Data Envelopment Analysis (BCC / VRS model)
DEA-BCC (Data Envelopment Analysis (BCC / VRS model)) is a dea multi-criteria decision-making (MCDM) method introduced by Banker, R. D., Charnes, A., Cooper, W. W. in 1984. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
Read the full method
Sign in with a free account to read this section.
Method map
The neighbourhood of related methods — select a node to explore.
When to use it
BCC extends CCR by adding the convexity constraint Σλ_j=1, allowing Variable Returns to Scale (VRS). BCC efficiency ≥ CCR efficiency always. Use BCC when DMUs operate at different scales (e.g., hospitals of varying sizes). Scale efficiency = CCR/BCC reveals whether inefficiency stems from scale vs. pure technical causes.
Strengths & limitations
- Follows a transparent, reproducible computational procedure that can be audited step by step.
- Handles multiple criteria of differing scales and units within a single decision matrix.
- Assumes full compensation — a strong score on one criterion can offset a weak score on another.
Sources
- Banker, R. D., Charnes, A., Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science DOI: 10.1287/mnsc.30.9.1078 ↗
How to cite this page
ScholarGate. (2026, June 2). Data Envelopment Analysis (BCC / VRS model). ScholarGate. https://scholargate.app/en/decision-making/dea-bcc