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Household-based E-commerce demand modeling for an agent-based urban transportation simulation platform

Author

Listed:
  • Takanori Sakai
  • Yusuke Hara
  • Ravi Seshadri
  • André Romano Alho
  • Md Sami Hasnine
  • Peiyu Jing
  • ZhiYuan Chua
  • Moshe Ben-Akiva

Abstract

The e-commerce market has grown rapidly in the past two decades. The need for predicting e-commerce demand and evaluating relevant policies and solutions is increasing. However, the existing simulation models for e-commerce demand are still limited and do not consider the impacts of delivery options and their attributes that shoppers face on multiple dimensions of e-commerce demand. We propose a novel framework involving disaggregate behavioral models that jointly predict e-commerce expenditure, purchase amount per transaction, delivery mode, and option choices. The proposed framework can simulate the changes in e-commerce demand and be used to evaluate the impacts of a range of policies and solutions. We specify the model parameters based on various sources of relevant information, integrate the model into an urban freight simulator, and conduct a demonstrative simulation for a prototypical North American city. The results of the analysis highlight the capability and applicability of the proposed modeling framework.

Suggested Citation

  • Takanori Sakai & Yusuke Hara & Ravi Seshadri & André Romano Alho & Md Sami Hasnine & Peiyu Jing & ZhiYuan Chua & Moshe Ben-Akiva, 2022. "Household-based E-commerce demand modeling for an agent-based urban transportation simulation platform," Transportation Planning and Technology, Taylor & Francis Journals, vol. 45(2), pages 179-201, February.
    • Handle: RePEc:taf:transp:v:45:y:2022:i:2:p:179-201
    DOI: 10.1080/03081060.2022.2084397
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    Cited by:

    1. Yuki Oyama & Daisuke Fukuda & Naoto Imura & Katsuhiro Nishinari, 2022. "E-commerce users' preferences for delivery options," Papers 2301.00666, arXiv.org, revised Aug 2023.
    2. Peiyu Jing & Ravi Seshadri & Takanori Sakai & Ali Shamshiripour & Andre Romano Alho & Antonios Lentzakis & Moshe E. Ben-Akiva, 2023. "Evaluating congestion pricing schemes using agent-based passenger and freight microsimulation," Papers 2305.07318, arXiv.org.

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