A multi-layer Bayesian network method for supply chain disruption modelling in the wake of the COVID-19 pandemic
Seyedmohsen Hosseini and Dmitry Ivanov
| Year of publication: |
2022
|
|---|---|
| Authors: | Hosseini, Seyedmohsen ; Ivanov, Dmitry |
| Published in: |
International journal of production research. - London [u.a.] : Taylor & Francis, ISSN 1366-588X, ZDB-ID 1485085-0. - Vol. 60.2022, 17, p. 5258-5276
|
| Subject: | Bayesian network | COVID-19 | pandemic | ripple effect | Supply chain dynamics | supply chain resilience | Bayes-Statistik | Bayesian inference | Coronavirus | Lieferkette | Supply chain | Epidemie | Epidemic | Risikomanagement | Risk management |
Online Resource
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1080/00207543.2021.1953180 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013500701