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An Empirical Analysis of Forecast Sharing in the Semiconductor Equipment Supply Chain

Department of Operations and Information Management, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Operations and Technology Management Department, School of Management, Boston University, Boston, Massachusetts 02215
Marketing Group, Haas School of Business, University of California, Berkeley, California 94720
Department of Operations and Information Management, University of Pennsylvania, Philadelphia, Pennsylvania 19104
terwiesch{at}wharton.upenn.edu
ren{at}bu.edu
hoteck{at}haas.berkeley.edu
cohen{at}wharton.upenn.edu

We study the demand forecast-sharing process between a buyer of customized production equipment and a set of equipment suppliers. Based on a large data collection we undertook in the semiconductor equipment supply chain, we empirically investigate the relationship between the buyer's forecasting behavior and the supplier's delivery performance. The buyer's forecasting behavior is characterized by the frequency and magnitude of forecast revisions it requests (forecast volatility) as well as by the fraction of orders that were forecasted but never actually purchased (forecast inflation). The supplier's delivery performance is measured by its ability to meet delivery dates requested by the customers. Based on a duration analysis, we are able to show that suppliers penalize buyers for unreliable forecasts by providing lower service levels. Vice versa, we also show that buyers penalize suppliers that have a history of poor service by providing them with overly inflated forecasts.

Key Words: forecast sharing; trust; empirical methods; supply chain management; collaborative planning
History: Received: January 15, 2003;

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