IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i3p367-d1325031.html
   My bibliography  Save this article

Assessing Strategies to Overcome Barriers for Drone Usage in Last-Mile Logistics: A Novel Hybrid Fuzzy MCDM Model

Author

Listed:
  • Snežana Tadić

    (Logistics Department, Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11000 Belgrade, Serbia)

  • Mladen Krstić

    (Logistics Department, Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11000 Belgrade, Serbia)

  • Ljubica Radovanović

    (Logistics Department, Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11000 Belgrade, Serbia)

Abstract

Effective last-mile (LM) delivery is critical to the efficient functioning of supply chains. In addition to speed and the cost of delivery, environmental and social sustainability are increasingly important factors in last-mile logistics (LML), especially in urban areas. Sustainable solutions such as drones attract special attention from researchers due to their high potential. The future of drone logistics is uncertain due to many barriers. This study analyzes, evaluates and ranks barriers to identify those that most significantly hinder broader drone adoption in LML, and proposes and ranks strategies to overcome them. This type of issue requires the involvement of multiple stakeholders with conflicting goals and interests. Therefore, the study employs a novel hybrid multi-criteria decision-making (MCDM) model that combines fuzzy Delphi-based fuzzy factor relationship (Fuzzy D-FARE) and fuzzy comprehensive distance-based ranking (Fuzzy COBRA) methods. The results indicate that the main obstacle to drone implementation in LM is the lack of aviation regulations. The risks of unauthorized access, data misuse, privacy breaches, and data security represent significant challenges. They are followed by ambiguously defined or burdensome requirements for insurance and liability for drone owners. The main contributions of this study are the establishment of a novel hybrid model, identification and ranking of barriers for broader application of drones in LML, and strategies for overcoming them.

