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Modelling high-tech product life cycles with short-term demand information: a case study
B Aytac and SD Wu
The Journal of the Operational Research Society
Vol. 62, No. 3, Special Issue: Supply Chain Forecasting and Planning (March 2011), pp. 425-432
Stable URL: http://www.jstor.org/stable/41058920
Page Count: 8
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Increasing competition and volatile conditions in high-tech markets result in shortening product life cycles with non-cyclic demand patterns. This study illustrates the use of a demand-characterisation approach that models the underlying shape of product demands in these markets. In the approach, a Bayesian-update procedure combines the demand projections obtained from historical data with the short-term demand information provided from demand leading indicators. The goal of the Bayesian procedure is to improve the accuracy and reduce the variation of historical data-based demand projections. This paper discusses the implementation experience of the proposed approach at a semiconductor-manufacturing company; the key test results are presented using product families introduced over the last few years with a comparison to real-world benchmark demand forecasts.
The Journal of the Operational Research Society © 2011 Operational Research Society