An application of artificial neural networks in evaluating business ethics: an exploratory study

Stimulated by the proliferation of a number of scandalous incidents, concerns about business ethics have increased significantly over the last decade. As such, research studies have focused on developing theoretical and empirical foundations for understanding ethical decision making. Empirical studies have, however, used traditional quantitative analytic tools such as regression or discriminant analysis to investigate ethical issues. With the increased emphasis on ethics in organizations, more advanced tools are needed. In this exploratory research, a new approach to classifying, categorizing and analyzing ethical decision situations is presented. A comparative performance analysis of artificial neural networks, MDA and the chance approach indicated that artificial neural networks are better predictors in both training and testing phases. While some limitations of this approach were noted, in the field of business ethics, these networks possess considerable potential as an alternative to traditional analytic tools like MDA