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

Author

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  • Carlos J. García Meza
  • M. Alicia Leal Garza

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.

Suggested Citation

  • Carlos J. García Meza & M. Alicia Leal Garza, 2012. "The MAKCi index: using logistic regression modelling for predicting most admired knowledge cities," International Journal of Knowledge-Based Development, Inderscience Enterprises Ltd, vol. 3(1), pages 83-99.
    • Handle: RePEc:ids:ijkbde:v:3:y:2012:i:1:p:83-99
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