of a delivery sets.When a unit receives new order (¼task announcement) i, it creates a contractor/manager set (manager i/contractor i) for task i inside. Manager i creates a new ordertowards the lower units to secure the contract with the upper layer.

There exist several situations in partnering amongst enterprise agents. In thispaper it is assumed that the product demand is predictable in the negotiation undermultipurpose criterion as basic study. That means order patterns are previouslygiven and the negotiations start after the order reaches each enterprise agent. Theyshould prepare robust solutions with maximum utilities against the order.


We propose several agent behaviours including game theoretic approach accordingto this assumption.

3.2 Negotiation algorithm

The timeline of the proposed negotiation mechanism in this paper is shown in

figure 4 (m-contractors n-managers model). Negotiation steps according to agent

roles are described as follows:

Manager (in layer x)

Step M1: Create a new task based on the received bid information.

Step M2: Task announcement (TA) to the upper units.

Step M3: After the bidding period (Bidding period) expires, check all the acquired

bids according to its standard. If there exists no bid to select, go to M4. Otherwise go

to M5.

Step M4: Modify the task and go to M2.

Step M5: Select the task and send reward (Reward) to the corresponding unit.

Figure 4. Negotiation flow.

Figure 3. Unit structure.


Contractor (in layer x� 1)

Step C1: Receive TAs.

Step C2: Create an estimated bid according to its own capability.

Step C3: Send the bid to the manager (Bid).

Step C4: Request task announcement to the manager.

We prepare several parameters to define unit behaviours as follows:

PijTA TA price of Unitij

QijTA TA quantity of Unitij

LijTA TA lead time of Unitij

Qðiþ1ÞjBID Bid quantity of Unit(iþ1)j

Lðiþ1ÞjBID Bid lead time of Unit(iþ1)j

PijBID Bid price of Unitij

QijBID Bid quantity of Unitij

LijBID Bid lead time of Unitij

Pðiþ1ÞjTA TA price of Unit(iþ1) j

Qðiþ1ÞjTA TA quantity of Unit(iþ1) j

Lðiþ1ÞjTA TA lead time of Unit(iþ1) j

costij Process cost of Unitij per productprofitij Profit rate of Unitij

process timeij Process time of Unitij per productplusij Quantity increase rate of Unitij

procure timeij Estimated procure time of Unitij per product

Unit formulation in each business model is described in the following

sections.

3.3 Vertically integrated VE model

CNP is just the skeleton in the negotiation algorithm, and it is necessary to define

how to select the appropriate bid (Step M5) to establish profitable contract.

Marketing science-based negotiation is applied into the managers’ decision making

to realize sophisticated bid selection based on consumers’ behaviours in the vertically

integrated business model.First of all, each attribute of managerij in the TA producing process (Step M1) is

as follows:

PijTA ¼ costij � ð1� profitijÞ ð1Þ

QijTA ¼ Q

ðiþ1ÞjBID ð2Þ

LijTA ¼ L

ðiþ1ÞjBID �Q

ðiþ1ÞjBID � processing timeij ð3Þ


Then contractorij tries to create its bid (Step C1) against TA from manager in layer(iþ 1) by the following equations:

PijBID ¼ costij �

1þ profitij2

� �ð4Þ

QijBID ¼ Q

ðiþ1ÞjTA � ð1þ plusijÞ ð5Þ

LijBID ¼ Qij

BID � ðprocessing timeij þ procure timeijÞ ð6Þ

In this model, the contractor democratically tries to share their profit with a loweragent (i.e. manager) equally, shown in equation (4). The marketing science approachis applied in the bid selection mechanism (Step M5) in the vertically integrated VEmodel. We consider two types of marketing science model, named lexicographicmodel and MLH model (Katahira 1987). Bid selection mechanism in manager agentis described in each model as follows:

Lexicographic model

Step L1: Set priorities on all the attributes.

Step L2: Select a bid with the highest value in the attribute. In case of a tie, moveto the next attribute and check the highest value. This routine is continued until onlyone bid is selected.

MLH model

Step MLH1: Set priorities on all the attributes.

Step MLH2: Standardize the highest attribute with the following equations:

~zij ¼ðhighest zij amongst unselected j Þ � zij

highest zij amongst unselected jð7Þ

where zij is the evaluation value of task j on ith attribute; ~zij is the standardized zij.

Step MLH3: If ~zij is within the tolerable amount (i.e. tolerance error: �i%),then keep this attribute for the calculation in the next step.

