Prioritizing the European Investment Sectors Based on Different Economic, Social, and Governance Factors Using a Fuzzy-MEREC-AROMAN Decision-Making Model DOI Open Access
Andreea Larisa Olteanu, Alina Elena Ionașcu,

Sorinel Cosma

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7790 - 7790

Published: Sept. 6, 2024

This study tackles the challenge of identifying optimal investment sectors amid growing importance environmental, social, and governance (ESG) factors, which are often complex conflicting. research aims to effectively evaluate prioritize ten based on twelve ESG criteria by integrating expert evaluations with two advanced multi-criteria decision-making (MCDM) methods. Three teams assessed each sector’s performance these using fuzzy logic manage uncertainties in judgments. The MEREC (MEthod Removal Effects Criteria) identified biodiversity land use as most critical factor, while transparency disclosure was least significant. AROMAN (Alternative Ranking Order Method Accounting for two-step Normalization) method further used rank alternative sectors, impact investing funds emerging top choice, followed renewable energy sustainable responsible funds. Conversely, ESG-compliant stocks, ESG-focused exchange-traded funds, real estate trusts ranked lowest. study’s findings were validated through comparisons other MCDM tools sensitivity analysis, confirming robustness proposed model. offers a valuable framework investors looking incorporate considerations into their decision-making, promoting practices.

Language: Английский

Evaluating solar power plant sites using integrated GIS and MCDM methods: a case study in Kermanshah Province DOI Creative Commons
Iman Zandi, Aynaz Lotfata

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 26, 2025

This study utilizes an integrated Geographic Information System (GIS)-based Multi-Criteria Decision-Making (MCDM) approach to perform Solar Power Plant Site Selection (SPPSS) in Kermanshah Province, Iran. It introduces a novel group weighting method, the Dempster-based Best-Worst Method (DBWM), which combines weights vectors derived from experts' opinions. The also conducts comprehensive sensitivity analysis comparing four GIS-based models for SPPSS. Findings indicate that Inverse Distance Weighted (IDW) method is most precise interpolation, was subsequently applied analysis. Results demonstrate DBWM-Technique Order Preference by Similarity Ideal Solution (GIS-based DBWM-TOPSIS) model stable, identifying slope as primary criterion Based on this model, 3% of area classified very low suitability, 9% low, 24% moderate, 33% high, and 31% high suitability. highlights substantial impact selecting appropriate spatial techniques uses normalization standardize input criteria with varied units ranges, enhancing comparability within MCDM process. Eslamabad-e Gharb, Kangavar, Gilan-e Gharb counties emerged suitable locations solar power plant (SPP) development.

Language: Английский

Citations

1

Prioritizing the European Investment Sectors Based on Different Economic, Social, and Governance Factors Using a Fuzzy-MEREC-AROMAN Decision-Making Model DOI Open Access
Andreea Larisa Olteanu, Alina Elena Ionașcu,

Sorinel Cosma

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7790 - 7790

Published: Sept. 6, 2024

This study tackles the challenge of identifying optimal investment sectors amid growing importance environmental, social, and governance (ESG) factors, which are often complex conflicting. research aims to effectively evaluate prioritize ten based on twelve ESG criteria by integrating expert evaluations with two advanced multi-criteria decision-making (MCDM) methods. Three teams assessed each sector’s performance these using fuzzy logic manage uncertainties in judgments. The MEREC (MEthod Removal Effects Criteria) identified biodiversity land use as most critical factor, while transparency disclosure was least significant. AROMAN (Alternative Ranking Order Method Accounting for two-step Normalization) method further used rank alternative sectors, impact investing funds emerging top choice, followed renewable energy sustainable responsible funds. Conversely, ESG-compliant stocks, ESG-focused exchange-traded funds, real estate trusts ranked lowest. study’s findings were validated through comparisons other MCDM tools sensitivity analysis, confirming robustness proposed model. offers a valuable framework investors looking incorporate considerations into their decision-making, promoting practices.

Language: Английский

Citations

1