2026-10-07T04:58:40Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34028859 2026-09-30T03:45:22Z category_27634 category_25969 category_28864 category_29173 item_type_3 month_year_09_2026

Redes de proveedores del Estado peruano: vínculos entidad-proveedor, concentración, dependencia y validación de sanciones, 2022–2024 Miluska Rodriguez-Saavedra (23594950) Public administration Financial economics Artificial intelligence not elsewhere classified Machine learning not elsewhere classified Public procurement and innovation Supplier networks Network analysis (Planning). Graph neural networks, concentration 0 Procurement risk <p dir="ltr">This dataset contains network-based public procurement data from Peru for the period 2022–2024, prepared for the analysis of concentration, dependency, and atypical structures in state supplier networks.</p><p dir="ltr">The database includes entity–supplier relationships, supplier-level and entity-level network measures, and consortium-based links between suppliers. It contains information on awarded amounts, number of procurement items, recurrence of supplier–entity relationships, supplier concentration, entity dependency, degree, weighted degree, PageRank, betweenness centrality, community membership, community size, HHI indicators, direct contracting, single-bid participation, consortium participation, and other procurement-related characteristics.</p><p dir="ltr">The dataset is organized into multiple analytical components, including annual entity–supplier edge lists, supplier-year node attributes, entity-year node attributes, and supplier–supplier links derived from consortium participation.</p><p dir="ltr">An external validation variable related to subsequent supplier sanctions is also included. This variable is intended for ex post validation and should not be used as a predictor when training unsupervised graph-based anomaly-detection models.</p><p dir="ltr">The database was constructed from official public procurement information from Peru’s Organismo Especializado para las Contrataciones Públicas Eficientes (OECE/SEACE) and related official sanction records. It is intended to support reproducible research using network analysis, graph representation learning, graph autoencoders, GraphSAGE, and explainable graph neural network methods.</p> 2026-09-30T03:45:22Z Dataset Dataset 10.6084/m9.figshare.34028859.v1 https://figshare.com/articles/dataset/Redes_de_proveedores_del_Estado_peruano_v_nculos_entidad-proveedor_concentraci_n_dependencia_y_validaci_n_de_sanciones_2022_2024/34028859 CC BY 4.0