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arXiv · 2010.14375

E-Commerce Delivery Demand Modeling Framework for An Agent-Based Simulation Platform

Takanori Sakai·Yusuke Hara·Ravi Seshadri·André Alho·Md Sami Hasnine·Peiyu Jing·ZhiYuan Chua·Moshe Ben-Akiva
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Abstract

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.

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Takanori Sakai, Yusuke Hara, Ravi Seshadri, André Alho, Md Sami Hasnine, Peiyu Jing, ZhiYuan Chua, Moshe Ben-Akiva. 2020-10-27. E-Commerce Delivery Demand Modeling Framework for An Agent-Based Simulation Platform. https://arxiv.org/abs/2010.14375

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