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In order to develop an instrument for solving the decision problem, we begin by examining the significance of communication standards for coordinating economic activities. We consider the decision to implement standards as an isolated coordination problem. Using the EDI example, we subsequently point out the potential advantages and disadvantages connected to changing communication standards. By including independent EDI service providers, we present our problem as a typical make-or-buy problem. For this purpose, in section 4 we analyze the efficiency increases made possible by external service businesses in information networks. Our evaluated results serve as the basis for developing a model to coordinate standardization decisions in a centrally coordinated information network. The model is based on linear programming. We conclude the paper with an illustration of our results by optimizing an exemplary network.
Participants of information networks, i.e. networks primarily based on communication, have a choice of different communication standards. The selection of such standards is subject to the efficiency rule, that is, weighing the costs against the benefits. Their implementation and use, on the one hand, induce resource consumption and, on the other hand, cost savings potentials. Selecting the optimal set of communication standards is therefore viewed as a separate coordination problem, referred to as the standardization problem [Buxmann 1997].
The need for coordination arises whenever interdependencies exist between activities [Malone/Crowston 1994]. Implementing and using individual communication standards represent such economic activities. Interdependencies between these and other activities result from the budget constraint. If the budget is invested in the implementation of a specific standard, these resources cannot be used for any other purpose. Next to the interdependency in the context of resource shortage, the standardization problem additionally considers interdependencies between activities due to so-called positive network effects. That is, the benefits a person or an organization derives from using a communication standard also depend on the extent to which it is used by other participants of the information network [Katz/Shapiro 1985]. An example is the e-mail technology which provides a quick and low cost exchange of information. The more communication partners are accessible with this standard, the higher the potential cost and time savings. Therefore, the evaluation of own activities depends on the activities of others.
To solve the standardization problem of an information network, the above mentioned interdependencies must be taken into consideration. The combination of communication standards for each individual node, which is determined for given volumes of exchanged data, induces the cost optimum of the entire network. However, the optimality of a determined solution is continuously questioned over time, since changes in attributes of decision parameters occur. The worldwide continuously decreasing telecommunication rates are a good example of this. In addition, the amount of data to be transmitted is consistently increasing. Furthermore, new communication standards constantly extend the existing set, and must be examined with regard to their efficiency. Since such future developments are difficult to predict, it is especially important to review the validity of the existing solutions when new standards emerge. Within this context, EDI standards are presently an especially innovative area. Using the EDI example, we begin by identifying and quantifying the decision parameters to solve the described coordination problem. This supplies the basis for the decision model we will subsequently introduce.
A coordinating unit faces alternative courses of action in making the decision to implement an EDI standard. On the one hand, the internal data management can be converted to the new technology. On the other hand, it can outsource the entire data management, or at least a part of it, to an external, independent service provider which offers EDI services, e.g. debis. Thus, in addition to deciding on which standard to use, the problem of a typical make-or-buy decision must be solved.
Table 1 summarizes the benefits and costs of company-provided EDI services [Emmelhainz 1993, Kilian et al. 1994, Neuburger 1994].
The benefits are primarily derived from achieving efficiency goals, i.e. cost reductions induced by rationalization and automation measures. On the one hand, costs that depend on the amount of data transferred can be reduced. Examples are avoiding redundant data entry and error rate improvements. On the other hand, cost savings can be induced that do not directly depend on the data volume, for example, by improving the value-added chain (just-in-time management, etc.). The same differentiation applies to the costs incurred for the implementation and use of EDI. For example, data transmission represents a variable figure, while the costs of hardware and software are for the most part independent from the amount of transferred data. Subsequently, we generalize the advantages and assume the benefits derived from EDI usage consist of reduced variable costs of transmitting data. The costs of implementing the EDI standard will in the following be referred to as set-up costs or standardization costs.
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In case the EDI services are outsourced to an external company, the high implementation costs of standards can be saved, without restricting communication to other nodes. Additional benefits can be derived from specific functions of external services, which will be discussed in the subsequent section. On the cost side, next to low reorganization expenditures for enabling communication to the EDI service provider, costs are mainly incurred charges depending on the data volume of the purchased services [Emmelhainz 1993, pp. 109-117]. The following chapter analyzes potential efficiency increases resulting from engaging an external service business.
