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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.09020 |
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| _version_ | 1866915385684525056 |
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| author | Asem, Ebenezer Fan, Ruijie Tian, Gloria Y. |
| author_facet | Asem, Ebenezer Fan, Ruijie Tian, Gloria Y. |
| contents | This paper explores how AI-powered tools could be leveraged to streamline the process of identifying, screening, and analyzing relevant literature in academic research. More specifically, we examine the documented relationship between environmental, social, and governance (ESG) factors and the cost of capital (CoC). By applying an AI-assisted workflow, we identified 36 published studies, synthesized their key findings, and highlighted relevant theories, moderators, and methodological challenges. Our analyses demonstrate the value of AI tools in enhancing business research processes and also contribute to the growing literature on the importance of ESG in the field of corporate finance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_09020 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | ESG and the Cost of Capital: Insights from an AI-Assisted Systematic Literature Review Asem, Ebenezer Fan, Ruijie Tian, Gloria Y. Computers and Society This paper explores how AI-powered tools could be leveraged to streamline the process of identifying, screening, and analyzing relevant literature in academic research. More specifically, we examine the documented relationship between environmental, social, and governance (ESG) factors and the cost of capital (CoC). By applying an AI-assisted workflow, we identified 36 published studies, synthesized their key findings, and highlighted relevant theories, moderators, and methodological challenges. Our analyses demonstrate the value of AI tools in enhancing business research processes and also contribute to the growing literature on the importance of ESG in the field of corporate finance. |
| title | ESG and the Cost of Capital: Insights from an AI-Assisted Systematic Literature Review |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2507.09020 |