Literature DB >> 33991754

An integrated approach of PCA and PROMETHEE in spatial assessment of circular economy indicators.

Jelena J Stanković1, Vesna Janković-Milić2, Ivana Marjanović3, Jasmina Janjić4.   

Abstract

In order to ensure environmental sustainability, reducing the consumption of renewable resources, finding adequate substitutes for non-renewable resources, and reducing the generation of waste and pollution are necessities. The concept of circular economy one of the possible and good responses to improve the sustainability of the system, as it places particular emphasis on the reduction, reutilization and recycling of its elements. The paper presents a comparative analysis of the circular economy development in European Union countries based on the dataset encompasses 11 indicators, covering the seven-year period with biennial data. The analysis was performed using the integrated approach of the Principal Component Analysis and PROMETHEE with the aim of creating a composite index as a measure of the development of the circular economy at the national level. The ranking outcomes indicate that during the observed period Germany has the most developed circular economy, followed by the Netherlands, France and Austria. Additionally, the results of the research clearly indicate the positive correlation between the development of circular economies at the national level and the socio-economic development of the country, while progress in the circular economy has no immediate impact on environmental sustainability, but the effects are realized subsequently, with the intensity of the relationship increasing in two-year lag periods.
Copyright © 2021 Elsevier Ltd. All rights reserved.

Keywords:  Circular economy; Environmental sustainability; PROMETHEE method; Principal component analysis; Sustainable development

Year:  2021        PMID: 33991754     DOI: 10.1016/j.wasman.2021.04.057

Source DB:  PubMed          Journal:  Waste Manag        ISSN: 0956-053X            Impact factor:   7.145


  1 in total

1.  Factor analysis, sparse PCA, and Sum of Ranking Differences-based improvements of the Promethee-GAIA multicriteria decision support technique.

Authors:  János Abonyi; Tímea Czvetkó; Zsolt T Kosztyán; Károly Héberger
Journal:  PLoS One       Date:  2022-02-25       Impact factor: 3.240

  1 in total

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