Leadtime

Chamsirisakskul K, Griffin P, Keskinocak P (2006) Pricing and scheduling decisions with leadtime flexibility. European Journal of Operational Research 171 (1) 153-169... 

Inderfurth, K. (1997), Simple Optimal Replenishment and Disposal Policies for a Product Recovery System with Leadtimes, OR Spektrum, Vol. 19, pp. 111-122. 

Glasserman, P. and Wang, Y. (1998), Leadtime-Inventory Tradeoffs in Assemble-to-Order Systems, Operations Research, Vol. 46, pp. 858-871. 

Song, J. S., Xu, S., and Liu, B. (1999), Order Fulfillment Performance Measiues in an Assemble-to-Order System with Stochastic Leadtimes, Operations Research, Vol. 47, pp. 131-149. 

Based on this approximation, we nse a standard resnlt from queueing theory to calculate the average waiting time for spares 7 as a function of the total demand rate X, the leadtime L, and the munher of spare parts kept on stock S ... 

We include an example with hypothetical, but realistic values. We consider a spare part (package) with a leadtime of 22/52 years and an annual holding cost of 0.25 X 9. >k%. We consider 6 pieces of equipment... 

Price Discrimination in a Supply Chain In B2B environments, the customers are themselves manufacturers or retailers who potentially differ along multiple attributes. In addition to factors that influence their willingness to pay, such as the end market in which they sell and the type of product they sell, these customers may also differ in (i) their order size, (zz) the specific combination or specification of products they wish to purchase and (zzz) the urgency with which they need their order, i.e., maximum acceptable leadtime. The current... 

By itself, research into pricing does not necessarily address the marketing-operations interface. However, because prices cannot be set in a vacuum, there are ample opportunities to study the relationship of prices to other dimensions affected by operations management practices, primarily leadtime and quality. 

Analogous to price/leadtime models are price/quality models, in which customer demand is a function of both price and product quality. Examples of research that addresses this interface include Banker et al., 1998, Curry, 1985, Moorthy, 1988, van Mieghem and Dada, 1999. The difficulty with such models is that quality is a multi-dimensional attribute. Quality is measured in different ways in different settings. So, to be of use, such research must address specific aspects of quality that are subject to influence by operating policies. 

Competing on response time became a popular management practice in the 1990 s (see Blackburn, 1990, Chamey, 1991, Schmenner, 1988, Stalk and Hout, 1990, Thomas, 1990 for discussions of the virtues and practices of time based competition). This trend motivated researchers in operations management to develop models to understand leadtimes and how to shorten them (see Karmarkar, 1993, for a review). 

Most directly relevant to the marketing-operations interface is research directly into methods for setting due dates and quoting leadtimes (e.g.. Baker, 1984, Baker and Bertrand, 1981, Bertrand, 1983a, Bertrand, 1983b, Duenyas,... 

In recent years, leadtime quoting has been addressed in commercial applications under the heading of available to promise (ATP) and capable to promise... 

CTP). Typically, ATP systems determine whether a particular due date is feasible given current finished goods and WIP inventory levels, while CTP checks component availability in the supply chain, as well as FGI and WIP, to determine due date feasibility. These systems are gaining popularity as a means to offer more competitive leadtimes in traditional production systems and as a result are starting to get attention by modeling researchers (e.g., Chen et al., 2000 and Chen et al., 2001). 

By using the Internet to both collect the demand and delivery data needed to evolve the model and to present the resulting dynamic leadtime quotes, statistical leadtime quoting models could play a key role in the operation of e-commerce systems. 

The sales step is only part of the overall customer experience with an e-tailer. Providing convenient on-line ordering is certainly important, but if the firm doesn t back it up with prompt, reliable delivery of the product or service, the customer is unlikely tp return. For this reason, customer leadtimes are a critical issue in e-commerce systems. 

For retailers (e.g., Amazon), leadtime performance is purely determined by the structure and execution of inventory and distribution policies. But for firms that also manufacture or assemble products (e.g., Dell), the production function is also a driver of performance. Of course, all of the usual methods for achieving manufacturing efficiency (lean, agile, cellular manufacturing, etc.) are relevant to e-commerce settings. As we have noted above, modular product architectures and assemble-to-order production systems are particularly well-adapted to supporting quick-response manufacturing with which to support an e-commerce system. Since the issues of speed, variety, quality and flexibility were clearly priorities prior to the advent of e-commerce, research that addresses these remains relevant but has not been radically affected by the Internet. 

Hopp, W.J., M.L. Roof 2001. A Simple Robust Leadtime Quoting Policy. Manufacturing Service Operations Management 3, 321-336. 

Hopp, W., M. Spearman. 1993. Setting Safety Leadtimes for Purchased Components in Assembly Systems. HE Transactions 25, 2-11. 

Huff, L.C., W.T. Robinson. 1994. The Impact of Leadtime and Years of Competitive Rivalry on Pioneer Market Share Advantages. Management Science 40(10), 1370-1377. 

Karmarkar, U.S. 1994. A Robust Forecasting Technique for Inventory and Leadtime Management. Journal of Operations Management 12(1), 45-54. 

Morton, T, and A. Vepsalainen. 1987. Priority Rules and Leadtime Estimation for Job Shop Scheduling with Weighted Tardiness Costs, Management Science 33, 1036-1047. 

Plambeck, E.L. 2003. Optimal Leadtime Differentiation via Diffusion Approximations. to appear in Operations Research. 

Song, J-S. 1994. The Effect of Leadtime Uncertainty in a Simple Stochastic Inventory Model. Management Science 40(5), 603-613. 

Tielemans, P.F.J., R. Kuik. 1996. An Exploration of Models that Minimize Leadtime Through Batching of Arrived Orders. European Journal of Operational Research 95(2), 374-389. 

Yano, C. 1987. Stochastic Leadtimes in Two-Level Assembly Systems. HE Transactions 19, 371-378. 

Some of the papers that consider multiple classes of customer differentiate them by service, and more particularly by leadtime within the production system. In the next section we consider papers with an explicit differentiation of leadtime, some of which could also clearly fall in the multiple classes section of this paper there is clearly overlap between these two sections. 

One of the earliest examples of a paper which considers simultaneous price and leadtime decisions is Easton and Moodie [45]. For their demand model, the authors use a logit based model, where customer s utility is based on the work required for a job, the price, and the leadtime. The manufacturer gives a bid to a customer for a job, and the customer decides whether to accept or reject the job thus the available shop time is a random variable. The authors develop a procedure for quoting a price and leadtime for one job at a time based on the current status of the system. 

Elhafsi considers price and delivery time quotation in [46] and [47]. In particular, the focus is on the leadtime aspect, with price calculated as a function of the cost of the job. 

In [77], Keskinocak et al focus on scheduling and leadtime quotation, particularly when customers exhibit sensitivity towards leadtime. Although price is not an explicit decision, the revenue of a joib depends on the leadtime. They develop algorithms to solve this problem and provide bounds on their performances. 

Plambeck [120] considers two classes of customers that differ by price and delay sensitivity. An initial static price and production rate are fixed by the manufacturer, and the firm dynamically quotes leadtimes and determines the processing of customer orders. The author shows her solution is asymptotically optimal in heavy traffic in the system. 

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