A generalized fuzzy Multiple-Layer NDEA: An application to performance-based budgeting
| Autor: | Hamidreza Eskandari, Peter Wanke, Mohamad Reza Amini, Adel Azar |
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| Rok vydání: | 2021 |
| Předmět: |
Structure (mathematical logic)
Measure (data warehouse) 020209 energy Network data 02 engineering and technology Fuzzy logic Standard deviation Power (physics) Multiple layer Component (UML) Statistics 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Software Mathematics |
| Popis: | Network data envelopment analysis (NDEA) is capable of considering operations and interdependence of a system’s component processes to measure efficiencies. There are numerous performance evaluation applications in which some indicators have hierarchical structures with a considerable number of sub-indicators. This problem of ignoring the hierarchical structure of indicators weakens the discrimination power of NDEA models and may result in inaccurate efficiency scores. In this paper we propose a generalized fuzzy Multiple-Layer NDEA (GFML-NDEA) model and GFML-NDEA-based composite indicators (GFML-NDEA-CI) to incorporate the hierarchical structures of indicators in the ambit of the particular two-stage NDEA models. To demonstrate the usefulness of the GFML-NDEA-CI model proposed, its application was tested by evaluating the efficiency of the performance-based budgeting (PBB) system in 14 governmental agencies in Iran. The comparative analysis results obtained from the GFML-NDEA-CI (multi-layer) model with those from the single-layer fuzzy NDEA-CI model indicate that the number of efficient decision-making units (DMUs) in the one-layer model is eight, whereas it is solely one DMU in the multi-layer model. The discrimination power of the multi-layer model proposed is significantly increased by observing that standard deviation of efficiency scores are increased by 41%, 61%, and 84% for possibility levels 0, 0.5, and 1, respectively. This is obtained while reducing information entropy, thus suggesting that the proposed model yields more reliable scores. |
| Databáze: | OpenAIRE |
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