Drone Technology in Transportation Management: A Systematic Review and Framework for Future Research

Yıl 2023, , 251 - 261, 25.07.2023

Muhammed Turgut , Bilal Şeker

https://doi.org/10.30518/jav.1277694

Cited By: 1

Öz

This study examines the current state of the drone technology literature in detail, both academically and industrially. It describes the advantages and disadvantages of drones in the use of logistics activities, the methods used in the studies and the gaps in the literature. In addition, this study aims to reveal the academic efforts about drone-based transportation systems that will have a say in the future and which areas require effort in the future. In this article, a systematic literature review (SLR) about the use of drones in the transportation industry has been carried out. In total, 56 articles published in Elsevier's Scopus, Thomson Reuter's Web of Science, IEEE Xplore and ScienceDirect (Elsevier) databases were examined in detail. The findings show that the use of drones in transportation activities is an effective method. However, the fact that it is a technology that has just been integrated into business processes reveals that there are aspects that need to be developed. Especially in the last ten years, they found that businesses have benefited from drone technology in their transportation activities that increased their last mile delivery speed, efficiency, accessibility and customer satisfaction.

Anahtar Kelimeler

Drone in Delivery, Drone in Logistics, Drone in Transportation, Drone Technology

Kaynakça

• Benarbia, T., & Kyamakya, K. (2021). A literature review of drone-based package delivery logistics systems and their implementation feasibility. Sustainability, 14(1), 360.
• Bonsor, K. (2018). How Maglev trains work. Retrieved from, https://science.howstuffworks.com/transport/engines-equipment/maglev-train.html.
• Canetta, L., Mattei, G., & Guanziroli, A. (2017, June). Multi criteria analysis applied on value chain definition in unmanned aerial vehicle (UAV) sector. In 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 1096-1103). IEEE.
• 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.
• Chen, J., Wang, W., Zhou, Y., Ahmed, S. H., & Wei, W. (2021). Exploiting 5G and blockchain for medical applications of drones. IEEE Network, 35(1), 30-36.
• Chen, X., Ulmer, M. W., & Thomas, B. W. (2019). Deep Q-learning for same-day delivery with a heterogeneous fleet of vehicles and drones. arXiv preprint arXiv:1910.11901.
• Cook, D.J., Greengold, N.L., Ellrodt, A.G., & Weingarten, S.R. (1997), “The relation between systematic reviews and practice guidelines”, Annals of Internal Medicine, Vol. 127 No. 3, pp. 210‐6
• Cvitanić, D. (2020). Drone applications in transportation. In 2020 5th International Conference on Smart and Sustainable Technologies (SpliTech) (pp. 1-4). IEEE.
• Das, D. N., Sewani, R., Wang, J., & Tiwari, M. K. (2020). Synchronized truck and drone routing in package delivery logistics. IEEE Transactions on Intelligent Transportation Systems, 22(9), 5772-5782.
• Denyer, D., & Tranfield, D. (2009), “Producing a systematic review”, in Buchanan, D. and Bryman, A. (Eds), The Sage Handbook of Organizational Research Methods, Sage Publications, London, pp. 671‐89, Ch. 39.
• Dorling, K., Heinrichs, J., Messier, G. G. & Magierowski, S. (2016). Vehicle routing problems for drone delivery. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47(1), 70-85.
• Erceg, A., Erceg, B. Č., & Vasilj, A. (2017). Unmanned aircraft systems in logistics–legal regulation and worldwide examples toward use in Croatia. Business Logistics in Modern Management.
• Fang, Z., & Hong-Hai, Z. (2020, September). A Method for “Last mile” Distribution Demand for Drones. In 2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE) (pp. 561-564). IEEE.
• Foth, J. (2017). We haven’t considered the true cost of drone delivery medical services in Africa. URL https://qz.com/africa/1090693/zipline-drones-in-africa-like-rwanda-and-tanzania-have-an-opportunity- cost/.
• Garg, P. K. (2021). Unmanned aerial vehicles: An introduction. Mercury Learning and Information.
• Ghelichi, Z., Gentili, M., & Mirchandani, P. B. (2022). Drone logistics for uncertain demand of disaster-impacted populations. Transportation research part C: emerging technologies, 141, 103735.
• Gligor, D. M., & Holcomb, M. C. (2012). Understanding the role of logistics capabilities in achieving supply chain agility: a systematic literature review. Supply Chain Management: An International Journal.
