A Cross-Cultural Classification of Service Export Performance Using Artificial Neural Networks

A sample of 1,246 exporting service firms from Japan, Germany and the United States are empirically analyzed in an attempt to answer the following primary questions: Does a common set of high-ranking export determinants for Exceptional Exporters exist amongservice firms from the examined countries, combined?

Abstract

Abstract Behavioral determinants and their relationship to exporting performance have been examined in varying capacities for the last several decades, although very few, in that time have examined them in a cross-cultural context. The offer here is a firm level examination of variables with a particular effort to validate performance measurements across cultural settings. Specifically, a sample of 1,246 exporting service firms from Japan, Germany and the United States are empirically analyzed in an attempt to answer the following primary questions: (a) Does a common set of high-ranking export determinants for Exceptional Exporters exist among service firms from the examined countries, combined? and furthermore, (b) Does a unique set of high-ranking export performance determinants for Exceptional Exporters exist within the service firms from each country, individually? An artificial neural network is selected as the statistical method because of the unique perspective it provides when examining a highly non-linear function with many variables, offering results that consistently prove to numerically approximate such functions much easier than conventional methods, along with the ability to dependably and accurately predict membership classification while providing weighted analyses of input variables.