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Problem definition: A canonical model in service management assumes that consumers base the purchase of a service on its full price, that is, a linear combination of the monetary price and the expected time commitment. Although analytically convenient, when this assumption holds is an unexplored question. Methodology/results: We present a model of consumers allocating their time and money between working, overhead activities that do not provide utility, one continuous leisure activity, and one discrete service. Both continuous leisure activity and discrete service increase utility. Consumers can allocate any nonnegative amount of time or money to the leisure activity. Consumption of the discrete service requires a specific amount of time and money. We examine when the decision to purchase the discrete service depends only on its full price. We show that the full-price assumption does hold in specific cases. To be precise, it depends on how consumers are paid. If consumers completely control the amount of time that they work and earn a constant wage, they base their purchase decision on the full price. If, however, they must work a fixed shift length, then the assumption fails, and the full price is not sufficient to determine the consumer's action. This leads to systematic differences in sellers' strategies when they serve consumers with different compensation structures. If the consumers must work longer than would be optimal if they controlled their schedule and earned the same hourly wage, that is, the consumers are overemployed shift workers, then a seller restricts sales (relative to selling to consumers who control their work hours), and the system is less congested. The reverse holds if the consumers would prefer to work longer at the offered wage; that is, the consumers are underemployed shift workers. Managerial implications: We show that sellers who fail to take prevailing compensation structures of the community they serve into consideration experience significant revenue loss. In some cases, we see losses in consumer surplus and social welfare as well. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2022.0357. [ABSTRACT FROM AUTHOR]

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. History: Accepted by Serguei Netessine, operations management. Keywords: learning * inventory availability * field experiment * flash sales * Amazon * retail operations, 1. Introduction Flash-deal websites, such as Amazon's deals, Groupon, and LivingSocial, have emerged as a popular means of selling products online. Using these platforms, sellers can advertise their products by [...]

The traditional operations management and queueing literature typically assumes that customers are fully rational. In contrast, in this paper we study canonical service models with boundedly rational customers. We capture [...]

Supply chain disruptions come with catastrophic consequences in spite of their low probability of occurrence. In this paper, we consider a facility location problem in the presence of random facility [...]