AI Performance by Technological Complementarity Using Alternative CEM Methods

9.5 KB of data in XLS format, authored by Sangrok Lee and last updated on May 5, 2026. The dataset appears to measure AI performance in relation to technological complementarity, likely using Coarsened Exact Matching (CEM) techniques. Its small size suggests it contains summary statistics or model results rather than raw observational data.

Use Cases

• Modeling the relationship between AI performance and technological complementarity based on the described research focus.
• Comparing results from different Coarsened Exact Matching (CEM) methodologies as suggested by the title.
• Conducting meta-analysis or replication studies on technology complementarity effects.

Strengths

• Dataset is small at 9.5 KB, facilitating quick download and inspection.
• Released under a permissive CC-BY-4.0 license, allowing for broad reuse and modification.
• Has a specific last update timestamp of 2026-05-05 17:32:22.

Limitations

• Row count is unknown, which may limit suitability assessment for statistical analysis.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Sangrok Lee via figshare

Collection Method

Likely derived from research analysis using Coarsened Exact Matching (CEM).

Freshness

Last updated 2026-05-05 17:32:22; freshness should be verified.