A generalized fuzzy Multiple-Layer NDEA: An application to performance-based budgeting

Network data envelopment analysis (NDEA) is capable of considering operations and interdependence a system’s component processes to measure efficiencies. There are numerous performance evaluation applications in which some indicators have hierarchical structures with considerable number sub-indicators. This problem ignoring the structure weakens discrimination power NDEA models may result inaccurate efficiency scores. In this paper we propose generalized fuzzy Multiple-Layer (GFML-NDEA) model GFML-NDEA-based composite (GFML-NDEA-CI) incorporate ambit particular two-stage models. To demonstrate usefulness GFML-NDEA-CI proposed, its application was tested by evaluating performance-based budgeting (PBB) system 14 governmental agencies Iran. The comparative results obtained from (multi-layer) those single-layer NDEA-CI indicate that efficient decision-making units (DMUs) one-layer eight, whereas it solely one DMU multi-layer model. proposed significantly increased observing standard deviation scores 41%, 61%, 84% for possibility levels 0, 0.5, 1, respectively. while reducing information entropy, thus suggesting yields more reliable • We multilayer network DEA Fuzzy set theory used represent vagueness ambiguity data. multiple layer based-CI A case study demonstrates applicability