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Automating of controlling processes in production networks.

Abstract: Suitable methodologies and procedures are necessary for the distribution of profit or loss which has been realised by value adding processes within networked production structures. Based on the evolutionary model "Non-hierarchical regional production networks" an approach for the automated distribution of profit within Competence Cell Networks (CCN) is under development. For support purposes a Profit Distribution Broker Unit (PDBU) is applied. Thereby, practical problems such as the transaction of money, the accounting, the nondisclosure of the information about the Competence Cells (CCs) e.g. expected profit, fixed share of costs etc. arise, when a fair and automated profit distribution is aimed at. This contribution focuses that topic and presents suitable approaches and hints for realising an automated and fair profit distribution for partners in Competence Cell Network. This paper is focused different problem fields concerning non-hierarchical regional Competence Cell Networks.

Key words: Production Network, Extended Value Chain Management, Competence Cells, Network Controlling, Profit Distribution

1. Motivation

Two general tendencies for development can be noticed by the help of observations of the worldwide activities of enterprises: on the one hand, the number of mergers and acquisitions, that grew considerable in the recent years, result in an increasing number of "global players" which concentrate power, competences and capital. In the year 2004, about 18.000 of such activities having a volume of 1,6 trillion US dollars (KPMG, 2004) were carried through. However, according to the survey "Inventing the Organizations of the 21st Century" carried out by the Massachusetts Institute of Technology (MIT), it appeared to be disadvantageous that those "global players" control bigger financial flows but on the other hand they increasingly loose control of operative processes. Difficulties--such as the merger of Daimler Chrysler or the takeover of PeopleSoft by Oracle--show that a takeover or a merger is not necessarily successful.

On the other hand, an increasing "atomisation" of existing enterprises can be observed. The reasons for that trend especially can be found in the environment of the enterprises: for example economic difficulties of small and medium-sized enterprises (SME) because of the current economic situation and the increasingly hard competition on the global market. Thus, many SME are newly established or hived off as a consequence of insolvencies or problems during the takeover of a company by the successor. Those micro-enterprises increasingly concentrate on their core competences and in general can only act successfully on the market by cooperating with other enterprises. Thereby, the economic significance of those SME remains indisputable. They represent the spine of the German economy as they perform about 50% of the gross value added and employ about two-thirds of all the employees (IfM, 2004).

Based on the current challenges and deficits of established SCM-approaches, an integral concept was developed which is focused on the management of production networks consisting of micro-enterprises. That concept is called Extended Value Chain Management (EVCM) and supports the networking of the competences and resources required for the manufacture of a product within networked organization structures.

2. Conception of the Extended Value Chain Management (EVCM)

2.1. Problem Formulation and Literature Review

This paper takes up the idea of the order-specific networking of micro-enterprises which can be called competence cells (CC) in this context (Muller, 2006). The operator concept "Extended Value Chain Management" was developed for the establishment, operation and dissolution of such production networks (Teich, 2003). That approach focuses on the intensive application of information and communication technologies (ICT). In that connection, a very high level of automation of network controlling is achieved for the processes (Jahn et al., 2006).

One major problem within networks is the equitable distribution of the profit or loss to the network participants made within the scope of a certain value-added process. The specific approach of EVCM requires an ICT-based and therefore automated solution which is introduced later.

It literature, the distribution of profit or loss in networks is recognised as an--in most cases--unsolved critical point of virtual enterprises which has to be discussed; however, the suggested solution approaches are in most cases coarse procedures such as the distribution according to value added shares, to negotiation processes or by the means of market solution principles (distribution according to pre-defined parameters) (Schuh & Strack, 1999). Thereby, it is based on the fact that the allocated amount at least corresponds to the missed utilisation of the resources within or for the own enterprise plus a corresponding profit share (Steven, 1999). Further approaches are based on the cooperative game theory (Fromen, 2004). However these publications are of limited relevancy for the EVCM because of some specific assumptions.

In practice, the procurement of information concerning the distribution of profit or loss often is very difficult. In many cases, relevant information is not given to third parties because of non-disclosure of confidential information. However, a tendency can be remarked that enterprises participating in networks directly calculate their individual profit share in their offer. In such cases, an explicit mechanism for the profit distribution is redundant. Still, it is not clear how to deal with lacing payments of customers, notifications of defects or product liability claims to the network.

The in this publication introduced approach for the distribution of profit or loss within networked production structures focuses approaches for the solution of this problem under consideration of competence cell based networking within the scope of the EVCM. Because of the high degree of automation, a centrally organised profit and loss distribution is favoured. The necessity for that results from the assumption that a profit maximisation for the entire network is aimed at in addition to the individual profit maximisation for the single network participants. Thereby, the maximisation of the network profit has to be regarded as a higher target because this might secure the survival of the network.

