The Dynamic Newsvendor Model with Correlated Demand

21 Pages Posted: 9 Jan 2015 Last revised: 12 Jan 2015

See all articles by Layth C. Alwan

Layth C. Alwan

University of Wisconsin - Milwaukee - Sheldon B. Lubar School of Business

Minghui Xu

Wuhan University - School of Economics and Management

Dong-Qing Yao

Towson University - College of Business and Economics

Xiaohang Yue

University of Wisconsin - Milwaukee - Sheldon B. Lubar School of Business

Date Written: January 9, 2015

Abstract

The classic newsvendor model was developed under the assumption that period-to-period demand is independent over time. In real-life applications, the notion of independent demand is often challenged. In this paper, we examine the newsvendor model in the presence of correlated demands. Specifically under a stationary AR(1) demand, we study the performance of the traditional newsvendor implementation versus a dynamic forecast-based implementation. We demonstrate theoretically that implementing a minimum mean square error (MSE) forecast model will always have improved performance relative to the traditional implementation in terms of cost savings. In light of the widespread usage of all-purpose models like the moving-average method and exponential smoothing method, we compare the performance of these popular alternative forecasting methods against both the MSE-optimal implementation and the traditional newsvendor implementation. If only alternative forecasting methods are being considered, we find that under certain conditions it is best to ignore the correlation and opt out of forecasting and to simply implement the traditional newsvendor model.

Keywords: Autocorrelated Demand, Demand Forecasting, Newsvendor

Suggested Citation

Alwan, Layth C. and Xu, Minghui and Yao, Dong-Qing and Yue, Xiaohang, The Dynamic Newsvendor Model with Correlated Demand (January 9, 2015). Available at SSRN: https://ssrn.com/abstract=2547424 or http://dx.doi.org/10.2139/ssrn.2547424

Layth C. Alwan

University of Wisconsin - Milwaukee - Sheldon B. Lubar School of Business ( email )

P.O. Box 742
3202 N. Maryland Ave.
Milwaukee, WI 53201-0742
United States

Minghui Xu (Contact Author)

Wuhan University - School of Economics and Management ( email )

Wu Han, Hu-Bei 430072
China

Dong-Qing Yao

Towson University - College of Business and Economics ( email )

United States

Xiaohang Yue

University of Wisconsin - Milwaukee - Sheldon B. Lubar School of Business ( email )

P.O. Box 742
3202 N. Maryland Ave.
Milwaukee, WI 53201-0742
United States

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