IDEAS home Printed from https://ideas.repec.org/a/eee/retrec/v113y2025ics0739885925000952.html
   My bibliography  Save this article

Solutions for sustainable last-mile delivery: Pick-up points location with customers’ choice

Author

Listed:
  • Bruno, Giuseppe
  • Diglio, Antonio
  • Piccolo, Carmela
  • Pipicelli, Eduardo

Abstract

The ever-growing increase of e-commerce is motivating the development of innovative solutions for optimized and sustainable last-mile logistics in the business-to-consumer (B2C) parcel delivery market. Self-collection is a recent but consolidated delivery strategy in the field, allowing customers to autonomously collect parcels from assisted or unassisted dedicated facilities (pick-up points and parcel lockers). However, the success of self-collection depends on the location of such facilities, as this strongly affects customers’ propensity to patronize them. In this context, this paper proposes a mathematical programming model for the optimal location of pick-up points in urban areas. The model seeks to maximize the proportion of customers opting for self-collection to promote this strategy over home delivery. It uses a MultiNomial Logit (MNL) to model customers’ choices. Specifically, in the MNL, parameters reflecting customers’ behaviors are included to represent their preferences for the two strategies. The model is applied to the case of Bologna (northern Italy), and various scenarios are produced by varying parameters. The results demonstrate the relevance of customers’ behavior in affecting decisions and provide numerous managerial insights, thus classifying the proposed model as an effective support tool for the design of self-collection networks.

Suggested Citation

  • Bruno, Giuseppe & Diglio, Antonio & Piccolo, Carmela & Pipicelli, Eduardo, 2025. "Solutions for sustainable last-mile delivery: Pick-up points location with customers’ choice," Research in Transportation Economics, Elsevier, vol. 113(C).
  • Handle: RePEc:eee:retrec:v:113:y:2025:i:c:s0739885925000952
    DOI: 10.1016/j.retrec.2025.101612
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0739885925000952
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.retrec.2025.101612?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:retrec:v:113:y:2025:i:c:s0739885925000952. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/620614/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.