Learning from inventory availability information: Evidence from field experiments on amazon

Ruomeng Cui*, Dennis J. Zhang, Achal Bassamboo

*Corresponding author for this work

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

Many online retailers provide real-time inventory availability information. Customers can learn from the inventory level and update their beliefs about the product. Thus, consumer purchasing behavior may be impacted by the availability information. Based on a unique setting from Amazon lightning deals, which displays the percentage of inventory consumed in real time, we explore whether and how consumers learn from inventory availability information. Identifying the effect of learning on consumer decisions has been a notoriously difficult empirical question because of endogeneity concerns. We address this issue by running two randomized field experiments on Amazon in which we create exogenous shocks on the inventory availability information for a random subset of Amazon lightning deals. In addition, we track the dynamic purchasing behavior and inventory information for 23,665 lightning deals offered by Amazon and use their panel structure to further explore the relative effect of learning. We find evidence of consumers learning from inventory information: a decrease in product availability causally attracts more sales in the future; in particular, a 10% increase in past claims leads to a 2.08% increase in cart add-ins in the next hour. Moreover, we show that buyers use observable product characteristics to moderate their inferences when learning from others; a deep discount weakens the learning momentum, whereas a good product rating amplifies the learning momentum.

Original languageEnglish (US)
Pages (from-to)1216-1235
Number of pages20
JournalManagement Science
Volume65
Issue number3
DOIs
StatePublished - Mar 2019

Keywords

  • Amazon
  • Field experiment
  • Flash sales
  • Inventory availability
  • Learning
  • Retail operations

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research

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