A Bayesian Network as a tool to measure Supply Chain Resilience

C.P.A. van Wagenberg; L.H. Aramyan; C.C. de Lauwere; M.P.M. Meuwissen; M.J. Timmer; D.J.M. Willems

A Bayesian Network as a tool to measure Supply Chain Resilience

C.P.A. van Wagenberg, L.H. Aramyan, C.C. de Lauwere, M.P.M. Meuwissen, M.J. Timmer, D.J.M. Willems

Research output: Contribution to conference › Conference paper › Academic › peer-review

Abstract

Resilience frameworks and tools are generally qualitative. The Diagnostic Tool presented in this paper provides a quantitative tool in the area of supply chain resilience. It is among the first tools to quantify the complex concept of resilience. We apply the tool to a sustainable pork chain in the Netherlands. We use a Bayesian Belief Networks (BNN) approach entailing among others the composition of multiple conditional probability tables. This proofed to provide necessary transparency and structure to the concept of resilience and resilience enhancing strategies in a business context.

Original language	English
Number of pages	12
Publication status	Published - 2018
Event	International Conference of Agricultural Economists (ICAE 2018) - Vancouver, Canada Duration: 28 Jul 2018 → 2 Aug 2018

Conference

Conference	International Conference of Agricultural Economists (ICAE 2018)
Country/Territory	Canada
City	Vancouver
Period	28/07/18 → 2/08/18

Access to Document

https://edepot.wur.nl/444761

Developing a prototype of a Supply Chain Resilience measuring methodology (KB-29-007-010)
van Wagenberg, C.
1/01/17 → 31/12/18
Project: LVVN project

Cite this

@conference{869d3e21ce564fe5870f53efeb1ec977,

title = "A Bayesian Network as a tool to measure Supply Chain Resilience",

abstract = "Resilience frameworks and tools are generally qualitative. The Diagnostic Tool presented in this paper provides a quantitative tool in the area of supply chain resilience. It is among the first tools to quantify the complex concept of resilience. We apply the tool to a sustainable pork chain in the Netherlands. We use a Bayesian Belief Networks (BNN) approach entailing among others the composition of multiple conditional probability tables. This proofed to provide necessary transparency and structure to the concept of resilience and resilience enhancing strategies in a business context.",

author = "{van Wagenberg}, C.P.A. and L.H. Aramyan and {de Lauwere}, C.C. and M.P.M. Meuwissen and M.J. Timmer and D.J.M. Willems",

year = "2018",

language = "English",

note = "International Conference of Agricultural Economists (ICAE 2018) ; Conference date: 28-07-2018 Through 02-08-2018",

}

TY - CONF

T1 - A Bayesian Network as a tool to measure Supply Chain Resilience

AU - van Wagenberg, C.P.A.

AU - Aramyan, L.H.

AU - de Lauwere, C.C.

AU - Meuwissen, M.P.M.

AU - Timmer, M.J.

AU - Willems, D.J.M.

PY - 2018

Y1 - 2018

N2 - Resilience frameworks and tools are generally qualitative. The Diagnostic Tool presented in this paper provides a quantitative tool in the area of supply chain resilience. It is among the first tools to quantify the complex concept of resilience. We apply the tool to a sustainable pork chain in the Netherlands. We use a Bayesian Belief Networks (BNN) approach entailing among others the composition of multiple conditional probability tables. This proofed to provide necessary transparency and structure to the concept of resilience and resilience enhancing strategies in a business context.

AB - Resilience frameworks and tools are generally qualitative. The Diagnostic Tool presented in this paper provides a quantitative tool in the area of supply chain resilience. It is among the first tools to quantify the complex concept of resilience. We apply the tool to a sustainable pork chain in the Netherlands. We use a Bayesian Belief Networks (BNN) approach entailing among others the composition of multiple conditional probability tables. This proofed to provide necessary transparency and structure to the concept of resilience and resilience enhancing strategies in a business context.

M3 - Conference paper

T2 - International Conference of Agricultural Economists (ICAE 2018)

Y2 - 28 July 2018 through 2 August 2018

ER -

A Bayesian Network as a tool to measure Supply Chain Resilience

Abstract

Conference

Access to Document

Fingerprint

Projects

Developing a prototype of a Supply Chain Resilience measuring methodology (KB-29-007-010)

Cite this