Evolution: Complexity, uncertainty and innovation

Simple item page
dc.contributor.authorAllen, Peter M.
dc.date.accessioned2016-06-14T11:57:40Z
dc.date.available2016-06-14T11:57:40Z
dc.date.issued2014-02-21
dc.description.abstractComplexity science provides a general mathematical basis for evolutionary thinking. It makes us face the inherent, irreducible nature of uncertainty and the limits to knowledge and prediction. Complex, evolutionary systems work on the basis of on-going, continuous internal processes of exploration, experimentation and innovation at their underlying levels. This is acted upon by the level above, leading to a selection process on the lower levels and a probing of the stability of the level above. This could either be an organizational level above, or the potential market place. Models aimed at predicting system behaviour therefore consist of assumptions of constraints on the micro-level – and because of inertia or conformity may be approximately true for some unspecified time. However, systems without strong mechanisms of repression and conformity will evolve, innovate and change, creating new emergent structures, capabilities and characteristics. Systems with no individual freedom at their lower levels will have predictable behaviour in the short term – but will not survive in the long term. Creative, innovative, evolving systems, on the other hand, will more probably survive over longer times, but will not have predictable characteristics or behaviour. These minimal mechanisms are all that are required to explain (though not predict) the co-evolutionary processes occurring in markets, organizations, and indeed in emergent, evolutionary communities of practice. Some examples will be presented briefly.en_UK
dc.identifier.citationAllen, P. M. (2014) Evolution: Complexity, uncertainty and innovation, Journal of Evolutionary Economics, Vol. 24, Iss. 2, pp. 265-289en_UK
dc.identifier.issn0936-9937
dc.identifier.urihttp://dx.doi.org/10.1007/s00191-014-0340-1
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/9976
dc.language.isoenen_UK
dc.publisherSpringer Verlagen_UK
dc.rightsAttribution-Non-Commercial-No Derivatives 3.0 Unported (CC BY-NC-ND 3.0). You are free to: Share — copy and redistribute the material in any medium or format. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Information: Non-Commercial — You may not use the material for commercial purposes. No Derivatives — If you remix, transform, or build upon the material, you may not distribute the modified material. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.en_UK
dc.rightsThe final publication is available at Springer via http://dx.doi.org/10.1007/s00191-014-0340-1en_UK
dc.subjectEvolutionen_UK
dc.titleEvolution: Complexity, uncertainty and innovationen_UK
dc.typeArticleen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Evolution_Complexity_uncertainty_and_innovation_2014.pdf
Size:
1.1 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.79 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SoM)