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.


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    Titel :

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


    Beteiligte:
    Sakai, Takanori (Autor:in) / Hara, Yusuke (Autor:in) / Seshadri, Ravi (Autor:in) / Alho, André Romano (Autor:in) / Hasnine, Md Sami (Autor:in) / Jing, Peiyu (Autor:in) / Chua, ZhiYuan (Autor:in) / Ben-Akiva, Moshe (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2022-02-17


    Format / Umfang :

    23 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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