Optimizing sustainable industry investment selection: A golden cut-enhanced quantum spherical fuzzy decision-making approach

APPLIED SOFT COMPUTING(2023)

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摘要
This study aims to rank sustainable industry alternatives in emerging markets based on the directional impact relations of the environmental, social, and governance (ESG) index components for a socially and environmentally conscious investment strategy. To achieve this goal, we employ a golden cut-enhanced quantum spherical fuzzy decision-making approach. Specifically, we first use a quantum spherical fuzzy DEMATEL technique to identify the impact-relation directions and the weights of the ESG criteria set. Second, we employ the extended TOPSIS with the quantum spherical fuzzy sets to rank the industry alternatives concerning their directional ESG performances. The findings show that (i) H20 Emissions, Innovation, Community Investment, Gender Equity, Human Rights, and CSR Strategy are the main influencing factors based on their impact-relations directional scores, (ii) Resource Usage, Product Responsibility, and Shareholders' Rights are the set of criteria under the influence of remaining ESG, (iii) Innovation is the strongest ESG performance criterion, whereas Human Rights is the weakest, (iv) technology and communication are the best-performing industries based on the directional ESG index performance scores, whereas real estate and basic materials industries are the worst performing. The study provides valuable and actionable insights for companies that aim to make socially responsible investments.
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关键词
Decision analytics,Sustainability,Emerging markets,Golden cut,Quantum spherical fuzzy sets
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