Evaluating Long-Term Service Performance in Two-Stage Newsvendor Models

30 Pages Posted: 30 Jan 2008 Last revised: 10 Apr 2014

See all articles by Alain Bensoussan

Alain Bensoussan

University of Texas at Dallas - Naveen Jindal School of Management; Hong Kong Polytechnic University - Faculty of Business; Ajou University

Qi Feng

Purdue University - Krannert School of Management

Suresh Sethi

University of Texas at Dallas - Naveen Jindal School of Management

Abstract

Managing customer satisfaction in a cost effective way has always been a major challenge faced by inventory managers. This paper studies long-term service performance of a two-stage newsvendor selling a perishable product with short-term demand patterns. We characterize the optimal inventory policy to minimize the expected inventory cost such that a long-term stock availability target is satisfied. Both in-stock probability and fill rate targets are examined and compared. In particular, we address the following questions: How should an inventory manager evaluate his long-term fill rate performance without observing the lost sales? How are in-stock probabilities and fill rates connected with respect to different demand patterns? How does the forecast update impact the evaluation of the long-term service performance? How do the short-term cost trade-offs under different long-term service targets depend on the monotone structures of the forecast signal?

Keywords: Newsvendor Model, inventory model, service measures, forecast updates, Two-stage newsvendor model, fill rate

JEL Classification: C61, M11

Suggested Citation

Bensoussan, Alain and Feng, Qi and Sethi, Suresh, Evaluating Long-Term Service Performance in Two-Stage Newsvendor Models. Available at SSRN: https://ssrn.com/abstract=1087584 or http://dx.doi.org/10.2139/ssrn.1087584

Alain Bensoussan

University of Texas at Dallas - Naveen Jindal School of Management ( email )

800 West Campbell Rd
SM 30
Richardson, TX 75080-3021
United States
9728836117 (Phone)

HOME PAGE: http://www.utdallas.edu/~axb046100/

Hong Kong Polytechnic University - Faculty of Business

Dept SEEM
Systems Engr * Engr Mgmt
Hong Kong, Hong Kong
China

Ajou University ( email )

Ajou
France

Qi Feng

Purdue University - Krannert School of Management ( email )

1310 Krannert Building
West Lafayette, IN 47907-1310
United States

Suresh Sethi (Contact Author)

University of Texas at Dallas - Naveen Jindal School of Management ( email )

800 W. Campbell Road, SM30
Richardson, TX 75080-3021
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
169
Abstract Views
1,080
rank
206,261
PlumX Metrics