EDI induces significant cost savings potentials, however, its implementation is costly and combined to different uncertainties. Therefore, institutions have emerged that mediate between organizations with EDI and those without. Such intermediaries provide each information network participant with the EDI advantages, without the participants having to implement the standard themselves.
We generally define intermediaries as independent mediators between associated (networked) participants. They transform data outputs of one participant into the appropriate data inputs of the other by eliminating incompatibilities between output and input attributes. A communication standard regulates the specific characteristics of a specific amount of data attributes. Transforming data from one standard into another is therefore nothing more than adapting incompatible data attributes. By describing the transformation process in the subsequent section, the services and functions of intermediaries will be elaborated.
Assuming an intermediary takes over basic responsibilities, such as receiving, storing, and forwarding electronic data, then many of the connections necessary for direct communication can be eliminated. In a formal approach, this relation can be derived from the law of contact cost reduction [Balderston 1958, Baligh/Richartz 1967]. An information network with N participants, each sustaining communication links to every other participant, results to N(N-1)/2 communication links. By employing an intermediary, the number can be reduced to N. Figure 1 illustrates the connection.

For N>3 a reduction of edges results for the whole communication system, independent of the amount of data to be transmitted; the number of communication contacts decreases correspondingly. The problems of synchronization in terms of time and technical compatibility are reduced. However, the intermediary must be capable of supporting the technical and organizational conditions of each participant in order to coordinate the reception and forwarding of data.
Other services offered by intermediaries of information networks are connected to data security. In exchanging business data, EDI users or users of other communication standards are often concerned with the security of sensitive data. In addition to authenticity, integrity, and confidentiality [Europäische Kommission 1997], a significant issue is system security. An intermediary specialized in forwarding data generally has a more solid know-how in the area of data security than individual users, and furthermore has improved technical possibilities to take any necessary security measures.
By determining his service range, an intermediary decides for which communication standards and for which storage mediums he wishes to transform data into which EDI standards. All of these standards must be supported in his own organization and, additionally, he must have the appropriate transformation instruments available. The choice of service range depends on the consumers, whose needs the intermediary aims at satisfying.
Our model optimizes an existing information network, consisting of N nodes with S available standards to choose from. The participants are already equipped with certain standards. When a node i (iÎ {1,...,N}) is equipped with a standard s (sÎ {0,...,S-1}), costs of stancostsis are incurred. The amount of information transferred in the communication link between nodes k and l (k,lÎ {1,...,N}) is indicated by flowkl. A flow along the edge between nodes i and j (jÎ {1,...,N}) incurs variable costs of comcostsijs, dependent on the standard s being used. If an information flow transmitted in node i is transformed from standard s into standard t (or vice versa), variable costs of trancostsist result. Nodes and edges are not subject to any capacity restrictions, i.e. no quantitative restrictions apply for redirecting or transforming data flows.
The action variables of the model are, on the one hand, the binary variable XisÎ {0,1}, assuming the value 1 if node i is equipped with standard s. On the other hand, the variable FijklsÎ R0+ (with i¹ j and k< l), indicates the data flow transmitted from node k as the sender to node l as the receiver (subsequently referred to as "communication link (k,l)"), passing through edge (i,j) on its way to the target node.
The binary variable YijklsÎ {0,1} (with i<j and k<l) serves as an auxiliary variable of the model. It indicates whether a flow takes place along edge (i,j) using standard s for the communication link (k,l). Another auxiliary variable, TiklstÎ {0,1} (with k<l and s<t), indicates whether in node i a flow of the communication link (k,l) is transformed from standard s into standard t (or vice versa).
The model is static, i.e. fixed costs must be compensated by potential variable cost savings within a specified service life time of the standard considered. This assumption is based on the already mentioned dynamics in connection with the development of new standards, which make long-term planning unrealistic. The (first best) cost optimum is determined from an overall viewpoint of the network.
