Speaker(s):    Christian Terwiesch (Wharton)
Title:                  Measuring Imputed Costs in the Semiconductor Equipment Supply Chain


Abstract

Note: Paper is co-authored with Morris A. Cohen, Teck H. Ho, Justin Z. Ren.

We report on an empirical study of forecast sharing related to the acquisition of customized production equipment for the manufacturing of semiconductors. Customers, who are responding to the turbulent environment they face in the demands for their end-products, press for short customer lead-times, requiring product delivery within three months or less. At the same time, the complexity and degree of customization of the equipment causes manufacturing lead-times to be long and stochastic, ranging between several months to a whole year. Taking the perspective of a supplier of customized semiconductor production equipment, we develop a formal model addressing the trade-off between the early start of a production process (leading to potential cancellation cost and holding cost) and a delay until more information has become available (leading to a potential delay cost due to loss of goodwill).

How this trade-off is resolved, depends on the cost structure of the supplier. While traditionally, the supply chain literature has taken these cost parameters as exogenously given and then searched for the optimal operational decision, we take a different approach. Based on an empirical observation of the supply chain over time, including detailed data of shared forecasts, actual purchase orders, production lead-times, and delivery dates, and on the assumption that the supplier is a rational actor, we are able to reconstruct the cost parameters that explain the empirical supply chain behavior. Our results show that the cancellation cost is about four times higher than the delay cost and the holding cost is twice as large.

Specifically, this paper makes two contributions. First, we quantify the effectiveness of an order forecast sharing system in the semiconductor equipment supply chain and show that it is not as effective as one would expect. Fearing order cancellation, the supplier, by and large, ignores the preliminary forecast information (c.f. Tang et. al, in press). Second, to the best of our knowledge, this is the first paper to empirically estimate the cost parameters that underlie the existing analytical models of coordination in supply chain management.

Full paper available under: http://grace.wharton.upenn.edu/~terwiesch/ImputedCosts.pdf
Info on Christian under: http://grace.wharton.upenn.edu/~terwiesch/cv.pdf