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Enterprise efficiency analysis based on explainable artificial intelligence: From predictive algorithms to mechanisms
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AI
DOI：10.1016/j.ipm.2026.104666.png)
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Abstract
En 中文
• Integrates a multi-stage framework combining DEA, machine learning, and causal inference. • Evaluates enterprise efficiency in two distinct stages: innovation and commercialization. • Differentiates between predictive importance and causal effects using explainable AI and Bayesian networks. • Identifies employee count as the key variable in causal pathways influencing efficiency.
Keywords:
Enterprise efficiency
Explainable AI
Causal inference
Machine learning
DEA
Journal
I
IF:
6.9
Papers:
330
Citations:
0