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Demand and Revenue Management of Deteriorating Inventory on the Internet: An Empirical Study of Flash Sales Markets
Abstract:In this study, we investigate demand and revenue management of deteriorating inventory in flash sales markets (FSM). Retailers operating FSM source excess inventories of products from secondary markets in fixed lot sizes and offer them as part of deals that get no replenishments and expire after running for predetermined periods (e.g., 24 hr) or when they sell out, whichever occurs first. We develop a demand forecasting model that incorporates the effects of sentiments conveyed by consumers in discussion forum posts associated with different deals on the deals’ empirical demand rates. We then conduct a survival analysis to find that the empirical demand rates projected from our forecasting model are significant predictors of the deals’ actual time to stockout, even after controlling for their initial inventory provisions and markdowns. We also find that the predicted effects of these demand rates on stockout times are stronger at low markdowns. Our investigation offers insights into different strategies that sellers operating FSM can pursue to improve their inventory performance. These strategies involve decisions that sellers must make both a priori, before deals start, and a posteriori, according to real‐time detection of departures from projected demand rates as deals run their course.
Keywords:Internet retailing  demand management  revenue management  predictive analytics  Bass model  survival analysis
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