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Article title
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Abstract
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Keywords
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Relevance to practice
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1. Introduction
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2. Literature review
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2.1. ESG Ratings: challenges and existing predictive models
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2.2. The impact of green innovation on ESG ratings
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2.3. Machine learning: Advancing the precision of ESG rating predictions
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2.4. Economic development and its impact on ESG ratings
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3. Data
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3.1. Choice of Indicators
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3.2. Data preparation and standardization
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3.3. Evaluating correlations and multi-collinearity
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4. Methodology
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4.1. Hypothesis Testing
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4.1.2. H2. The impact of green innovation on machine learning predictions of ESG ratings
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4.1.3. H3: Differential Impact of green innovation in economic contexts
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5. Empirical results
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5.1. H1: Impact of green innovation on ESG ratings
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5.1.1. Findings
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5.1.2. Robustness Tests
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5.1.3. Discussion
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5.2. H2: The impact of green innovation on machine learning predictions of ESG ratings
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5.2.1. Findings
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5.2.2. Robustness tests
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5.2.3. Discussion
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5.3. H3: Differential impact of green innovation in economic contexts
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5.3.1. Findings
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5.3.2. Robustness tests
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5.3.3. Discussion
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6. Conclusion, limitations, and future research
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6.1. Conclusions
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6.2. Limitations
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6.3. Future research
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References
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