EconPapers    
Economics at your fingertips  
 

Deep Complexity and the Social Sciences

Robert Delorme

in Books from Edward Elgar Publishing

Abstract: In this innovative work, Robert Delorme comprehensively explores uncertainty (the irreducibility to numerically measurable probabilities) and ignorance in economics, management and the social sciences through an alternative, systematically built analytical framework. This unique book takes uncertainty and ignorance seriously and addresses them as instances of ‘deep complexity’ (problem situations so deeply ill-structured that they cannot be grasped with the concepts and tools of classical science). Building on the works of Herbert Simon, Heinz von Foerster and John von Neumann, the author develops an alternative framework that encompasses, rather than rejects, the classical framework. The outcome of this novel approach is ‘effective deep complexity’, comprising three aspects: an effective alternative framework, which brings an answer to a fundamental issue on the implications of uncertainty for scientific reasoning; a behavioural theory of deeply ill-structured problem-situations; and a decision-and-action support system.

Keywords: Economics and Finance (search for similar items in EconPapers)
JEL-codes: B52 (search for similar items in EconPapers)
Date: 2010
ISBN: 9781849800266
References: Add references at CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
https://www.elgaronline.com/view/9781849800266.xml (application/pdf)
Our link check indicates that this URL is bad, the error code is: 503 Service Temporarily Unavailable

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:elg:eebook:13888

Ordering information: This item can be ordered from
http://www.e-elgar.com

Access Statistics for this book

More books in Books from Edward Elgar Publishing
Bibliographic data for series maintained by Darrel McCalla ().

 
Page updated 2025-03-31
Handle: RePEc:elg:eebook:13888