Public acceptance of drone applications in a highly urbanized environment

Human societies are constantly affected by advancement in technologies. Could drone application be the next game changer? Building on the Knowledge, Attitude and Practice (KAP) model, we conducted a study to examine public perceptions of drone application in a South East Asian city state. While there are a number of common findings with past research, we were able to extend the understanding of drone application in urban areas with the following findings. First, using two knowledge tests, we were able to confirm that the majority of the public seems to have a good understanding of what a drone is. Second, acceptance levels towards drones did significantly differ depending on the context of use. Industrial areas had the highest acceptance level, followed by recreational areas and commercial areas while residential areas had the lowest acceptance level. Finally, different factors may be responsible for the varying levels of acceptance across the different contexts. We provided preliminary evidence that two factors – fears and concerns, and perceived potential benefits – affected the public acceptance levels differently depending on the contexts of drone applications. We concluded with implications for future research and policy makers. •This study examines public perceptions of drone application in a South East Asian city state. While there are some common findings with past research, we were able to extend our understanding of drone application in urban areas.•Using two knowledge tests, we were able to confirm that a majority of the Singaporean public seem to have a good understanding of what a drone is.•Acceptance levels towards drones significantly differed depending on the context of use. Industrial areas had the highest acceptance level, followed by recreational areas and business districts, and lastly, residential areas.•Finally, different factors, such as perceived potential benefits and fears and concerns towards drones, may be responsible for the varying levels of acceptance across the different contexts.