Data-Driven Stochastic Dynamic Pricing and Ordering

Rainer Schlosser ()
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Rainer Schlosser: Hasso Plattner Institute

A chapter in Operations Research Proceedings 2018, 2019, pp 397-403 from Springer

Abstract: Abstract In many markets, firms use data-driven dynamic pricing and ordering strategies to increase their profits. To successfully manage both inventory levels as well as offer prices is a highly challenging task as (i) demand is typically uncertain and (ii) optimized pricing and ordering decisions are mutually dependent. In this paper, we analyze stochastic dynamic joint pricing and ordering models for the sale of durable goods. In a first step, a data-driven approach is used to estimate demand intensities and to quantify sales probabilities. In a second step, we use a dynamic programming model to compute optimized feedback pricing and ordering strategies. We are able to study the impact of ordering costs, inventory holding costs, and a delay in delivery. Further, we discuss potential extensions of the model proposed.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-030-18500-8_49

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DOI: 10.1007/978-3-030-18500-8_49

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