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

Area of Science:

• Decision Science
• Information Systems
• Financial Risk Management

Background:

• Electronic commerce expansion decisions involve significant uncertainty.
• Traditional methods may not adequately capture the risk associated with uncertain benefits.
• Effective risk quantification is crucial for strategic IS/IT investments.

Purpose of the Study:

• To develop and apply a novel method for evaluating electronic commerce expansion decisions.
• To quantify the maximum potential losses of alternative IS/IT projects.
• To assess the role of uncertainty in IS/IT project evaluation.

Main Methods:

• Utilized a combined stochastic process and value-at-risk (VaR) methodology.
• Modeled uncertain benefits within the expansion as a stochastic process.
• Quantified and compared the maximum losses associated with different decision alternatives.

Main Results:

• Uncertainty was demonstrated to be a critical factor in evaluating IS/IT projects.
• The value-at-risk (VaR) method effectively quantified maximum possible losses.
• The proposed method provides a robust framework for comparing project risks.

Conclusions:

• The combined stochastic process and VaR method offers a valuable tool for IS/IT project decision-making.
• Managers can leverage VaR to better understand and mitigate potential financial risks.
• This approach enhances the strategic evaluation of electronic commerce initiatives.