ESG Sustainable Management Report Dataset for Predicting Corporate Management Performance Using AI: CEO Strategy Insights

This dataset integrates corporate ESG (Environmental, Social, and Governance) sustainability management report data with firm-level financial indicators, aimed at predicting corporate management performance using AI. CEO strategic orientation was classified using the SBSC (Sustainability Balanced Scorecard) framework into five categories: financial, customer, internal process, learning and growth, and sustainability.

Strategic classification process:

• Keywords with TF-IDF ≥ 1.5 were extracted from each CEO’s message in the sustainability report.

• Keywords were categorized into the five SBSC perspectives.

• The category with the highest keyword frequency determined the company’s strategic emphasis.

• A binary indicator (1 for the dominant category, 0 for others) was assigned accordingly.

Data coverage:

• Period: 2016–2023

• Scope: KOSPI and KOSDAQ listed companies in South Korea

• Sources:

  • CEO message text and ESG indicators from the ESG Portal Site

  • Financial data from NICE Credit Rating Information Value Search

Variables (partial list):

• name: Company name

• stock: Stock code

• year: Reporting year

• KOSPI: Market type indicator

• fnd_year: Foundation year

• ind: Industry code

• own, forn: Ownership ratios

• big4: Big4 audit indicator

• c_asset, inv, asset, sales, cogs, dep, tax, rec, ni, ocf, cash, tan, land, cip, intan: Financial statement metrics (in KRW)

• finance, customer, internal, learning_growth, sustainability: Binary variables indicating SBSC strategy classification

Potential uses:

• AI/ML modeling for corporate performance prediction

• ESG–financial performance relationship analysis

• Text–numeric data fusion for strategic decision-making research

File format: Microsoft Excel (.xls)
License: Publicly accessible data (processed and compiled for research purposes)