Corporate Management Performance Predictions for Korean Listed Companies, 2016-2023

From 2016 to 2023, this dataset contains information on 1,271 listed companies from Korea's KOSPI and KOSDAQ markets, used to predict corporate management performance. It was created by Xiao Wang and combines financial variables with strategic indicators derived from text mining CEO messages in sustainability reports. The dataset, last updated in May 2026, is provided as an Excel file under a CC-BY-4.0 license.

Use Cases

• Predict corporate management performance based on combined financial and strategic text data.
• Benchmark machine learning and deep learning classifiers (e.g., Transformer, LSTM) for financial prediction tasks.
• Analyze the impact of strategic communication in sustainability reports on corporate outcomes.
• Apply the Sustainable Balanced Scorecard (SBSC) framework to categorize text-mined strategic variables.

Strengths

• Dataset covers 1,271 companies over an 8-year period (2016-2023), providing a longitudinal view.
• Model performance metrics are provided, with the best hybrid model achieving Accuracy=0.8467, AUC=0.8481, and F1=0.8572.
• Methodology is clearly described, combining established financial variables with novel text-mined strategic indicators.

Limitations

• Row count and column-level documentation are unknown, which may limit suitability assessment.
• Data is specific to Korean markets (KOSPI and KOSDAQ), which may limit generalizability.
• The dataset is very small (5.5 KB), suggesting it may contain aggregated results or a limited feature set rather than raw source data.

Provenance

Source

figshare, author Xiao Wang.

Collection Method

Financial variables selected from prior accounting research; strategic variables derived via text mining of CEO messages in sustainability reports.

Time Range

2016-2023

Freshness

Last updated 2026-05-06 17:32:45; freshness should be verified.

Geography

South Korea (companies listed on KOSPI and KOSDAQ markets)