2.2. The Phase Model as a Life Cycle Model

The EVCM-concept offers the possibility especially for SME to take part in a value-added process, which is designed according to the individual needs of the customers, with regard to their specific core competences. All the partners have equal rights but they are competitors in case their qualifications are equal. A long-term stable enterprise network, which consists of potential participants that trust each other, represents the basis for the establishment of a dynamic (order-specific) production network. That strategic network exists for a longer time period and can be interpreted as a pool of resources. A temporary network disposing of the competences required for fulfilling the specific offer is derived from that pool for the processing of a concrete customer order.

In the following sections, a brief overview is given on the procedures and models of the Extended Value Chain Management for a better understanding before specific approaches within the procedural model will be focused on in the following chapters. Figure 1 illustrates the conceptual framework for the generation of a network--this corresponds to the life cycle of a temporal network and is called EVCM-phase model.


2.3. Phases of the Phase Model

The phase model consists of nine consecutive phases starting with the phase "Decomposition of value chain" and finishing with the evaluation of the network participants and the break-up of the network. The phases are explained in detail next. First of all, the functional decomposition of the requested good is required for the generation of a network. That means the product has to be deconstructed into its components. In the following, suitable technologies need to be defined for the manufacture of those products. The result is a process variant plan (PVP) which comprises all the technologically suitable possibilities of the manufacture of a product.

The selection of technologically suitable SME for the process variant plan takes place in phase two and is a task of a central database--the information-technical model core (IMC). The IMC acts as a central broker instance, that means the competences required in the IMC and the profiles of the partners existing in the database are compared (Fischer et al., 2003). A specific PVP is formulated as a result which allocates suitable candidates to each of the necessary process steps.

In the following phase the potential candidates (CC) are recursively (that means starting from the final product) inquired. They check themselves, if the appropriate resources are sufficient for fulfilling the corresponding process steps of the PVP, that means stocks are inquired on the one hand and, if necessary, suitable manufacturing orders are planned simulatively. If pre-products are lacking, those are inquired again. In case the results of those checks are positive, the enterprise is able to fulfil the corresponding process step also from the point of view of perspectives.

After going through the internal process planning, a CC has gained all the necessary information concerning the use situation of their own resources and thus can submit corresponding offers in the following. After all the inquired candidates have sent replies, a first optimisation according to the hard facts is started. It is the target to ascertain those manufacturing variants with corresponding partners which achieve the highest level of fulfilling the target with regard to the customer's preferences.

Subsequently, the best variants that were considered "adequate" are investigated regarding the social "suitability" within the phase "Soft-fact integration". Thereby, the measures connectivity and eccentricity are calculated by the help of the Polyhedral Analysis (Teich, 2003) and thus they allow an evaluation and statement about the (social) quality of the cooperation. The final decision for a concrete manufacturing variant (network configuration) and the selection of the participating CC is arranged by considering both soft-facts and hard-facts. The most suitable combination is chosen.

The operation of the network starts after the activation of the network. Thereby, it is necessary to collect specific information concerning the production progress and the compliance to the offers within a monitoring / workflow management (Zschorn et al., 2005). After the product has been finished and delivered and the invoice has been sent to the customer, the participating enterprises are evaluated according to the collected information. That means the target state is compared to the actual state. The result subsequently has a direct effect on the CC-related profit shares. Finally, the temporary network breaks up within the final phase.

3. Basic Modelling for the Distribution of Profit

3.1. Basic Assumptions

It cannot be assumed that the network is going to submit an offer at a loss. Therefore, this situation won't be considered in the following. The process of the offer calculation takes place in phase 4 whereas the actual performance evaluation including the profit distribution is carried out in phase 8 of the EVCM phase model. When preparing an offer, the CC are not allowed to calculate individual profits into the offer price. Because usually several CC disposing of similar core competences exist in the pool of resources and thus compete for one order, that kind of abuse is efficiently avoided. However, should CC still secretly calculate individual profit shares in the CC-offer, this happens bearing the risk of not being considered because of a too high offer price.

The most important information that has to be made available by the CC is the individual value added (net value added). That parameter corresponds to the service of a CC which is performed by this within the scope of the correspondingly considered value added process. The publication of this parameter by the CC takes place when submitting individual CC-offers for single required value added steps.

The sum of all the CC-related value added shares results in the whole value added realised in the network (gross value added). That parameter represents the basis for the offer which can be submitted from the network for a concrete customer inquiry. Here, the EVCM adds an offer profit and this addition results in the offer price. However, it is emphasised that the offer price does not necessarily have to be equal to the sales price after the delivery of the product. Possible reasons and sources for that will be discussed in detail in a further chapter.

3.2. Ascertainment of the Offer Profit

The procedural model illustrated in figure 2 is applied for the ascertainment of the profit which is calculated in an offer and thus termed offer profit in the following.


