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Optimal Product Lifecycle and Partial Information with Active Learning

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  • Arik Sadeh

Abstract

During production processes there is an accumulation of uncertainty aboutproduction and its output. However, decision-makers can reduce uncertainty bytaking measuremens. The role of value of measurements is discussed in adynamic production framework where the number of measurements depends on theattitude of a decision-maker toward risk, the unit cost of a measurement andits impact on the uncertainty, and the level of production and its quality.A model describing the way of handling such information in an active learningframework is shown by considering the impact of future uncertainty on currentdecisions. The model is illustrated using given functional forms and anumerical example. It is shown how the production level and its quality areaffected by the unit price of a measurement. Copyright Kluwer Academic Publishers 2003

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  • Arik Sadeh, 2003. "Optimal Product Lifecycle and Partial Information with Active Learning," Computational Economics, Springer;Society for Computational Economics, vol. 21(1), pages 125-136, February.
    • Handle: RePEc:kap:compec:v:21:y:2003:i:1:p:125-136
    DOI: 10.1023/A:1022259518788
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    References listed on IDEAS

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    4. Amman, Hans M. & Kendrick, David A., 1994. "Active learning Monte Carlo results," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 119-124, January.
    5. Hess, James, 1982. "Risk and the gain from information," Journal of Economic Theory, Elsevier, vol. 27(1), pages 231-238, June.
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