Predicting the survival or failure of click-and-mortar corporations: A knowledge discovery approach

With the boom in e-business, several corporations have emerged in the late 1990s 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. 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 three classification techniques—discriminant analysis, neural networks, and support vector machines to find out whether they can predict the financial fate of companies. Neural networks perform the task better than other techniques. Using discriminant analysis and neural networks, the key financial ratios that play a major role in the process of prediction are identified. Statistical tests are conducted to validate the findings.