In case a customer sends an inquiry to the network, it has to be differentiated if the customer has a fixed idea of the price or not. In the first case an offer price can be determined based on the net value added and the individual profit expectations of the CC. This offer price then is compared to the desired price. If the desired price is higher than the offer price, the product is offered at the offer price by the help of which the offer price was fixed. Otherwise, further negotiations are required.

However, if the customer does not have any idea of the price yet, the EVCM calculates an offer price based on the net value added and the individual profit expectations. This offer price is reported to the client. If the customer agrees, the offer profit is fixed. If he does not agree, further negotiations have to be carried out again. Such negotiations are based on the readiness of the CC to reduce their profit expectations and thus the offer price or respectively on the readiness of the customer to pay a higher price. Thereby, it is also possible to find an acceptable price step by step that means to go through several iteration loops. However, the situation that there is no agreement in the end might still occur, but this is to be regarded as an exception.

3.3 Concept for the Distribution of Profit

The integral model of the profit distribution in competence cell-based production networks is based on a basic model for the profit distribution as well as mechanisms for incentives and sanctions (Jahn, 2005). The connection of the partial models can be seen in figure 3.


Sanction mechanisms reduce the profit share of a CC. The degree of the sanction thereby depends on the degree of the performance of a CC with regard to a certain value added process. In case a CC has not or only insufficiently performed the contractually agreed services, a reduced profit share is paid out. That mechanism predominantly serves the harmonisation of the interests of CC and network.

As opposed to that, Incentives are especially required of CC are not willing to take part in a certain value added despite of their competences although this would be advantageous for the maximisation of the utility (in that case profit) of the entire network. Corresponding incentives should be granted for persuading the CC to participate. Detailed models for the application of incentive and sanction mechanisms have already been developed (Jahn et al., 2005).

The basic approach for the profit distribution includes a subdivision into a value added-related and a fixed profit share. The weighting is carried out using the parameter [alpha]. The next chapter is going to explain possibilities of calculating [alpha]. The subdivision into variable and fixed profit shares is explained as follows: while the CC-related share of the value added has to be taken into consideration, there also has to be a guaranteed fixed profit share especially for those CC which have a relatively small share of the value added. In that connection, a suitable calculation rule must be made available for the distribution parameter [alpha] in order to be able to guarantee an automated calculation. This is going to be the topic of the next chapter.

3.4 Determination of the Distribution Parameter [alpha]

The distribution parameter [alpha] plays a significant role with regard to the calculation of the individual profit shares of single CC and also concerning the just distribution of the achieved profit. For this reason it is very important that [alpha] is "just". However, generally valid calculation rules need to be applied in order to achieve a possibly objective consideration of this parameter. The simplest way for that is the determination of a fixed [alpha] for all the CC.

When a production process is considered from the point of view of cost accounting and this model is simplified so that the input is subdivided into variable and fixed costs, the following assumption can be made: the variable costs are defined as the quantity of the input which only is the basis of the value added (e.g. raw materials, external products) whereas the fixed factors are defined as costs which finally effect the actual increase of the value (e.g. loan costs, energy, spendings for advertising). If this assumption is compared to the definition of Gunther and Tempelmeier who simply define industrial production as the "manufacturing of output goods (products) from material and nonmaterial input goods (production factors) ..." (Gunther & Tempelmeier, 1995), it can be concluded that the amount of the arising fixed costs determines the value added of the output in comparison to that of the input because the variable costs only represent the material application of appliances. If, based on the rules of the (free) market economy, it is assumed that every single CC is able to procure the same material input as the competitors the value of the CC can be found in the non-material production factors. This means that the amount of the variable factors does not express much about the fact to which degree a CC has performed a service, but the fixed factors inform about the fact which appliances or materials have been used for performing the value added. Using that argumentation, it is successful to formulate an approach for the determination of the distribution parameter [alpha].

Thus, taking into consideration the argumentation from the previous chapters, it seems efficient to calculate a variable and a fixed share of the complete profit for each CC so that the fixed costs of each CC can be covered in relation to its complete costs. This results in a factor in the interval ]0,1[, which allows to state how strong the value added of the CC is (towards 1: achievement of a high value added; towards 0: achievement of a low value added). If this parameter is subsequently multiplied by the relation of the complete costs of the CC and the complete costs of the network and finally it is summed up for all the CC, the parameter [alpha] results. So it becomes clear that [alpha] is independent from the individual value added of one CC and thus is identical for all CC. This means that it is possible to distribute the profit.

If a calculation with test data is carried out based on the aforementioned assumptions, it can be remarked that the CC-related profit share of the aggregated value added grows clearly less fast than the individual value added share of the value added of the network. That tendency increases the higher [alpha] is because the fixed profit share and thus also the complete profit share of a CC increases. In reverse, a smaller [alpha] also results in a smaller CC-related profit share. As mentioned above, it is absolutely desired that CC with a relatively low share of the complete added value are given a relatively higher profit share per value added share. However, it still has to be emphasised that a fixed distribution parameter [alpha] does not generally lead to satisfactory results. This especially applies to situations when [alpha] is high. In that case the "small" CC are given a too high fixed profit share which would be a disadvantage for the larger CC. For that reason, a modification of the model was elaborated.

