  The e-commerce delivery demand has grown rapidly in the past two decades and
such trend has accelerated tremendously due to the ongoing coronavirus
pandemic. Given the situation, the need for predicting e-commerce delivery
demand and evaluating relevant logistics solutions is increasing. However, the
existing simulation models for e-commerce delivery demand are still limited and
do not consider the delivery options and their attributes that shoppers face on
e-commerce order placements. We propose a novel modeling framework which
jointly predicts the average total value of e-commerce purchase, the purchase
amount per transaction, and delivery option choices. The proposed framework can
simulate the changes in e-commerce delivery demand attributable to the changes
in delivery options. We assume the model parameters based on various sources of
relevant information and conduct a demonstrative sensitivity analysis.
Furthermore, we have applied the model to the simulation for the
Auto-Innovative Prototype city. While the calibration of the model using
real-world survey data is required, the result of the analysis highlights the
applicability of the proposed framework.
