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Cities-benchmarking algorithm: a meta-ranking exercise

Cities-benchmarking algorithm: a meta-ranking exercise The World Capital Institute uses the Most Admired Knowledge Cities (MAKCi) framework to compare cities. This framework considers other capitals than the financial one and allows to evaluate cities as knowledge cities. The MAKCi framework contains specifications about which indicators should be used; nevertheless, the same kind of information is not always available from all the cities. Besides, the data could be non-existent, restricted from public use, or hard to find. For this reason, comparing cities through the MAKCi framework becomes a major challenge. The purpose of this paper is to propose an algorithm to compare cities using reliable and available information for all the cities compared at the evaluation time. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Knowledge-Based Development Inderscience Publishers

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
2040-4468
eISSN
2040-4476
DOI
10.1504/IJKBD.2012.047036
Publisher site
See Article on Publisher Site

Abstract

The World Capital Institute uses the Most Admired Knowledge Cities (MAKCi) framework to compare cities. This framework considers other capitals than the financial one and allows to evaluate cities as knowledge cities. The MAKCi framework contains specifications about which indicators should be used; nevertheless, the same kind of information is not always available from all the cities. Besides, the data could be non-existent, restricted from public use, or hard to find. For this reason, comparing cities through the MAKCi framework becomes a major challenge. The purpose of this paper is to propose an algorithm to compare cities using reliable and available information for all the cities compared at the evaluation time.

Journal

International Journal of Knowledge-Based DevelopmentInderscience Publishers

Published: Jan 1, 2012

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