Integrating 5PL Frameworks with Drone-Based Last-Mile Delivery: A Model for Future-Ready Logistics

Authors

  • Tejinder Singh Lakhwani *

    School of Management & Entrepreneurship, Institute of Technology Jodhpur, Karwar, District Jodhpur, Jodhpur, Rajasthan 342030, India

DOI:

https://doi.org/10.55121/tdr.v3i1.449

Keywords:

Fifth-Party Logistics (5PL), Drone-Based Last-Mile Delivery, AI-Enabled Logistics Optimization, IoT in Supply Chains, Blockchain-Orchestrated Logistics, Sustainable Logistics Frameworks

Abstract

The rapid evolution of logistics service providers from 1PL to 5PL has underscored the growing need for intelligent, data-driven orchestration across the supply chain. Simultaneously, drone-based delivery has emerged as a promising solution to last-mile challenges, particularly in urban congestion zones and infrastructure-deficient rural areas. However, current deployments of drone logistics remain largely siloed and unintegrated with broader digital logistics platforms. This paper proposes a novel conceptual framework that embeds drone-based last-mile delivery within the orchestration architecture of fifth-party logistics (5PL) systems. Leveraging a multi-agent digital twin model, the study integrates technologies such as IoT for real-time tracking, AI-based metaheuristics (ALNS, PSO, NSGA-II) for route and hub optimization, and blockchain for SLA compliance. A simulation case based on India’s rural healthcare supply chain and ONDC clusters demonstrates substantial improvements in delivery time (↓65%), operational cost (↓40%), and carbon footprint (↓90%) over conventional 4PL systems. Sensitivity analyses under weather fluctuations, demand surges, and battery degradation validate the model’s resilience and adaptability. The findings position 5PLs as future-ready orchestrators of autonomous delivery systems and offer actionable insights for policymakers, supply chain managers, and technology developers toward building sustainable and scalable drone logistics ecosystems.The framework emphasizes
interoperability and modular deployment, ensuring ease of integration with evolving logistics platforms.

References

[1] de Souza, N.L.S., Frazzon, E.M., de Oliveira, B.R., 2024. Evolution of Logistics Service Providers: A Study of 5 PL. In: Gonçalves dos Reis, J.C., Mendonça Freires, F.G., Vieira Junior, M., et al. (eds.). Industrial Engineering and Operations Management. Springer Nature: Cham, Switzerland. pp. 99–110. DOI: https://doi.org/10.1007/978-3-031-80785-5_8

[2] Nicoletti, B., Appolloni, A., 2025. Digital transformation in ecosystems: integrated operations model and its application to fifth-party logistics operators. Journal of Global Operations and Strategic Sourcing. 18(1), 91–122.

[3] Choi, T.M., Siqin, T., 2022. Blockchain in logistics and production from Blockchain 1.0 to Blockchain 5.0: An intra-inter-organizational framework. Transportation Research Part E: Logistics and Transportation Review. 160, 102653. DOI: https://doi.org/10.1016/j.tre.2022.102653

[4] Singh, R.K., Modgil, S., Shore, A., 2024. Building artificial intelligence enabled resilient supply chain: a multi-method approach. Journal of Enterprise Information Management. 37(2), 414–436.

[5] Xu, X., He, Y., 2024. Blockchain application in modern logistics information sharing: A review and case study analysis. Production Planning and Control. 35(9), 886–900.

[6] Engesser, V., Rombaut, E., Vanhaverbeke, L., et al., 2023. Autonomous delivery solutions for last-mile logistics operations: A literature review and research agenda. Sustainability. 15(3), 2774. DOI: https://doi.org/10.3390/su15032774

[7] Giuffrida, N., Fajardo-Calderin, J., Masegosa, A.D., et al., 2022. Optimization and machine learning applied to last-mile logistics: A review. Sustainability. 14(9), 5329. DOI: https://doi.org/10.3390/su14095329

[8] Bayliss, C., Bektaş, T., Tjon-Soei-Len, V., et al., 2023. Designing a multi-modal and variable-echelon delivery system for last-mile logistics. European Journal of Operational Research. 307(2), 645–662.