Step MLH4: After all the attributes are evaluated, then the preference index Vj

of task j is calculated:

Vj ¼ ð�1 � ~z1jÞ � ð�2 � ~z2jÞ � � � � � ð�i � ~zijÞ ð8Þ

Finally selection probability of taskj is calculated by the following equation:

Pj ¼VjPnk¼1 Vk

ð9Þ

3.4 Horizontally specialized VE model

The horizontally specialized business model includes N-person game theoreticnegotiations to realize the coordination amongst enterprises in the same business


segment. In this model we consider there is a coordinator to manage the negotiation

process amongst all the enterprises (i.e. contractors) in each layer. The coordinator in

layer i manages all the units in the layer. It receives all TAs from lower layer (iþ 1)

on behalf of coordinators in the layer i, and replies to the manager. The N-person

cooperative game approach is applied to share its profit amongst all the units in the

layer based on their attributes. So it is regarded as a kind of joint order organization.Firstly, the TA producing process (Step M1) is in common with the vertically

integrated business model. Then the Bidding process is automatically replied based

on the received TA, unless it yields no profit in any cooperation of contractor units

(Step C2). So the attributes in the bid are defined as follows:

PijBID ¼ P

ðiþ1ÞjTA ð10Þ

QijBID ¼ Q

ðiþ1ÞjTA ð11Þ

LijBID ¼ L

ðiþ1ÞjTA ð12Þ

Finally the order sharing process is formulated with axioms called Shapley value.

We applied the Shapley value because our VE cooperation model doesn’t always

satisfy super-additivity condition. This horizontally specialized VE corresponds to

a kind of enterprise union in our VE model, and it sometimes requires some

enterprise to make a sacrifice so as to obtain global profit for their union. That

means super-additivity condition isn’t always satisfied in this horizontally specialized

VE model. The Shapley value describes one approach to the fair allocation of gains

obtained by cooperation among several actors even in non-super-additivity

conditions. The setup is as follows: a coalition of actors cooperates, and obtains

a certain overall gain from that cooperation. Since some actors may contribute more

to the coalition than others, the question arises of how to distribute fairly the gains

among the actors; in other words, how important is each actor to the overall

operation, and what payoff can they reasonably expect? The Shapley value is one

way to distribute the total gains to the actors, assuming that they all collaborate.At first we define characteristic function (V(S)) as follows:

VðS Þ ¼ UprofitðS Þ �UleadtimeðS Þ ð13Þ

where Uprofit(S ) is the profit in cooperation S, Uleadtime(S ) is the Boolean of lead

time constraint (1: OK, 0: NG).Then the task is divided under the cooperation S 0, which maximizes V(S).

The contribution of unit i in cooperation S is calculated as follows:

�i ¼X

S:i2S�N

ð Sj j � 1Þ!ðn� Sj jÞ!

n!vðS Þ � v

S

fig

� �� ð14Þ

where N is a set of all units, v is all the profit in cooperation S, jSj is the number of

members in cooperation S, (S\{i}) is the cooperation without unit i.Then naturally the following equation is acquired:X

i2N

�iðvÞ ¼ vðNÞ ð15Þ


So the profit, which gained in the coordinator, is divided into each unit in the layer

according to the Shapley value in equation (14).

3.5 Hybrid VE model

The hybrid business model combines the two above-mentioned business models.

There exists a parent–child relationship amongst units in VE, and the parentcompany has the advantage in their contract, such as in automobile or spaceindustries. Units in the child companies try to keep harmony as a group in their

management.The TA producing process (Step M1) has no difference in the two above-

mentioned business models. Then contractorij creates its bid (Step C1) against TA

from manager in layer (iþ 1) by the following equations:

PijBID ¼ costijð1þ profitijÞ ð16Þ

QijBID ¼

Qðiþ1ÞjTA

Nið17Þ

LijBID ¼ Qij

TA � ðprocessing timeij þ procure timeijÞ ð18Þ

where N is the number of cooperate units in layer i.Finally the bid selection process by manager (Step M5) is formulated by the

cooperative game theory under super-additivity condition. We define characteristicfunction (V(S)) as follows:

VðS Þ ¼ U0profitðS Þ �UleadtimeðS Þ ð19Þ

where U 0profit (S) is the manager’s profit in cooperation S.Then the characteristic function values in all the received bids are calculated and

the manager finally selects the bid with the highest value amongst them.

4. Experimental results

4.1 Simulation parameters

As a basic study, a three-layered VE model for computer simulation was developedto clarify VE formulation dynamism with the proposed negotiation mechanism.Each layer consists of three enterprises in this simulation model described in figure 2.

Simulation parameters are shown in table 1. All the results are the average of

500 trials in each simulation scenario.

