Antonia Hermelbracht

Pattern Detection with Growing Neural Networks - An Application to Marketing and Library Data

This paper introduces a new growing neural network for pattern detection which bears certain resemblances to the growing neural gas network suggested by Pritzke (1995) [2]. However, the algorithm at hand is more parsimonious with respect to the number of parameters to be specified a priori. Thus it is largely autonomous regarding the data-driven construction of the final network topology which unburdens the user significantly. To demonstrate its performance and adaptability the new algorithm is applied to real classification tasks in lifestyle analysis and media usage analysis.

The Importance of E-Commerce in China and Russia — An Empirical Comparison

This paper presents selected results of a comparative study focussing on the political, social and economic conditions, as well as the current status quo and future prospects of e-commerce in China and Russia. The empirical findings are based on data collected by two independent online-surveys covering Chinese and Russian companies from different branches as well as management consultancies engaged in these countries. The surveys provide information about the current importance of e-commerce in both countries and work out both potentials and challenges for market development.

Competition Analysis in Marketing Using Rank Ordered Data

A new approach to evaluating competition between different products of one category using individual rankings is introduced. The approach is based on the principle of ordinal regression and focusses on the determination of the sources of existing market shares. To account for this the success of a particular product is put down to the consumers’ perception of relevant attributes. The functionality of our approach is demonstrated by applying it to an empirical data set from the car industry.