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)