Table 1. Simulation parameters.

m n �i cost0j cost1j cost2j profitij plusij processing timeij procure timeij

3 3 0.4 15–25* 45–55* 85–95* 0.17–0.23* 0.08–0.12* 0.08–0.12* 0.10–0.20*

*Followed by uniformed random distribution.


4.2 Vertically integrated VE model

We applied two types of marketing science model, named lexicographic model and

MLH model, as described previously. The priority of attributes plays an important

role in marketing science. Several simulation patterns in different priority, shown in

table 2, were carried out so as to analyze the performance of proposed negotiation

mechanisms.The results of two types of marketing science model, lexicographic model and

MLH model, are shown in tables 3 and 4, respectively. The parameter � is set as 0.4in MLH model (table 4) after several preliminary experiments.

Table 4. Total results in MLH model (n¼ 3, �¼ 0.4).

AverageStandarddeviation Average

Standarddeviation Average

Standarddeviation

Pattern 1 Pattern 2 Pattern 3

Profit 7513.20 879.24 8092.63 946.84 7513.20 879.25Stock (WIP) 23.56 2.81 20.51 2.47 23.56 2.82Lead time 21.18 2.44 22.35 2.65 21.18 2.45



Table 3. Total results in lexicographic model (n¼ 3).



Standarddeviation





Table 2. Priority in negotiation attributes.

Pattern 1 price4quantity4leadtimePattern 2 price4leadtime4quantityPattern 3 quantity4price4leadtimePattern 4 quantity4leadtime4pricePattern 5 leadtime4price4quantityPattern 6 leadtime4quantity4price


It is obvious that the results depend only on the highest prioritized attribute

in lexicographic model. The bid selection process is carried out according to the

direct managers’ preferences in this model, and that causes only the highest attribute

to affect the bid selection in the negotiation domain. In other words, the negotiation

with lexicographic model tends to establish the manager-driven negotiation,

i.e. lower layer-driven negotiation environment, in supply chains.We observed the similarity between Patterns 1 and 3, Patterns 2 and 5, and

Patterns 3 and 6, in table 4. They are all classified into the same group in terms of

attributes within the second highest. MLH model has a tolerance (�) in its selection

attributes, and it has been confirmed that the bid selection process is carried out

within the second highest attributes in (�¼ 0.4) in the simulation scenario. As a

consequence, it has been confirmed that the bid selection based on MLH model

emerges comprehensive and well-balanced tradings in terms of managers attributes,

although it also has a tendency to establish the manager-driven negotiation amongst

all the layers in VE.We increased the number of agents to 10 in all the layers so as to investigate the

scalability of the above mentioned observations. As an example, the results in MLH

model is shown in table 5, and it is obvious that the large VE model has the similar

tendency as the small model shown in table 4. We have confirmed that our

considerations mentioned before are validated even in larger VE model.

4.3 Horizontally specialized VE model

Figure 5 illustrates an experimental model of the horizontally specialized VE model

in three layers. It is assumed that the middle layer has a coordinator to realize

collaborations amongst all the enterprise inside the layer. The cooperation is carried

out according to the negotiation mechanism described in section 3.4.Simulation results from each enterprise in layer 1 and 2 are shown in table 6.

It is obvious that the total profit of layer 1 is greater than that of layer 2 in this table.

It has been clarified that coordinator increases the efficiency of layer 1 by conducting

collaboration amongst enterprises in the layer, and that means it plays an important

role in establishing a contractor-driven negotiation environment, i.e. upper layer-

Table 5. Total results in MLH model (n¼ 10, �¼ 0.4).



Standarddeviation






driven negotiation environment, compared with vertically integrated VE models in

section 4.2.Total results of horizontally specialized VE model in n¼ 3, 10 are described

in table 7. It has been observed that this model has better performance in lead time

but less in total profit due to the collaborative negotiation in layer 1. The difference

between n¼ 3, and 10 is very small, and that means the horizontal VE model is stable

and robust in terms of VE scalability. It has been proved that their collaborative

behaviour enhances their stability against structural change, but sacrifices their profit

for the robustness in this experiment.

4.4 Hybrid VE model

An experimental model of hybrid VE model is shown in figure 6. It combines vertical

and horizontal models, and establishes complex negotiation under the super-

additivity condition described in section 3.5.

Unit00

Unit01

Unit0j

Unit0n

Unit10

Unit11

Unit12

Unit20

Unit21

Unit2j

Unit2n

CustomerUpper Stream Lower Stream

Co-ordinator

Figure 5. Experimental model (n¼ 3).