A relation to the fixed costs of a CC also has to be made for the calculation of a CC-specific [alpha] according to the previous argumentation. Thereby it is assumed that each CC submits its individual (proportionate) fixed costs within the scope of the submission of the offers for a value added step. The sum of the CC-related fixed costs for all the CC involved in the value added process is defined as the fixed share of the aggregated value added in the network. Subsequently, the CC-specific [alpha] can be calculated based on those data. Therefore, the fixed share of the value added of each CC is proportionated to the aggregated fixed value added of the complete network. Finally the equation is analogously used for the calculation of the profit shares of the CC. Further investigations and reflections are required because the calculated distributed profit almost never is equal to the profit, which can be distributed, during the profit distribution with a CC-specific [alpha]. Thus, it seems efficient to introduce a standardisation parameter. It is the task of that standardisation parameter to make sure that the complete achieved profit is distributed. The standardisation parameter must be calculated for fulfilling that pre-condition. This happens by proportionating the profit, that can be distributed, and the profit, that has already been distributed. Thereby it does not matter if the profit, that is ready to be distributed, is bigger or smaller than the profit already paid out. Finally, the final profit share per CC is calculated in a finishing step. The sum of this profit share then has to be equal to the profit that can be distributed. Therefore, the ascertained profit share is multiplied by the standardisation parameter. A calculation of the profit shares with test data makes clear that there is a tendency that there is a bigger deviation of the value added share and the profit share when [alpha] is constant for all the CC. Thus, the passage to a CC-related [alpha] seems a suitable measure for achieving a performance-related as well as just profit distribution based on the two components value added share and number of competence cells.

4. Expansion of the Model as a Three-Component-Approach

4.1. Basic remarks

The expansion of the profit distribution model which is described within that chapter is based on the aforementioned two-component-approach. The expansion is realised by introducing a third component that is dependent on the profit expectation of a CC. As has already been discussed above, the individual profit expectation of a CC (with regard to the own value added share) is one of the assumed input variables of the model. Because the calculation of the network profit (called offer profit), which is included in the calculation of the offer, is oriented towards the individual profit expectations of the CC, it is possible that the paid out profit expectation-dependent profit share is equal to the whole profit that can be distributed after the value added has been carried through. However, in case the realised network profit (that means the profit that can be distributed) deviates from the calculative offer profit, which means the customer does not pay the agreed purchase price (reductions, external influences, etc.), a positive or negative difference results that has to be distributed. Therefore, a modified procedure is suggested as it is illustrated in figure 4.

The most important component of the model is the profit expectation-dependent share of the profit. It presents itself to pay out the profit, which has been calculated based on the value for the profit expectation of the CC stored in the IMC, directly to the CC. However, this procedure is not favoured because the individual profit expectations are very subjective. That deficit could be cleared by a standardisation that means an average profit expectation value is calculated. Therefore, we have two options. Thus, it is one possibility to take into consideration the average unweighted value of the profit expectations or the average profit expectation weighted according to value added shares. Thereby, the second option is favoured in the following because that CC which are strong in the value added should also be allowed a higher profit expectation. It has to be remarked that the calculated parameter is valid for all the CC. According to that procedure two cases arise for the profit distribution: calculation with or without remaining profits. Thereby, the difference between the offer profit and the actually realised profit is the remaining profit.


4.2. Calculation excluding remaining Profit

In the basic case, the offer price is calculated based on the individual value added shares and the correspondingly submitted profit expectations of the CC. If a customer accepts the offer including the proposed price, the good is produced and subsequently it is delivered. Usually, the customer then pays the agreed sales price, which includes the calculated profit that is based on the individual profit expectations. Thus, the whole profit can be distributed to the single CC and there is no remaining rest. This effect also occurs if the offer profit was calculated on the basis of the unweighted CC-related profit expectations but the realised profit is distributed based on the CC-related profit expectations that have been weighted according to the value added shares. However, thereby the CC-related profit shares vary considerably. One problem of this procedure is the input variable of the CC-related profit expectation. As mentioned above, the CC submit this variable independent from a certain value added process. However, the problem remains, that the CC might submit a wrong parameter intendedly. For that reason, a variable should be introduced which eliminates outliers and obvious wrong submissions. That parameter is termed average percentage of the expected profit and it is equal for all the CC. However, this often results in the situation that the distributed profit does not necessarily correspond to the profit that can be distributed anymore. Thus, suitable distribution mechanisms have to be applied which are also valid if the resulting profit deviates from the offer profit. An applicable mechanism is introduced in the following section.

