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Last Word in Last-Mile Logistics: A Novel Hybrid Multi-Criteria Decision-Making Model for Ranking Industry 4.0 Technologies

Author

Listed:
  • Miloš Veljović

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

  • 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
    Department of Economic Sciences, University of Salento, 73100 Lecce, Italy)

Abstract

The complexity, increasing flow number and volumes, and challenges of last-mile logistics (LML) motivate or compel companies, authorities, and the entire community to think about ways to increase efficiency, reliability, and profits, reduce costs, reduce negative environmental impacts, etc. These objectives can be met by applying Industry 4.0 (I4.0) technologies, but the key question is which one. To solve this task, this paper used an innovative method that combines the fuzzy analytic network process (fuzzy ANP) and the fuzzy axial-distance-based aggregated measurement (fuzzy ADAM) method. The first was used for determining criteria weights and the second for selecting the best variant. The best solution is e/m-marketplaces, followed by cloud-computing-supported management and control systems and blockchain. These results indicate that widely adopted and implemented technologies are suitable for last-mile logistics. Newer technologies already producing significant results have serious potential for further development in this area. The main novelties and contributions of this paper are the definition of a new methodology based on multi-criteria decision-making (MCDM) methods, as well as its application for ranking I4.0 technologies for LML.

Suggested Citation

  • Miloš Veljović & Snežana Tadić & Mladen Krstić, 2024. "Last Word in Last-Mile Logistics: A Novel Hybrid Multi-Criteria Decision-Making Model for Ranking Industry 4.0 Technologies," Mathematics, MDPI, vol. 12(13), pages 1-30, June.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:13:p:2010-:d:1424754
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    References listed on IDEAS

    as
    1. Valeska Engesser & Evy Rombaut & Lieselot Vanhaverbeke & Philippe Lebeau, 2023. "Autonomous Delivery Solutions for Last-Mile Logistics Operations: A Literature Review and Research Agenda," Sustainability, MDPI, vol. 15(3), pages 1-17, February.
    2. 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.
    3. Mladen Krstić & Giulio Paolo Agnusdei & Snežana Tadić & Milovan Kovač & Pier Paolo Miglietta, 2023. "A Novel Axial-Distance-Based Aggregated Measurement (ADAM) Method for the Evaluation of Agri-Food Circular-Economy-Based Business Models," Mathematics, MDPI, vol. 11(6), pages 1-27, March.
    4. Jharkharia, Sanjay & Shankar, Ravi, 2007. "Selection of logistics service provider: An analytic network process (ANP) approach," Omega, Elsevier, vol. 35(3), pages 274-289, June.
    5. Agatz, Niels A.H. & Fleischmann, Moritz & van Nunen, Jo A.E.E., 2008. "E-fulfillment and multi-channel distribution - A review," European Journal of Operational Research, Elsevier, vol. 187(2), pages 339-356, June.
    6. Chopra, Sunil, 2003. "Designing the distribution network in a supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(2), pages 123-140, March.
    7. 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.
    8. Saaty, Thomas L. & Takizawa, Masahiro, 1986. "Dependence and independence: From linear hierarchies to nonlinear networks," European Journal of Operational Research, Elsevier, vol. 26(2), pages 229-237, August.
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