Properties of B2B invoice graphs and detection of structures - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

Properties of B2B invoice graphs and detection of structures

Résumé

In economy, a major issue is the potential lack of liquidity for settling the debts generated by payment delays among companies. Since this lack may trigger cascading failures, we analyse the interconnection of debts. Settling debts means lowering the systemic risks. We analyse the data of a large economic network from an Italian invoice operator on a one-year span. We compare different methods to detect structures or communities that could be helpful for debt netting algorithms. The structure of such networks is not currently well known. We give hints on how to sort and identify the type of B2B invoice graphs. In particular, we address the possibility to identify relevant communities in such networks.
Fichier principal
Vignette du fichier
Properties&CommunitiesOfEconomicGraphs_HAL.pdf (459.46 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Licence : CC BY NC ND - Paternité - Pas d'utilisation commerciale - Pas de modification

Dates et versions

hal-04230839 , version 1 (06-10-2023)
hal-04230839 , version 2 (12-10-2023)

Licence

Paternité

Identifiants

  • HAL Id : hal-04230839 , version 2

Citer

Joannès Guichon, Nazim A. Fatès, Sylvain Contassot-Vivier, Massimo Amato. Properties of B2B invoice graphs and detection of structures. Complex Networks 2023, Nov 2023, Menton, France. ⟨hal-04230839v2⟩
100 Consultations
30 Téléchargements

Partager

Gmail Facebook X LinkedIn More