IDEAS home Printed from https://ideas.repec.org/a/bla/bstrat/v34y2025i3p2897-2916.html

Assessing Urban Freight Tours: A Machine Learning and Life Cycle Sustainability Assessment Approach for Logistics Management

Author

Listed:
  • Sakthivelan Chakravarthy
  • Aakanksha Kishore
  • Sathiya Prabhakaran
  • Marimuthu Venkadavarahan

Abstract

The main aim of this study is to assess urban freight tours through integrating machine learning with the Life Cycle Sustainability Assessment (LCSA). The research captures supply chain operations using the Gradient Boosting Regressor (GBR) model with real‐time data from surveys and Global Positioning System (GPS) tracking. These predictions were analysed using LCSA to assess the sustainability impacts of Hydrogen Fuel Light Commercial Vehicles (HFLCVs) and Electric Light Commercial Vehicles (ELCVs) compared to traditional fuel‐based vehicles. HFLCVs show remarkable reductions in ecosystem and health damage by 58% and 61%, indicating substantial environmental and health benefits. Findings suggest that strategic investment in hydrogen‐fuel and electric LCVs can significantly decrease operational costs and environmental impacts, making them crucial for advancing sustainable urban logistics. This research highlights the benefits and possibilities of using an integrated data‐driven approach to achieve urban sustainability, thus creating an urgency to shift policies favouring green urban freight systems.

Suggested Citation

  • Sakthivelan Chakravarthy & Aakanksha Kishore & Sathiya Prabhakaran & Marimuthu Venkadavarahan, 2025. "Assessing Urban Freight Tours: A Machine Learning and Life Cycle Sustainability Assessment Approach for Logistics Management," Business Strategy and the Environment, Wiley Blackwell, vol. 34(3), pages 2897-2916, March.
    • Handle: RePEc:bla:bstrat:v:34:y:2025:i:3:p:2897-2916
    DOI: 10.1002/bse.4114
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/bse.4114
    Download Restriction: no
    File URL: https://libkey.io/10.1002/bse.4114?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
    ---><---

    References listed on IDEAS

    as
    1. Ferguson, Mark & Maoh, Hanna & Ryan, Justin & Kanaroglou, Pavlos & Rashidi, Taha Hossein, 2012. "Transferability and enhancement of a microsimulation model for estimating urban commercial vehicle movements," Journal of Transport Geography, Elsevier, vol. 24(C), pages 358-369.
    2. José Holguín-Veras & Ning Xu & Miguel Jaller & John Mitchell, 2016. "A Dynamic Spatial Price Equilibrium Model of Integrated Urban Production-Transportation Operations Considering Freight Delivery Tours," Transportation Science, INFORMS, vol. 50(2), pages 489-519, May.
    3. Rolf Moeckel & Rick Donnelly, 2016. "A model for national freight flows, distribution centers, empty trucks and urban truck movements," Transportation Planning and Technology, Taylor & Francis Journals, vol. 39(7), pages 693-711, October.
    4. Khan, Mubassira & Machemehl, Randy, 2017. "Analyzing tour chaining patterns of urban commercial vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 84-97.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sha, Xiaowen & Su, Miao, 2026. "Ownership, regulation, and ESG in transport and logistics: Insights for policy from explainable machine learning," Transport Policy, Elsevier, vol. 178(C).

