Title: Assessing the value of early order commitment for supply chains with (s, S) policies and lost sales

Authors: Xiaoying Hu, Jinxing Xie

Addresses: Beijing Miracle Information and Technology Develop Co., Ltd., Beijing 100083, China. ' Department of Mathematical Sciences, Tsinghua University, Beijing 100084, China

Abstract: Early order commitment (EOC) is one of the strategies for supply chain coordination, wherein a retailer places its orders to a supplier in advance, i.e., the retailer|s ordering lead time is longer than the regular delivery time from the supplier to the retailer. This paper explores the value of practicing EOC in a supply chain with demand uncertainty and lost sales. It also examines the impact of forecasting errors and inventory policies used by the retailers on the performance of the supply chain. The methodology adopted in this study is computer simulation. Analyses of the simulation outputs show that: 1) using the periodical review (s, S) policy can reduce the cost of the supply chain in many environments compared to deterministic lot-sizing rules such as the economic order quantity rule, the periodic order quantity rule and the Silver-Meal rule; 2) the EOC strategy can generate significant cost savings for the whole supply chain when the retailers| forecasting errors are not too large or the supplier|s forecasting horizon is relatively long. However, the advantage of EOC disappears when the forecasting errors are large and the supplier|s forecasting horizon is very short. Sensitivity analyses show that these findings are robust with respect to the supply chain|s cost structure and the supplier|s production lead time.

Keywords: simulation; SCM; supply chain management; early order commitment; inventories; (s, S) policies; lost sales; forecasting errors; retailers; retailing; orders; suppliers; delivery times; demand uncertainty; determinism; lot sizing; economic order quantity; EOQ rules; periodic order quantity; Silver-Meal rule; cost savings; forecasting horizons; cost structures; lead times.

DOI: 10.1504/IJAMS.2010.033565

International Journal of Applied Management Science, 2010 Vol.2 No.3, pp.205 - 223

Published online: 06 Jun 2010 *

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