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Title: | Evaluating Barriers to the Adoption of Delivery Drones in Rural Healthcare Supply Chains: Preparing the Healthcare System for the Future |
Authors: | Koshta, Nitin Devi, Yashoda Chauhan, Chetna |
Keywords: | Drones Medical services Supply chains Electronic commerce Costs COVID-19 Vaccines |
Issue Date: | 10-Oct-2022 |
Publisher: | IEEE Transactions on Engineering Management |
Abstract: | Emerging technologies, such as delivery drones have enormous potential to revolutionize the rural healthcare supply chain (RHSC) and assist the countries in achieving sustainable development goal 3: good health and well-being. The advantages of delivery drones include faster delivery, high responsiveness, and a lack of dependence on road infrastructure. Given these advantages, prior literature on drone delivery has extensively explored their applicability in last-mile delivery from the e-commerce or retailer's perspective. However, their applicability in RHSC from an academic as well as practical perspective is still at a nascent stage. The present study fills this gap by examining the barriers inhibiting the adoption of delivery drones in RHSC using the Grey Decision-Making Trial and Evaluation Laboratory technique. The results suggest that “lack of government regulations” is the most critical barrier. The study findings indicate that seven barriers are causal, and six are the effect barriers. “Limited load carrying capacity,” “low flight range,” and “difficulty in flying in adverse weather conditions” are the most prominent cause barriers. Moreover, “lack of skilled manpower,” “limited accuracy of navigation system,” and “lack of leadership commitment” are the most prominent effect barriers. We also perform sensitivity analysis to prove the robustness of the study output. The study results provide an in-depth understanding to the decision-makers and policymakers to help pave the way for the successful adoption of delivery drones in RHSC. |
URI: | https://doi.org/10.1109/TEM.2022.3210121 http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/2060 |
ISSN: | 0018-9391 1558-0040 |
Appears in Collections: | Journal Articles |
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