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Measuring local competitiveness: comparing and integrating two methods PCA and AHP

Author

Listed:
  • Katarzyna A. Kurek

    (Wageningen University and Research)

  • Wim Heijman

    (Wageningen University and Research
    Czech University of Life Sciences)

  • Johan Ophem

    (Wageningen University and Research)

  • Stanisław Gędek

    (Rzeszów University of Technology)

  • Jacek Strojny

    (Rzeszów University of Technology)

Abstract

This article discusses two methods to measure the concept of local competitiveness: Principal Component Analysis (PCA) and Analytical Hierarchy Process (AHP). The goal of this analysis is to determine whether these two methods used in social sciences research lead to comparable model results. By non-parametric tests we show that there is a significant correlation between the PCA and AHP local competitiveness indexes. Thereafter, a developed mixed method examination of whether the methods can be used interchangeably is presented and illustrated with detailed examples of two mixed approaches. The mixed method confirms the correlation between the PCA and AHP models. However, the mixed modelling results indicate the utility of the PCA in the situation of a multicriteria local competitiveness data examination.

Suggested Citation

  • Katarzyna A. Kurek & Wim Heijman & Johan Ophem & Stanisław Gędek & Jacek Strojny, 2022. "Measuring local competitiveness: comparing and integrating two methods PCA and AHP," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(3), pages 1371-1389, June.
    • Handle: RePEc:spr:qualqt:v:56:y:2022:i:3:d:10.1007_s11135-021-01181-z
    DOI: 10.1007/s11135-021-01181-z
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    1. Juan Li & Xunzhou Chunyu & Feng Huang, 2022. "Land Use Pattern Changes and the Driving Forces in the Shiyang River Basin from 2000 to 2018," Sustainability, MDPI, vol. 15(1), pages 1-27, December.

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