One approach to supply chain coordination is early order commitment, whereby a retailer commits to purchase a fixed-order quantity at a fixed delivery time before demand uncertainty is resolved. In this paper, we develop an analytical model to quantify the cost savings of an early order commitment in a two-level supply chain where demand is serially correlated. A decision rule is derived to determine whether early order commitment will benefit the supply chain, and accordingly to determine the optimal timing for early commitment. Our results indicate that the supply chain would experience greater savings from early order commitment when-(a) the inventory item receives less value-added activities at the retailer site; (b) the manufacturing lead time is short; (c) demand correlation over time is positive but weak; or (d) the delivery lead time is long (if a condition exists). We also propose a rebate scheme for the supply chain partners to share the gains of practicing early order commitment.

This note extends the results in the manufacturer-dominated game model of the paper by Li et al. (Omega 30 (2002) 347) to the case where the manufacturer's marginal profit is not large enough. In such situations, the profit of the entire supply chain under the co-op advertising mode is higher than the one under the Stackelberg game, which is consistent with the results of the original paper. However, the advertising expenditures of the manufacturer and the retailer under the co-op advertising model are not always larger than those under the Stackelberg game, which is different from the results of the original paper. Furthermore, the results are also compared with the simultaneous move game of the paper by Huang and Li (Eur. J. Oper. Res. 135 (2001) 527). The manufacturer always prefers the leader-follower structure rather than the simultaneous move structure, which is consistent with the results of the original paper. However, the retailer always prefers the simultaneous move structure rather than the leader–follower structure, which differs from the results of the original paper.

This paper deals with the single machine scheduling problem with multiple financial resource constraints. It: is shown that the problem can be reduced to the two machine flow shop scheduling problem if the financial resources arrive uniformly over time, and it is also shown that the LPT (Largest Processing Time) rule generates an optimal solution to the problem if the financial resources are consumed uniformly by all the jobs. Hence there exist polynomial algorithms for these two special cases of the problem.

Aligning its quality initiatives in synchronization with the customer's perception of values is one of the key management strategies for improving the competitive edge of an organization. Therefore, it will be a distinct advantage if one can succeed in effectively capturing the genuine and major customer attributes (requirements), systematically analysing and duly transforming them into the appropriate product attributes (features). This paper puts forward a novel approach for analysing customer attributes and projecting them into the relevant design, engineering and product attributes in order to facilitate decision-making and to guide downstream manufacturing planning and control activities. The proposed hybrid system incorporates the principles of quality function deployment, analytic hierarchy process and fuzzy set theory to tackle the complex and often imprecise problem domain encountered in customer requirement management. It offers an analytical and intelligent tool for decoding, prioritizing and inferring the qualitative, sometimes vague and imprecise Voice of Customer. As a result, the appropriate product attributes can be mapped out and their relevant design targets can be determined quantitatively and consistently. The software supporting the hybrid system is constructed within a generic framework which can be easily customized and configured into specific enterprise models capable of offering more timely responses to the dynamic market demand.

This paper compares the performance of a new improved heuristic (STIL) proposed by Coleman and McKnew (1991) against those of the Wagner-Whitin (WW), cost-modified Wagner-Whitin (MWW) and some simple lot-sizing rules found to perform well by Zhao et al. (1995). It also investigates the impact of the lot-sizing rules on the selection of the parameters for freezing the master production schedule (MPS). The experimental settings include forecasting, master production scheduling and material requirements planning under a rolling time horizon. The result of the study shows that the STIL heuristic, the WW rule and the MWW rule do not really outperform the simple cost-modified Silver-Meal (MSM) and the Silver-Meal/Lot-for-Lot (SM/LFL) even though they require substantially higher computation time. The study also shows that the selection of the parameters for freezing the MPS is not significantly influenced by the selection of the lot-sizing rules.