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The Value of Information Updating in New Product Development [electronic resource] / by Christian Artmann.

By: Contributor(s): Material type: TextTextSeries: Lecture Notes in Economics and Mathematical Systems ; 620Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009Description: XVIII, 208 p. 41 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540938330
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 519 23
LOC classification:
  • T57-57.97
Online resources:
Contents:
Literature Review -- Model Description -- Model Properties -- Numerical Study -- Conclusion -- Statistical Distributions -- Supplement to Performance Variability Limitation -- Supplement to Mean-Variance Update -- Program Listing.
In: Springer eBooksSummary: Managing uncertainty in new product development projects for improved valuation and decision making is one of the most complex and challenging problems in operations management. It is important for any corporation depending on the success of new products and innovations. This work shows how uncertainty can be handled and partly resolved by conducting an information update during the development process. It is one of the first comprehensive models that combine statistical decision theory in form of Bayesian analysis with a real options framework for projects exposed to different sources of uncertainty. The proposed framework makes an important theoretical contribution in addressing this problem, while at the same time being of significant value to managers who face the difficult task of evaluating and managing complex product development projects.
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Literature Review -- Model Description -- Model Properties -- Numerical Study -- Conclusion -- Statistical Distributions -- Supplement to Performance Variability Limitation -- Supplement to Mean-Variance Update -- Program Listing.

Managing uncertainty in new product development projects for improved valuation and decision making is one of the most complex and challenging problems in operations management. It is important for any corporation depending on the success of new products and innovations. This work shows how uncertainty can be handled and partly resolved by conducting an information update during the development process. It is one of the first comprehensive models that combine statistical decision theory in form of Bayesian analysis with a real options framework for projects exposed to different sources of uncertainty. The proposed framework makes an important theoretical contribution in addressing this problem, while at the same time being of significant value to managers who face the difficult task of evaluating and managing complex product development projects.

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