Assessment of Türkiye’s renewable energy, economic growth, and emissions (2000-2021): A decision-making approach with MAXC and MUTRISS models

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Özet

This study investigates Türkiye’s performance in renewable energy utilization, economic growth, and carbon emissions between 2000 and 2021 through the application of multi-criteria decision-making (MCDM) methods. By employing MAXC and MUTRISS as decision-making models, this study facilitates the integrated assessment of economic development and environmental sustainability objectives. The MAXC-based analysis identifies economic growth (GDP) as the most influential criterion aligned with national development objectives, while environmental sustainability emerges as a secondary yet essential component. Renewable energy consumption is underscored as a fundamental element of sustainable development. The MUTRISS findings indicate that Türkiye exhibited its highest overall performance in 2004, whereas 2007 and 2008 were marked by the lowest performance levels, potentially reflecting the adverse effects of economic downturns and environmental pressures. To validate the robustness of the applied methods, comparative analyses were conducted with other MCDM techniques. Spearman rank correlation results reveal strong concordance between MAXC and objective weighting methods such as Entropy, MPSI, and IDOCRIW, while showing a negative correlation with CILOS. Conversely, MUTRISS demonstrated moderate positive correlations with PIV, SAW, and CoCoSo, indicating relatively lower ranking consistency. The findings contribute to the methodological evaluation of MCDM tools and emphasize the importance of integrated economic–environmental policy approaches in sustainability assessments.

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dc.contributor.authorMacit, Nazife Sahin
dc.date.accessioned2026-10-22T10:52:17.089015086Z
dc.date.available2026-10-22T10:52:17.089015086Z
dc.date.issued2025
dc.description.abstractThis study investigates Türkiye’s performance in renewable energy utilization, economic growth, and carbon emissions between 2000 and 2021 through the application of multi-criteria decision-making (MCDM) methods. By employing MAXC and MUTRISS as decision-making models, this study facilitates the integrated assessment of economic development and environmental sustainability objectives. The MAXC-based analysis identifies economic growth (GDP) as the most influential criterion aligned with national development objectives, while environmental sustainability emerges as a secondary yet essential component. Renewable energy consumption is underscored as a fundamental element of sustainable development. The MUTRISS findings indicate that Türkiye exhibited its highest overall performance in 2004, whereas 2007 and 2008 were marked by the lowest performance levels, potentially reflecting the adverse effects of economic downturns and environmental pressures. To validate the robustness of the applied methods, comparative analyses were conducted with other MCDM techniques. Spearman rank correlation results reveal strong concordance between MAXC and objective weighting methods such as Entropy, MPSI, and IDOCRIW, while showing a negative correlation with CILOS. Conversely, MUTRISS demonstrated moderate positive correlations with PIV, SAW, and CoCoSo, indicating relatively lower ranking consistency. The findings contribute to the methodological evaluation of MCDM tools and emphasize the importance of integrated economic–environmental policy approaches in sustainability assessments.
dc.identifier.eissn2651-4117
dc.identifier.endpage437
dc.identifier.issn1302-1966
dc.identifier.issue2
dc.identifier.startpage421
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/19566
dc.identifier.volume27
dc.language.isoen
dc.relation.ispartofAfyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectÇevre Çalışmaları
dc.subjectİktisat
dc.titleAssessment of Türkiye’s renewable energy, economic growth, and emissions (2000-2021): A decision-making approach with MAXC and MUTRISS models
dc.typeArticle
rdl.citation.trdizin0
rdl.source.indexTRDIZIN