Project Selection Under Uncertainty

Name: Project Selection Under Uncertainty
Brand: Springer-Verlag New York Inc.
SKU: 9781461347859
Price: 38753 HUF
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Dynamically Allocating Resources to Maximize Value

Szerző: Stylianos Kavadias, Christoph H. Loch

Nyelv:

Kötés: Puha kötésű

Kiadó: Springer-Verlag New York Inc.

Elérhetőség: Beszállítói készleten

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Project Selection Under Uncertainty is the result of a five-year research program on the selection o...

Információk a könyvről

Szerző

Stylianos Kavadias, Christoph H. Loch

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2012

oldal

145

EAN

9781461347859

ISBN

1461347858

Enbook ID

06796101

Kiadó

Springer-Verlag New York Inc.

Súly

260

Méretek

155 x 235 x 10

Teljes leírás

Project Selection Under Uncertainty is the result of a five-year research program on the selection of projects in New Product Development (NPD). Choosing the New Product Development portfolio is of critical importance in today's business environment. The NPD portfolio has considerable strategic effect on the "middle term" success of a business. §This book takes a step in developing a theory that addresses the need for quantitative prioritization criteria within the broader strategic context of the R&D portfolios. Its foundation lies in mathematical theory of resource-constrained optimization with the goal to maximize quantitative returns. The book seeks to broaden the portfolio discussion in two ways. First, simplified models - appropriate for the data-poor NPD context - are developed, which attempt to illuminate the structure of the choice problem and robust qualitative rules of thumb, rather than detailed algorithmic decision support. Such robust rules can be applied in the R&D environment of poor data availability. Second, the annual portfolio review is not the only important choice in resource allocation. In addition, the book discusses how ideas might be pre-screened as they emerge, and how projects should be prioritized once they are funded and ongoing.

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Project Selection Under Uncertainty

Dynamically Allocating Resources to Maximize Value

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Project Selection Under Uncertainty

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