4.3. Calculation including remaining Profit

The aforementioned procedure has to be applied for the calculation of the (weighted) average expected profit (in % of the added value). Therefore, the individual percentage of the profit expectation is weighted by the share of the individual added value from the complete added value. Thereby, it has to be taken into consideration that that variable is CC-independent, that means it is the same for all the CC. In the next step it becomes possible to calculate the profit share for each CC that depends on the profit expectation. Therefore, the average weighted profit expectation is multiplied by the CC-related added value. That parameter represents the first component of the complete profit share of a CC. Finally, the profit that is dependent on the profit expectation and has already been paid out results from the sum of the individual profit expectation-dependent profit shares. The summing up of the profit shares per CC is necessary in order to determine the further procedure. Thus, next step after the added value is a comparison between the profit that has already been paid out and the profit that can be paid out in total. A remaining profit, that has not been paid out yet and thus can be distributed results by subtracting the paid out profit from the amount that can be distributed. However, in case the non-distributed remaining profit amounts to 0, that means the profit, that can be distributed, equals to the profit that has been distributed, no further step is required. In case the nondistributed remaining profit is positive, that amount can be distributed to the CCs as variable and fixed profit shares. However, should the remaining profit be negative, a too large amount has already been distributed and the individual profit shares need to be adjusted. This might also happen as variable and fixed shares, so that the following processes basically remain the same. An alternative would be to minimise the distributed profit via the CC-related profit expectations or by a devaluation factor. However, those procedures will not be explained here. In case the distributed profit does not correspond to the profit that can be distributed after consideration of all three components, a different standardisation procedure is required.

5. Realisation of the Concept by the means of a Broker Instance

5.1. Problem Formulation

The theoretical solution of the problem of a fair and automated profit distribution results in practical problems, such as the transaction of money, accounting, nondisclosure of the given information of the CC e.g. expected profit, fixed cost share etc. After concluding a contract of sale or for services and the transfer of perils, the payment usually is made. The share of payments of invoices carried out via the Internet grows because of the increasing applications of the ICT. Thus, it must be assumed that there will hardly be any more cash payments between the single enterprises or CC. However, this tendency supports an automation of all transactions, but it does not solve the problem of the various bank transfers that need to be carried out within a CC-based production network. When the added value is completed, a sale price is determined and the good has been shipped, the customer currently has three alternatives. The first alternative is that the customer transfers the corresponding share of the price to each of the participating CC. However, this involves that the customer is informed about the share of the performance of every single CC and thus can estimate the single profits. Furthermore, it is very laborious for the client to carry out all the single transactions. The second alternative is that one CC is given the full amount of money and subsequently distributes it to the other CC. However, in addition to the problems mentioned in alternative one, there is the further risk that the CC transfer the money too late to other CC and probable gains interests. It might also happen that the CC becomes bankrupt or does not pay out the money to the others at all. The third option is to authorise a trustee to receive the money from the customer which causes costs and again comprises the risk of indiscretion. There is an enormous expenditure for the transactions in all three possibilities which causes costs and consumes a lot of time. In addition, the competition advantages resulting from the cooperation might be reduced.

5.2. The Role of the Profit Distribution Broker Unit (PDBU) in the EVCM Concept

Because of the aforementioned problems, it becomes necessary to develop a full automation of all the money transactions. With reference to the research done for the EVCM, an instance would be imaginable which exclusively deals with the question of the network evaluation and is integrated into the EVCM concept. The introduction of that so-called Profit Distribution Broker Unit (PDBU) might meet the requirements of that approach. The PDBU is an instance that has only been developed for the network evaluation and profit distribution. It is represented by an information-technical realisation (program) which is integrated into the information-technical concept of the EVCM (Zschorn et al., 2005) that has already been developed. The two basic elements of that concept are two servers. The Web Service "EVCM-Control" of the EVCM Web Server represents the interface to the outside. This interface communicates with the information-technical model core (IMC) which represents the second server and basically offers a database functionality including logics in order to answer search inquiries for CC. The PDBU is given all the required data, which are necessary within the scope of the network evaluation, from IMC as well as from the EVCM Web Server. Thereby, the static data (e.g. profit expectation, readiness for incentives etc.) should be saved on the IMC server because they are independent from a concrete value adding process. For a concrete process, the necessary data are available on the EVCM Web Server where the PDBU can find the required information (Figure 5). The basic tasks of the PDBU are to ascertain the profit, to account the incentive and sanction payments and to inform the customer about the sum of invoice via the information system of the EVCM. The client is also sent the demand of payment after the manufacture of the product and he can directly transfer the price he has to pay via online banking, bank transfer or inpayment in his bank on the given network bank account. Therefore, in addition to the PDBU, another network bank account in a bank is necessary. This bank account only has two functions: to take inpayments and to carry through outpayments which have been ordered by the PDBU. Thereby, it must be stressed that this bank account exists for an infinite period of time and independent from a concrete value adding process and that it is available for all the value adding processes within the EVCM. Thus, the necessary marginal conditions for the introduction of the PDBU have sufficiently been described by the investigations concerning CCN (Teich, 2003), (Zschorn et al., 2005).


