Article ID: | iaor20161523 |
Volume: | 25 |
Issue: | 4 |
Start Page Number: | 701 |
End Page Number: | 718 |
Publication Date: | Apr 2016 |
Journal: | Production and Operations Management |
Authors: | Yang Yi, Lu Ye, Song Miao |
Keywords: | demand, retailing, information |
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%.