Journal article

Competitiveness of nations: A knowledge discovery examination

Zanakis S, Becerra-Fernandez I ...see all

European Journal of Operational Research, vol. 166, issue 1 SPEC. ISS. (2005) pp. 185-211

  • 66


    Mendeley users who have this article in their library.
  • 41


    Citations of this article.
  • 5.3k


    ScienceDirect users who have downloaded this article.
Sign in to save reference


This paper presents the insights gained from the use of data mining and multivariate statistical techniques to identify important factors associated with a country's competitiveness and the development of knowledge discovery in databases (KDD) models to predict it. In addition to stepwise regression and weighted non-linear programming techniques, intelligent learning techniques (artificial neural networks), and inferential techniques (classification and regression trees), were applied to a dataset of 43 countries from the World Competitiveness Yearbook (WCY). The dataset included 55 variables on economic, internationalization, governmental, financial, infrastructure, management, science and technology, as well as demographic and cultural characteristics. Exploratory data analysis and parameter calibration of the intelligent method architectures preceded the development and evaluation of reasonably accurate models (mean absolute error

Author-supplied keywords

  • Competitiveness
  • Country comparisons
  • Data mining
  • Knowledge discovery
  • Statistics

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Get full text


  • Stelios H. Zanakis

  • Irma Becerra-Fernandez

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free