Critical Performance Factors for Large World Cities - In Search of Qualitative Causal Patterns by means of Rough Set Analysis

  • Karima Kourtit DR. MBA
  • Peter Nijkamp
Keywords: urbanization, cities, performance, rough set analysis, piazza model

Abstract

In the currently emerging ‘urban century’, large cities and urban agglomerations are increasingly turning into (socio-)economic and political powerhouses of great importance. This paper offers a comparative assessment of the multidimensional performance profile of major cities in our world, with particular emphasis on the livability and economic features of these cities. The explanatory cohesive framework in the present study is offered by the so-called ‘urban piazza’ model. Using an extensive database on various rankings of global 40 cities (the so-called GPCI data base), the relative performance of these cities is ‘explained’ in a qualitative sense by means of a non-parametric ordinal ranking method, known as rough set analysis. The approach allows us to identify the driving forces that altogether are responsible for the economic and livability achievements of these cities. The empirical analysis highlights the combined ‘power’ of selected success conditions and drivers of these cities concerned. Our empirical results demonstrate that the geographical accessibility of these urban areas appears to play in many cases an important role.

 

Author Biography

Karima Kourtit, DR. MBA
Dr. Karima Kourtit (MBA) KTH Royal Institute of Technology School of Architecture and the Built Environment (ABE) Division of Urban and Regional Studies Drottning Kristinas väg 30 10044 Stockholm Sweden Telephone: +46 8 790 94 30 E-mail: karima.kourtit@abe.kth.se KTH-website: www.kth.se/profile/karimak orcid.org/0000-0002-7171-994X

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Published
2017-05-09
How to Cite
Kourtit, K. and Nijkamp, P. (2017) “Critical Performance Factors for Large World Cities - In Search of Qualitative Causal Patterns by means of Rough Set Analysis”, REGION, 4(1), pp. 51-70. doi: 10.18335/region.v4i1.118.
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