Dynamic-Network DEA with Carryovers and Bad Outputs
DEA-DYNAMIC-NETWORK (Dynamic-Network DEA with Carryovers and Bad Outputs) is a dea multi-criteria decision-making (MCDM) method introduced by Fukuyama, H. Weber, W. L. in 2013. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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When to use it
DEA-DYNAMIC-NETWORK extends static two-stage network DEA over T time periods by incorporating (i) carryover assets c^t that link current-period choices to future production possibilities, and (ii) lagged bad inputs b^{t-1} (e.g. nonperforming loans from prior period) that constrain stage 1 capacity. Performance is measured via the weighted DN-directional distance function DN~D. Efficiency: DN~D=0. Productivity change: DNL indicator decomposed into efficiency change (DNEC) and technical change (DNTC). The nonlinear LP is linearised using Kuosmanen's (2005) variable substitution γ=φλ.
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
- Fukuyama, H., Weber, W. L. (2013). A dynamic network DEA model with an application to Japanese Shinkin banks. Efficiency and Productivity Growth: Modelling in the Financial Services Industry DOI: 10.1002/9781118541531.ch9 ↗
How to cite this page
ScholarGate. (2026, June 2). Dynamic-Network DEA with Carryovers and Bad Outputs. ScholarGate. https://scholargate.app/en/decision-making/dea-dynamic-network