• Gonzalez-R, P. L., Canca, D., Andrade-Pineda, J. L., Calle, M., & Leon-Blanco, J. M. (2020). Truck-drone team logistics: A heuristic approach to multi-drop route planning. Transportation Research Part C: Emerging Technologies, 114, 657-680.
• He, Z. (2020). The challenges in sustainability of urban freight network design and distribution innovations: a systematic literature review. International Journal of Physical Distribution & Logistics Management, 50(6), 601-640.
• Hua, H. Y., & Zhang, Z. (2019). Application of artificial intelligence technology in short-range logistics drones. In 2019 8th International Symposium on Next Generation Electronics (ISNE) (pp. 1-4). IEEE.
• Iranmanesh, S., Raad, R., Raheel, M. S., Tubbal, F., & Jan, T. (2019). Novel DTN mobility-driven routing in autonomous drone logistics networks. IEEE access, 8, 13661-13673.
• Johannessen, K. A., Comtet, H., & Fosse, E. (2021). A Drone Logistic Model for Transporting the Complete Analytic Volume of a Large-Scale University Laboratory. International Journal of Environmental Research and Public Health, 18(9), 4580.
• Khan, K.S., Kunz, R., Kleijnen, J. & Antes, G. (2003), “Five steps to conducting a systematic review”, Journal of the Royal Society of Medicine, Vol. 96 No. 3, pp. 118-121.
• Koshta, N., Devi, Y., & Chauhan, C. (2022). Evaluating Barriers to the Adoption of Delivery Drones in Rural Healthcare Supply Chains: Preparing the Healthcare System for the Future. IEEE Transactions on Engineering Management.
• Kuru, K., Ansell, D., Khan, W., & Yetgin, H. (2019). Analysis and optimization of unmanned aerial vehicle swarms in logistics: An intelligent delivery platform. Ieee Access, 7, 15804-15831.
• Lai, M. C., Liu, D., & Tsay, W. D. (2020). Functional deployment of drone logistics. In 2020 IEEE 2nd Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS) (pp. 1-4). IEEE.
• Leon-Blanco, J. M., Gonzalez-R, P. L., Andrade-Pineda, J. L., Canca, D., & Calle, M. (2022). A multi-agent approach to the truck multi-drone routing problem. Expert Systems with Applications, 195, 116604.
• Liu, J., Guan, Z., & Xie, X. (2018). Truck and drone in tandem route scheduling under sparse demand distribution. In 2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS) (pp. 1- 6). IEEE.
• Mahroof, K., Omar, A., Rana, N. P., Sivarajah, U., & Weerakkody, V. (2021). Drone as a Service (DaaS) in promoting cleaner agricultural production and Circular Economy for ethical Sustainable Supply Chain development. Journal of Cleaner Production, 287, 125522.
• Mangiaracina, R., Perego, A., Seghezzi, A., & Tumino, A. (2019). Innovative solutions to increase last-mile delivery efficiency in B2C e-commerce: a literature review. International Journal of Physical Distribution & Logistics Management.
• Marintseva, K., Yun, G., & Vasilenko, I. (2021). Delivery of special cargoes using the unmanned aerial vehicles. In Research Anthology on Reliability and Safety in Aviation Systems, Spacecraft, and Air Transport (pp. 1564- 1587). IGI Global.
• Meincke, P., Asmer, L., Geike, L., & Wiarda, H. (2018). Concepts for cargo ground handling of unmanned cargo aircrafts and their influence on the supply chain. In 2018 8th International Conference on Logistics, Informatics and Service Sciences (LISS) (pp. 1-10). IEEE.
• Merkert, R., & Bushell, J. (2020). Managing the drone revolution: A systematic literature review into the current use of airborne drones and future strategic directions for their effective control. Journal of Air Transport Management, 89, 101929.
• Merkert, R., Bliemer, M. C., & Fayyaz, M. (2022). Consumer preferences for innovative and traditional last-mile parcel delivery. International Journal of Physical Distribution & Logistics Management.
• Moshref-Javadi, M., & Winkenbach, M. (2021). Applications and Research avenues for drone-based models in logistics: A classification and review. Expert Systems with Applications, 177, 114854.
• Moshref-Javadi, M., Hemmati, A., & Winkenbach, M. (2020). A truck and drones model for last-mile delivery: A mathematical model and heuristic approach. Applied Mathematical Modelling, 80, 290-318.
• Mualla, Y., Bai, W., Galland, S., & Nicolle, C. (2018). Comparison of agent-based simulation frameworks for unmanned aerial transportation applications. Procedia computer science, 130, 791-796.
