A Multiordering Newsvendor Model with Dynamic Forecast Evolution

Authors:
Tong Wang;Atalay Atasu;Mümin Kurtuluş
Affiliations:
NUS Business School, National University of Singapore, Singapore 119245;College of Management, Georgia Institute of Technology, Atlanta, Georgia 30308;Owen Graduate School of Management, Vanderbilt University, Nashville, Tennessee 37203
Venue:
Manufacturing & Service Operations Management
Year:
2012

Citing 15
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Abstract

We consider a newsvendor who dynamically updates her forecast of the market demand over a finite planning horizon. The forecast evolves according to the martingale model of forecast evolution (MMFE). The newsvendor can place multiple orders with increasing ordering cost over time to satisfy demand that realizes at the end of the planning horizon. In this context, we explore the trade-off between improving demand forecast and increasing ordering cost. We show that the optimal ordering policy is a state-dependent base-stock policy and analytically characterize that the base-stock level depends on the information state in a linear (log-linear) fashion for additive (multiplicative) MMFE. We also study a benchmark model where the newsvendor is restricted to order only once. By comparing the multiordering and single-ordering models, we quantify the impact of the multiordering strategy on the newsvendor's expected profit and risk exposure.