[9] Russo, F., Comi, A., 2021. Sustainable urban delivery: The learning process of path costs enhanced by information and communication technologies. Sustainability. 13(23), 13103. DOI: https://doi.org/10.3390/su132313103

[10] Niglio, F., Comite, P., Cannas, A., et al., 2022. Preliminary clinical validation of a drone-based delivery system in urban scenarios using a smart capsule for blood. Drones. 6(8), 195. DOI: https://doi.org/10.3390/drones6080195

[11] Raivi, A.M., Huda, S.A., Alam, M.M., et al., 2023. Drone routing for drone-based delivery systems: A review of trajectory planning, charging, and security. Sensors. 23(3), 1463. DOI: https://doi.org/10.3390/s23031463

[12] Chen, H., Hu, Z., Solak, S., 2021. Improved delivery policies for future drone-based delivery systems. European Journal of Operational Research. 294(3), 1181–1201.

[13] Zang, X., Jiang, L., Liang, C., et al., 2022. Optimization approaches for the urban delivery problem with trucks and drones. Swarm and Evolutionary Computation. 75, 101147. DOI: https://doi.org/10.1016/j.swevo.2022.101147

[14] Lagorio, A., Zenezini, G., Mangano, G., Pinto, R., 2022. A systematic literature review of innovative technologies adopted in logistics management. International Journal of Logistics Research and Applications. 25(7), 1043–1066.

[15] Mourad, A., Puchinger, J., Van Woensel, T., 2021. Integrating autonomous delivery service into a passenger transportation system. International Journal of Production Research. 59(7), 2116–2139.

[16] Srinivas, S., Ramachandiran, S., Rajendran, S., 2022. Autonomous robot-driven deliveries: A review of recent developments and future directions. Transportation Research Part E: Logistics and Transportation Review. 165, 102834. DOI: https://doi.org/10.1016/j.tre.2022.102834

[17] Sajid, M.J., Tanveer, M., 2025. Revisiting the Spectrum of the Logistics Service Providers for a Circular Logistics Service: From 1PL to a Circular Logistics Service Provider. In: Khan, S.A.R. (ed.). Innovation and Sustainability Through Circular Economy in Businesses. IGI Global Scientific Publishing: Hershey, PA, USA. pp. 237–252.

[18] Cherchata, A., Popovychenko, I., Andrusiv, U., et al., 2022. Innovations in logistics management as a direction for improving the logistics activities of enterprises. Management Systems in Production Engineering. 30(1), 9–17. DOI: https://doi.org/10.2478/mspe-2022-0026

[19] Frederico, G.F., 2021. From supply chain 4.0 to supply chain 5.0: Findings from a systematic literature review and research directions. Logistics. 5(3), 49. DOI: https://doi.org/10.3390/logistics5030049

[20] Samadhiya, A., Agrawal, R., Kumar, A., et al., 2023. Regenerating the logistics industry through the Physical Internet Paradigm: A systematic literature review and future research orchestration. Computers and Industrial Engineering. 178, 109150. DOI: https://doi.org/10.1016/j.cie.2023.109150

[21] Li, L., Liu, Y., Jin, Y., et al., 2024. Generative AI-enabled supply chain management: The critical role of coordination and dynamism. International Journal of Production Economics. 277, 109388. DOI: https://doi.org/10.1016/j.ijpe.2024.109388

[22] Ding, Y., Jin, M., Li, S., Feng, D., 2021. Smart logistics based on the Internet of Things technology: an overview. International Journal of Logistics Research and Applications. 24(4), 323–345.

[23] Golpîra, H., Khan, S.A.R., Safaeipour, S., 2021. A review of logistics internet-of-things: Current trends and scope for future research. Journal of Industrial Information Integration. 22, 100194.

[24] Ilin, I., Maydanova, S., Lepekhin, A., et al., 2021. Digital platforms for the logistics sector of the Russian Federation. In: Shaumburg, H., Korablev, V., Laszlo, U. (eds.). Technological Transformation: A New Role For Human, Machines And Management: TT-2020. Springer International Publishing: Cham, Switzerland. pp. 179–188.

[25] Ismail, M.M., Ahmed, Z., Abdel-Gawad, A.F., et al., 2024. Toward supply chain 5.0: An integrated multi-criteria decision-making models for sustainable and resilience enterprise. Decision Making: Applications in Management and Engineering. 7(1), 160–186.

