<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The aim of this work is to compare EU countries in their efforts to implement the circular economy model and to indicate the EU’s strategic objectives in this area, by analyzing circular economy indicators within the member states. To achieve this, a qualitative and quantitative analysis of the following indicators in THE EUROSTAT database has been carried out: total waste recycling rate, recycling rate of construction and demolition waste, recycling rate of electronic waste, and contribution of recyclable materials to the demand for raw materials in 2019 within the EU. A linear multiple regression was achieved through the SRSS program, which showed that the dependent variable of gross domestic product (GDP) is explained by 69%, and 68% respectively of the recycling rate of construction waste and the recycling rate of electronic waste. The analysis has shown significant correlation between the recycling rate of construction waste and the recycling rate of electronic waste.</p>
</abstract>

The aim of this work is to compare EU countries in their efforts to implement the circular economy model and to indicate the EU’s strategic objectives in this area, by analyzing circular economy indicators within the member states. To achieve this, a qualitative and quantitative analysis of the following indicators in THE EUROSTAT database has been carried out: total waste recycling rate, recycling rate of construction and demolition waste, recycling rate of electronic waste, and contribution of recyclable materials to the demand for raw materials in 2019 within the EU. A linear multiple regression was achieved through the SRSS program, which showed that the dependent variable of gross domestic product (GDP) is explained by 69%, and 68% respectively of the recycling rate of construction waste and the recycling rate of electronic waste. The analysis has shown significant correlation between the recycling rate of construction waste and the recycling rate of electronic waste.

Circular economy indicators – multiple linear regression

Proceedings of the International Conference on Business Excellence

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Circular economy indicators \u2013 multiple linear regression"}

The aim of this work is to compare EU countries in their efforts to implement the circular economy model and to indicate the EU’s strategic objectives in this...

Circular economy indicators – multiple linear regression

Online veröffentlicht: 08. Aug. 2022

Seitenbereich: 437 - 445

DOI: https://doi.org/10.2478/picbe-2022-0043

Schlüsselwörter
circular economy, circularity indicators, gross domestic product, waste recycling rate, recyclable materials

© 2022 Cristina Maria Sterie et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Circular economy indicators – multiple linear regression

Online veröffentlicht: 08. Aug. 2022

Seitenbereich: 437 - 445

DOI: https://doi.org/10.2478/picbe-2022-0043

Schlüsselwörtercircular economy, circularity indicators, gross domestic product, waste recycling rate, recyclable materials

© 2022 Cristina Maria Sterie et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
circular economy, circularity indicators, gross domestic product, waste recycling rate, recyclable materials