If a CC is accepted in the database, it submits its specific information concerning its competences. On behalf of those, the selection for a concrete customer order is carried through later. Because of the introduction of the PDBU, it is now demanded that also data for the later profit ascertainment are recorded. If it is assumed that the CC will always perform the same or a similar share of the value adding in the network, its profit expectation should also not change with every single order. Thus, the CC has to submit its expected profit as a percentage. In addition, it is expected that the CC is willing to pay for incentives. This willingness must also be stated as a percentage. The customer must also submit information concerning bank account data and price ideas. The CC and the customers use the Web Service for the transmission and the receipt of the required information for the price calculation and the payment transactions. The PDBU, which is installed on the EVCM Web Server thus disposes of an interface to the CC and the customers via the Web Service "EVCM-Control". Thus, the customers as well as the CC are able to transmit the required data via the Internet. The IMC is available as storage space for storing information such as prices, bank account data, profit shares etc.

5.3. Tasks of the PDBU

In the course of the value adding process, the application of the PDBU can be subdivided into two phases. With regard to the phase model of the EVCM, the customer is informed about a specific price in the phase "Preparation of offers" and in the second last phase "Evaluation and profit distribution", the individual profit shares are ascertained, incentives and sanctions are calculated and the invoice is transmitted to the client. After he has paid the invoice, the single profit shares are distributed to the corresponding CCs (cf. Figure 6).


Therefore, the specific amounts are transferred to the CCs from a bank account that has especially been opened for the duration of a certain value adding process. The PDBU carries out this task in a fully automated way after it has checked the amount of the invoice. Thus, the PDBU has three main tasks. On the one hand it is responsible for the complete calculations which are necessary within the scope of the network evaluation. On the other hand, it carries out all the monetary transactions and functions of accounting between the CCs and the customers. Furthermore, all the payment transactions are supervised by a permanent monitoring (cf. figure 6). If a customer inquires a concrete product, first of all the CCs are selected as described in chapter 1. However, in parallel, it is necessary to ascertain the price so that the customer can be informed. The price calculation based on the profit distribution model (cf. chapter 2) already needs to be carried though in the phase of the generation of offers because for this process it is efficient to inform the customer about a concrete price in addition to the information he is given about capability, date, quantity and probability of delivery. This makes clear the necessity to integrate the PDBU as a component of the EVCM-operator concept as an independently working software. In case of a concrete customer order, the PDBU thus has to perform the following tasks: The PDBU can ascertain the offer price, which the customer finally has to pay, by the means of the expenses of every single CC--the individual offer price--and the network profit ascertained by the help of the approved vote procedure. The algorithm for the determination of G described in chapter 2 (cf. figure 5) is carried out by the PDBU. Thereby, the expected profit share of the CC as well as the desired price of the customer is inquired in the IMC. The Web Service serves as the communication medium of the PDBU in case of price negotiations. Thereby, in case of too high price expectations on behalf of the CC, the PDBU would send it an e-mail including the task to adapt their profit expectations because the customer does not accept the price. When this is finished and the PDBU was given a new idea from each of the CC, the customer can be informed about the corrected price. The PDBU checks the corrected profit expectations with regard to their differences to the first percentage. This is to make sure that it is not possible that some CC only reduce their expectations by a very small percentage whereas others show a much higher readiness to reduce their profit expectations. In has to be mentioned again that there are no disadvantages for those CC which submit a lower profit expectation, because the later calculation of the actual profit share is independent from the expectations. The customer is informed about the adapted price and he now has to possibility to accept the price or to start renegotiations again. If the value adding process can finally take place after all the negotiations and the concrete selection of the CCs, the evaluation takes place in the network after finishing all the activities which belong to the network operation. Thereby, the PDBU is applied for the second time. After the receipt of the price has been confirmed by the PDBU, the single profit shares can be ascertained and distributed to the CC according to their performed services. Therefore, the PDBU inquires the necessary data from the database. Using the CC-related value adding share and the fixed share comprised in that, the PDBU ascertains the individual parameters, which are required for the classification of the fixed and variable profit share. Subsequently, every single profit share can be calculated for every CC according to the calculation rule explained in chapter 3. The data from the single value adding processes are stored within the PDBU. The necessity arises because when competences are missing in the network, it is under certain circumstances not possible to provide an offer for the customer because the required information is missing. The missing competences must be convinced of taking part in the network if the customer shall still get an offer for the inquired service. Therefore, monetary incentives have proved to be efficient. For the determination of the available incentive amount, it however is necessary to know the gained profit. This presumes that an offer including the prices has been prepared. Thus, for the submission of offers it is necessary to simulate the lacking CC. Those simulated CC (sCC) meet all the requirements concerning the network conformity and agree to the profit expectations of the already existing CC. However, for the calculation of the offer price, the PDBU needs concrete values for the CC-related value adding share and the fixed share. If the PDBU disposes of data from former value adding processes, experienced values might be applied instead of estimated values. Then, the PDBU can calculate an offer price by the help of those data. When concrete CC are selected afterwards, the simulated CC are replaced by real CC. Because each CC is expected to be ready to pay incentives, the amount of the available incentives can be ascertained by the PDBU. The available incentive amount can be used for winning missing CC for the network in the search for CC. After the completion of the value adding process, the agreed and the actual performances are compared within the scope of a performance evaluation system. If a deviation is recognised between the actual and the target performance, sanction payments are demanded from the corresponding CC. The calculation of the amount of those sanction payments is also carried through by the PDBU.

