Calculation Results of CCI Parameters for AI-Empowered Construction Safety

A 45.9% increase in the Comprehensive Competency Index (CCI) under an AI-empowered mode relative to a traditional mode was calculated. The dataset contains calculation results from a comparative experimental design and Analytic Hierarchy Process (AHP) evaluation, authored by Jing Guan and last updated in May 2026. It supports a framework for enhancing safety director competency in Engineering–Procurement–Construction projects.

Use Cases

• Benchmarking safety management competency improvements based on the reported 45.9% CCI increase.
• Applying the Analytic Hierarchy Process (AHP) for multi-criteria decision analysis in construction safety.
• Developing tiered improvement strategies for talent selection based on the proposed quantitative evaluation system.
• Training models to shift from experience-driven to data-driven safety governance as described in the framework.

Strengths

• Quantifies a 45.9% improvement in the Comprehensive Competency Index (CCI).
• Based on a comparative experimental design and Analytic Hierarchy Process (AHP) evaluation.
• Released under a permissive CC-BY-4.0 license for reuse.

Limitations

• Dataset is very small (5.5 KB), indicating limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Results from a comparative experimental design and Analytic Hierarchy Process (AHP) evaluation.

Freshness

Last updated 2026-05-18 17:24:40; freshness should be verified.