Analysis of E-commerce Operational Strategies for Capacity Increase in the Last Mile under Demand Uncertainty: An Approach by Pascal and Markowitz Methods

This study analyzes operational strategies for capacity expansion in last-mile operations under demand uncertainty. The research addresses the decision-making problem faced by companies in e-commerce, where volatility requires a balance between service levels and costs. A quantitative approach based on Expected Value’s Criterion, from Pascal, was used to evaluate average efficiency, while the Markowitz Model was employed to quantify operational risk through variabi-
lity (standard deviation). Five strategies were evaluated, ranging from labor flexibility to large-scale automation. The results reveal that the Automation strategy, despite presenting the highest expected value, carries a critical risk due to high volatility. Conversely, the adjustment of the Operations Clock proved to be the most resilient alternative, offering stability with a low standard deviation. It is concluded that the explicit incorporation of risk alters the prioritization of strategies, revealing
that average statistical efficiency can mask severe operational vulnerabilities.