---
_id: '57208'
abstract:
- lang: eng
  text: '<jats:p> Home delivery failures, traffic congestion, and relatively large
    handling times have a negative impact on the profitability of last-mile logistics.
    A potential solution is the delivery to parcel lockers or parcel shops, denoted
    by out-of-home (OOH) delivery. In the academic literature, models for OOH delivery
    are so far limited to static settings, contrasting with the sequential nature
    of the problem. We model the sequential decision-making problem of which OOH location
    to offer against what incentive for each incoming customer, taking into account
    future customer arrivals and choices. We propose dynamic selection and pricing
    of OOH (DSPO), an algorithmic pipeline that uses a novel spatial-temporal state
    encoding as input to a convolutional neural network. We demonstrate the performance
    of our method by benchmarking it against two state-of-the-art approaches. Our
    extensive numerical study, guided by real-world data, reveals that DSPO can save
    19.9 percentage points (%pt) in costs compared with a situation without OOH locations,
    7%pt compared with a static selection and pricing policy, and 3.8%pt compared
    with a state-of-the-art demand management benchmark. We provide comprehensive
    insights into the complex interplay between OOH delivery dynamics and customer
    behavior influenced by pricing strategies. The implications of our findings suggest
    that practitioners adopt dynamic selection and pricing policies. </jats:p><jats:p>
    History: This paper has been accepted for the Transportation Science special issue
    on TSL Conference 2023. </jats:p><jats:p> Funding: This work was supported by
    TKI DINALOG. </jats:p>'
author:
- first_name: Fabian
  full_name: Akkerman, Fabian
  last_name: Akkerman
- first_name: Peter
  full_name: Dieter, Peter
  id: '88592'
  last_name: Dieter
- first_name: Martijn
  full_name: Mes, Martijn
  last_name: Mes
citation:
  ama: Akkerman F, Dieter P, Mes M. Learning Dynamic Selection and Pricing of Out-of-Home
    Deliveries. <i>Transportation Science</i>. Published online 2024. doi:<a href="https://doi.org/10.1287/trsc.2023.0434">10.1287/trsc.2023.0434</a>
  apa: Akkerman, F., Dieter, P., &#38; Mes, M. (2024). Learning Dynamic Selection
    and Pricing of Out-of-Home Deliveries. <i>Transportation Science</i>. <a href="https://doi.org/10.1287/trsc.2023.0434">https://doi.org/10.1287/trsc.2023.0434</a>
  bibtex: '@article{Akkerman_Dieter_Mes_2024, title={Learning Dynamic Selection and
    Pricing of Out-of-Home Deliveries}, DOI={<a href="https://doi.org/10.1287/trsc.2023.0434">10.1287/trsc.2023.0434</a>},
    journal={Transportation Science}, publisher={Institute for Operations Research
    and the Management Sciences (INFORMS)}, author={Akkerman, Fabian and Dieter, Peter
    and Mes, Martijn}, year={2024} }'
  chicago: Akkerman, Fabian, Peter Dieter, and Martijn Mes. “Learning Dynamic Selection
    and Pricing of Out-of-Home Deliveries.” <i>Transportation Science</i>, 2024. <a
    href="https://doi.org/10.1287/trsc.2023.0434">https://doi.org/10.1287/trsc.2023.0434</a>.
  ieee: 'F. Akkerman, P. Dieter, and M. Mes, “Learning Dynamic Selection and Pricing
    of Out-of-Home Deliveries,” <i>Transportation Science</i>, 2024, doi: <a href="https://doi.org/10.1287/trsc.2023.0434">10.1287/trsc.2023.0434</a>.'
  mla: Akkerman, Fabian, et al. “Learning Dynamic Selection and Pricing of Out-of-Home
    Deliveries.” <i>Transportation Science</i>, Institute for Operations Research
    and the Management Sciences (INFORMS), 2024, doi:<a href="https://doi.org/10.1287/trsc.2023.0434">10.1287/trsc.2023.0434</a>.
  short: F. Akkerman, P. Dieter, M. Mes, Transportation Science (2024).
date_created: 2024-11-18T18:40:55Z
date_updated: 2024-11-19T18:59:24Z
department:
- _id: '277'
doi: 10.1287/trsc.2023.0434
language:
- iso: eng
publication: Transportation Science
publication_identifier:
  issn:
  - 0041-1655
  - 1526-5447
publication_status: published
publisher: Institute for Operations Research and the Management Sciences (INFORMS)
status: public
title: Learning Dynamic Selection and Pricing of Out-of-Home Deliveries
type: journal_article
user_id: '88592'
year: '2024'
...