Pick your poison: pricing and inventories at unlicensed online pharmacies.

EC(2013)

引用 11|浏览3
暂无评分
摘要
ABSTRACTElectronic commerce has transformed how goods are supplied to consumers, but has also exposed weaknesses in supply regulations of certain goods, such as alcohol, weapons or prescription drugs. While licensed pharmacies have tread carefully with online sales, many enterprising operators have been selling pharmaceuticals without a license for years. Despite facing considerable adversity, unlicensed online pharmacies have managed not only to survive, but even to generate considerable revenue. In this paper, we attempt 1) to understand the economic reasons for their success, while facing stiff competition from both legal and illegal alternatives, and 2) to identify characteristics of their supply chains that could be used to disrupt illicit sales. We collected six months' worth of inventory and pricing data from 265 online pharmacies that advertise through search- engine poisoning. We compare this to data from Silk Road, an anonymous online marketplace, and from familymeds.com, a licensed online pharmacy. We discover that instead of directly competing with licensed pharmacies, unlicensed pharmacies often sell drugs that licensed pharmacies do not or cannot sell. Furthermore, unlicensed pharmacies are not only cheaper overall, but they also offer volume discounts. Clustering analysis of inventories reveals that only a few suppliers appear to cater for most unlicensed pharmacies, which suggests that cutting them off could disrupt unlicensed sales. Cross-validating our data with inventories from a random sample of 265 different pharmacies deemed ``not recommended'' by the National Association of Boards of Pharmacy shows that our results are consistent across different types of questionable vendors.
更多
查看译文
关键词
online sale,pricing data,unlicensed sale,online pharmacy,licensed online pharmacy,licensed pharmacy,anonymous online marketplace,unlicensed online pharmacy,unlicensed pharmacy,certain goods,pharmacies,search engine poisoning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要