5.4. Transactions by the PDBU

After the network operation has taken place and the PDBU could ascertain the profit shares, incentive payments and sanctions, the second main task of the PDBU is applied. Via the Web Service, the customer is sent an online invoice including the demand of payment to transfer the amount to the network's bank account. This account, which might exist at whatever bank and disposes of the functions and securities of online banking, is directly connected to the PCBU, and thus to the EVCM Server. Thereby, it would be imaginable to win a bank as a competence which permanently provides the bank account for the EVCM. The current legal problem that a corporate body must be available for every single bank account is neglected in that approach. A solution would be a trustee who is the legal owner of the bank account but does not have any access to it. When the customer transfers the amount, it is first of all checked if the amount was paid in time and if it is the right amount. If this has not happened, a reminder is immediately sent to the customer and should the occasion arise reminder charges are claimed. This is also the fact when the customer does not pay the bill after the legal respite. If the PDBU can confirm the receipt of the amount, the calculated profit shares are directly transferred to the single CC. In case the customer is granted a discount, it can immediately be cleared and subtracted from the profit shares of the CC. The PDBU is given the required bank account information for the bank transfers by the IMC. This kind of automation guarantees that the CC are not informed about the profit shares or expectations of the other CC. Furthermore, many transactions can be carried out in a relatively short period of time. A further function, which can be realised by the PDBU, is clearing. Thereby, claims among the CC are cleared. This is for example the case when a CC X performs a service for a CC Y or the other way round within the scope of a certain value adding process. Thus, both CCs would have some claims left to be cleared after finishing the value adding process and receiving the profit shares. The clearing function of the PDBU would make it possible that the claims are cleared because both CC owe money to the corresponding other CC. If the claims of CC X are higher than those of CC Y, the remaining amount could be paid using the profit share. The advantage for both CC is that all the claims between the CC, which arose during this specific value adding process, would be cleared with the receipt of the profit share and that no further transactions would be required. However, the precondition for that is that the corresponding CC agrees to the clearing.

5.5. Monitoring within the PDBU

The number of interactions between the CC and the customer in the process of the offer submission and the profit ascertainment result in an urgent necessity of a monitoring mechanism. Therefore, in addition to the price calculation, profit ascertainment and transaction of money, the PDBU also has a monitoring function. This is required especially because a variety of agreements is made between the CC and the given information must be treated confidentially. Thus, the CC are expected to submit their profit expectation and readiness for incentives. Thereby, the PDBU must additionally check whether the ideas of the single CC are in the interest of the whole network. It the profit expectations of single CC would be too high, the whole added value process could not take place. Within the scope of monitoring, the PDBU would compare every single profit expectation to the average and in case of a too low or too high expectation it would ask the specific CC for a modification. This is also valid for the readiness to pay for incentives. In addition to the check of the initial data for the calculations, the PDBU also checks all the transactions of the network bank account. Thus, outpayments are only ordered if the full amount of the invoice has been checked before. Thereby, however, the case must be considered that deposits might have been paid which are already pays out to the CC before the start or in the beginning period of the added value.

6. Conclusion and Result

In this paper possibilities for the calculation of profit shares for participants in competence cell-based production networks and an information-technical concept for its implementation were introduced. It is shown that an approach based on three independent influence factors delivers the best results. However it is necessary to check the results by the application of test data sets. The application of selected approaches of the profit distribution in competence cell-based production networks is based on the claim to automate the tasks and processes within the scope of the EVCM as far as possible. This is realised by the application of an independent broker instance which is called PDBU in that context. The PDBU represents one central component of the EVCM-operator concept. In order to guarantee an automated distribution procedure concrete calculation rules and procedures need to be formulated. A future claim is to develop a further approach which makes a standardisation parameter absolutely unnecessary. Therefore, an expanded three-phase model would be imaginable within which each component has a certain weight which takes into consideration the profit share. The calculation and the comparison of the results with further test data is planned in the future for the abovementioned approaches in order to achieve further ascertainments concerning the resulting solutions. Thereby, it is also imaginable to receive statements concerning the elasticity of the results by varying specific parameters. These works represent the next approach for dealing with this topic. The development and application of a evaluation and profit distribution model based on exact calculation rules will represent a valuable contribution to an effective network controlling.

