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

Katarzyna A. Kurek (), Wim Heijman, Johan Ophem, Stanisław Gędek and Jacek Strojny
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Katarzyna A. Kurek: Wageningen University and Research
Wim Heijman: Wageningen University and Research
Johan Ophem: Wageningen University and Research
Stanisław Gędek: Rzeszów University of Technology
Jacek Strojny: Rzeszów University of Technology

Quality & Quantity: International Journal of Methodology, 2022, vol. 56, issue 3, No 24, 1389 pages

Abstract: 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.

Keywords: Local competitiveness; Multivariate models; Multicriteria decision-making method; Socioeconomic indicators; Principal Component Analysis; Analytical Hierarchy Process; Non-parametric testing (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11135-021-01181-z

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