Table 7. Total results in horizontal VE model.

n¼ 3 n¼ 10

Average Standard deviation Average Standard deviation

Profit 6179.73 730.06 6200.25 765.00Stock (WIP) 21.28 2.56 21.13 2.50Lead time 16.43 2.14 16.57 2.16

Table 6. Unit results in horizontal VE model (n¼ 3).

Unit20 Unit21 Unit22 Unit10 Unit11 Unit12

Profit 1024.94 31.54 14.292 2858.94 2250.02 0Stock (WIP) 10.08 0.26 0.10 6.39 4.44 0Lead time 8.78 0.225 0.087 8.36 4.42 0


Simulation results about individual enterprise in layer 1 and 2 are shown intable 8. Compared with table 6, it is observed that the total profit of layer 1 is muchcloser to that of layer 2 in this table. Spontaneous collaborated behaviour betweenUnit10 and Unit11 is also observed without coordinator in horizontal model. It hasbeen confirmed that the hybrid model obtains the characteristics observed in thevertical and horizontal models.

Total results of hybrid VE model in n¼ 3,10 are shown in table 9. They are alsoalmost equivalent, but the stability is slightly weaker in terms of scalability comparedwith the horizontal VE model shown in table 7. They maintain, however, higherprofit with relatively short lead time. That means the hybrid VE model is well-balanced in terms of efficiency and robustness because of its spontaneouscollaborative negotiations.

4.5 Comparison of three business models in VE

The performances of finally acquired VE in three business models are compared intable 10 (Model 1: Vertically integrated business model), table 11 (Model 2:Horizontally specialized business model) and table 12 (Model 3: Hybrid model) inn¼ 3. We tried to analyze the VE robustness of each business model against ‘duedate change’ and ‘production volume change’ in this experiment and 500 trials areexamined in each business model. The default due date and production volumeare set to 30 and 100, respectively, and (0.5, 1.0), for example, means the due date isshortened to 1/2 (0.5) and production volume is equivalent (1.0) to the default inthese tables. Only the results of the lexicographic model are described in table 10.

Unit00

Unit01

Unit0j

Unit0n

Unit10

Unit11

Unit12

Unit20

Unit21

Unit2j

Unit2n

CustomerUpper Stream Lower Stream

Figure 6. Experimental model (n¼ 3).

Table 8. Unit results in hybrid VE model (n¼ 3).

Unit20 Unit21 Unit22 Unit10 Unit11 Unit12

Profit 3968.46 91.86 54.67 1959.81 1853.74 0Stock (WIP) 10.31 0.22 0.12 5.11 6.53 0Lead time 8.79 0.19 0.10 6.85 7.55 0


Table 11. Experimental results of horizontally specialized businessmodel (Model 2).


(1.0, 1.0) (0.5, 1.0)

Profit 6179.73 730.06 5919.06 708.20Stock(WIP) 21.28 2.56 21.82 2.68Lead time 16.43 2.14 13.47 1.81

(1.0, 1.5) (0.5, 1.5)


Table 12. Experimental results of hybrid model (Model 3).


(1.0, 1.0) (0.5, 1.0)


(1.0, 1.5) (0.5, 1.5)


Table 10. Experimental results of vertically integrated businessmodel (Model 1).


(1.0, 1.0) (0.5, 1.0)


(1.0, 1.5) (0.5, 1.5)


Table 9. Total results in hybrid VE model.

n¼ 3 n¼ 10




The following points have been observed in those experiments:

. Any models don’t satisfy lead time (15.00) in (0.5, 1.5), because therequirement change is too heavy to handle.

. Lead time is satisfied at Model 2 and 3 both in (0.5, 1.0) and (1.0, 1.5).These relatively slight changes are manageable in those business modelsexcept Model 1.

. Total profit is the highest at Model 1, because only the contributed units cantake direct profit. Additionally stock is the least at this model.

. Model 3 attains the shortest lead time in most cases.

These results have been summarized as follows:

. It is difficult for the vertically integrated business model to adapt due datechange and production volume change, because it does not include any unitcooperation mechanisms. However, it performs best in profit, and this modelis efficient in case there are enough margins in lead time (i.e. stablesituations).

. The horizontally specialized business model is robust against due date changeand production volume change, although the profit is less than the verticallyintegrated business model. This business model is suitable for agilemanufacturing situations with autonomous cooperation alliance.

. The hybrid model takes a middle position between vertically integratedbusiness model and horizontally specialized business model. Although ittakes advantages of both models, it has been observed that the shared profitis inclined into lower layer units in VE compared with horizontallyspecialized business model.