The following target function determines the solution of the coordination problem for centrally coordinated networks:

The constraints of the linear problem are illustrated in the appendix. The solution resulting from the optimization can be used to determine the optimal total costs of the information network, the use of communication standards in each node, as well as the standards and the series of edges of each data transfer. In addition, the nodes functioning as intermediaries, the extent of data transformation, as well as the intermediary’s range of standards can be determined. The following section illustrates an example of optimizing a given network.
To simplify, we demonstrate a network with five participants (individuals, organizations or machines), represented by nodes 1 through 5. Determined data flows take place along the communication links between the participants. The determined amount of data is listed along the edges. For example, 900 data units are exchanged between participant 1 and participant 4. In the initial state of the network each node is equipped with a standard Z. Node 2 is additionally equipped with EDI, symbolized by the shaded area in figure 2. The entire communication of the network is based on the standard Z, since node 2 does not have a partner to communicate with using EDI. Variable costs are incurred along the edges for exchanging information. Table 2 lists their amounts for both standards.
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| var. comcosts (Z) |
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| var. comcosts (EDI) |
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The exchange of information between nodes 3 and 4, for example, incurs costs of 15,000* 3=45,000 monetary units. The costs of the initial state therefore total 77,900 monetary units for the data exchange. At the same time, these costs represent the total costs of the information network, since no costs are incurred for implementing a new standard.
Figure 3 presents the optimal standardization solution of the network without intermediaries. Based on the situation described above, we evaluate whether it is economically viable to implement EDI in the individual nodes. Table 3 lists the respective standardization costs incurred.
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The standardization costs of node 2 of course equal zero, since EDI is already available. Nodes 1 through 4 are equipped with EDI in the optimum, and use this standard to communicate. Standardization costs totaling 16,500 monetary units result. Node 5, on the other hand, continues to communicate with its partners using standard Z. The costs of transferring data amount to 44,200 monetary units, and therefore total costs of 60,700 monetary units result.
Figure 4 shows the optimal solution of the network under consideration of intermediation. Considering the initial state, each node can take over intermediary functions. Table 3 lists the edge-specific variable costs incurred for transforming data.
In the optimal solution of this example, less nodes implement the EDI standard than in the solution without an intermediary. Only nodes 1 and 4 are additionally equipped with EDI. Node 1 serves as the intermediary. It directs data flows between nodes 3 and 4 and nodes 4 and 5. Along edge (1,4), for example, flow34=15,000 data units results, that is assigned to the communication link between nodes 3 and 4. The intermediary’s service consists of transforming data from standard Z into the EDI standard, and vice versa. The participating nodes are charged a total of (15,000+5,000)* 0.1=2,000 monetary units in transformation costs. It is clear that in this example, even with redirecting data, lower total costs result for the entire information network.
Our model provides various points for future extensions. Possible extensions could include dynamic aspects as well as introducing edge and node capacities. Furthermore, the effects on the overall network of entirely new intermediary nodes emerging could be examined. With the rapid developments of the internet in mind, we are also currently examining the extent to which the results can also be applied to decentralized networks.
(Un-)Balanced Data Flow in Nodes:
For each communication link (k,l) an information flow flowkl is transmitted from node k into the network (1) as well as an information flow being received from every node l (2).
(1)
(with k<l)
(2)
(with k<l)
For each node (i¹ k) and (i¹ l) the sum of all incoming flows of the communication link (k,l) must equal the sum of all outgoing information flows of this link.
(3)
(with i¹
k and i¹ l and k<l)
Node Standardization as a Constraint of Yijkls<0
Low communication costs can only be achieved between two nodes i and j if both nodes are using the same standard s.
(4)
(with i<j
and k<l)
Indication of Necessary Transformations by Yijkls
Inequation (5) ensures that Yijkls assumes the value one as soon as a flow of the communication link (k,l) using the standard s flows along edge (i,j).
(5)
(with i<j and k<l and M³
)
Activating Transformation Costs
Transformation costs must only be borne if a flow of the communication link (k,l) passing through node i is changed from standard s to standard t (or vice versa).
(6)
(with i¹ k and i¹ l and k<l and s<t)
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