Suggested Citation

  • Snežana Tadić & Mladen Krstić & Ljubica Radovanović, 2024. "Assessing Strategies to Overcome Barriers for Drone Usage in Last-Mile Logistics: A Novel Hybrid Fuzzy MCDM Model," Mathematics, MDPI, vol. 12(3), pages 1-25, January.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:3:p:367-:d:1325031
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/3/367/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/3/367/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lindawati & Johan van Schagen & Mark Goh & Robert de Souza, 2014. "Collaboration in urban logistics: motivations and barriers," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 18(2), pages 278-290, July.
    2. Stacy A. Voccia & Ann Melissa Campbell & Barrett W. Thomas, 2019. "The Same-Day Delivery Problem for Online Purchases," Service Science, INFORMS, vol. 53(1), pages 167-184, February.
    3. John Olsson & Daniel Hellström & Henrik Pålsson, 2019. "Framework of Last Mile Logistics Research: A Systematic Review of the Literature," Sustainability, MDPI, vol. 11(24), pages 1-25, December.
    4. Amit Verma, 2018. "Electric vehicle routing problem with time windows, recharging stations and battery swapping stations," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(4), pages 415-451, December.
    5. Shanshan Zha & Yu Guo & Shaohua Huang & Shengbo Wang, 2020. "A Hybrid MCDM Method Using Combination Weight for the Selection of Facility Layout in the Manufacturing System: A Case Study," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-16, February.
    6. Emma Marris, 2013. "Drones in science: Fly, and bring me data," Nature, Nature, vol. 498(7453), pages 156-158, June.
    7. John Gunnar Carlsson & Siyuan Song, 2018. "Coordinated Logistics with a Truck and a Drone," Management Science, INFORMS, vol. 64(9), pages 4052-4069, September.
    8. Mladen Krstić & Snežana Tadić & Valerio Elia & Stefania Massari & Muhammad Umar Farooq, 2023. "Intermodal Terminal Subsystem Technology Selection Using Integrated Fuzzy MCDM Model," Sustainability, MDPI, vol. 15(4), pages 1-17, February.
    9. Michael Schneider & Andreas Stenger & Dominik Goeke, 2014. "The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations," Transportation Science, INFORMS, vol. 48(4), pages 500-520, November.
    10. Vakulenko, Yulia & Hellström, Daniel & Hjort, Klas, 2018. "What's in the parcel locker? Exploring customer value in e-commerce last mile delivery," Journal of Business Research, Elsevier, vol. 88(C), pages 421-427.
    11. Schneider, M. & Stenger, A. & Goeke, D., 2014. "The Electric Vehicle Routing Problem with Time Windows and Recharging Stations," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 62382, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    12. Cohen, Adam P & Shaheen, Susan A PhD & Farrar, Emily M, 2021. "Urban Air Mobility: History, Ecosystem, Market Potential, and Challenges," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8nh0s83q, Institute of Transportation Studies, UC Berkeley.
    13. Xuping Wang & Linmin Zhan & Junhu Ruan & Jun Zhang, 2014. "How to Choose “Last Mile” Delivery Modes for E-Fulfillment," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-11, June.
    14. Kwon, Heeyeul & Kim, Jieun & Park, Yongtae, 2017. "Applying LSA text mining technique in envisioning social impacts of emerging technologies: The case of drone technology," Technovation, Elsevier, vol. 60, pages 15-28.
    15. Cleophas, Catherine & Cottrill, Caitlin & Ehmke, Jan Fabian & Tierney, Kevin, 2019. "Collaborative urban transportation: Recent advances in theory and practice," European Journal of Operational Research, Elsevier, vol. 273(3), pages 801-816.
    16. 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.
    17. Mladen Krstić & Snežana Tadić & Milovan Kovač & Violeta Roso & Slobodan Zečević, 2021. "A Novel Hybrid MCDM Model for the Evaluation of Sustainable Last Mile Solutions," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-17, October.
    18. Niels Agatz & Paul Bouman & Marie Schmidt, 2018. "Optimization Approaches for the Traveling Salesman Problem with Drone," Transportation Science, INFORMS, vol. 52(4), pages 965-981, August.
    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. John Olsson & Daniel Hellström & Henrik Pålsson, 2019. "Framework of Last Mile Logistics Research: A Systematic Review of the Literature," Sustainability, MDPI, vol. 11(24), pages 1-25, December.
    2. Raeesi, Ramin & Zografos, Konstantinos G., 2020. "The electric vehicle routing problem with time windows and synchronised mobile battery swapping," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 101-129.
    3. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2021. "Green vehicle routing problem: A state-of-the-art review," International Journal of Production Economics, Elsevier, vol. 231(C).
    4. Buldeo Rai, Heleen & Verlinde, Sara & Macharis, Cathy, 2021. "Unlocking the failed delivery problem? Opportunities and challenges for smart locks from a consumer perspective," Research in Transportation Economics, Elsevier, vol. 87(C).
    5. Joonyup Eun & Byung Duk Song & Sangbok Lee & Dae-Eun Lim, 2019. "Mathematical Investigation on the Sustainability of UAV Logistics," Sustainability, MDPI, vol. 11(21), pages 1-15, October.
    6. Leandro do C. Martins & Rafael D. Tordecilla & Juliana Castaneda & Angel A. Juan & Javier Faulin, 2021. "Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation," Energies, MDPI, vol. 14(16), pages 1-30, August.
    7. Erfan Ghorbani & Mahdi Alinaghian & Gevork. B. Gharehpetian & Sajad Mohammadi & Guido Perboli, 2020. "A Survey on Environmentally Friendly Vehicle Routing Problem and a Proposal of Its Classification," Sustainability, MDPI, vol. 12(21), pages 1-71, October.
    8. Qiuping Ni & Yuanxiang Tang, 2023. "A Bibliometric Visualized Analysis and Classification of Vehicle Routing Problem Research," Sustainability, MDPI, vol. 15(9), pages 1-37, April.
    9. Mohammad Asghari & Seyed Mohammad Javad Mirzapour Al-E-Hashem, 2021. "Green vehicle routing problem: A state-of-the-art review," Post-Print hal-03182944, HAL.
    10. Csilla Bartucz & László Buics & Edit Süle, 2023. "Lack of Collaboration on the CEP Market and the Underlying Reasons—A Systematic Literature Review," Sustainability, MDPI, vol. 15(13), pages 1-22, June.
    11. Sören Lauenstein & Christoph Schank, 2022. "Design of a Sustainable Last Mile in Urban Logistics—A Systematic Literature Review," Sustainability, MDPI, vol. 14(9), pages 1-14, May.
    12. Nils Boysen & Stefan Fedtke & Stefan Schwerdfeger, 2021. "Last-mile delivery concepts: a survey from an operational research perspective," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 1-58, March.
    13. Wei Xu & Chenghao Zhang & Ming Cheng & Yucheng Huang, 2022. "Electric Vehicle Routing Problem with Simultaneous Pickup and Delivery: Mathematical Modeling and Adaptive Large Neighborhood Search Heuristic Method," Energies, MDPI, vol. 15(23), pages 1-25, December.
    14. Liu, Zeyu & Li, Xueping & Khojandi, Anahita, 2022. "The flying sidekick traveling salesman problem with stochastic travel time: A reinforcement learning approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    15. Milioti, Christina & Pramatari, Katerina & Kelepouri, Ioanna, 2020. "Modelling consumers’ acceptance for the click and collect service," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    16. Juan Guillermo Urzúa-Morales & Juan Pedro Sepulveda-Rojas & Miguel Alfaro & Guillermo Fuertes & Rodrigo Ternero & Manuel Vargas, 2020. "Logistic Modeling of the Last Mile: Case Study Santiago, Chile," Sustainability, MDPI, vol. 12(2), pages 1-18, January.
    17. Zhou, Yu & Meng, Qiang & Ong, Ghim Ping, 2022. "Electric Bus Charging Scheduling for a Single Public Transport Route Considering Nonlinear Charging Profile and Battery Degradation Effect," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 49-75.
    18. 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).
    19. Roel M. Post & Paul Buijs & Michiel A. J. uit het Broek & Jose A. Lopez Alvarez & Nick B. Szirbik & Iris F. A. Vis, 2018. "A solution approach for deriving alternative fuel station infrastructure requirements," Flexible Services and Manufacturing Journal, Springer, vol. 30(3), pages 592-607, September.
    20. Mommens, Koen & Buldeo Rai, Heleen & van Lier, Tom & Macharis, Cathy, 2021. "Delivery to homes or collection points? A sustainability analysis for urban, urbanised and rural areas in Belgium," Journal of Transport Geography, Elsevier, vol. 94(C).

    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:gam:jmathe:v:12:y:2024:i:3:p:367-:d:1325031. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.