| Article ID: | iaor201525660 |
| Volume: | 13 |
| Issue: | 6 |
| Start Page Number: | 440 |
| End Page Number: | 456 |
| Publication Date: | Dec 2014 |
| Journal: | Journal of Revenue and Pricing Management |
| Authors: | Marcotte Patrice, Savard Gilles, Sharif Azadeh Shadi |
| Keywords: | management, statistics: inference |
Revenue management systems rely on customer data, and are thus affected by the absence of registered demand that arises when a product is no longer available. In the present work, we review the uncensoring (or unconstraining) techniques that have been proposed to deal with this issue, and develop a taxonomy based on their respective features. This study will be helpful in identifying the relative merits of these techniques, as well as avenues for future research.