Real Options "in" Projects and Systems Design

This book describes a comprehensive approach to
identify and deal with real options in projects,
that is, those real options (flexibility) that are
integral parts of the technical design. It attempts
to specify analytically the design parameters that
provide good opportunities for flexibility for any
specific engineering system.

It proposes a two-stage integrated process: options
identification followed by options analysis. The
options identification stage discovers the design
elements most likely to provide worthwhile
flexibility, including a screening and a simulation
model. Options analysis stage develops a stochastic
mixed-integer programming model to value options.
This approach decreases the complexity and size of
the models at each stage and thus permits efficient
computation.

The framework developed is generally applicable to
engineering systems. The book explores two cases in
river basin development and satellite
communications, showing significant value of real
options in projects, in the form of increased
expected net benefit and/or lowered downside risk.

Autorentext
Dr. Tao Wang received his PhD in Engineering systems from MIT in
June 2005. He got his MS in Economics and BS in Electrical
Engineering from Fudan University in China. He has been working
for Morgan Stanley in Hong Kong and China International Capital
Company in Beijing.

Klappentext
This book describes a comprehensive approach to identify and deal with real options "in" projects, that is, those real options (flexibility) that are integral parts of the technical design. It attempts to specify analytically the design parameters that provide good opportunities for flexibility for any specific engineering system. It proposes a two-stage integrated process: options identification followed by options analysis. The options identification stage discovers the design elements most likely to provide worthwhile flexibility, including a screening and a simulation model. Options analysis stage develops a stochastic mixed-integer programming model to value options. This approach decreases the complexity and size of the models at each stage and thus permits efficient computation. The framework developed is generally applicable to engineering systems. The book explores two cases in river basin development and satellite communications, showing significant value of real options "in" projects, in the form of increased expected net benefit and/or lowered downside risk.