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.

Includes supplementary material: sn.pub/extras

Inhalt
Literature Review.- Model Description.- Model Properties.- Numerical Study.- Conclusion.- Statistical Distributions.- Supplement to Performance Variability Limitation.- Supplement to Mean-Variance Update.- Program Listing.