Combined Stochastic Process and Value at Risk: A Real-World Information System Decision Case.

In this study, we used a combined stochastic process and value-at-risk (VaR) method to examine an electronic commerce expansion decision. By modeling uncertain benefits as a stochastic process, maximum losses of alternative decisions were quantified and compared to help managers to make information system/information technology (IS/IT) project decisions. Our results, based on the maximum loss perspective, demonstrated that uncertainty plays a critical role in evaluating IS/IT projects.