5. Conclusions

In this paper, we focused on the negotiation process in VE formation to clarify itseffective management. We firstly classified the business model into three types: thevertically integrated business model, horizontally specialized business model andhybrid business model. Then we proposed a CNP-based negotiation protocolamongst enterprises with marketing science models, such as lexicographic model andMLH model, and N-person game theoretic approach. Marketing science-basednegotiation was applied into the vertically integrated business model considering arealistic enterprise management strategy. The horizontally specialized business modelincluded N-person game theoretic negotiations to realize the coordination amongstenterprises in the same business segment. We developed a computer simulationmodel to form VE through multiple negotiations amongst several potential membersin the negotiation domain, and finally clarified the formation dynamism with thenegotiation process. It has been confirmed that the vertically integrated businessmodel is profit-oriented and it is the best in relatively stable business situations.On the contrary, the horizontally specialized business model is robust against theorder change, and it suits agile manufacturing situations. The hybrid business modelis moderate characteristic between them, and it seems useful practically as oftenshown in real situations.


The contribution of this paper lies in the idea of a multi-agent-based VE

negotiation mechanism combined with marketing science and cooperative game,

which take a metaphor of decision making processes in social activities. This paper

gives an initial illustration of the approach into a primitive VE structure. Effective

enterprise partnering in global industrial collaborative networks is expected by this

research. There is one obvious extension, which is to elaborate the negotiation

protocol, possibly by exploiting some adaptive decision processes. It is expected that

the extension makes the enterprise agent collaborate more rationally and that leads

to more effective VE formulation with robustness.

References

Camarinha-Matos, L.M. and Afsarmanesh, H., The Virtual Enterprise Concept.Infrastructures for Virtual Enterprises, pp. 3–14, 1999 (Kluwer Academic Publishers:Boston, MA).

Camarinha-Matos, L.M., and Afsarmanesh, H., Modeling Framework for CollaborativeNetworked Organizations. Network-Centric Collaboration and Supporting Frameworks,224, pp. 3–14, 2006 (Springer, Boston, MA).

Chang, Y.S., Makatsoris, H.C. and Richards, H.D., Evolution of Supply Chain Management,2004 (Kluwer: Boston, MA).

Conen, W. and Sandholm, T., Differential-Revelation VCG Mechanisms for CombinatorialAuctionsAgent-Mediated Electronic Commerce IV, pp. 69–86, 2002 (Springer: Berlin).

Durfee, E., Lesser, V. and Corkill, D., Coherent cooperation among communication problemsolvers. IEEE Trans. Comp., 1987, 36, 1275–1291.

Fisher, M.L., Making supply meet demand in uncertain world. Harv. Bus. Rev., 1994, May/June, pp. 83–93.

Fox, M.S., Barbuceanu, M. and Teigen, R., Agent-oriented supply chain management. Int. J.FMS, 2000, 12, 165–188.

Goldratt, E.M., The GOAL, 1983 (North River Press: Great Barrington).Kaihara, T. and Fujii, S., A Proposal on Negotiation Methodology in Virtual Enterprise.

Collaborative Business Ecosystems and Virtual Enterprises, pp. 125–132, 2002(Kluwer Academic Publishers: Boston, MA).

Kaihara, T. and Fujii, S., Partnering Mechanism with Adaptive Multi-agent Protocol forVirtual EnterpriseProcess and Foundations for Virtual Organisations, pp. 407–414, 2003(Kluwer Academic Publishers: Boston, MA).

Kansai Bureau of Economy, Trade and Industry. Available online at: http://www.kansai.meti.go.jp/3-2sanki/cluster-beam/english.html (accessed 16 February 2006).

Katahira, H., Marketing Science [in Japanese], 1987 (Tokyo University Press: Tokyo).Kovacs, G.L., Bertok, P. and Haidegger, G., Digital Enterprise Challenges, 2001 (Kluwer:

Boston, MA).Putnik, G.D. and Cunha, M.M., Virtual Enterprise Integration, 2005 (Idea Group: Hershey).Sandholm, T., An implication of the contact net protocol based on marginal cost calculations,

in Proceedings of the National Conference on AI, 1993, pp. 256–262.Shen, W., Information Technology for Balanced Manufacturing Systems, 2006 (Springer:

New York, NY).Smith, R., The contract net protocol. IEEE Trans. Comp., 1980, C-29, 104–1113.Von Neumann, J. and Morgenstern, O., Theory of Games and Economic Behavior, 1947

(Princeton University Press: Princeton).


supply chain pedagogy 1

Documents

virtual enterprise ve

better management of

threelayered ve model

ve formulation dynamism

different enterprises

extended enterprise

business opportunities

agile environment