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A hazard-based approach to modelling the effects of online shopping on intershopping duration

Author

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  • Esra Suel

    (Imperial College London)

  • Nicolò Daina

    (Imperial College London)

  • John W. Polak

    (Imperial College London)

Abstract

Despite growing prevalence of online shopping, its impacts on mobility are poorly understood. This partially results from the lack of sufficiently detailed data. In this paper we address this gap using consumer panel data, a new dataset for this context. We analyse one year long longitudinal grocery shopping purchase data from London shoppers to investigate the effects of online shopping on overall shopping activity patterns and personal trips. We characterise the temporal structure of shopping demand by means of the duration between shopping episodes using hazard-based duration models. These models have been used to study inter-shopping spells for traditional shopping in the literature, however effects of online shopping were not considered. Here, we differentiate between shopping events and shopping trips. The former refers to all types of shopping activity including both online and in-store, while the latter is restricted to physical shopping trips. Separate models were estimated for each and results suggest potential substitution effects between online and in-store in the context of grocery shopping. We find that having shopped online since the last shopping trip significantly reduces the likelihood of a physical shopping trip. We do not observe the same effect for inter-event durations. Hence, shopping online does not have a significant effect on overall shopping activity frequency, yet affects shopping trip rates. This is a key finding and suggests potential substitution between online shopping and physical trips to the store. Additional insights on which factors, including basket size and demographics, affect inter-shopping durations are also drawn.

Suggested Citation

  • Esra Suel & Nicolò Daina & John W. Polak, 2018. "A hazard-based approach to modelling the effects of online shopping on intershopping duration," Transportation, Springer, vol. 45(2), pages 415-428, March.
    • Handle: RePEc:kap:transp:v:45:y:2018:i:2:d:10.1007_s11116-017-9838-3
    DOI: 10.1007/s11116-017-9838-3
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    References listed on IDEAS

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    Cited by:

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    2. Alexander Rossolov & Halyna Rossolova & José Holguín-Veras, 2021. "Online and in-store purchase behavior: shopping channel choice in a developing economy," Transportation, Springer, vol. 48(6), pages 3143-3179, December.
    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. Mar Vazquez-Noguerol & Jose A. Comesaña-Benavides & Sara Riveiro-Sanroman & J. Carlos Prado-Prado, 2022. "A mixed integer linear programming model to support e-fulfillment strategies in warehouse-based supermarket chains," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(4), pages 1369-1402, December.
    5. 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.

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