### Abstract

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.

Language | English |
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Title of host publication | WSC 2018 - 2018 Winter Simulation Conference |

Subtitle of host publication | Simulation for a Noble Cause |

Editors | M. Rabe, A.A. Juan, N. Mustafee, A. Skoogh, S. Jain, B. Johansson |

Place of Publication | Piscataway |

Publisher | Institute of Electrical and Electronics Engineers (IEEE) |

Pages | 3132-3143 |

Number of pages | 12 |

ISBN (Electronic) | 9781538665725 |

DOIs | |

State | Published - 31 Jan 2019 |

Event | 2018 Winter Simulation Conference, WSC 2018 - Gothenburg, Sweden Duration: 9 Dec 2018 → 12 Dec 2018 |

### Conference

Conference | 2018 Winter Simulation Conference, WSC 2018 |
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Abbreviated title | WSC 2018 |

Country | Sweden |

City | Gothenburg |

Period | 9/12/18 → 12/12/18 |

### Fingerprint

### Cite this

*WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause*(pp. 3132-3143). [8632314] Piscataway: Institute of Electrical and Electronics Engineers (IEEE). DOI: 10.1109/WSC.2018.8632314

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*WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause.*, 8632314, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, pp. 3132-3143, 2018 Winter Simulation Conference, WSC 2018, Gothenburg, Sweden, 9/12/18. DOI: 10.1109/WSC.2018.8632314

**Risk assessment in pharmaceutical supply chains under unknown input-model parameters.** / Akcay, Alp; Martagan, Tugce; Corlu, Canan G.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Risk assessment in pharmaceutical supply chains under unknown input-model parameters

AU - Akcay,Alp

AU - Martagan,Tugce

AU - Corlu,Canan G.

PY - 2019/1/31

Y1 - 2019/1/31

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85062610820&partnerID=8YFLogxK

U2 - 10.1109/WSC.2018.8632314

DO - 10.1109/WSC.2018.8632314

M3 - Conference contribution

SP - 3132

EP - 3143

BT - WSC 2018 - 2018 Winter Simulation Conference

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway

ER -