    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. Thoen, Sebastiaan & Tavasszy, Lóránt & de Bok, Michiel & Correia, Goncalo & van Duin, Ron, 2020. "Descriptive modeling of freight tour formation: A shipment-based approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    2. Cong Qi & Jonas De Vos & Tao Tao & Linxuan Shi & Xiucheng Guo, 2025. "Trip chaining patterns of tourists: a real-world case study," Transportation, Springer, vol. 52(1), pages 239-261, February.
    3. Márquez, Luis & Cantillo, Víctor & Paternina-Arboleda, Carlos D., 2024. "Temporal accessibility and freight generation of agricultural products: An empirical study in Colombia," Research in Transportation Economics, Elsevier, vol. 104(C).
    4. Yang, Yitao & Nadi, Ali & Song, Dongdong & Cebeci, Merve Seher & Jia, Bin & de Bok, Michiel & Tavasszy, Lóránt A., 2026. "Uncovering heterogeneous decision-making in truck tour organization: A shipment-based behavioral modeling approach," Transport Policy, Elsevier, vol. 178(C).
    5. Tapia, Rodrigo J. & de Jong, Gerard & Larranaga, Ana M. & Bettella Cybis, Helena B., 2020. "Application of MDCEV to infrastructure planning in regional freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 255-271.
    6. Jesús Muñuzuri & Pablo Cortés & Luis Onieva & José Guadix, 2013. "Simulating the effects of pedestrianisation on urban freight deliveries," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 54, pages 1-10.
    7. Pani, Agnivesh & Sahu, Prasanta K. & Tavasszy, Lóránt & Mishra, Sabya, 2023. "Freight activity-travel pattern generation (FAPG) as an enhancement of freight (trip) generation modelling: Methodology and case study," Transport Policy, Elsevier, vol. 144(C), pages 34-48.
    8. Noruzoliaee, Mohamadhossein & Zou, Bo & Zhou, Yan (Joann), 2021. "Truck platooning in the U.S. national road network: A system-level modeling approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    9. Lovelace, Robin & Ballas, Dimitris & Watson, Matt, 2014. "A spatial microsimulation approach for the analysis of commuter patterns: from individual to regional levels," Journal of Transport Geography, Elsevier, vol. 34(C), pages 282-296.
    10. Kalahasthi, Lokesh & Holguín-Veras, José & Yushimito, Wilfredo F., 2022. "A freight origin-destination synthesis model with mode choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    11. Balster, Andreas & Friedrich, Hanno, 2019. "Dynamic freight flow modelling for risk evaluation in food supply," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 121(C), pages 4-22.
    12. Takanori Sakai & B. K. Bhavathrathan & André Alho & Tetsuro Hyodo & Moshe Ben-Akiva, 2020. "Commodity flow estimation for a metropolitan scale freight modeling system: supplier selection considering distribution channel using an error component logit mixture model," Transportation, Springer, vol. 47(2), pages 997-1025, April.
    13. Yanni Huang & Taha Hossein Rashidi & Lauren Gardner, 2018. "Modelling the global maritime container network," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(3), pages 400-420, September.
    14. Dalla Chiara, Giacomo & Goodchild, Anne, 2020. "Do commercial vehicles cruise for parking? Empirical evidence from Seattle," Transport Policy, Elsevier, vol. 97(C), pages 26-36.
    15. Gonzalez-Calderon, Carlos A. & Holguín-Veras, José & Amaya, Johanna & Sánchez-Díaz, Iván & Sarmiento, Iván, 2021. "Generalized noortman and van es’ empty trips model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 260-268.
    16. Tirumalachetty, Sumala & Kockelman, Kara M. & Nichols, Brice G., 2013. "Forecasting greenhouse gas emissions from urban regions: microsimulation of land use and transport patterns in Austin, Texas," Journal of Transport Geography, Elsevier, vol. 33(C), pages 220-229.
    17. Davis, Haggai & Landes, Hector & Namdarpour, Farnoosh & Yang, Hai & Y. J. Chow, Joseph & Ozbay, Kaan, 2024. "Aggregate urban truck tour synthesis from public data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 185(C).
    18. Shobhit Saxena & Abdul Rawoof Pinjari & Chandra R. Bhat & Aupal Mondal, 2024. "A flexible multiple discrete–continuous probit (MDCP) model: application to analysis of expenditure patterns of domestic tourists in India," Transportation, Springer, vol. 51(4), pages 1299-1326, August.
    19. Siripirote, Treerapot & Sumalee, Agachai & Ho, H.W., 2020. "Statistical estimation of freight activity analytics from Global Positioning System data of trucks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    20. Friesz, Terry L., 2024. "Dynamic spatial price equilibrium, dynamic user equilibrium, and freight transportation in continuous time: A differential variational inequality perspective," Transportation Research Part B: Methodological, Elsevier, vol. 190(C).

    More about this item

    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:bla:bstrat:v:34:y:2025:i:3:p:2897-2916. 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: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1099-0836 .

    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.