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Drone technology for last-mile delivery in Russia: a tool to develop local markets

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  • Kitonsa, H.

Abstract

As the popularity of online shopping increases, last-mile delivery is gaining more and more attention of e-commerce companies. One of the viable solutions to maximizing the benefits of such delivery and cutting its costs is the usage of the rapidly developing drone technology. However, drone delivery is associated with a number of safety and privacy, which makes legislators uneasy about permitting the commercial use of drones. In this paper, we compare the drone regulations applied in various countries with those of Russia and analyze the criteria used to develop such regulations. Six general approaches are thus outlined: officially banning commercial drone operation; making it virtually impossible for drone operators to acquire the necessary registration and license; allowing to fly drones in exceptional cases over restricted areas; prohibiting to fly drones beyond the pilot’s line of visual sight; allowing to fly drones if standard requirements are met; and, finally, following the substantial precedent principle. This analysis shows us the possible strategies Russia could adopt to regulate commercial drone usage. It is thus suggested that Russia should follow the example of Rwanda and China and allow to experiment with drone delivery in rural areas, where the risk to people’s lives and property in case of drone malfunction are lower than in urban areas.

Suggested Citation

  • Kitonsa, H., 2018. "Drone technology for last-mile delivery in Russia: a tool to develop local markets," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 4(2), pages 51-58.
    • Handle: RePEc:aiy:journl:v:4:y:2018:i:2:p:51-58
    DOI: 10.15826/recon.2018.4.2.007
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    1. Ann Melissa Campbell & Martin W. P. Savelsbergh, 2005. "Decision Support for Consumer Direct Grocery Initiatives," Transportation Science, INFORMS, vol. 39(3), pages 313-327, August.
    2. Ryan L. Skiver & Michael Godfrey, 2017. "Crowdserving: A Last Mile Delivery Method For Brick-And-Mortar Retailers," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 11(2), pages 67-77.
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