Learning from Inventory Availability Information: Evidence from Field Experiments on Amazon

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. This paper was accepted by Serguei Netessine, operations management.

Behavioral Operations and Supply Chain Management–A Review and Literature Mapping

“…The designers and their artifacts were subsequently scored from idea generation to implementation, and insights were derived from these scores. In another study, Cui, Zhang, and Bassamboo () use an innovative field experiment to explore how consumer behavior is impacted by inventory availability at the retailer. Using the lightning deals on Amazon, they downloaded customer and inventory information every 30 seconds and developed metrics to assess customers' purchasing behavior.…”

“…In their field experiment, Cui et al. () create a shock in inventory availability information for a subset of Amazon products and measure cart add‐ins after this shock.…”

Prosocial Goal Pursuit in Crowdfunding: Evidence from Kickstarter

“…Prior research has suggested that when project quality is uncertain, backers may engage in rational herding, making Bayesian inferences of a project’s quality from observing other backers’ actions and then making funding decisions based on their inferences (Banerjee 1992; Bikhchandani, Hirshleifer, and Welch 1992; Cui, Zhang, and Bassamboo 2018; Zhang and Liu 2012). 1 In other words, other backers’ funding choices are signals reflecting their private information, and an individual faced with uncertain product quality may update her belief about a project’s quality using information inferred from others’ choices.…”

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