IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v162y2025icp559-574.html

An incentive-based delivery scheme and its effect evaluated via explainable machine learning

Author

Listed:
  • Wang, Yang
  • Sun, Yu
  • Lai, Jianhui
  • Chen, Yanyan
  • Holguín-Veras, José

Abstract

The current delivery mode acquiesces E-shopping consumers to provide only a single address for delivery, despite their potential to have multiple addresses available. Inspired by this, we propose a new delivery mode with an economic incentive scheme to encourage consumers to provide more addresses and empower the delivery operator to determine the final delivery address following a certain optimization criteria. To examine the incentive's effect, we conducted a survey. The survey reveals a substantial, near-linear impact on promoting multiple address provision through the incentive, resulting in a 32% increase in consumers providing additional addresses. We develop an eXtreme Gradient Boosting model, which outperformed Logistic Regression and Support Vector Machine, to explore the relationship between address provision decision and E-shopping behavior. Augmented by Shapley Additive Explanations, the model can interpret how both the incentive and E-shopping behavior influence address provision. In addition to the incentive, factors such as the number of available addresses and the average price of the parcel also significantly influence the decision-making process for providing delivery addresses. The insights extracted from this study can provide a foundation for policymakers to establish more practical delivery management policies.

Suggested Citation

  • Wang, Yang & Sun, Yu & Lai, Jianhui & Chen, Yanyan & Holguín-Veras, José, 2025. "An incentive-based delivery scheme and its effect evaluated via explainable machine learning," Transport Policy, Elsevier, vol. 162(C), pages 559-574.
    • Handle: RePEc:eee:trapol:v:162:y:2025:i:c:p:559-574
    DOI: 10.1016/j.tranpol.2025.01.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X25000046
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tranpol.2025.01.004?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.

