Title: The MAKCi index: using logistic regression modelling for predicting most admired knowledge cities

Authors: Carlos J. García Meza; M. Alicia Leal Garza

Addresses: Department of Industrial Engineering and Systems, ITESM, Ave. E. Garza Sada 2501, Col. Tecnológico, Monterrey, NL, CP 64849, México. ' Department of Industrial Engineering and Systems, ITESM, Ave. E. Garza Sada 2501, Col. Tecnológico, Monterrey, NL, CP 64849, México

Abstract: This study applied logistic regression modelling for the development of a quantitative index for most admired knowledge cities. Drawing on the MAKCi framework and the theoretical model of the generic capitals system, a MAKCi index was defined as the probability a city has of being selected as the most admired knowledge city. The resulting logistic regression model was satisfactorily tested for validity, and it was utilised for evaluating and ranking cities.

Keywords: most admired cities; MAKCi; knowledge cities; KBD; generic capitals system; measurement; logistic regression modelling; knowledge-based development; city rankings.

DOI: 10.1504/IJKBD.2012.045571

International Journal of Knowledge-Based Development, 2012 Vol.3 No.1, pp.83 - 99

Received: 16 Dec 2011
Accepted: 20 Dec 2011

Published online: 31 Jul 2014 *

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