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Wicked Problems - Social Messes: Decision Support Modelling with Morphological Analysis (Risk, Governance and Society) Hardcover – July 2, 2011

ISBN-13: 978-3642196522 ISBN-10: 3642196527 Edition: 2011th

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Product Details

  • Series: Risk, Governance and Society (Book 17)
  • Hardcover: 106 pages
  • Publisher: Springer; 2011 edition (July 2, 2011)
  • Language: English
  • ISBN-10: 3642196527
  • ISBN-13: 978-3642196522
  • Product Dimensions: 9.2 x 6.1 x 0.6 inches
  • Shipping Weight: 11.2 ounces (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #2,535,244 in Books (See Top 100 in Books)

Editorial Reviews

From the Back Cover

This is the first dedicated book to be published on computer-aided General Morphological Analysis (GMA) as a non-quantified modelling method. It presents the history and theory of GMA and describes how it is used to develop interactive, non-quantified inference models. Eleven case studies are presented out of more than 100 projects carried out since 1995, illustrating how GMA has been employed for structuring complex policy and planning issues, developing scenario and strategy laboratories, and analysing organisational and stakeholder structures. Also discussed are the concepts of “wicked problems” and “social messes”, their characteristics and treatment, and problems concerning the facilitation of morphological analysis workshops. 

About the Author

Tom Ritchey is a former Research Director for the Institution for Technology Foresight and Assessment at the Swedish National Defence Research Agency (FOI) in Stockholm. He is the founder of the Swedish Morphological Society, is director of Ritchey Consulting Inc. and a founding partner in the U.K. based Strategy Foresight Partnership LLP.

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Most Helpful Customer Reviews

6 of 6 people found the following review helpful By John L. Peterson on September 5, 2011
Format: Hardcover
This book presents the theory and process of how to use the computer to analyze very complex social situations that do not lend themselves to simplistic scenario analysis. It therefore provides an extraordinary view into a methodology that has great applications for very important situations, whether for governments, businesses or research institutes. If, for example, you wanted to seriously think through how a population might actually react to a catastrophic event, say, a very near miss by an asteroid, this would be the ticket .. . . and perhaps the only ticket, as there certainly isn't another approach in the public that would effectively help one think through all of the variables associated with such an event and exercise them in a variety of ways to expose the most interesting behavior modes -- that strategies can then be built around.

The principles and methodologies of this book have been practically used for developing national early warning systems for governments, so the approach is well tested and shown to be very effective.
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4 of 4 people found the following review helpful By jfarl on March 2, 2013
Format: Hardcover Verified Purchase
This is a good book, interesting and useful; It is however ridiculously priced, like most Springer books: about 80 'real' pages for $100! Printing quality is so-so and the figures, in black and white, are hard to read, even with a magnifier.

In fact, most if not all of the useful content of this book is easily found for free in PDF format on the Web site of the Swedish Morphological Society with the very significant added bonus that the figures are much easier to understand because they are in color and can be enlarged and displayed side-by-side.

This is why I rate it only 3 stars: I don't think it's worth buying, despite its quality.
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1 of 1 people found the following review helpful By UL on January 10, 2012
Format: Hardcover
I was expecting a lot more detail on GMA. However, for a start, this is a good book for someone who is just introducing himself to the world of wicked problems. Its a short read and can be finished in a day or 2.
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