A decision support model for selecting unmanned aerial vehicle for medical supplies: context of COVID-19 pandemic

Abstract

PurposeIn recent times, due to rapid urbanization and the expansion of the E-commerce industry, drone delivery has become a point of interest for many researchers and industry practitioners. Several factors are directly or indirectly responsible for adopting drone delivery, such as customer expectations, delivery urgency and flexibility to name a few. As the traditional mode of delivery has some potential drawbacks to deliver medical supplies in both rural and urban settings, unmanned aerial vehicles can be considered as an alternative to overcome the difficulties. For this reason, drones are incorporated in the healthcare supply chain to transport lifesaving essential medicine or blood within a very short time. However, since there are numerous types of drones with varying characteristics such as flight distance, payload-carrying capacity, battery power, etc., selecting an optimal drone for a particular scenario becomes a major challenge for the decision-makers. To fill this void, a decision support model has been developed to select an optimal drone for two specific scenarios related to medical supplies delivery.Design/methodology/approachThe authors proposed a methodology that incorporates graph theory and matrix approach (GTMA) to select an optimal drone for two specific scenarios related to medical supplies delivery at (1) urban areas and (2) rural/remote areas based on a set of criteria and sub-criteria critical for successful drone implementation.FindingsThe findings of this study indicate that drones equipped with payload handling capacity and package handling flexibility get more preference in urban region scenarios. In contrast, drones with longer flight distances are prioritized most often for disaster case scenarios where the road communication system is either destroyed or inaccessible.Research limitations/implicationsThe methodology formulated in this paper has implications in both academic and industrial settings. This study addresses critical gaps in the existing literature by formulating a mathematical model to find the most suitable drone for a specific scenario based on its criteria and sub-criteria rather than considering a fleet of drones is always at one's disposal.Practical implicationsThis research will serve as a guideline for the practitioners to select the optimal drone in different scenarios related to medical supplies delivery.Social implicationsThe proposed methodology incorporates GTMA to assist decision-makers in order to appropriately choose a particular drone based on its characteristics crucial for that scenario.Originality/valueThis research will serve as a guideline for the practitioners to select the optimal drone in different scenarios related to medical supplies delivery.

Hospital Supply Chain Management: Cross-Disciplinarity Opportunities in the Post-Pandemic Era and Research Agenda

“…Another focus of the studies analyzed corresponds to macro logistical processes: 8% correspond to procurement, where studies on PPE forecasting (Best and Williams, 2021;Gonzatto et al, 2022), supplier selection (Pamucar et al, 2022), and analysis on public procurement during the pandemic (Harland et al, 2021). About 3% of the studies are related to storage, location of inventory (Rastegar et al, 2021), and PPE inventory tracking and control (Means et al, 2020), 12% are related to distribution, formulating scheduling models to optimize transportation of PPE, vaccines, and wastes (Ash et al, 2022;Bala et al, 2021;Göçmen, 2022;Goentzel et al, 2022;Gonzatto et al, 2022;Kargar et al, 2020;Tirkolaee et al, 2021); use of drones to deliver drugs (Banik et al, 2022;Koshta et al, 2021) and a study (2%) related to internal production logistics focusing on the implementation of process modularity at HSCM (Saïah et al, 2022).…”

Guest editorial: Bridging the research-practice gaps in supply chain management: lessons from COVID-19

“…Finally, we understand that the analytical-based articles have significantly contributed to advancing operations and the supply chain management field (Boyer and Swink, 2008) by solving problems. We accepted some relevant articles that may be useful for the practitioners based on analytical methods (see, Zhang et al , 2021; Paul et al , 2021; Dohale et al , 2021; Abdolazimi et al , 2021; Mariappan et al ., 2022; Banik et al , 2022; Yassine, 2022).…”

Possibilities of Using UAVs in Pre-Hospital Security for Medical Emergencies

“…It turned out that drones equipped with cargo handling capability and parcel handling flexibility are more preferred in scenarios with urban areas, while drones with longer flight distances are most often prioritized in disaster scenarios where the road communication system is destroyed or inaccessible. This analysis covered so-called critical gaps in the existing literature by formulating a mathematical model to find the most suitable drone for a specific scenario based on its criteria [ 69 ]. However, it is not just about UAVs.…”