Contributions published at Department of Business Administration (Egon Franck)

An artificial neural network (ANN) algorithm is proposed that incorporates both market segmentation and discriminant (regression) analysis of the segments. The method simultaneously estimates the models relating consumer characteristics to market segments, i.e., subjects are assigned to (unique) segments so that subjects within a class show similar purchase behavior and share the same characteristics (psychographics/sociodemographics). Parameters of all models are estimated by the backpropagation algorithm. The performance of the ANN methodology is assessed in a Monte-Carlo study. In contrast to the usual stepwise approach adopted in segmentation studies, our study found that simultaneous segmentation and discrimination are preferable for finding an overall optimum in that this way clusters are formed not only to create homogeneous submarkets but also to show a good dicriminatory behavior.

We compare the performance of a specifically designed feedforward artificial neural network with one layer of hidden units to the K-means clustering technique in solving the problem of cluster-based market segmentation. The data set analyzed consists of usages of brands (product category: household cleaners) in different usage situations. The proposed feedforward neural network model results in a two segment solution that is confirmed by appropriate tests. On the other hand, the K-means algorithm fails in discovering any somewhat stronger cluster structure. Classification of respondents on the basis of external criteria is better for the neural network solution. We also demonstrate the managerial interpretability of the network results.

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This paper compares the performance of transfer pricing and tidy cost allocations in a multiproduct firm in presence of output market competition and production externalities. In absence of competition, tidy cost allocations are creating inefficient allocations within the firm while transfer prices can always be adjusted to replicate the first best solution of the centralized firm. While the second result is well known, the first result draws a parallel to the impossibility of solving the free rider problem in team production by a profit sharing scheme. Under duopolistic competition, transfer prices are still the best accounting rule but the solution depends on the nature of competition on the final product market. When firms compete in prices, the strategic rationale requires to allocate more than the total cost of the congested service to the duopolistic departments. While transfer prices can still be adjusted accordingly, the tidiness requirement prevents the cost allocation scheme from providing the desired strategic incentives to the firms' managers. Under quantity competition, the strategic motive requires to allocate less than the cost of the service to the duopolistic departments. Although a tidy cost allocation scheme does not contradict the required direction of the strategic effect, the optimal allocation is at best found incidentally while the transfer prices can again always be adjusted in an optimal way.