Predicting the survival or failure of click-and-mortar corporations

Abstract

With the boom in e-business, several corporations have emerged in the late nineties that have primarily conducted their business through the Internet and the Web. They have come to be known as the dotcoms or click-and-mortar corporations. The success of these companies has been short lived and many of these companies have failed rapidly in a short span of 4-5 years. This research is an investigation of the burst of the dotcom bubble from a financial perspective. Data from the financial statements of several survived and failed dotcom companies is used to compute financial ratios, which are analyzed using two data mining techniques - discriminant analysis (DA) and neural networks (NN) to find out whether they can predict the financial fate of companies. Neural networks perform better than discriminant analysis in predicting survival or failure of click-and-mortar corporations. The key financial ratios that play a major role in the process of prediction are identified. © 2005 IEEE.published_or_final_versio