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Uncovering interrelationships between barriers to unmanned aerial vehicles in humanitarian logistics

Author

Listed:
  • Aditya Kamat

    (Maulana Azad National Institute of Technology)

  • Saket Shanker

    (Maulana Azad National Institute of Technology)

  • Akhilesh Barve

    (Maulana Azad National Institute of Technology)

  • Kamalakanta Muduli

    (Papua New Guinea University of Technology
    CV Raman Global University)

  • Sachin Kumar Mangla

    (University of Plymouth)

  • Sunil Luthra

    (Ch. Ranbir Singh State Institute of Engineering & Technology)

Abstract

Recent disasters, such as the ongoing COVID-19 pandemic, have sparked an interest in new applications for unmanned aerial vehicles (UAVs) in humanitarian aid. Nevertheless, there are still many divisive changes that need to be made in order to implement UAVs into a country’s humanitarian sector successfully. Hence, this paper aims to analyze the various barriers hindering the implementation of UAVs in humanitarian logistics for both developed and developing nations. To accomplish this, the study is presented in three steps. First, previous literature and opinions from experts are analyzed to illuminate particular factors that hinder UAV implementation. Next, we propose an interval-valued intuitionistic fuzzy set (IVIFS) based graph theory and matrix approach (GTMA) to calculate a drone implementation hindrance index (DIHI). The GTMA method used in this paper utilizes the PERMAN algorithm to calculate the permanent function. Finally, the DIHI values are plotted and analyzed to compare the readiness of drone implementation between developed and developing economies. A sensitivity analysis is then performed to provide validity to the results obtained. The study has revealed that both types of countries must first improve their inadequate government regulations regarding humanitarian UAVs. Developing countries must also focus on enhancing the technological awareness of their population. The results of this study can be used by policymakers and practitioners to smoothly implement UAVs in their country's humanitarian sector. The general index defined in this paper can also be calculated for specific countries using the steps mentioned in the manuscript.

