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Flexible Multidimensional Scaling for Human Smart Development Analysis in EU Countries

Author

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  • Malgorzata Markowska
  • Andrzej Sokolowski
  • Danuta Strahl

Abstract

Purpose: The aim of the paper is to propose a flexible procedure to Multidimensional Scaling, allowing to calculate the input distance matrix based on slightly different set of variables for each pair of objects. Design/Methodology/Approach: The procedure starts from the classical standardization of each variable. Before the calculation of flexible distance between two objects, we eliminate the variable with the biggest absolute value in the first object, and the same we do for the second object. So, we have two variables less in the list for these two objects. If by chance the same variable is pointed for elimination by both objects, the next variable with the biggest (out of both objects) absolute standardized value should be eliminated. With this procedure, each element of distance matrix is based on the same number of variables, but some of actual variables can be different. Findings: As an example – Flexible Multidimensional Scaling is performed on the list of 17 variables describing so called smart society, for 28 European Union countries. It shows how the proposed procedure works in practice. Practical Implications: The proposed flexible procedure can be used for the analysis of any problem treated by Multidimensional Scaling. Originality/Value: Flexible Multidimensional Scaling (FMDS) is a new idea and method. It eliminates some elements of subjective choice of initial variables and seems to be more robust against outliers than classical Multidimensional Scaling (MDS).

Suggested Citation

  • Malgorzata Markowska & Andrzej Sokolowski & Danuta Strahl, 2021. "Flexible Multidimensional Scaling for Human Smart Development Analysis in EU Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 4), pages 435-445.
    • Handle: RePEc:ers:journl:v:xxiv:y:2021:i:special4:p:435-445
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    References listed on IDEAS

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    1. Gary S. Becker, 1962. "Investment in Human Capital: A Theoretical Analysis," NBER Chapters, in: Investment in Human Beings, pages 9-49, National Bureau of Economic Research, Inc.
    2. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    3. Marcus Gumpert, 2019. "Multidimensional Core-peripheral Model," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 192-208.
    4. Malgorzata Markowska & Danuta Strahl & Andrzej Sokolowski, 2021. "Dynamic Cluster Analysis of Educated and Smart Society Development in European Union Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 4), pages 52-64.
    5. Marcus Gumpert, 2019. "Multidimensional Core-peripheral Model," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 192-208.
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    Citations

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    Cited by:

    1. Kozar Łukasz, 2021. "Non-Monetary Indicators of Social Exclusion – A Multidimensional Comparative Analysis of the Eu-10 Countries," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 25(4), pages 40-53, December.

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    More about this item

    Keywords

    Multidimensional scaling; flexibility; smart society; European Union countries.;
    All these keywords.

    JEL classification:

    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

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