Risk assessment in pharmaceutical supply chains under unknown input-model parameters

Alp Akcay, Tugce Martagan, Canan G. Corlu

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Samenvatting

We consider a pharmaceutical supply chain where the manufacturer sources a customized product with unique attributes from a set of unreliable suppliers. We model the likelihood of a supplier to successfully deliver the product via Bayesian logistic regression and use simulation to obtain the posterior distribution of the unknown parameters of this model. We study the role of so-called input-model uncertainty in estimating the likelihood of the supply failure, which is the probability that none of the suppliers in a given supplier portfolio can successfully deliver the product. We investigate how the input-model uncertainty changes with respect to the characteristics of the historical data on the past realizations of the supplier performances and the product attributes.

Originele taal-2Engels
TitelWSC 2018 - 2018 Winter Simulation Conference
SubtitelSimulation for a Noble Cause
RedacteurenM. Rabe, A.A. Juan, N. Mustafee, A. Skoogh, S. Jain, B. Johansson
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's3132-3143
Aantal pagina's12
ISBN van elektronische versie9781538665725
DOI's
StatusGepubliceerd - 31 jan 2019
Evenement2018 Winter Simulation Conference, WSC 2018 - Gothenburg, Zweden
Duur: 9 dec 201812 dec 2018

Congres

Congres2018 Winter Simulation Conference, WSC 2018
Verkorte titelWSC 2018
LandZweden
StadGothenburg
Periode9/12/1812/12/18

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Akcay, A., Martagan, T., & Corlu, C. G. (2019). Risk assessment in pharmaceutical supply chains under unknown input-model parameters. In M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, & B. Johansson (editors), WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause (blz. 3132-3143). [8632314] Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/WSC.2018.8632314