The Effect of Censored Demand in the Data-driven Newsvendor Problem: A Comparative Study

• In Event: SUPPLY CHAIN MANAGEMENT: Topics on Supply Chain Management

Abstract

When demand exceeds supply, sales are lost, often resulting in the excess demand being censored, particularly when no backordering system is in place. The performance of a data-driven newsvendor model will be distorted when estimated with observed censored demand. The actual effect of censoring on the model varies with patterns and distributions. A comparative simulation study examines the effect of censoring on data-driven approaches to the newsvendor model with price-dependent demand. A modified approach using a Tobit model is introduced and a comparative study with recommended approaches illustrates the effect of commonly censored data on data-driven newsvendor approaches.

Authors

• Adeela Gulzari, University of North Texas

• Robert Pavur, University of North Texas