[26] Ivanov, D., 2021. Digital supply chain management and technology to enhance resilience by building and using end-to-end visibility during the COVID-19 pandemic. IEEE Transactions on Engineering Management. 71, 10485–10495. DOI: https://doi.org/10.1109/TEM.2021.3095193

[27] Kundu, T., Sheu, J.B., Kuo, H.T., 2022. Emergency logistics management—Review and propositions for future research. Transportation Research Part E: Logistics and Transportation Review. 164, 102789. DOI: https://doi.org/10.1016/j.tre.2022.102789

[28] Li, X., Tupayachi, J., Sharmin, A., et al., 2023. Drone-aided delivery methods, challenge, and the future: A methodological review. Drones. 7(3), 191. DOI: https://doi.org/10.3390/drones7030191

[29] Mikl, J., Herold, D.M., Ćwiklicki, M., et al., 2021. The impact of digital logistics start-ups on incumbent firms: a business model perspective. The International Journal of Logistics Management. 32(4), 1461–1480.

[30] Tian, G., Lu, W., Zhang, X., et al., 2023. A survey of multi-criteria decision-making techniques for green logistics and low-carbon transportation systems. Environmental Science and Pollution Research. 30(20), 57279–57301. DOI: https://doi.org/10.1007/s11356-023-26577-2

[31] Deng, X., Guan, M., Ma, Y., et al., 2022. Vehicle-assisted uav delivery scheme considering energy consumption for instant delivery. Sensors. 22(5), 2045. DOI: https://doi.org/10.3390/s22052045

[32] Agyabeng-Mensah, Y., Tang, L., 2021. The relationship among green human capital, green logistics practices, green competitiveness, social performance and financial performance. Journal of Manufacturing Technology Management. 32(7), 1377–1398. DOI: https://doi.org/10.1108/JMTM-11-2020-0441

[33] Shee, H.K., Miah, S.J., De Vass, T., 2021. Impact of smart logistics on smart city sustainable performance: an empirical investigation. The International Journal of Logistics Management. 32(3), 821–845.

[34] Beckers, J., Cardenas, I., Le Pira, M., et al., 2023. Exploring Logistics-as-a-Service to integrate the consumer into urban freight. Research in Transportation Economics. 101, 101354. DOI: https://doi.org/10.1016/j.retrec.2023.101354

[35] Archetti, C., Bertazzi, L., 2021. Recent challenges in Routing and Inventory Routing: E‐commerce and last‐mile delivery. Networks. 77(2), 255–268.

[36] Froio, P.J., Bezerra, B.S., 2021. Environmental sustainability initiatives adopted by logistics service providers in a developing country–an overview in the Brazilian context. Journal of Cleaner Production. 304, 126989. DOI: https://doi.org/10.1016/j.jclepro.2021.126989

[37] Pourrahmani, E., Jaller, M., 2021. Crowdshipping in last mile deliveries: Operational challenges and research opportunities. Socio-Economic Planning Sciences. 78, 101063. DOI: https://doi.org/10.1016/j.seps.2021.101063

[38] Yang, Y., Zhang, J., Liu, X., Ma, J., 2022. A scalable and auditable secure data sharing scheme with traceability for fog-based smart logistics. IEEE Internet of Things Journal. 10(10), 8603–8617.

[39] Ayyildiz, E., Erdogan, M., 2024. Addressing the challenges of using autonomous robots for last-mile delivery. Computers and Industrial Engineering. 190, 110096. DOI: https://doi.org/10.1016/j.cie.2024.110096

[40] Azzaoui, A.E., Kim, T.W., Pan, Y., et al., 2021. A quantum approximate optimization algorithm based on blockchain heuristic approach for scalable and secure smart logistics systems. Human-centric Computing and Information Sciences. 11(46), 1–12. DOI: https://doi.org/10.22967/HCIS.2021.11.046

[41] Barykin, S.E., Smirnova, E.A., Chzhao, D., et al., 2021. Digital echelons and interfaces within value chains: end-to-end marketing and logistics integration. Sustainability. 13(24), 13929. DOI: https://doi.org/10.3390/su132413929

[42] Bono, A., D’Alfonso, L., Fedele, G., et al., 2022. Path planning and control of a UAV fleet in bridge management systems. Remote Sensing. 14(8), 1858. DOI: https://doi.org/10.3390/rs14081858

[43] Ahmed, R.R., Zhang, X., 2021. Multi-stage network-based two-type cost minimization for the reverse logistics management of inert construction waste. Waste Management. 120, 805–819.

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