• Nyaaba, A. A., & Ayamga, M. (2021). Intricacies of medical drones in healthcare delivery: Implications for Africa. Technology in Society, 66, 101624.
• Olivares, V., Córdova, F., & Durán, C. (2017). Transport logistics and simulation model for fleet of drones in a Mass Customization System. In 2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) (pp. 1-6). IEEE.
• Osakwe, C. N., Hudik, M., Říha, D., Stros, M., & Ramayah, T. (2022). Critical factors characterizing consumers’ intentions to use drones for last-mile delivery: Does delivery risk matter?. Journal of Retailing and Consumer Services, 65, 102865.
• Pan, J. S., Song, P. C., Chu, S. C., & Peng, Y. J. (2020). Improved compact cuckoo search algorithm applied to location of drone logistics hub. Mathematics, 8(3), 333.
• Patchou, M., Sliwa, B., & Wietfeld, C. (2019). Unmanned aerial vehicles in logistics: Efficiency gains and communication performance of hybrid combinations of ground and aerial vehicles. In 2019 IEEE Vehicular Networking Conference (VNC) (pp. 1-8). IEEE.
• Pinto, R., & Lagorio, A. (2022). Point-to-point drone-based delivery network design with intermediate charging stations. Transportation Research Part C: Emerging Technologies, 135, 103506.
• Precedence Research (2020). Drone Logistics and Transportation Market Size, Share, Growth Analysis. Retrieved from https://www.precedenceresearch. com/drone-logistics-and-transportation-market.
• Rabta, B., Wankmüller, C., & Reiner, G. (2018). A drone fleet model for last-mile distribution in disaster relief operations. International Journal of Disaster Risk Reduction, 28, 107-112.
• Raj, A., & Sah, B. (2019). Analyzing critical success factors for implementation of drones in the logistics sector using grey-DEMATEL based approach. Computers & Industrial Engineering, 138, 106118.
• Rejeb, A., Rejeb, K., Simske, S. J., & Treiblmaier, H. (2021). Drones for supply chain management and logistics: a review and research agenda. International Journal of Logistics Research and Applications, 1-24.
• Sah, B., Gupta, R., & Bani-Hani, D. (2021). Analysis of barriers to implement drone logistics. International Journal of Logistics Research and Applications, 24(6), 531-550.
• Sarder, M. D. (2020). Logistics transportation systems. Elsevier.
• Shavarani, S. M., M. G. Nejad, F. Rismanchian, & G. Izbirak. (2018). “Application of Hierarchical Facility Location Problem for Optimization of a Drone Delivery System: A Case Study of Amazon Prime Air in the City of San Francisco.” The International Journal of Advanced Manufacturing Technology 95 (9–12): 3141–3153.
• Smith, A., Dickinson, J. E., Marsden, G., Cherrett, T., Oakey, A., & Grote, M. (2022). Public acceptance of the use of drones for logistics: The state of play and moving towards more informed debate. Technology in Society, 68, 101883.
• Statista (2019). Commercial Drones are Taking Off. Retrieved from https://www.statista.com/chart/17201/commecial-drones-projected-growth/
• Thiels, C. A., Aho, J. M., Zietlow, S. P., & Jenkins, D. H. (2015). Use of unmanned aerial vehicles for medical product transport. Air medical journal, 34(2), 104-108.
• Triche, R. M., Greve, A. E., & Dubin, S. J. (2020). UAVs and their role in the health supply chain: A case study from Malawi. In 2020 International Conference on Unmanned Aircraft Systems (ICUAS) (pp. 1241-1248). IEEE.
• Troudi, A., Addouche, S. A., Dellagi, S., & El Mhamedi, A. (2017). Post-production analysis approach for drone delivery fleet. In 2017 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI) (pp. 150-155). IEEE.
• Troudi, A., Addouche, S. A., Dellagi, S., & Mhamedi, A. E. (2018). Sizing of the drone delivery fleet considering energy autonomy. Sustainability, 10(9), 3344.
• Tümenbatur, A. & Tanyaş, M. (2021). Havalimani Kenti Kavrami: Türkiye’deki Bazi Havalimanlarinin Karşilaştirilmasi. Beykoz Akademi Dergisi , 9 (1) , 108-119.
• Varigonda, V. K., Borole, A., Hudge, A., Yadav, C., & Annamalai, V. K. (2021). Feasibility of Multi-Configuration Unmanned Aerial Vehicle for Last Mile Delivery of Medical Supplies. In 2021 Asian Conference on Innovation in Technology (ASIANCON) (pp. 1-7). IEEE.
• Yoo, W., Yu, E., & Jung, J. (2018). Drone delivery: Factors affecting the public’s attitude and intention to adopt. Telematics and Informatics, 35(6), 1687-1700.
• Zhu, X., Pasch, T. J., & Bergstrom, A. (2020). Understanding the structure of risk belief systems concerning drone delivery: A network analysis. Technology in Society, 62, 101262.