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Incorporating online shopping into travel demand modelling: challenges, progress, and opportunities

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  • Esra Suel
  • John W. Polak

Abstract

There is a large body of literature, spanning multiple disciplines, concerned with the relationship between traditional (physical) shopping and associated travel behaviour. However, despite the recent rapid growth of digital retailing and online shopping, the impact on travel behaviour remain poorly understood. Although the issue of the substitution and complementarity between conventional and virtual retail channels has been extensively explored, few attempts have been made to extend this work so as to incorporate virtual retail channels into modelling frameworks that can link shopping and mobility decisions. Here, we review the existing literature base with a focus on most relevant dimensions for personal mobility. How online activity can be incorporated into operational transport demand models and benefits of such effort are discussed. Existing frameworks of shopping demand are flexible and can, in principle, be extended to incorporate virtual shopping and the associated additional complexities. However, there are significant challenges associated with lack of standard ontologies for crucial concepts and insufficiencies in traditional data collection methods. Also, supply-side questions facing businesses and policy-makers are changing as retailing goes through a digital transformation. Opportunities and priorities need to be defined for future research directions for an assessment of existing tools and frameworks.

Suggested Citation

  • Esra Suel & John W. Polak, 2018. "Incorporating online shopping into travel demand modelling: challenges, progress, and opportunities," Transport Reviews, Taylor & Francis Journals, vol. 38(5), pages 576-601, September.
    • Handle: RePEc:taf:transr:v:38:y:2018:i:5:p:576-601
    DOI: 10.1080/01441647.2017.1381864
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    Citations

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    Cited by:

    1. Gozde Ozonder & Eric J. Miller, 2021. "Longitudinal analysis of activity generation in the Greater Toronto and Hamilton Area," Transportation, Springer, vol. 48(3), pages 1149-1183, June.
    2. Wang, Kaili & Gao, Ya & Liu, Yicong & Nurul Habib, Khandker, 2023. "Exploring the choice between in-store versus online grocery shopping through an application of Semi-Compensatory Independent Availability Logit (SCIAL) model with latent variables," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
    3. Takanori Sakai & Yusuke Hara & Ravi Seshadri & Andr'e Alho & Md Sami Hasnine & Peiyu Jing & ZhiYuan Chua & Moshe Ben-Akiva, 2020. "E-Commerce Delivery Demand Modeling Framework for An Agent-Based Simulation Platform," Papers 2010.14375, arXiv.org.
    4. Saphores, Jean-Daniel & Xu, Lu, 2021. "E-shopping changes and the state of E-grocery shopping in the US - Evidence from national travel and time use surveys," Research in Transportation Economics, Elsevier, vol. 87(C).
    5. Shi, Kunbo & De Vos, Jonas & Yang, Yongchun & Li, Enlong & Witlox, Frank, 2020. "Does e-shopping for intangible services attenuate the effect of spatial attributes on travel distance and duration?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 86-97.
    6. Yicong Liu & Kaili Wang & Patrick Loa & Khandker Nurul Habib, 2022. "Modelling the Frequency of Home Deliveries: An Induced Travel Demand Contribution of Aggrandized E-shopping in Toronto during COVID-19 Pandemics," Papers 2209.10664, arXiv.org.
    7. Minh Hieu Nguyen & Jimmy Armoogum & Binh Nguyen Thi, 2021. "Factors Affecting the Growth of E-Shopping over the COVID-19 Era in Hanoi, Vietnam," Sustainability, MDPI, vol. 13(16), pages 1-21, August.
    8. Ozbilen, Basar & Wang, Kailai & Akar, Gulsah, 2021. "Revisiting the impacts of virtual mobility on travel behavior: An exploration of daily travel time expenditures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 49-62.
    9. Harsh Shah & Andre L. Carrel & Huyen T. K. Le, 2024. "Impacts of teleworking and online shopping on travel: a tour-based analysis," Transportation, Springer, vol. 51(1), pages 99-127, February.
    10. Mishra, Sabyasachee & Sharma, Ishant & Pani, Agnivesh, 2023. "Analyzing autonomous delivery acceptance in food deserts based on shopping travel patterns," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    11. Mateos-Mínguez, Paloma & Arranz-López, Aldo & Soria-Lara, Julio A. & Lanzendorf, Martin, 2021. "E-shoppers and multimodal accessibility to in-store retail: An analysis of spatial and social effects," Journal of Transport Geography, Elsevier, vol. 96(C).
    12. Balbontin, Camila & Hensher, David A. & Ho, Chinh, 2023. "Light commercial vehicles destination choice: Understanding preferences relative to the number of stop and tour-based trip type," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 171(C).
    13. Shah, Harsh & Carrel, Andre L. & Le, Huyen T.K., 2021. "What is your shopping travel style? Heterogeneity in US households’ online shopping and travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 83-98.
    14. Reiffer, Anna S. & Kübler, Jelle & Kagerbauer, Martin & Vortisch, Peter, 2023. "Agent-based model of last-mile parcel deliveries and travel demand incorporating online shopping behavior," Research in Transportation Economics, Elsevier, vol. 102(C).

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