Modelling high-tech product life cycles with short-term demand information: a case study

B Aytac () and S D Wu
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B Aytac: Lehigh University
S D Wu: Lehigh University

Journal of the Operational Research Society, 2011, vol. 62, issue 3, 425-432

Abstract: Abstract 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.

Keywords: Bayesian forecasting; leading indicators; cumulative demand growth; short life-cycle products; high-tech industry (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (4)

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DOI: 10.1057/jors.2010.89

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