AI-ESG Alignment in E-Commerce: Structured Literature Review Dataset (2021-2025)
Description
Dataset of 190 articles classified across a 2×3 AI×ESG matrix from a structured literature review (2021-2025). Includes automated screening formulas, Web of Science metadata, and decision logs. Enables systematic mapping of AI capabilities to ESG outcomes in e-commerce platforms. Data freeze: March 30, 2026.
Files
Steps to reproduce
1. Export data from Web of Science Core Collection using Topic Search: ("artificial intelligence" OR "machine learning" OR "generative AI" OR "algorithmic decision*" OR "AI-driven") AND ("electronic commerce" OR "e-commerce" OR "digital commerce" OR "online retail" OR "online marketplace*" OR "social commerce") AND (ESG OR sustainab* OR governance OR ethic* OR trust OR responsib*) 2. Apply filters: Publication Years 2021–2025; Document Types: Articles, Reviews 3. Download WoS metadata export (684 records) 4. Open AI-ESG-Screening-Formulas.xlsx file 5. Paste WoS metadata into columns A-D (Title, Abstract, Keywords Plus) 6. Excel formulas automatically calculate: Title_score (SUMPRODUCT with AI/ESG terms) Abstract_score (refined matching) KW_score (keyword verification) 7. Filter for records with Final_decision = "KEEP" (190 articles) 8. Assign each article to one of six thematic nodes (AI1/AI2 × ESG1/ESG2/ESG3) based on dimensional scores 9. Results: AI-ESG-Final-Dataset.csv with 190 classified articles See supplementary formulas documentation for detailed SUMPRODUCT syntax.