Joint Inventory and Pricing Coordination with Incomplete Demand Information

Ye Lu, Miao Song, Yi Yang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

12 Citations (Scopus)

Abstract

In retailing operations, retailers face the challenge of incomplete demand information. We develop a new concept named K-approximate convexity, which is shown to be a generalization of K-convexity, to address this challenge. This idea is applied to obtain a base-stock list-price policy for the joint inventory and pricing control problem with incomplete demand information and even non-concave revenue function. A worst-case performance bound of the policy is established. In a numerical study where demand is driven from real sales data, we find that the average gap between the profits of our proposed policy and the optimal policy is 0.27%, and the maximum gap is 4.6%.
Original languageEnglish
Pages (from-to)701-718
Number of pages18
JournalProduction and Operations Management
Volume25
Issue number4
DOIs
Publication statusPublished - 1 Apr 2016

Keywords

  • incomplete demand information
  • inventory and pricing coordination
  • K-approximate convexity

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Management of Technology and Innovation

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