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A greener last mile: Analyzing the carbon emission impact of pickup points in last-mile parcel delivery

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  • Niemeijer, R.
  • Buijs, P.

Abstract

This paper analyzes the carbon emission impact of pickup points in last-mile parcel delivery. Pickup points provide customers and delivery companies with an alternative to attended home delivery. The delivery company can drop a parcel off at the pickup point, such as a service desk in a grocery store or a parcel locker, from where the customer collects the parcel. Because of the potential efficiency gains for the delivery vehicle, pickup points are often presented as a sustainable alternative to home delivery. The efficiency gains for the delivery vehicle need to be weighed against customers traveling to the pickup point by car, however. The mathematical analysis presented in this paper integrates continuous approximation techniques to assess the potential for improved delivery route efficiency with multinomial logistic regression for estimating the travel distance and mode choice of customers collecting their parcels. The results challenge the suggestion that pickup points are a universally sustainable alternative to home delivery. The potential for a net positive carbon emission impact is greatest when pickup points are established in urban settings, while in rural settings, the carbon emission benefits derived from improved delivery route efficiency are quickly offset by the carbon footprint associated with customer travel.

Suggested Citation

  • Niemeijer, R. & Buijs, P., 2023. "A greener last mile: Analyzing the carbon emission impact of pickup points in last-mile parcel delivery," Renewable and Sustainable Energy Reviews, Elsevier, vol. 186(C).
    • Handle: RePEc:eee:rensus:v:186:y:2023:i:c:s1364032123004872
    DOI: 10.1016/j.rser.2023.113630
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    References listed on IDEAS

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    1. Janjevic, Milena & Winkenbach, Matthias & Merchán, Daniel, 2019. "Integrating collection-and-delivery points in the strategic design of urban last-mile e-commerce distribution networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 37-67.
    2. Lin, Yun Hui & Wang, Yuan & He, Dongdong & Lee, Loo Hay, 2020. "Last-mile delivery: Optimal locker location under multinomial logit choice model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    3. Schwerdfeger, Stefan & Boysen, Nils, 2020. "Optimizing the changing locations of mobile parcel lockers in last-mile distribution," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1077-1094.
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    Cited by:

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    2. Ma, Bohao & Teo, Chee-Chong & Wong, Yiik Diew, 2024. "Location analysis of parcel locker Network: Effects of spatial characteristics on operational performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 192(C).
    3. Arevalo-Ascanio, Rafael & De Meyer, Annelies & Gevaers, Roel & Guisson, Ruben & Dewulf, Wouter, 2024. "From operational to strategic modelling: A continuous multi-scale approach for last-mile analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 191(C).
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    5. Sina Mohri, Seyed & Ghaderi, Hadi & Van Woensel, Tom & Mohammadi, Mehrdad & Nassir, Neema & Thompson, Russell G., 2024. "Contextualizing alternative delivery points in last mile delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 192(C).

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