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Production and Operations Management 2015

Joint Inventory and Pricing Coordination with Incomplete Demand Information

Ye Lu1; Miao Song2; Yi Yang3

1 City University of Hong Kong · 2 Hong Kong Polytechnic University · 3 Zhejiang University

open access

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%.

DOI
10.1111/poms.12504
Sources
openalex

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