Suggested Citation

  • Aditya Kamat & Saket Shanker & Akhilesh Barve & Kamalakanta Muduli & Sachin Kumar Mangla & Sunil Luthra, 2022. "Uncovering interrelationships between barriers to unmanned aerial vehicles in humanitarian logistics," Operations Management Research, Springer, vol. 15(3), pages 1134-1160, December.
    • Handle: RePEc:spr:opmare:v:15:y:2022:i:3:d:10.1007_s12063-021-00235-7
    DOI: 10.1007/s12063-021-00235-7
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    1. Ruth Banomyong & Paitoon Varadejsatitwong & Richard Oloruntoba, 2019. "A systematic review of humanitarian operations, humanitarian logistics and humanitarian supply chain performance literature 2005 to 2016," Annals of Operations Research, Springer, vol. 283(1), pages 71-86, December.
    2. Wagner, Stephan M. & Neshat, Nikrouz, 2010. "Assessing the vulnerability of supply chains using graph theory," International Journal of Production Economics, Elsevier, vol. 126(1), pages 121-129, July.
    3. Aydin, Burchan, 2019. "Public acceptance of drones: Knowledge, attitudes, and practice," Technology in Society, Elsevier, vol. 59(C).
    4. Casiano Flores, Cesar & Tan, Evrim & Crompvoets, Joep, 2021. "Governance assessment of UAV implementation in Kenyan land administration system," Technology in Society, Elsevier, vol. 66(C).
    5. Günay Uzun & Metin Dağdeviren & Mehmet Kabak, 2016. "Determining the Distribution of Coast Guard Vessels," Interfaces, INFORMS, vol. 46(4), pages 297-314, August.
    6. Wen Jun Tan & Allan N. Zhang & Wentong Cai, 2019. "A graph-based model to measure structural redundancy for supply chain resilience," International Journal of Production Research, Taylor & Francis Journals, vol. 57(20), pages 6385-6404, October.
    7. Mahmoud Golabi & Seyed Mahdi Shavarani & Gokhan Izbirak, 2017. "An edge-based stochastic facility location problem in UAV-supported humanitarian relief logistics: a case study of Tehran earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(3), pages 1545-1565, July.
    8. Milan Ranđelović & Jelena Stanković & Kristijan Kuk & Gordana Savić & Dragan Ranđelović, 2018. "An Approach to Determining the Importance of Model Criteria in Certifying a City as Business-Friendly," Interfaces, INFORMS, vol. 48(2), pages 156-165, April.
    9. Hossein Abdollahnejadbarough & Kalyan S Mupparaju & Sagar Shah & Colin P. Golding & Abelardo C. Leites & Timothy D. Popp & Eric Shroyer & Yanai S. Golany & Anne G. Robinson & Vedat Akgun, 2020. "Verizon Uses Advanced Analytics to Rationalize Its Tail Spend Suppliers," Interfaces, INFORMS, vol. 50(3), pages 197-211, May.
    10. Si Jung Kim & Yunhwan Jeong & Sujin Park & Kihyun Ryu & Gyuhwan Oh, 2018. "A Survey of Drone use for Entertainment and AVR (Augmented and Virtual Reality)," Progress in IS, in: Timothy Jung & M. Claudia tom Dieck (ed.), Augmented Reality and Virtual Reality, pages 339-352, Springer.
    11. Doole, Malik & Ellerbroek, Joost & Hoekstra, Jacco, 2020. "Estimation of traffic density from drone-based delivery in very low level urban airspace," Journal of Air Transport Management, Elsevier, vol. 88(C).
    12. Muhammad Azmat & Sebastian Kummer, 2020. "Potential applications of unmanned ground and aerial vehicles to mitigate challenges of transport and logistics-related critical success factors in the humanitarian supply chain," Asian Journal of Sustainability and Social Responsibility, Springer, vol. 5(1), pages 1-22, December.
    13. Jeong, Ho Young & Yu, David J. & Min, Byung-Cheol & Lee, Seokcheon, 2020. "The humanitarian flying warehouse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    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. Rao, Bharat & Gopi, Ashwin Goutham & Maione, Romana, 2016. "The societal impact of commercial drones," Technology in Society, Elsevier, vol. 45(C), pages 83-90.
    16. Chowdhury, Sudipta & Emelogu, Adindu & Marufuzzaman, Mohammad & Nurre, Sarah G. & Bian, Linkan, 2017. "Drones for disaster response and relief operations: A continuous approximation model," International Journal of Production Economics, Elsevier, vol. 188(C), pages 167-184.
    17. Ho, William & Ma, Xin, 2018. "The state-of-the-art integrations and applications of the analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 267(2), pages 399-414.
    18. Chiang, Wen-Chyuan & Li, Yuyu & Shang, Jennifer & Urban, Timothy L., 2019. "Impact of drone delivery on sustainability and cost: Realizing the UAV potential through vehicle routing optimization," Applied Energy, Elsevier, vol. 242(C), pages 1164-1175.
    19. Reece A. Clothier & Dominique A. Greer & Duncan G. Greer & Amisha M. Mehta, 2015. "Risk Perception and the Public Acceptance of Drones," Risk Analysis, John Wiley & Sons, vol. 35(6), pages 1167-1183, June.
    20. Xinyi Zhou & Yong Hu & Yong Deng & Felix T. S. Chan & Alessio Ishizaka, 2018. "A DEMATEL-based completion method for incomplete pairwise comparison matrix in AHP," Annals of Operations Research, Springer, vol. 271(2), pages 1045-1066, December.
    21. Yaohan Shen & Xianhao Xu & Bipan Zou & Hongwei Wang, 2021. "Operating policies in multi-warehouse drone delivery systems," International Journal of Production Research, Taylor & Francis Journals, vol. 59(7), pages 2140-2156, April.
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