7. References

Fischer, M; Jaehn, H.; Zschorn, L. & Teich, C. (2003). Production Networks--A New Approach To Select Partners, In: DAAAM International Scientific Book 2003,

Katalinic, B. (Ed.), pp. 243-260, DAAAM Internat., ISBN 3-901509-30-5, Vienna Fromen, B. (2004). Faire Aufteilung in Unternehmensnetzwerken, DUV, ISBN 3-8244-8164-2, Wiesbaden

Guenther, H.O. & Tempelmeier, H. (1995). Produktion und Logistik, Springer, ISBN 3-540-59194-X, Berlin, Heidelberg, New York

IfM (2004) Institut fuer Mittelstandsforschung Mittelstand--Definition und Schlusselzahlen, 21.12.2004, Available from: daten.htm Accessed: 2006-04-18

Jaehn, H. (2005). Profit Ascertainment and Distribution in Production Networks, Proceedings of the 16th International DAAAM Symposium 2005, Katalinic, B. (Ed.), pp. 169-170, ISBN 3-901509-46-1, Opatija, Croatia, October 2005, DAAAM International, Vienna

Jaehn, H.; Fischer, M. & Zimmermann, M. (2005). An Approach for the Ascertainment of Profit Shares for Network Participants. In: Collaborative Networks and Their Breeding Environments, Camarinha-Matos, L.M.; Afsarmanesh, H.; Ortiz, A., (Eds.), pp. 257-264, Springer, ISBN 0-387-28259-9, New York

Jaehn, H.; Fischer, M. & Zschorn, L (2006). The Application of Methodologies for Evaluation Processes in Production Networks, Proceedings of the 5th International DAAAM Baltic Conference, Industrial Engineering--Adding Innovation Capacity of Labour Force and Entrepreneurs, Kyttner, R. (Ed.), pp. 191-196, ISBN 9985-894-92-8, Tallinn, Estonia, April 2006, University of Technology, Tallinn, Estonia

KPMG (2004). Klare Anzeichen einer Erholung am weltweiten M&A-Markt--Positivtrend bestaetigt sich auch in Oesterreich. Press Information, 13.12.2004, Available from: Accessed: 2006-04-18

Mueller, E. (2006). Production Planning and Operation in Competence-Cell-based Networks. Production Planning & Control, Vol. 17, No 2, March 2006, Taylor & Francis, S. 99-112, ISSN 0953-7287

Schuh, G. & Strack, J. (1999). Virtualitaet in der produzierenden Industrie. Technologie & Management, Vol. 48, No. 1, Jan. 1999, pp. 10-14, ISSN 0932-2558

Steven, M. (1999). Organisation von virtuellen Produktionsnetzwerken. In: Produktionswirtschaft 2000, Nagel, K. et al. (Eds.), pp. 242-260, Gabler, ISBN 3-409-11461-0, Wiesbaden

Teich, T. (2003). Extended Value Chain Management--ein Konzept zur Koordination von Wertschoepfungsnetzen, Verlag der GUC, ISBN 3-934235-23-9, Chemnitz

Zschorn, L.; Zimmermann, M; Fischer, M. & Meyer, M. (2005). From the Customer's Inquiry to the Production Network with Partners having equal Rights--the Activity of the Determination of the Production Process, Proceedings of the 15th International Conference on Flexible Automation & Intelligent Manufacturing (FAIM 2005) Vol. 1, Alvarez, E. et al., (Eds.), pp. 28-35, ISBN 84-7485-990-5, Bilbao, Spain, July 2005, University of Deusto, Bilbao, Spain

This Publication has to be referred as: Jaehn, H.; Kaeschel, J. & Teich, T. (2006). Automating of controlling processes in production networks, Chapter 23 in DAAAM International Scientific Book 2006, B. Katalinic (Ed.), Published by DAAAM International, ISBN 3-901509-47-X, ISSN 1726-9687, Vienna, Austria

DOI: 10.2507/daaam.scibook.2006.23

Authors' data: Dipl.-Kfm., Dipl-Vw. Jaehn H.[endrik] *, Prof. Dr. rer. nat. Dr. oec. habil. Kaeschel J.[oachim] *, Prof. Dr. rer. pol. habil. Teich T.[obias] **, * Chemnitz University of Technology, ** University of Applied Sciences of West-Saxony Zwickau, Germany,
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Author:Jaehn, Hendrik; Kaeschel, Joachim; Teich, Tobias
Publication:DAAAM International Scientific Book
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Date:Jan 1, 2006
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