Connecting Customers and Merchants Offline: Experimental Evidence From the Commercialization of Last-Mile Stations at Alibaba

Brian Rongqing Han, Tianshu Sun, Leon Yang Chu, Lixia Wu

Research output: Working paper

Abstract

Many e-commerce platforms have established extensive networks of stations as their last-mile logistics infrastructure. In this study, we investigate how this last-mile infrastructure may serve as an offline platform to connect customers and merchants in the physical world and stimulate offline-to-online effect by leveraging the spontaneous walk-in traffic (organic interaction) and by prompting interested customers through online intervention (induced interaction). Using free sample distribution as an example, we design two large-scale experimental studies in collaboration with Alibaba---a quasi-experiment across 1,032 stations and a randomized field experiment among 189,019 customers---to examine the causal effects of organic and induced interactions on customers' subsequent online purchases at the focal brands, respectively. We find that induced interaction drives significantly more online sales compared with organic interaction. We further identify a \textit{screening} mechanism underlying its effectiveness. Because of the additional traveling cost on the customer side, induced interaction tends to attract customers who have a stronger preference over the focal products. Such advantageous self-selection, in turn, leads to a large increase in customers' subsequent online engagement. Finally, we propose a customized targeting framework using instrumental forest to further enhance the effectiveness of induced interaction at the last-mile stations.
Original languageEnglish (US)
Number of pages39
DOIs
StatePublished - Sep 20 2019
Externally publishedYes

Keywords

  • offline platform
  • last-mile logistics
  • natural experiment
  • randomized field experiment
  • induced interaction
  • instrumental forest

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