    References listed on IDEAS

    as
    1. Zhou, Min & Zhao, Lindu & Kong, Nan & Campy, Kathryn S. & Xu, Ge & Zhu, Guiju & Cao, Xianye & Wang, Song, 2020. "Understanding consumers’ behavior to adopt self-service parcel services for last-mile delivery," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    2. Boggio-Marzet, Alessandra & Villa-Martínez, Rafael & Monzón, Andrés, 2023. "Selection of policy actions for e-commerce last-mile delivery in cities: An online multi-actor multi-criteria evaluation," Transport Policy, Elsevier, vol. 142(C), pages 15-27.
    3. Fessler, Andreas & Thorhauge, Mikkel & Mabit, Stefan & Haustein, Sonja, 2022. "A public transport-based crowdshipping concept as a sustainable last-mile solution: Assessing user preferences with a stated choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 210-223.
    4. Mohri, Seyed Sina & Nassir, Neema & Thompson, Russell G. & Lavieri, Patricia Sauri, 2024. "Public transportation-based crowd-shipping initiatives: Are users willing to participate? Why not?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 182(C).
    5. Wang, Yi-Jia & Wang, Yue & Huang, George Q. & Lin, Ciyun, 2024. "Public acceptance of crowdsourced delivery from a customer perspective," European Journal of Operational Research, Elsevier, vol. 317(3), pages 793-805.
    6. Li, Xiaowei & Shi, Lanxin & Tang, Junqing & Yang, Chenyu & Zhao, Ting & Wang, Yuting & Wang, Wei, 2023. "Determinants of passengers' ticketing channel choice in rail transit systems: New evidence of e-payment behaviors from Xi'an, China," Transport Policy, Elsevier, vol. 140(C), pages 30-41.
    7. Punel, Aymeric & Stathopoulos, Amanda, 2017. "Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 18-38.
    8. Tsai, Yao-Te & Tiwasing, Praewwanit, 2021. "Customers’ intention to adopt smart lockers in last-mile delivery service: A multi-theory perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    9. Yuen, Kum Fai & Wang, Xueqin & Ng, Li Ting Wendy & Wong, Yiik Diew, 2018. "An investigation of customers’ intention to use self-collection services for last-mile delivery," Transport Policy, Elsevier, vol. 66(C), pages 1-8.
    10. Wang, Yang & Bi, Mengyu & Lai, Jianhui & Wang, Chenxi & Chen, Yanyan & Holguín-Veras, José, 2024. "Recourse strategy for the routing problem of mobile parcel lockers with time windows under uncertain demands," European Journal of Operational Research, Elsevier, vol. 316(3), pages 942-957.
    11. Rafael Villa & Andrés Monzón, 2021. "Mobility Restrictions and E-Commerce: Holistic Balance in Madrid Centre during COVID-19 Lockdown," Economies, MDPI, vol. 9(2), pages 1-19, April.
    12. Bi, Hui & Li, Aoyong & Hua, Mingzhuang & Zhu, He & Ye, Zhirui, 2022. "Examining the varying influences of built environment on bike-sharing commuting: Empirical evidence from Shanghai," Transport Policy, Elsevier, vol. 129(C), pages 51-65.
    13. Zhu, Siying & Zhu, Feng, 2019. "Cycling comfort evaluation with instrumented probe bicycle," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 217-231.
    14. Holguín-Veras, José & Wang, Xiaokun (Cara) & Sánchez-Díaz, Iván & Campbell, Shama & Hodge, Stacey D. & Jaller, Miguel & Wojtowicz, Jeffrey, 2017. "Fostering unassisted off-hour deliveries: The role of incentives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 172-187.
    15. dell’Olio, Luigi & Moura, Jose Luis & Ibeas, Angel & Cordera, Ruben & Holguin-Veras, Jose, 2017. "Receivers’ willingness-to-adopt novel urban goods distribution practices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 130-141.
    16. Comi, Antonio, 2020. "A modelling framework to forecast urban goods flows," Research in Transportation Economics, Elsevier, vol. 80(C).
    17. Cebeci, Merve Seher & Tapia, Rodrigo Javier & Kroesen, Maarten & de Bok, Michiel & Tavasszy, Lóránt, 2023. "The effect of trust on the choice for crowdshipping services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chua, Rachel & Wu, Min & Yuen, Kum Fai, 2025. "Sustainable crowdshipping: Navigating technological fit and security risks," Technology in Society, Elsevier, vol. 81(C).
    2. 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).
    3. Samani, Ali Riahi & Talebian, Ahmadreza & Mishra, Sabyasachee & Golias, Mihalis, 2025. "Evaluating consumer shopping, delivery demands, and last-mile preferences: An integrated MDCEV-HCM approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 197(C).
    4. Dayal, Eshwar & Khuntia, Lisa & Lakshay, Lakshay & Buldeo Rai, Heleen & Pani, Agnivesh, 2025. "Behavioral intention to use parcel lockers in the last mile and underlying linkages with travel modal choice," Research in Transportation Economics, Elsevier, vol. 111(C).
    5. Lorenzo-Espejo, Antonio & Muñuzuri, Jesús & Pegado-Bardayo, Ana & Guadix, José, 2024. "A framework for analyzing service disruptions in last-mile and first-mile reverse logistics," Research in Transportation Economics, Elsevier, vol. 108(C).
    6. Savall-Mañó, Maria & Hook, Hannah & Abouelela, Mohamed, 2025. "Can higher delivery costs promote greener practices? Consumer behaviour insights from Barcelona," Journal of Retailing and Consumer Services, Elsevier, vol. 86(C).
    7. Cai, Lanhui & Yuen, Kum Fai & Xie, Diancen & Fang, Mingjie & Wang, Xueqin, 2021. "Consumer's usage of logistics technologies: Integration of habit into the unified theory of acceptance and use of technology," Technology in Society, Elsevier, vol. 67(C).
    8. Yang, Hye-jeong & Fang, Mingjie & Yao, Jinge & Su, Miao, 2023. "Green cooperation in last-mile logistics and consumer loyalty: An empirical analysis of a theoretical framework," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    9. Rossolov, Oleksandr & Susilo, Yusak O., 2024. "Are consumers ready to pay extra for crowd-shipping e-groceries and why? A hybrid choice analysis for developing economies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 187(C).
    10. Li, Zhaotong & Wu, Min & Teo, Chee-Chong & Yuen, Kum Fai, 2024. "An investigation of consumer switching intention on the use of automated courier station from a signaling perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    11. Leise Kelli de Oliveira & Carla de Oliveira Leite Nascimento & Paulo Renato de Sousa & Paulo Tarso Vilela de Resende & Francisco Gildemir Ferreira da Silva, 2019. "Transport Service Provider Perception of Barriers and Urban Freight Policies in Brazil," Sustainability, MDPI, vol. 11(24), pages 1-17, December.
    12. Schmidt, Sebastian & Saraceni, Adriana, 2024. "Consumer acceptance of drone-based technology for last mile delivery," Research in Transportation Economics, Elsevier, vol. 103(C).
    13. Mohri, Seyed Sina & Nassir, Neema & Thompson, Russell G. & Lavieri, Patricia Sauri & Ghaderi, Hadi, 2025. "Crowd-shipping systems with public transport passengers: Operational planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 194(C).
    14. Wang, Xueqin & Wong, Yiik Diew & Sun, Shanshan & Yuen, Kum Fai, 2022. "An investigation of self-service technology usage during the COVID-19 pandemic: The changing perceptions of ‘self’ and technologies," Technology in Society, Elsevier, vol. 70(C).
    15. Xu, Shibo & Zhang, Xiaoxue & Kim, Rohan & Su, Miao, 2024. "Anthropomorphic last-mile robots and consumer intention: An empirical test under a theoretical framework," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    16. Zhang, Zhuoye & Zhang, Fangni, 2024. "Optimal operation strategies of an urban crowdshipping platform in asset-light, asset-medium, or asset-heavy business format," Transportation Research Part B: Methodological, Elsevier, vol. 189(C).
    17. Jiang, Yi & Lai, Po-Lin & Yang, Ching-Chiao & Wang, Xinchen, 2023. "Exploring the factors that drive consumers to use contactless delivery services in the context of the continued COVID-19 pandemic," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    18. Xueqin Wang & Yiik Diew Wong & Kum Fai Yuen, 2021. "Does COVID-19 Promote Self-Service Usage among Modern Shoppers? An Exploration of Pandemic-Driven Behavioural Changes in Self-Collection Users," IJERPH, MDPI, vol. 18(16), pages 1-22, August.
    19. Björn Asdecker, 2021. "Building the E-Commerce Supply Chain of the Future: What Influences Consumer Acceptance of Alternative Places of Delivery on the Last-Mile," Logistics, MDPI, vol. 5(4), pages 1-17, December.
    20. Cebeci, Merve Seher & de Bok, Michiel & Tapia, Rodrigo & Nadi, Ali & Tavasszy, Lóránt, 2025. "Feasibility of crowdshipping for outlier parcels in last-mile delivery," Research in Transportation Economics, Elsevier, vol. 112(C).

    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:trapol:v:162:y:2025:i:c:p:559-574. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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/30473/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.